From eaa06ac621ff2bac9f47dc256cfa8be52faf1c1e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Lo=C3=AFc=20Est=C3=A8ve?= Date: Wed, 15 Mar 2023 11:36:20 +0100 Subject: [PATCH 1/9] CI Update lock files (#25849) --- build_tools/azure/debian_atlas_32bit_lock.txt | 2 +- ...onda_defaults_openblas_linux-64_conda.lock | 44 +++---- .../py38_conda_forge_mkl_win-64_conda.lock | 74 +++++------ ...e_openblas_ubuntu_2204_linux-64_conda.lock | 110 ++++++++++------- ...latest_conda_forge_mkl_linux-64_conda.lock | 111 +++++++++-------- ..._forge_mkl_no_coverage_linux-64_conda.lock | 109 +++++++++------- ...pylatest_conda_forge_mkl_osx-64_conda.lock | 73 ++++++----- ...test_conda_mkl_no_openmp_osx-64_conda.lock | 51 ++++---- ...st_pip_openblas_pandas_linux-64_conda.lock | 54 ++++---- ...pylatest_pip_scipy_dev_linux-64_conda.lock | 34 ++--- build_tools/azure/pypy3_linux-64_conda.lock | 60 +++++---- build_tools/azure/ubuntu_atlas_lock.txt | 6 +- build_tools/circle/doc_environment.yml | 3 +- build_tools/circle/doc_linux-64_conda.lock | 116 +++++++++--------- .../doc_min_dependencies_linux-64_conda.lock | 54 ++++---- .../py39_conda_forge_linux-aarch64_conda.lock | 54 ++++---- .../update_environments_and_lock_files.py | 3 +- .../calibration/plot_calibration_curve.py | 2 +- .../calibration/plot_compare_calibration.py | 2 +- examples/svm/plot_svm_margin.py | 7 +- sklearn/_min_dependencies.py | 2 +- .../tests/test_confusion_matrix_display.py | 5 +- 22 files changed, 525 insertions(+), 451 deletions(-) diff --git a/build_tools/azure/debian_atlas_32bit_lock.txt b/build_tools/azure/debian_atlas_32bit_lock.txt index cb69c8b876f86..dbcc32cd1ff78 100644 --- a/build_tools/azure/debian_atlas_32bit_lock.txt +++ b/build_tools/azure/debian_atlas_32bit_lock.txt @@ -10,7 +10,7 @@ cython==0.29.33 # via -r build_tools/azure/debian_atlas_32bit_requirements.txt joblib==1.1.1 # via -r build_tools/azure/debian_atlas_32bit_requirements.txt -more-itertools==9.0.0 +more-itertools==9.1.0 # via pytest packaging==23.0 # via pytest diff --git a/build_tools/azure/py38_conda_defaults_openblas_linux-64_conda.lock b/build_tools/azure/py38_conda_defaults_openblas_linux-64_conda.lock index 9e6179c378343..4ca6039ea4824 100644 --- a/build_tools/azure/py38_conda_defaults_openblas_linux-64_conda.lock +++ b/build_tools/azure/py38_conda_defaults_openblas_linux-64_conda.lock @@ -4,7 +4,7 @@ @EXPLICIT https://repo.anaconda.com/pkgs/main/linux-64/_libgcc_mutex-0.1-main.conda#c3473ff8bdb3d124ed5ff11ec380d6f9 https://repo.anaconda.com/pkgs/main/linux-64/blas-1.0-openblas.conda#9ddfcaef10d79366c90128f5dc444be8 -https://repo.anaconda.com/pkgs/main/linux-64/ca-certificates-2022.10.11-h06a4308_0.conda#e9b86b388e2cf59585fefca34037b783 +https://repo.anaconda.com/pkgs/main/linux-64/ca-certificates-2023.01.10-h06a4308_0.conda#7704989a2ccf6c1f5a50c985509841c4 https://repo.anaconda.com/pkgs/main/linux-64/ld_impl_linux-64-2.38-h1181459_1.conda#68eedfd9c06f2b0e6888d8db345b7f5b https://repo.anaconda.com/pkgs/main/linux-64/libgfortran4-7.5.0-ha8ba4b0_17.conda#e3883581cbf0a98672250c3e80d292bf https://repo.anaconda.com/pkgs/main/linux-64/libgfortran-ng-7.5.0-ha8ba4b0_17.conda#ecb35c8952579d5c8dc56c6e076ba948 @@ -13,49 +13,49 @@ https://repo.anaconda.com/pkgs/main/linux-64/libstdcxx-ng-11.2.0-h1234567_1.cond https://repo.anaconda.com/pkgs/main/linux-64/_openmp_mutex-5.1-1_gnu.conda#71d281e9c2192cb3fa425655a8defb85 https://repo.anaconda.com/pkgs/main/linux-64/libgcc-ng-11.2.0-h1234567_1.conda#a87728dabf3151fb9cfa990bd2eb0464 https://repo.anaconda.com/pkgs/main/linux-64/expat-2.4.9-h6a678d5_0.conda#3a6139fbcd96384855f0e6037502bf28 -https://repo.anaconda.com/pkgs/main/linux-64/giflib-5.2.1-h7b6447c_0.conda#c2583ad8de5051f19479580c58336f15 +https://repo.anaconda.com/pkgs/main/linux-64/giflib-5.2.1-h5eee18b_3.conda#aa7d64adb3cd8a75d398167f8c29afc3 https://repo.anaconda.com/pkgs/main/linux-64/icu-58.2-he6710b0_3.conda#48cc14d5ad1a9bcd8dac17211a8deb8b -https://repo.anaconda.com/pkgs/main/linux-64/jpeg-9e-h7f8727e_0.conda#a0571bd2254b360aef526307a17f3526 +https://repo.anaconda.com/pkgs/main/linux-64/jpeg-9e-h5eee18b_1.conda#ac373800fda872108412d1ccfe3fa572 https://repo.anaconda.com/pkgs/main/linux-64/lerc-3.0-h295c915_0.conda#b97309770412f10bed8d9448f6f98f87 -https://repo.anaconda.com/pkgs/main/linux-64/libdeflate-1.8-h7f8727e_5.conda#6942d65edab9a800900f43e750b3ad1f +https://repo.anaconda.com/pkgs/main/linux-64/libdeflate-1.17-h5eee18b_0.conda#b4891fa07ca4cad1c53a0d0e539482da https://repo.anaconda.com/pkgs/main/linux-64/libffi-3.4.2-h6a678d5_6.conda#6d65e299b535d3b3613b6d4bce901834 https://repo.anaconda.com/pkgs/main/linux-64/libopenblas-0.3.18-hf726d26_0.conda#10422bb3b9b022e27798fc368cda69ba https://repo.anaconda.com/pkgs/main/linux-64/libuuid-1.41.5-h5eee18b_0.conda#4a6a2354414c9080327274aa514e5299 -https://repo.anaconda.com/pkgs/main/linux-64/libwebp-base-1.2.4-h5eee18b_0.conda#f5f56389136bcd9ca92ee1d64afcceb3 +https://repo.anaconda.com/pkgs/main/linux-64/libwebp-base-1.2.4-h5eee18b_1.conda#a65a20c48061ecf2a6f4f02eae9f2366 https://repo.anaconda.com/pkgs/main/linux-64/libxcb-1.15-h7f8727e_0.conda#ada518dcadd6aaee9aae47ba9a671553 https://repo.anaconda.com/pkgs/main/linux-64/lz4-c-1.9.4-h6a678d5_0.conda#53915e9402180a7f22ea619c41089520 -https://repo.anaconda.com/pkgs/main/linux-64/ncurses-6.3-h5eee18b_3.conda#0c616f387885c1bbb57ec0bd1e779ced +https://repo.anaconda.com/pkgs/main/linux-64/ncurses-6.4-h6a678d5_0.conda#5558eec6e2191741a92f832ea826251c https://repo.anaconda.com/pkgs/main/linux-64/nspr-4.33-h295c915_0.conda#78454e8819eb6701abc74b2ab2889f21 -https://repo.anaconda.com/pkgs/main/linux-64/openssl-1.1.1s-h7f8727e_0.conda#25f9c4e2394976be98d01cccef2ce43a +https://repo.anaconda.com/pkgs/main/linux-64/openssl-1.1.1t-h7f8727e_0.conda#0410db682c02665511bd4203ade48a32 https://repo.anaconda.com/pkgs/main/linux-64/pcre-8.45-h295c915_0.conda#b32ccc24d1d9808618c1e898da60f68d -https://repo.anaconda.com/pkgs/main/linux-64/xz-5.2.8-h5eee18b_0.conda#224260858072f0071140ae18c513620d +https://repo.anaconda.com/pkgs/main/linux-64/xz-5.2.10-h5eee18b_1.conda#dd172c348274807ec0d841df8295b670 https://repo.anaconda.com/pkgs/main/linux-64/zlib-1.2.13-h5eee18b_0.conda#333e31fbfbb5057c92fa845ad6adef93 https://repo.anaconda.com/pkgs/main/linux-64/ccache-3.7.9-hfe4627d_0.conda#bef6fc681c273bb7bd0c67d1a591365e https://repo.anaconda.com/pkgs/main/linux-64/glib-2.69.1-he621ea3_2.conda#51cf1899782b3f3744aedd143fbc07f3 https://repo.anaconda.com/pkgs/main/linux-64/libedit-3.1.20221030-h5eee18b_0.conda#7c724a17739aceaf9d1633ff06962137 https://repo.anaconda.com/pkgs/main/linux-64/libevent-2.1.12-h8f2d780_0.conda#8de03cd4b6ee0ddeb0571a5199db5637 https://repo.anaconda.com/pkgs/main/linux-64/libllvm10-10.0.1-hbcb73fb_5.conda#198e840fc17a5bff7f1ee543ee1981b2 -https://repo.anaconda.com/pkgs/main/linux-64/libpng-1.6.37-hbc83047_0.conda#689f903925dcf6c5ab7bc1de0f58b67b +https://repo.anaconda.com/pkgs/main/linux-64/libpng-1.6.39-h5eee18b_0.conda#f6aee38184512eb05b06c2e94d39ab22 https://repo.anaconda.com/pkgs/main/linux-64/libxml2-2.9.14-h74e7548_0.conda#2eafeb1cb5f00b034d150f3d70436e52 https://repo.anaconda.com/pkgs/main/linux-64/readline-8.2-h5eee18b_0.conda#be42180685cce6e6b0329201d9f48efb https://repo.anaconda.com/pkgs/main/linux-64/tk-8.6.12-h1ccaba5_0.conda#fa10ff4aa631fa4aa090a6234d7770b9 https://repo.anaconda.com/pkgs/main/linux-64/zstd-1.5.2-ha4553b6_0.conda#0e926a5f2e02fe4a9376ece4b732ce36 https://repo.anaconda.com/pkgs/main/linux-64/dbus-1.13.18-hb2f20db_0.conda#6a6a6f1391f807847404344489ef6cf4 https://repo.anaconda.com/pkgs/main/linux-64/freetype-2.12.1-h4a9f257_0.conda#bdc7b5952e9c5dca01bc2f4ccef2f974 -https://repo.anaconda.com/pkgs/main/linux-64/gstreamer-1.14.0-h28cd5cc_2.conda#6af5d0cbd7310e1cd8a6a5c1c99649b2 -https://repo.anaconda.com/pkgs/main/linux-64/krb5-1.19.2-hac12032_0.conda#62a43976b48799377103390c340a3824 +https://repo.anaconda.com/pkgs/main/linux-64/gstreamer-1.14.1-h5eee18b_1.conda#f2f26e6f869b5d87f41bd059fae47c3e +https://repo.anaconda.com/pkgs/main/linux-64/krb5-1.19.4-h568e23c_0.conda#649816c5e24c76bd06e74a0eb671a82e https://repo.anaconda.com/pkgs/main/linux-64/libclang-10.0.1-default_hb85057a_2.conda#9e39ee5217327ba25e341c629b642247 -https://repo.anaconda.com/pkgs/main/linux-64/libtiff-4.5.0-hecacb30_0.conda#ee78c57621673ab656d341c5cd3de211 +https://repo.anaconda.com/pkgs/main/linux-64/libtiff-4.5.0-h6a678d5_2.conda#b3391ee6956636eb8ef159c1c454e3da https://repo.anaconda.com/pkgs/main/linux-64/libxkbcommon-1.0.1-hfa300c1_0.conda#913e6c7c04026ff341960a9700889498 https://repo.anaconda.com/pkgs/main/linux-64/libxslt-1.1.35-h4e12654_0.conda#328c111d87dccd5a3e471a691833f670 https://repo.anaconda.com/pkgs/main/linux-64/sqlite-3.40.1-h5082296_0.conda#7d44bb7460f1b1b0764d63240d7f7f81 https://repo.anaconda.com/pkgs/main/linux-64/fontconfig-2.14.1-h52c9d5c_1.conda#cd3f711abef17203045b7bcfc83fac2f -https://repo.anaconda.com/pkgs/main/linux-64/gst-plugins-base-1.14.0-h8213a91_2.conda#838648422452405b86699e780e293c1d +https://repo.anaconda.com/pkgs/main/linux-64/gst-plugins-base-1.14.1-h6a678d5_1.conda#afd9cbe949d670d24cc0a007aaec1fe1 https://repo.anaconda.com/pkgs/main/linux-64/lcms2-2.12-h3be6417_0.conda#719db47afba9f6586eecb5eacac70bff https://repo.anaconda.com/pkgs/main/linux-64/libpq-12.9-h16c4e8d_3.conda#0f127be216a734916faf456bb21404e9 -https://repo.anaconda.com/pkgs/main/linux-64/libwebp-1.2.4-h11a3e52_0.conda#971acc20767cc834a6baffdeaae6a100 +https://repo.anaconda.com/pkgs/main/linux-64/libwebp-1.2.4-h11a3e52_1.conda#9f9153b30e58e9ce896f74634622cbf1 https://repo.anaconda.com/pkgs/main/linux-64/nss-3.74-h0370c37_0.conda#fb2426b2f3cb17c9015fcbdf917a2f7b -https://repo.anaconda.com/pkgs/main/linux-64/python-3.8.15-h7a1cb2a_2.conda#9252075f5f42bf4bc633fe348bbbb3a4 +https://repo.anaconda.com/pkgs/main/linux-64/python-3.8.16-h7a1cb2a_3.conda#c11c0992727585f5f991760f5b18c968 https://repo.anaconda.com/pkgs/main/linux-64/attrs-22.1.0-py38h06a4308_0.conda#51beb64c6f06b5a69529df7ecaccc3f9 https://repo.anaconda.com/pkgs/main/linux-64/certifi-2022.12.7-py38h06a4308_0.conda#243cddde550e2c3e765db25cdea99a13 https://repo.anaconda.com/pkgs/main/noarch/charset-normalizer-2.0.4-pyhd3eb1b0_0.conda#e7a441d94234b2b5fafee06e25dbf076 @@ -68,7 +68,7 @@ https://repo.anaconda.com/pkgs/main/linux-64/joblib-1.1.1-py38h06a4308_0.conda#e https://repo.anaconda.com/pkgs/main/linux-64/kiwisolver-1.4.4-py38h6a678d5_0.conda#7424aa335d22974192800ec19a68486e https://repo.anaconda.com/pkgs/main/linux-64/numpy-base-1.17.3-py38h2f8d375_0.conda#40edbb76ecacefb1e6ab639b514822b1 https://repo.anaconda.com/pkgs/main/linux-64/packaging-22.0-py38h06a4308_0.conda#f09d8a44adf4dae78562c6f9af3603d6 -https://repo.anaconda.com/pkgs/main/linux-64/pillow-9.3.0-py38hace64e9_1.conda#25eba78d0ac0b82f750c09f89d033097 +https://repo.anaconda.com/pkgs/main/linux-64/pillow-9.4.0-py38h6a678d5_0.conda#8afd1f4f8b23a1c44fca4975253b17f7 https://repo.anaconda.com/pkgs/main/linux-64/pluggy-1.0.0-py38h06a4308_1.conda#87bb1d3f6cf3e409a1dac38cee99918e https://repo.anaconda.com/pkgs/main/linux-64/ply-3.11-py38_0.conda#d6a69c576c6e4d19e3074eaae3d149f2 https://repo.anaconda.com/pkgs/main/noarch/py-1.11.0-pyhd3eb1b0_0.conda#7205a898ed2abbf6e9b903dff6abe08e @@ -82,7 +82,7 @@ https://repo.anaconda.com/pkgs/main/noarch/threadpoolctl-2.2.0-pyh0d69192_0.cond https://repo.anaconda.com/pkgs/main/noarch/toml-0.10.2-pyhd3eb1b0_0.conda#cda05f5f6d8509529d1a2743288d197a https://repo.anaconda.com/pkgs/main/linux-64/tomli-2.0.1-py38h06a4308_0.conda#791cce9de9913e9587b0a85cd8419123 https://repo.anaconda.com/pkgs/main/linux-64/tornado-6.2-py38h5eee18b_0.conda#db2f7ebc500d97a4af6889dfd0d03dbc -https://repo.anaconda.com/pkgs/main/noarch/wheel-0.37.1-pyhd3eb1b0_0.conda#ab85e96e26da8d5797c2458232338b86 +https://repo.anaconda.com/pkgs/main/linux-64/wheel-0.38.4-py38h06a4308_0.conda#52f195e95a5f11c5b9a9eed9cd3d6958 https://repo.anaconda.com/pkgs/main/linux-64/cffi-1.15.1-py38h5eee18b_3.conda#ebf03031554d834c5aafdbed9be24f7f https://repo.anaconda.com/pkgs/main/linux-64/numpy-1.17.3-py38h7e8d029_0.conda#5f2b196b515f8fe6b37e3d224650577d https://repo.anaconda.com/pkgs/main/linux-64/pytest-7.1.2-py38h06a4308_0.conda#8d7f526a3d29273e06957d302f515755 @@ -91,21 +91,21 @@ https://repo.anaconda.com/pkgs/main/linux-64/qt-webengine-5.15.9-hd2b0992_4.cond https://repo.anaconda.com/pkgs/main/linux-64/setuptools-65.6.3-py38h06a4308_0.conda#7676b836ec3f9cb1b0f8661d5863d1a4 https://repo.anaconda.com/pkgs/main/linux-64/sip-6.6.2-py38h6a678d5_0.conda#cb3f0d10f7f79870945f4dbbe0000f92 https://repo.anaconda.com/pkgs/main/linux-64/brotlipy-0.7.0-py38h27cfd23_1003.conda#e881c8ee8a4048f29da5d20f0330fe37 -https://repo.anaconda.com/pkgs/main/linux-64/cryptography-38.0.4-py38h9ce1e76_0.conda#069a127658760920e9d53c31325fb8ce +https://repo.anaconda.com/pkgs/main/linux-64/cryptography-39.0.1-py38h9ce1e76_0.conda#ad365e5ba98df04384bb85fe322bc1a4 https://repo.anaconda.com/pkgs/main/linux-64/matplotlib-base-3.1.3-py38hef1b27d_0.conda#a7ad7d097c25b7beeb76f370d51687a1 https://repo.anaconda.com/pkgs/main/linux-64/pandas-1.2.4-py38ha9443f7_0.conda#5bd3fd807a294f387feabc65821b75d0 -https://repo.anaconda.com/pkgs/main/linux-64/pip-22.3.1-py38h06a4308_0.conda#6d68389c38118ff466fa861c8904950c +https://repo.anaconda.com/pkgs/main/linux-64/pip-23.0.1-py38h06a4308_0.conda#76496ff05a04113680df82fd3566e215 https://repo.anaconda.com/pkgs/main/linux-64/pyqt5-sip-12.11.0-py38h6a678d5_1.conda#7bc403c7d55f1465e922964d293d2186 https://repo.anaconda.com/pkgs/main/noarch/pytest-cov-3.0.0-pyhd3eb1b0_0.conda#bbdaac2947f507399816d509107945c2 https://repo.anaconda.com/pkgs/main/noarch/pytest-forked-1.3.0-pyhd3eb1b0_0.tar.bz2#07970bffdc78f417d7f8f1c7e620f5c4 https://repo.anaconda.com/pkgs/main/linux-64/qtwebkit-5.212-h4eab89a_4.conda#7317bbf3f3e66a0a02b07b860783ecff https://repo.anaconda.com/pkgs/main/linux-64/scipy-1.3.2-py38he2b7bc3_0.conda#a9df91d5a41c1f39524fc8a53c56bc29 https://repo.anaconda.com/pkgs/main/linux-64/pyamg-4.2.3-py38h79cecc1_0.conda#6e7f4f94000b244396de8bf4e6ae8dc4 -https://repo.anaconda.com/pkgs/main/noarch/pyopenssl-22.0.0-pyhd3eb1b0_0.conda#1dbbf9422269cd62c7094960d9b43f36 +https://repo.anaconda.com/pkgs/main/linux-64/pyopenssl-23.0.0-py38h06a4308_0.conda#3f667b964a242e8c4463935ea3a3331e https://repo.anaconda.com/pkgs/main/linux-64/pyqt-5.15.7-py38h6a678d5_1.conda#62232dc285be8e7e85ae9596d89b3b95 https://repo.anaconda.com/pkgs/main/noarch/pytest-xdist-2.5.0-pyhd3eb1b0_0.conda#d15cdc4207bcf8ca920822597f1d138d https://repo.anaconda.com/pkgs/main/linux-64/matplotlib-3.1.3-py38_0.conda#70d5f6df438d469dc78f082389ada23d -https://repo.anaconda.com/pkgs/main/linux-64/urllib3-1.26.13-py38h06a4308_0.conda#74608767d976ca14529b126842ffb685 -https://repo.anaconda.com/pkgs/main/linux-64/requests-2.28.1-py38h06a4308_0.conda#04d482ea4a1e190d688dee2e4048e49f +https://repo.anaconda.com/pkgs/main/linux-64/urllib3-1.26.14-py38h06a4308_0.conda#c84afcc85e999af5ef824aae356cce6a +https://repo.anaconda.com/pkgs/main/linux-64/requests-2.28.1-py38h06a4308_1.conda#657ef918b2c2ee58064feb167e451dc6 https://repo.anaconda.com/pkgs/main/noarch/codecov-2.1.11-pyhd3eb1b0_0.conda#83a743cc928162d53d4066c43468b2c7 # pip cython @ https://files.pythonhosted.org/packages/4c/59/3702d649aeb0fef4dac55036279d3981130cc7024ea2492753f66fb622dd/Cython-0.29.33-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl#sha256=b5e8ce3039ff64000d58cd45b3f6f83e13f032dde7f27bb1ab96070d9213550b diff --git 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+https://repo.anaconda.com/pkgs/main/noarch/appdirs-1.4.4-pyhd3eb1b0_0.conda#5673d98d06171cb6eed03a6736845c4d https://repo.anaconda.com/pkgs/main/osx-64/attrs-22.1.0-py39hecd8cb5_0.conda#d0b7738bb61bd74eedfc833533dd14d4 https://repo.anaconda.com/pkgs/main/osx-64/certifi-2022.12.7-py39hecd8cb5_0.conda#92d58f42b23801c40b4fe2ee5ba93085 https://repo.anaconda.com/pkgs/main/noarch/charset-normalizer-2.0.4-pyhd3eb1b0_0.conda#e7a441d94234b2b5fafee06e25dbf076 @@ -48,7 +48,7 @@ https://repo.anaconda.com/pkgs/main/noarch/iniconfig-1.1.1-pyhd3eb1b0_0.tar.bz2# https://repo.anaconda.com/pkgs/main/osx-64/joblib-1.1.1-py39hecd8cb5_0.conda#8c96155e60c4723afd642a6cee396c26 https://repo.anaconda.com/pkgs/main/osx-64/kiwisolver-1.4.4-py39hcec6c5f_0.conda#2ee58ba7ba854969d0b7f7db4d07459d https://repo.anaconda.com/pkgs/main/osx-64/lcms2-2.12-hf1fd2bf_0.conda#697aba7a3308226df7a93ccfeae16ffa -https://repo.anaconda.com/pkgs/main/osx-64/libwebp-1.2.4-h56c3ce4_0.conda#55aab5176f109c67c355ac018e5f7b4a +https://repo.anaconda.com/pkgs/main/osx-64/libwebp-1.2.4-hf6ce154_1.conda#07d0981c3847293d4aea5778298a12d3 https://repo.anaconda.com/pkgs/main/noarch/munkres-1.1.4-py_0.conda#148362ba07f92abab76999a680c80084 https://repo.anaconda.com/pkgs/main/osx-64/packaging-22.0-py39hecd8cb5_0.conda#a1ac08e4d5f08fcb7240edb91639ac0e https://repo.anaconda.com/pkgs/main/osx-64/pluggy-1.0.0-py39hecd8cb5_1.conda#c5507133514846cc5f54dc4de9ba1563 @@ -62,34 +62,37 @@ https://repo.anaconda.com/pkgs/main/noarch/threadpoolctl-2.2.0-pyh0d69192_0.cond https://repo.anaconda.com/pkgs/main/noarch/toml-0.10.2-pyhd3eb1b0_0.conda#cda05f5f6d8509529d1a2743288d197a https://repo.anaconda.com/pkgs/main/osx-64/tomli-2.0.1-py39hecd8cb5_0.conda#49318006e63c8628ce0a1e2e1433d30d https://repo.anaconda.com/pkgs/main/osx-64/tornado-6.2-py39hca72f7f_0.conda#2653da9c248d53e811364e65353c8742 -https://repo.anaconda.com/pkgs/main/noarch/wheel-0.37.1-pyhd3eb1b0_0.conda#ab85e96e26da8d5797c2458232338b86 +https://repo.anaconda.com/pkgs/main/osx-64/wheel-0.38.4-py39hecd8cb5_0.conda#a220b0cb159f300ced9a8fc9974a2f14 +https://repo.anaconda.com/pkgs/main/osx-64/zipp-3.11.0-py39hecd8cb5_0.conda#9bef65af2d31209e9b0db05b2c83df42 https://repo.anaconda.com/pkgs/main/osx-64/cffi-1.15.1-py39h6c40b1e_3.conda#c9df0a268b6168cb890a6f65e2a81c71 https://repo.anaconda.com/pkgs/main/noarch/fonttools-4.25.0-pyhd3eb1b0_0.conda#bb9c5b5a6d892fca5efe4bf0203b6a48 +https://repo.anaconda.com/pkgs/main/noarch/importlib_resources-5.2.0-pyhd3eb1b0_1.conda#3e7caf9dbd3b4771e9b951ffc7cdad80 https://repo.anaconda.com/pkgs/main/osx-64/mkl-service-2.4.0-py39h9ed2024_0.conda#68ed4da109042256b78f9c46537bd2a3 -https://repo.anaconda.com/pkgs/main/osx-64/pillow-9.3.0-py39h81888ad_1.conda#f4d55ddb76868ac9823f1e986fdfe535 +https://repo.anaconda.com/pkgs/main/osx-64/pillow-9.4.0-py39hcec6c5f_0.conda#5b5389309701442bd3949665e9a88d7e https://repo.anaconda.com/pkgs/main/osx-64/pytest-7.1.2-py39hecd8cb5_0.conda#8239bdb679b675ab8aac1bdc0756d383 https://repo.anaconda.com/pkgs/main/noarch/python-dateutil-2.8.2-pyhd3eb1b0_0.conda#211ee00320b08a1ac9fea6677649f6c9 https://repo.anaconda.com/pkgs/main/osx-64/setuptools-65.6.3-py39hecd8cb5_0.conda#762fa88e92dfd5b5158cc58e7860b252 https://repo.anaconda.com/pkgs/main/osx-64/brotlipy-0.7.0-py39h9ed2024_1003.conda#a08f6f5f899aff4a07351217b36fae41 -https://repo.anaconda.com/pkgs/main/osx-64/cryptography-38.0.4-py39hf6deb26_0.conda#60f85eabbcadcab133178381076a53cb +https://repo.anaconda.com/pkgs/main/osx-64/cryptography-39.0.1-py39hf6deb26_0.conda#47eae0abc1b7f4c285ab4a4b49e34f4b https://repo.anaconda.com/pkgs/main/osx-64/numpy-base-1.22.3-py39h3b1a694_0.conda#f68019d1d839b40739b64b6feae2b436 -https://repo.anaconda.com/pkgs/main/osx-64/pip-22.3.1-py39hecd8cb5_0.conda#2b9cc526d938898ddac198c863985532 +https://repo.anaconda.com/pkgs/main/osx-64/pip-23.0.1-py39hecd8cb5_0.conda#e1064a892ad81368df4de5f5c66225e0 https://repo.anaconda.com/pkgs/main/noarch/pytest-cov-3.0.0-pyhd3eb1b0_0.conda#bbdaac2947f507399816d509107945c2 https://repo.anaconda.com/pkgs/main/noarch/pytest-forked-1.3.0-pyhd3eb1b0_0.tar.bz2#07970bffdc78f417d7f8f1c7e620f5c4 -https://repo.anaconda.com/pkgs/main/noarch/pyopenssl-22.0.0-pyhd3eb1b0_0.conda#1dbbf9422269cd62c7094960d9b43f36 +https://repo.anaconda.com/pkgs/main/osx-64/pyopenssl-23.0.0-py39hecd8cb5_0.conda#ed50ac428785ce7539f175822e834cfd https://repo.anaconda.com/pkgs/main/noarch/pytest-xdist-2.5.0-pyhd3eb1b0_0.conda#d15cdc4207bcf8ca920822597f1d138d -https://repo.anaconda.com/pkgs/main/osx-64/urllib3-1.26.13-py39hecd8cb5_0.conda#e70b93b82feff4e4f9331ed455d1f6dc -https://repo.anaconda.com/pkgs/main/osx-64/requests-2.28.1-py39hecd8cb5_0.conda#c2a59bb72db0abd039ce447be18c139d +https://repo.anaconda.com/pkgs/main/osx-64/urllib3-1.26.14-py39hecd8cb5_0.conda#dc5d0364bf213af8a0ab1e75d608230c +https://repo.anaconda.com/pkgs/main/osx-64/requests-2.28.1-py39hecd8cb5_1.conda#ca1021033fe6ba4cf13b563afed0b9ef https://repo.anaconda.com/pkgs/main/noarch/codecov-2.1.11-pyhd3eb1b0_0.conda#83a743cc928162d53d4066c43468b2c7 +https://repo.anaconda.com/pkgs/main/noarch/pooch-1.4.0-pyhd3eb1b0_0.conda#69ec83cb3d152f9e854115555004f368 https://repo.anaconda.com/pkgs/main/osx-64/bottleneck-1.3.5-py39h67323c0_0.conda#312133560b81ec1a2aaf95835e90b5e9 https://repo.anaconda.com/pkgs/main/osx-64/contourpy-1.0.5-py39haf03e11_0.conda#e4bf1c4fc91f39170273f422f2c97481 -https://repo.anaconda.com/pkgs/main/osx-64/matplotlib-3.6.2-py39hecd8cb5_0.conda#0a51906c4a2e76edaaffac06a1b352e8 -https://repo.anaconda.com/pkgs/main/osx-64/matplotlib-base-3.6.2-py39h220de94_0.conda#3e1c1bc56bf1636b5dd01510cf511c05 +https://repo.anaconda.com/pkgs/main/osx-64/matplotlib-3.7.1-py39hecd8cb5_0.conda#def38432cfad6112990ab62dda400df2 +https://repo.anaconda.com/pkgs/main/osx-64/matplotlib-base-3.7.1-py39hda11e5a_0.conda#855735aaf9938f5a56fa5d02e92cb615 https://repo.anaconda.com/pkgs/main/osx-64/mkl_fft-1.3.1-py39h4ab4a9b_0.conda#f947c9a1c65da729963b3035c219ba10 https://repo.anaconda.com/pkgs/main/osx-64/mkl_random-1.2.2-py39hb2f4e1b_0.conda#1bc33de45069ad534182ca92e616ec7e https://repo.anaconda.com/pkgs/main/osx-64/numpy-1.22.3-py39h2e5f0a9_0.conda#16892a18dae1fb1522845e4b6005b436 https://repo.anaconda.com/pkgs/main/osx-64/numexpr-2.8.4-py39he696674_0.conda#9776eb34625bf969ba017f7362ecf23f -https://repo.anaconda.com/pkgs/main/osx-64/scipy-1.9.3-py39h3d31255_0.conda#c2917042394d646f4a2ca22e0b665a06 -https://repo.anaconda.com/pkgs/main/osx-64/pandas-1.5.2-py39h07fba90_0.conda#ff5c1d08cf4022f6b58ef4f53ba768d1 +https://repo.anaconda.com/pkgs/main/osx-64/scipy-1.10.0-py39h91c6ef4_1.conda#517710e1e02bcaff317d317d73455939 +https://repo.anaconda.com/pkgs/main/osx-64/pandas-1.5.3-py39h07fba90_0.conda#69af9747b3840ae270bf0ec30d321da1 https://repo.anaconda.com/pkgs/main/osx-64/pyamg-4.2.3-py39hc29d2bd_0.conda#728a52ac4cc423a4895158c08b95bedf # pip cython @ https://files.pythonhosted.org/packages/56/3a/e59db3769dee48409c759a88b62cd605324e05d396e10af0a065adc956ad/Cython-0.29.33-py2.py3-none-any.whl#sha256=8b99252bde8ff51cd06a3fe4aeacd3af9b4ff4a4e6b701ac71bddc54f5da61d6 diff --git a/build_tools/azure/pylatest_pip_openblas_pandas_linux-64_conda.lock b/build_tools/azure/pylatest_pip_openblas_pandas_linux-64_conda.lock index adb785ba36f92..0b72d882699fb 100644 --- a/build_tools/azure/pylatest_pip_openblas_pandas_linux-64_conda.lock +++ b/build_tools/azure/pylatest_pip_openblas_pandas_linux-64_conda.lock @@ -3,7 +3,7 @@ # input_hash: c268536f64c353efd8a32b7f76ae09489ef30493354dfdfa69f5e648f908ad75 @EXPLICIT https://repo.anaconda.com/pkgs/main/linux-64/_libgcc_mutex-0.1-main.conda#c3473ff8bdb3d124ed5ff11ec380d6f9 -https://repo.anaconda.com/pkgs/main/linux-64/ca-certificates-2022.10.11-h06a4308_0.conda#e9b86b388e2cf59585fefca34037b783 +https://repo.anaconda.com/pkgs/main/linux-64/ca-certificates-2023.01.10-h06a4308_0.conda#7704989a2ccf6c1f5a50c985509841c4 https://repo.anaconda.com/pkgs/main/linux-64/ld_impl_linux-64-2.38-h1181459_1.conda#68eedfd9c06f2b0e6888d8db345b7f5b https://repo.anaconda.com/pkgs/main/noarch/tzdata-2022g-h04d1e81_0.conda#833facc4bfeebcb61babe76257e8c9e8 https://repo.anaconda.com/pkgs/main/linux-64/libgomp-11.2.0-h1234567_1.conda#b372c0eea9b60732fdae4b817a63c8cd @@ -11,15 +11,15 @@ https://repo.anaconda.com/pkgs/main/linux-64/libstdcxx-ng-11.2.0-h1234567_1.cond https://repo.anaconda.com/pkgs/main/linux-64/_openmp_mutex-5.1-1_gnu.conda#71d281e9c2192cb3fa425655a8defb85 https://repo.anaconda.com/pkgs/main/linux-64/libgcc-ng-11.2.0-h1234567_1.conda#a87728dabf3151fb9cfa990bd2eb0464 https://repo.anaconda.com/pkgs/main/linux-64/libffi-3.4.2-h6a678d5_6.conda#6d65e299b535d3b3613b6d4bce901834 -https://repo.anaconda.com/pkgs/main/linux-64/ncurses-6.3-h5eee18b_3.conda#0c616f387885c1bbb57ec0bd1e779ced -https://repo.anaconda.com/pkgs/main/linux-64/openssl-1.1.1s-h7f8727e_0.conda#25f9c4e2394976be98d01cccef2ce43a -https://repo.anaconda.com/pkgs/main/linux-64/xz-5.2.8-h5eee18b_0.conda#224260858072f0071140ae18c513620d +https://repo.anaconda.com/pkgs/main/linux-64/ncurses-6.4-h6a678d5_0.conda#5558eec6e2191741a92f832ea826251c +https://repo.anaconda.com/pkgs/main/linux-64/openssl-1.1.1t-h7f8727e_0.conda#0410db682c02665511bd4203ade48a32 +https://repo.anaconda.com/pkgs/main/linux-64/xz-5.2.10-h5eee18b_1.conda#dd172c348274807ec0d841df8295b670 https://repo.anaconda.com/pkgs/main/linux-64/zlib-1.2.13-h5eee18b_0.conda#333e31fbfbb5057c92fa845ad6adef93 https://repo.anaconda.com/pkgs/main/linux-64/ccache-3.7.9-hfe4627d_0.conda#bef6fc681c273bb7bd0c67d1a591365e https://repo.anaconda.com/pkgs/main/linux-64/readline-8.2-h5eee18b_0.conda#be42180685cce6e6b0329201d9f48efb https://repo.anaconda.com/pkgs/main/linux-64/tk-8.6.12-h1ccaba5_0.conda#fa10ff4aa631fa4aa090a6234d7770b9 https://repo.anaconda.com/pkgs/main/linux-64/sqlite-3.40.1-h5082296_0.conda#7d44bb7460f1b1b0764d63240d7f7f81 -https://repo.anaconda.com/pkgs/main/linux-64/python-3.9.15-h7a1cb2a_2.conda#11aaa2155e45d001f854b7edb84bca39 +https://repo.anaconda.com/pkgs/main/linux-64/python-3.9.16-h7a1cb2a_2.conda#6b4f255f11b3facb3fa17061757b8cc2 https://repo.anaconda.com/pkgs/main/noarch/alabaster-0.7.12-pyhd3eb1b0_0.tar.bz2#21ad3b69a5ce6c22e724e9dbb4cffa65 https://repo.anaconda.com/pkgs/main/linux-64/certifi-2022.12.7-py39h06a4308_0.conda#b4238d910e43d09651eebe8db79b5c68 https://repo.anaconda.com/pkgs/main/noarch/charset-normalizer-2.0.4-pyhd3eb1b0_0.conda#e7a441d94234b2b5fafee06e25dbf076 @@ -40,7 +40,7 @@ https://repo.anaconda.com/pkgs/main/noarch/sphinxcontrib-htmlhelp-2.0.0-pyhd3eb1 https://repo.anaconda.com/pkgs/main/noarch/sphinxcontrib-jsmath-1.0.1-pyhd3eb1b0_0.tar.bz2#e43f8de7d6a717935ab220a0c957771d https://repo.anaconda.com/pkgs/main/noarch/sphinxcontrib-qthelp-1.0.3-pyhd3eb1b0_0.tar.bz2#08d67f73f640b4d1e5e8890a324b60e3 https://repo.anaconda.com/pkgs/main/noarch/sphinxcontrib-serializinghtml-1.1.5-pyhd3eb1b0_0.conda#0440b84dfd478f340cf14c2d7c24f6c7 -https://repo.anaconda.com/pkgs/main/noarch/wheel-0.37.1-pyhd3eb1b0_0.conda#ab85e96e26da8d5797c2458232338b86 +https://repo.anaconda.com/pkgs/main/linux-64/wheel-0.38.4-py39h06a4308_0.conda#83e731cfecb3797a0f2865615177f433 https://repo.anaconda.com/pkgs/main/linux-64/zipp-3.11.0-py39h06a4308_0.conda#6b0ec14d6d5182748006e984590daca5 https://repo.anaconda.com/pkgs/main/linux-64/babel-2.11.0-py39h06a4308_0.conda#57afaec3ce18928835e87fa5187ef22c https://repo.anaconda.com/pkgs/main/linux-64/cffi-1.15.1-py39h5eee18b_3.conda#89bf9aee92a2429222630337bec3d73f @@ -48,23 +48,24 @@ https://repo.anaconda.com/pkgs/main/linux-64/importlib-metadata-4.11.3-py39h06a4 https://repo.anaconda.com/pkgs/main/linux-64/jinja2-3.1.2-py39h06a4308_0.conda#1ae40578c29a6ed9ca0cf23c89d48fa4 https://repo.anaconda.com/pkgs/main/linux-64/setuptools-65.6.3-py39h06a4308_0.conda#c45480250c7a422ae327df494aced180 https://repo.anaconda.com/pkgs/main/linux-64/brotlipy-0.7.0-py39h27cfd23_1003.conda#be47bcffb9e3e7495897b02589f5ad1a -https://repo.anaconda.com/pkgs/main/linux-64/cryptography-38.0.4-py39h9ce1e76_0.conda#52136f55ebc78ad10354df15ddaa581a -https://repo.anaconda.com/pkgs/main/linux-64/pip-22.3.1-py39h06a4308_0.conda#551a81c65d85d3bfd0f849fdda5bfad8 -https://repo.anaconda.com/pkgs/main/noarch/pyopenssl-22.0.0-pyhd3eb1b0_0.conda#1dbbf9422269cd62c7094960d9b43f36 -https://repo.anaconda.com/pkgs/main/linux-64/urllib3-1.26.13-py39h06a4308_0.conda#5028912afd81b82cb7f70bbb45ce873b -https://repo.anaconda.com/pkgs/main/linux-64/requests-2.28.1-py39h06a4308_0.conda#5ae2a5b6b791e0a8f5b0129b59e5e793 +https://repo.anaconda.com/pkgs/main/linux-64/cryptography-39.0.1-py39h9ce1e76_0.conda#38eea02c5f2ff123ddfa0b706482d0d3 +https://repo.anaconda.com/pkgs/main/linux-64/pip-23.0.1-py39h06a4308_0.conda#e36d76b4611ca9b5d8bd180232aecbac +https://repo.anaconda.com/pkgs/main/linux-64/pyopenssl-23.0.0-py39h06a4308_0.conda#9043b6369acf9a81d7156404c0b38806 +https://repo.anaconda.com/pkgs/main/linux-64/urllib3-1.26.14-py39h06a4308_0.conda#db9c2b56e835ae5ba800e8821c37b27c +https://repo.anaconda.com/pkgs/main/linux-64/requests-2.28.1-py39h06a4308_1.conda#90e023425c3be3a4b905278703984fbc https://repo.anaconda.com/pkgs/main/linux-64/sphinx-5.0.2-py39h06a4308_0.conda#8ea4d14304219bfcb4a67da8b34d76ce # pip attrs @ https://files.pythonhosted.org/packages/fb/6e/6f83bf616d2becdf333a1640f1d463fef3150e2e926b7010cb0f81c95e88/attrs-22.2.0-py3-none-any.whl#sha256=29e95c7f6778868dbd49170f98f8818f78f3dc5e0e37c0b1f474e3561b240836 # pip cycler @ https://files.pythonhosted.org/packages/5c/f9/695d6bedebd747e5eb0fe8fad57b72fdf25411273a39791cde838d5a8f51/cycler-0.11.0-py3-none-any.whl#sha256=3a27e95f763a428a739d2add979fa7494c912a32c17c4c38c4d5f082cad165a3 # pip cython @ https://files.pythonhosted.org/packages/87/4c/41e4fc95a31ec6747e74283e987fb9b3b7c0b3cb2cf10af65f02bd0359d4/Cython-0.29.33-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl#sha256=4f88c2dc0653eef6468848eb8022faf64115b39734f750a1c01a7ba7eb04d89f -# pip exceptiongroup @ https://files.pythonhosted.org/packages/e8/14/9c6a7e5f12294ccd6975a45e02899ed25468cd7c2c86f3d9725f387f9f5f/exceptiongroup-1.1.0-py3-none-any.whl#sha256=327cbda3da756e2de031a3107b81ab7b3770a602c4d16ca618298c526f4bec1e +# pip exceptiongroup @ https://files.pythonhosted.org/packages/61/97/17ed81b7a8d24d8f69b62c0db37abbd8c0042d4b3fc429c73dab986e7483/exceptiongroup-1.1.1-py3-none-any.whl#sha256=232c37c63e4f682982c8b6459f33a8981039e5fb8756b2074364e5055c498c9e # pip execnet @ https://files.pythonhosted.org/packages/81/c0/3072ecc23f4c5e0a1af35e3a222855cfd9c80a1a105ca67be3b6172637dd/execnet-1.9.0-py2.py3-none-any.whl#sha256=a295f7cc774947aac58dde7fdc85f4aa00c42adf5d8f5468fc630c1acf30a142 -# pip fonttools @ https://files.pythonhosted.org/packages/e3/d9/e9bae85e84737e76ebbcbea13607236da0c0699baed0ae4f1151b728a608/fonttools-4.38.0-py3-none-any.whl#sha256=820466f43c8be8c3009aef8b87e785014133508f0de64ec469e4efb643ae54fb +# pip fonttools @ https://files.pythonhosted.org/packages/43/6e/810648a366d6488e1e0543f72dcb2016e54ec02933e302cd41d72599e90d/fonttools-4.39.0-py3-none-any.whl#sha256=f5e764e1fd6ad54dfc201ff32af0ba111bcfbe0d05b24540af74c63db4ed6390 # pip iniconfig @ https://files.pythonhosted.org/packages/ef/a6/62565a6e1cf69e10f5727360368e451d4b7f58beeac6173dc9db836a5b46/iniconfig-2.0.0-py3-none-any.whl#sha256=b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374 # pip joblib @ https://files.pythonhosted.org/packages/91/d4/3b4c8e5a30604df4c7518c562d4bf0502f2fa29221459226e140cf846512/joblib-1.2.0-py3-none-any.whl#sha256=091138ed78f800342968c523bdde947e7a305b8594b910a0fea2ab83c3c6d385 # pip kiwisolver @ https://files.pythonhosted.org/packages/a4/36/c414d75be311ce97ef7248edcc4fc05afae2998641bf6b592d43a9dee581/kiwisolver-1.4.4-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl#sha256=7c43e1e1206cd421cd92e6b3280d4385d41d7166b3ed577ac20444b6995a445f +# pip lazy-loader @ https://files.pythonhosted.org/packages/bc/bf/58dbe1f382ecac2c0571c43b6e95028b14e159d67d75e49a00c26ef63d8f/lazy_loader-0.1-py3-none-any.whl#sha256=623bd4831a40ce659d74472af40a58d016f2a5a047685409affbc2ba5c044641 # pip networkx @ https://files.pythonhosted.org/packages/11/eb/929b1a04b1778f4dd606c739c93c134306e4a31012e31e184c8308f3d985/networkx-3.0-py3-none-any.whl#sha256=58058d66b1818043527244fab9d41a51fcd7dcc271748015f3c181b8a90c8e2e -# pip numpy @ https://files.pythonhosted.org/packages/43/55/fea3342371187dea4044521c0ba82b90fb5a42fb92446be019b316dd3320/numpy-1.24.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=ef85cf1f693c88c1fd229ccd1055570cb41cdf4875873b7728b6301f12cd05bf +# pip numpy @ https://files.pythonhosted.org/packages/f4/f4/45e6e3f7a23b9023554903a122c95585e9787f9403d386bafb7a95d24c9b/numpy-1.24.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=f64bb98ac59b3ea3bf74b02f13836eb2e24e48e0ab0145bbda646295769bd780 # pip pillow @ https://files.pythonhosted.org/packages/f2/cc/71b11ec996744b704637d9ef53ff924b7d208c41be1d251cca33991f6833/Pillow-9.4.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=0884ba7b515163a1a05440a138adeb722b8a6ae2c2b33aea93ea3118dd3a899e # pip pluggy @ https://files.pythonhosted.org/packages/9e/01/f38e2ff29715251cf25532b9082a1589ab7e4f571ced434f98d0139336dc/pluggy-1.0.0-py2.py3-none-any.whl#sha256=74134bbf457f031a36d68416e1509f34bd5ccc019f0bcc952c7b909d06b37bd3 # pip py @ https://files.pythonhosted.org/packages/f6/f0/10642828a8dfb741e5f3fbaac830550a518a775c7fff6f04a007259b0548/py-1.11.0-py2.py3-none-any.whl#sha256=607c53218732647dff4acdfcd50cb62615cedf612e72d1724fb1a0cc6405b378 @@ -72,24 +73,25 @@ https://repo.anaconda.com/pkgs/main/linux-64/sphinx-5.0.2-py39h06a4308_0.conda#8 # pip six @ https://files.pythonhosted.org/packages/d9/5a/e7c31adbe875f2abbb91bd84cf2dc52d792b5a01506781dbcf25c91daf11/six-1.16.0-py2.py3-none-any.whl#sha256=8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254 # pip threadpoolctl @ https://files.pythonhosted.org/packages/61/cf/6e354304bcb9c6413c4e02a747b600061c21d38ba51e7e544ac7bc66aecc/threadpoolctl-3.1.0-py3-none-any.whl#sha256=8b99adda265feb6773280df41eece7b2e6561b772d21ffd52e372f999024907b # pip tomli @ https://files.pythonhosted.org/packages/97/75/10a9ebee3fd790d20926a90a2547f0bf78f371b2f13aa822c759680ca7b9/tomli-2.0.1-py3-none-any.whl#sha256=939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc -# pip typing-extensions @ https://files.pythonhosted.org/packages/0b/8e/f1a0a5a76cfef77e1eb6004cb49e5f8d72634da638420b9ea492ce8305e8/typing_extensions-4.4.0-py3-none-any.whl#sha256=16fa4864408f655d35ec496218b85f79b3437c829e93320c7c9215ccfd92489e +# pip typing-extensions @ https://files.pythonhosted.org/packages/31/25/5abcd82372d3d4a3932e1fa8c3dbf9efac10cc7c0d16e78467460571b404/typing_extensions-4.5.0-py3-none-any.whl#sha256=fb33085c39dd998ac16d1431ebc293a8b3eedd00fd4a32de0ff79002c19511b4 # pip contourpy @ https://files.pythonhosted.org/packages/c7/97/ba9ace011734cd01b63eb7d39b2cf97afbfa985b0239ab0db85bafa9b207/contourpy-1.0.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=e7281244c99fd7c6f27c1c6bfafba878517b0b62925a09b586d88ce750a016d2 -# pip coverage @ https://files.pythonhosted.org/packages/9b/38/b407288f8142c3b14c3f36a145d1380e5750781b22997eb1b659f194b093/coverage-7.0.5-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=13250b1f0bd023e0c9f11838bdeb60214dd5b6aaf8e8d2f110c7e232a1bff83b -# pip imageio @ https://files.pythonhosted.org/packages/11/4a/3e6de99afd3227c68b384f5dd420fe8c2d95f9ad765826a3ce75c5f22dc7/imageio-2.24.0-py3-none-any.whl#sha256=c4ccd0293a1aeb566c7fa04260d51897be064b8fb287a77548ce42050ec06d7a +# pip coverage @ 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pip pytest @ https://files.pythonhosted.org/packages/cc/02/8f59bf194c9a1ceac6330850715e9ec11e21e2408a30a596c65d54cf4d2a/pytest-7.2.1-py3-none-any.whl#sha256=c7c6ca206e93355074ae32f7403e8ea12163b1163c976fee7d4d84027c162be5 +# pip pytest @ https://files.pythonhosted.org/packages/b2/68/5321b5793bd506961bd40bdbdd0674e7de4fb873ee7cab33dd27283ad513/pytest-7.2.2-py3-none-any.whl#sha256=130328f552dcfac0b1cec75c12e3f005619dc5f874f0a06e8ff7263f0ee6225e # pip python-dateutil @ https://files.pythonhosted.org/packages/36/7a/87837f39d0296e723bb9b62bbb257d0355c7f6128853c78955f57342a56d/python_dateutil-2.8.2-py2.py3-none-any.whl#sha256=961d03dc3453ebbc59dbdea9e4e11c5651520a876d0f4db161e8674aae935da9 # pip pywavelets @ https://files.pythonhosted.org/packages/5a/98/4549479a32972bdfdd5e75e168219e97f4dfaee535a8308efef7291e8398/PyWavelets-1.4.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=71ab30f51ee4470741bb55fc6b197b4a2b612232e30f6ac069106f0156342356 -# pip scipy @ https://files.pythonhosted.org/packages/30/71/bb9e677e30c52f938ff71ba528915c579e794ac0f59804e06bfed3596dff/scipy-1.10.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=0490dc499fe23e4be35b8b6dd1e60a4a34f0c4adb30ac671e6332446b3cbbb5a +# pip scipy @ https://files.pythonhosted.org/packages/5d/30/b2a2a5bf1a3beefb7609fb871dcc6aef7217c69cef19a4631b7ab5622a8a/scipy-1.10.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=1b4735d6c28aad3cdcf52117e0e91d6b39acd4272f3f5cd9907c24ee931ad601 # pip setuptools-scm @ https://files.pythonhosted.org/packages/1d/66/8f42c941be949ef2b22fe905d850c794e7c170a526023612aad5f3a121ad/setuptools_scm-7.1.0-py3-none-any.whl#sha256=73988b6d848709e2af142aa48c986ea29592bbcfca5375678064708205253d8e -# pip tifffile @ https://files.pythonhosted.org/packages/d2/cb/1ecf9f39113a7ad0529a0441a16982791e7b37a4efdba2f89a687fdf15c9/tifffile-2022.10.10-py3-none-any.whl#sha256=87f3aee8a0d06b74655269a105de75c1958a24653e1930d523eb516100043503 +# pip tifffile @ https://files.pythonhosted.org/packages/df/30/b3a70a98b1be0ef881593b7f0ea7fd2aed9f5f3440e90547aa79000a8792/tifffile-2023.2.28-py3-none-any.whl#sha256=8357cd8ccbdd4378ad4d6b84ffe3ab15b1d96630b1719f576d4de386f45546f1 # pip codecov @ https://files.pythonhosted.org/packages/dc/e2/964d0881eff5a67bf5ddaea79a13c7b34a74bc4efe917b368830b475a0b9/codecov-2.1.12-py2.py3-none-any.whl#sha256=585dc217dc3d8185198ceb402f85d5cb5dbfa0c5f350a5abcdf9e347776a5b47 -# pip matplotlib @ https://files.pythonhosted.org/packages/71/4d/6d5176b64cfc5b128e859b7675e72c05db52dcb128196b8a27ba834ff5cd/matplotlib-3.6.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=809119d1cba3ece3c9742eb01827fe7a0e781ea3c5d89534655a75e07979344f -# pip pandas @ https://files.pythonhosted.org/packages/5e/ed/5c9cdaa5d48c7194bef4335eab3cdc2f8afa868a5546027e018ea9deb4c3/pandas-1.5.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=344021ed3e639e017b452aa8f5f6bf38a8806f5852e217a7594417fb9bbfa00e +# pip matplotlib @ https://files.pythonhosted.org/packages/9f/77/0cd22f92f7103383cb1ce3b3efc77411b9cc3a495242c8f2a623b498f586/matplotlib-3.7.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=f883a22a56a84dba3b588696a2b8a1ab0d2c3d41be53264115c71b0a942d8fdb +# pip pandas @ https://files.pythonhosted.org/packages/e1/4d/3eb96e53a9208350ee21615f850c4be9a246d32bf1d34cd36682cb58c3b7/pandas-1.5.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=9f69c4029613de47816b1bb30ff5ac778686688751a5e9c99ad8c7031f6508e5 # pip pyamg @ https://files.pythonhosted.org/packages/8e/08/d512b6e34d502152723b5a4ad9d962a6141dfe83cd8bcd01af4cb6e84f28/pyamg-4.2.3-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl#sha256=18af99d2551df07951c35cf270dc76703f8c5d30b16ea8e61657fda098f57dd7 # pip pytest-cov @ https://files.pythonhosted.org/packages/fe/1f/9ec0ddd33bd2b37d6ec50bb39155bca4fe7085fa78b3b434c05459a860e3/pytest_cov-4.0.0-py3-none-any.whl#sha256=2feb1b751d66a8bd934e5edfa2e961d11309dc37b73b0eabe73b5945fee20f6b -# pip pytest-forked @ https://files.pythonhosted.org/packages/0c/36/c56ef2aea73912190cdbcc39aaa860db8c07c1a5ce8566994ec9425453db/pytest_forked-1.4.0-py3-none-any.whl#sha256=bbbb6717efc886b9d64537b41fb1497cfaf3c9601276be8da2cccfea5a3c8ad8 -# pip scikit-image @ https://files.pythonhosted.org/packages/0f/29/d157cd648b87212e498189c183a32f0f48e24fe22e9673dacd97594f39fa/scikit_image-0.19.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=ff3b1025356508d41f4fe48528e509d95f9e4015e90cf158cd58c56dc63e0ac5 -# pip scikit-learn @ https://files.pythonhosted.org/packages/83/b5/0436307cb4f91ba280c74746fde7c89bed7a87703a2bf6e21791f56ce6de/scikit_learn-1.2.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=de897720173b26842e21bed54362f5294e282422116b61cd931d4f5d870b9855 -# pip lightgbm @ https://files.pythonhosted.org/packages/1f/8f/cb077c8cdb54848ee43d4f4cff927ce4812878d01e677583f3f63c575b2c/lightgbm-3.3.4-py3-none-manylinux1_x86_64.whl#sha256=bf79910a75ba6260cdefa3ddfe030707928ba2a0ffb204c0b6ab31f56fc27ebd +# pip pytest-forked @ https://files.pythonhosted.org/packages/f4/af/9c0bda43e486a3c9bf1e0f876d0f241bc3f229d7d65d09331a0868db9629/pytest_forked-1.6.0-py3-none-any.whl#sha256=810958f66a91afb1a1e2ae83089d8dc1cd2437ac96b12963042fbb9fb4d16af0 +# pip scikit-image @ https://files.pythonhosted.org/packages/82/e7/c2ac9801403de908462437c05485c806ae8744edcf8d640862f9501e0c48/scikit_image-0.20.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=b856efc75e3051bea6d40a8ffcdaabd5682783ece1aa91c3f6777c3372a98ca1 +# pip scikit-learn @ https://files.pythonhosted.org/packages/81/84/756be2b975959a5f94124d5584ead75d7ca99184f2d16664a0157b274b9a/scikit_learn-1.2.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=ea061bf0283bf9a9f36ea3c5d3231ba2176221bbd430abd2603b1c3b2ed85c89 +# pip lightgbm @ https://files.pythonhosted.org/packages/38/5c/d9773cf0ea7938f3b777eaacc6f9d58f69ca76a667771364ffefed9095b4/lightgbm-3.3.5-py3-none-manylinux1_x86_64.whl#sha256=044f65664c1a32c98cb619bafa97d8cd9d93c2c2d5053376aadfe509a3a3e7fa # pip pytest-xdist @ https://files.pythonhosted.org/packages/21/08/b1945d4b4986eb1aa10cf84efc5293bba39da80a2f95db3573dd90678408/pytest_xdist-2.5.0-py3-none-any.whl#sha256=6fe5c74fec98906deb8f2d2b616b5c782022744978e7bd4695d39c8f42d0ce65 diff --git a/build_tools/azure/pylatest_pip_scipy_dev_linux-64_conda.lock b/build_tools/azure/pylatest_pip_scipy_dev_linux-64_conda.lock index 79bae626bf65c..151c6e0a62fdb 100644 --- a/build_tools/azure/pylatest_pip_scipy_dev_linux-64_conda.lock +++ b/build_tools/azure/pylatest_pip_scipy_dev_linux-64_conda.lock @@ -3,7 +3,7 @@ # input_hash: 401344e88dad2c8fde3bee9593788afe08d47c9714c6bb772ee8cc2d1cdcc03e @EXPLICIT https://repo.anaconda.com/pkgs/main/linux-64/_libgcc_mutex-0.1-main.conda#c3473ff8bdb3d124ed5ff11ec380d6f9 -https://repo.anaconda.com/pkgs/main/linux-64/ca-certificates-2022.10.11-h06a4308_0.conda#e9b86b388e2cf59585fefca34037b783 +https://repo.anaconda.com/pkgs/main/linux-64/ca-certificates-2023.01.10-h06a4308_0.conda#7704989a2ccf6c1f5a50c985509841c4 https://repo.anaconda.com/pkgs/main/linux-64/ld_impl_linux-64-2.38-h1181459_1.conda#68eedfd9c06f2b0e6888d8db345b7f5b https://repo.anaconda.com/pkgs/main/noarch/tzdata-2022g-h04d1e81_0.conda#833facc4bfeebcb61babe76257e8c9e8 https://repo.anaconda.com/pkgs/main/linux-64/libgomp-11.2.0-h1234567_1.conda#b372c0eea9b60732fdae4b817a63c8cd @@ -13,15 +13,15 @@ https://repo.anaconda.com/pkgs/main/linux-64/libgcc-ng-11.2.0-h1234567_1.conda#a https://repo.anaconda.com/pkgs/main/linux-64/bzip2-1.0.8-h7b6447c_0.conda#9303f4af7c004e069bae22bde8d800ee https://repo.anaconda.com/pkgs/main/linux-64/libffi-3.4.2-h6a678d5_6.conda#6d65e299b535d3b3613b6d4bce901834 https://repo.anaconda.com/pkgs/main/linux-64/libuuid-1.41.5-h5eee18b_0.conda#4a6a2354414c9080327274aa514e5299 -https://repo.anaconda.com/pkgs/main/linux-64/ncurses-6.3-h5eee18b_3.conda#0c616f387885c1bbb57ec0bd1e779ced -https://repo.anaconda.com/pkgs/main/linux-64/openssl-1.1.1s-h7f8727e_0.conda#25f9c4e2394976be98d01cccef2ce43a -https://repo.anaconda.com/pkgs/main/linux-64/xz-5.2.8-h5eee18b_0.conda#224260858072f0071140ae18c513620d +https://repo.anaconda.com/pkgs/main/linux-64/ncurses-6.4-h6a678d5_0.conda#5558eec6e2191741a92f832ea826251c +https://repo.anaconda.com/pkgs/main/linux-64/openssl-1.1.1t-h7f8727e_0.conda#0410db682c02665511bd4203ade48a32 +https://repo.anaconda.com/pkgs/main/linux-64/xz-5.2.10-h5eee18b_1.conda#dd172c348274807ec0d841df8295b670 https://repo.anaconda.com/pkgs/main/linux-64/zlib-1.2.13-h5eee18b_0.conda#333e31fbfbb5057c92fa845ad6adef93 https://repo.anaconda.com/pkgs/main/linux-64/ccache-3.7.9-hfe4627d_0.conda#bef6fc681c273bb7bd0c67d1a591365e https://repo.anaconda.com/pkgs/main/linux-64/readline-8.2-h5eee18b_0.conda#be42180685cce6e6b0329201d9f48efb https://repo.anaconda.com/pkgs/main/linux-64/tk-8.6.12-h1ccaba5_0.conda#fa10ff4aa631fa4aa090a6234d7770b9 https://repo.anaconda.com/pkgs/main/linux-64/sqlite-3.40.1-h5082296_0.conda#7d44bb7460f1b1b0764d63240d7f7f81 -https://repo.anaconda.com/pkgs/main/linux-64/python-3.10.8-h7a1cb2a_1.conda#c50aebbb632aea22b13bd654dfe80a5b +https://repo.anaconda.com/pkgs/main/linux-64/python-3.10.9-h7a1cb2a_2.conda#6f7b15ceb8bbfbadbd8574ceb3912328 https://repo.anaconda.com/pkgs/main/noarch/alabaster-0.7.12-pyhd3eb1b0_0.tar.bz2#21ad3b69a5ce6c22e724e9dbb4cffa65 https://repo.anaconda.com/pkgs/main/linux-64/certifi-2022.12.7-py310h06a4308_0.conda#1f28faeb97a361c9998090edc4e7d729 https://repo.anaconda.com/pkgs/main/noarch/charset-normalizer-2.0.4-pyhd3eb1b0_0.conda#e7a441d94234b2b5fafee06e25dbf076 @@ -42,34 +42,34 @@ https://repo.anaconda.com/pkgs/main/noarch/sphinxcontrib-htmlhelp-2.0.0-pyhd3eb1 https://repo.anaconda.com/pkgs/main/noarch/sphinxcontrib-jsmath-1.0.1-pyhd3eb1b0_0.tar.bz2#e43f8de7d6a717935ab220a0c957771d https://repo.anaconda.com/pkgs/main/noarch/sphinxcontrib-qthelp-1.0.3-pyhd3eb1b0_0.tar.bz2#08d67f73f640b4d1e5e8890a324b60e3 https://repo.anaconda.com/pkgs/main/noarch/sphinxcontrib-serializinghtml-1.1.5-pyhd3eb1b0_0.conda#0440b84dfd478f340cf14c2d7c24f6c7 -https://repo.anaconda.com/pkgs/main/noarch/wheel-0.37.1-pyhd3eb1b0_0.conda#ab85e96e26da8d5797c2458232338b86 +https://repo.anaconda.com/pkgs/main/linux-64/wheel-0.38.4-py310h06a4308_0.conda#fbb0a31c9dbe6a43fd4a8c6abe744890 https://repo.anaconda.com/pkgs/main/linux-64/babel-2.11.0-py310h06a4308_0.conda#1eff25d9f192342c01d960c6bae79c32 https://repo.anaconda.com/pkgs/main/linux-64/cffi-1.15.1-py310h5eee18b_3.conda#d65505a7028c5cb1d6a078fa688be2be https://repo.anaconda.com/pkgs/main/linux-64/jinja2-3.1.2-py310h06a4308_0.conda#f22cc11648fc31b2cebaafed2dd8d5ec https://repo.anaconda.com/pkgs/main/linux-64/setuptools-65.6.3-py310h06a4308_0.conda#d8331a85881df5712194edf67638cf08 https://repo.anaconda.com/pkgs/main/linux-64/brotlipy-0.7.0-py310h7f8727e_1002.conda#a8dfa5aefcc49d5e78000b16d2b7714e -https://repo.anaconda.com/pkgs/main/linux-64/cryptography-38.0.4-py310h9ce1e76_0.conda#f75cc72c0e3460f6959f68171721c74f -https://repo.anaconda.com/pkgs/main/linux-64/pip-22.3.1-py310h06a4308_0.conda#3e3d6059e30595fba64fccb77f9044f0 -https://repo.anaconda.com/pkgs/main/noarch/pyopenssl-22.0.0-pyhd3eb1b0_0.conda#1dbbf9422269cd62c7094960d9b43f36 -https://repo.anaconda.com/pkgs/main/linux-64/urllib3-1.26.13-py310h06a4308_0.conda#01a21b6deb69cf39894c174790c3264f -https://repo.anaconda.com/pkgs/main/linux-64/requests-2.28.1-py310h06a4308_0.conda#40bbc3476dde7f941c78c2b10fd73166 +https://repo.anaconda.com/pkgs/main/linux-64/cryptography-39.0.1-py310h9ce1e76_0.conda#71f493886ed29220fb1b6e60ae511e68 +https://repo.anaconda.com/pkgs/main/linux-64/pip-23.0.1-py310h06a4308_0.conda#f8f27960f21f51c3945fae93e2993e85 +https://repo.anaconda.com/pkgs/main/linux-64/pyopenssl-23.0.0-py310h06a4308_0.conda#be4c8fd04572aabe5c4cf6f80cfcb1b8 +https://repo.anaconda.com/pkgs/main/linux-64/urllib3-1.26.14-py310h06a4308_0.conda#e0b4cfc539954199295eda612157b195 +https://repo.anaconda.com/pkgs/main/linux-64/requests-2.28.1-py310h06a4308_1.conda#65a9f765635f12679cbfff91d8ebed8e https://repo.anaconda.com/pkgs/main/linux-64/sphinx-5.0.2-py310h06a4308_0.conda#9636e58b351ac5c4cc8367bcc0c29321 -# pip appdirs @ https://files.pythonhosted.org/packages/3b/00/2344469e2084fb287c2e0b57b72910309874c3245463acd6cf5e3db69324/appdirs-1.4.4-py2.py3-none-any.whl#sha256=a841dacd6b99318a741b166adb07e19ee71a274450e68237b4650ca1055ab128 # pip attrs @ https://files.pythonhosted.org/packages/fb/6e/6f83bf616d2becdf333a1640f1d463fef3150e2e926b7010cb0f81c95e88/attrs-22.2.0-py3-none-any.whl#sha256=29e95c7f6778868dbd49170f98f8818f78f3dc5e0e37c0b1f474e3561b240836 -# pip exceptiongroup @ https://files.pythonhosted.org/packages/e8/14/9c6a7e5f12294ccd6975a45e02899ed25468cd7c2c86f3d9725f387f9f5f/exceptiongroup-1.1.0-py3-none-any.whl#sha256=327cbda3da756e2de031a3107b81ab7b3770a602c4d16ca618298c526f4bec1e +# pip exceptiongroup @ https://files.pythonhosted.org/packages/61/97/17ed81b7a8d24d8f69b62c0db37abbd8c0042d4b3fc429c73dab986e7483/exceptiongroup-1.1.1-py3-none-any.whl#sha256=232c37c63e4f682982c8b6459f33a8981039e5fb8756b2074364e5055c498c9e # pip execnet @ https://files.pythonhosted.org/packages/81/c0/3072ecc23f4c5e0a1af35e3a222855cfd9c80a1a105ca67be3b6172637dd/execnet-1.9.0-py2.py3-none-any.whl#sha256=a295f7cc774947aac58dde7fdc85f4aa00c42adf5d8f5468fc630c1acf30a142 # pip iniconfig @ https://files.pythonhosted.org/packages/ef/a6/62565a6e1cf69e10f5727360368e451d4b7f58beeac6173dc9db836a5b46/iniconfig-2.0.0-py3-none-any.whl#sha256=b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374 +# pip platformdirs @ https://files.pythonhosted.org/packages/7b/e1/593f693096c50411a2bf9571f66bc3be9d0f79a4a50e95aab581458b0e3c/platformdirs-3.1.1-py3-none-any.whl#sha256=e5986afb596e4bb5bde29a79ac9061aa955b94fca2399b7aaac4090860920dd8 # pip pluggy @ https://files.pythonhosted.org/packages/9e/01/f38e2ff29715251cf25532b9082a1589ab7e4f571ced434f98d0139336dc/pluggy-1.0.0-py2.py3-none-any.whl#sha256=74134bbf457f031a36d68416e1509f34bd5ccc019f0bcc952c7b909d06b37bd3 # pip py @ https://files.pythonhosted.org/packages/f6/f0/10642828a8dfb741e5f3fbaac830550a518a775c7fff6f04a007259b0548/py-1.11.0-py2.py3-none-any.whl#sha256=607c53218732647dff4acdfcd50cb62615cedf612e72d1724fb1a0cc6405b378 # pip six @ https://files.pythonhosted.org/packages/d9/5a/e7c31adbe875f2abbb91bd84cf2dc52d792b5a01506781dbcf25c91daf11/six-1.16.0-py2.py3-none-any.whl#sha256=8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254 # pip threadpoolctl @ https://files.pythonhosted.org/packages/61/cf/6e354304bcb9c6413c4e02a747b600061c21d38ba51e7e544ac7bc66aecc/threadpoolctl-3.1.0-py3-none-any.whl#sha256=8b99adda265feb6773280df41eece7b2e6561b772d21ffd52e372f999024907b # pip tomli @ https://files.pythonhosted.org/packages/97/75/10a9ebee3fd790d20926a90a2547f0bf78f371b2f13aa822c759680ca7b9/tomli-2.0.1-py3-none-any.whl#sha256=939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc -# pip coverage @ https://files.pythonhosted.org/packages/01/01/8d17427fbeb0ee132111c543bfeea5ab403d6869812cf6085adc18debecf/coverage-7.0.5-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=a9fed35ca8c6e946e877893bbac022e8563b94404a605af1d1e6accc7eb73289 +# pip coverage @ https://files.pythonhosted.org/packages/f3/ff/0bf7a9497dc91e4b0f11656a50c95fd1e641d912a281a0b0921d20fa5760/coverage-7.2.1-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=b2167d116309f564af56f9aa5e75ef710ef871c5f9b313a83050035097b56820 # pip numpydoc @ https://files.pythonhosted.org/packages/c4/81/ad9b8837442ff451eca82515b41ac425f87acff7e2fc016fd1bda13fc01a/numpydoc-1.5.0-py3-none-any.whl#sha256=c997759fb6fc32662801cece76491eedbc0ec619b514932ffd2b270ae89c07f9 -# pip pooch @ https://files.pythonhosted.org/packages/8d/64/8e1bfeda3ba0f267b2d9a918e8ca51db8652d0e1a3412a5b3dbce85d90b6/pooch-1.6.0-py3-none-any.whl#sha256=3bf0e20027096836b8dbce0152dbb785a269abeb621618eb4bdd275ff1e23c9c -# pip pytest @ https://files.pythonhosted.org/packages/cc/02/8f59bf194c9a1ceac6330850715e9ec11e21e2408a30a596c65d54cf4d2a/pytest-7.2.1-py3-none-any.whl#sha256=c7c6ca206e93355074ae32f7403e8ea12163b1163c976fee7d4d84027c162be5 +# pip pooch @ https://files.pythonhosted.org/packages/84/8c/4da580db7fb4cfce8f5ed78e7d2aa542e6f201edd69d3d8a96917a8ff63c/pooch-1.7.0-py3-none-any.whl#sha256=74258224fc33d58f53113cf955e8d51bf01386b91492927d0d1b6b341a765ad7 +# pip pytest @ https://files.pythonhosted.org/packages/b2/68/5321b5793bd506961bd40bdbdd0674e7de4fb873ee7cab33dd27283ad513/pytest-7.2.2-py3-none-any.whl#sha256=130328f552dcfac0b1cec75c12e3f005619dc5f874f0a06e8ff7263f0ee6225e # pip python-dateutil @ https://files.pythonhosted.org/packages/36/7a/87837f39d0296e723bb9b62bbb257d0355c7f6128853c78955f57342a56d/python_dateutil-2.8.2-py2.py3-none-any.whl#sha256=961d03dc3453ebbc59dbdea9e4e11c5651520a876d0f4db161e8674aae935da9 # pip codecov @ https://files.pythonhosted.org/packages/dc/e2/964d0881eff5a67bf5ddaea79a13c7b34a74bc4efe917b368830b475a0b9/codecov-2.1.12-py2.py3-none-any.whl#sha256=585dc217dc3d8185198ceb402f85d5cb5dbfa0c5f350a5abcdf9e347776a5b47 # pip pytest-cov @ https://files.pythonhosted.org/packages/fe/1f/9ec0ddd33bd2b37d6ec50bb39155bca4fe7085fa78b3b434c05459a860e3/pytest_cov-4.0.0-py3-none-any.whl#sha256=2feb1b751d66a8bd934e5edfa2e961d11309dc37b73b0eabe73b5945fee20f6b -# pip pytest-forked @ https://files.pythonhosted.org/packages/0c/36/c56ef2aea73912190cdbcc39aaa860db8c07c1a5ce8566994ec9425453db/pytest_forked-1.4.0-py3-none-any.whl#sha256=bbbb6717efc886b9d64537b41fb1497cfaf3c9601276be8da2cccfea5a3c8ad8 +# pip pytest-forked @ https://files.pythonhosted.org/packages/f4/af/9c0bda43e486a3c9bf1e0f876d0f241bc3f229d7d65d09331a0868db9629/pytest_forked-1.6.0-py3-none-any.whl#sha256=810958f66a91afb1a1e2ae83089d8dc1cd2437ac96b12963042fbb9fb4d16af0 # pip pytest-xdist @ https://files.pythonhosted.org/packages/21/08/b1945d4b4986eb1aa10cf84efc5293bba39da80a2f95db3573dd90678408/pytest_xdist-2.5.0-py3-none-any.whl#sha256=6fe5c74fec98906deb8f2d2b616b5c782022744978e7bd4695d39c8f42d0ce65 diff --git a/build_tools/azure/pypy3_linux-64_conda.lock 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+https://conda.anaconda.org/conda-forge/linux-64/scipy-1.10.1-py39h60c9533_0.conda#5ffadbb1f4fa2758c57ec1579bc3e953 +https://conda.anaconda.org/conda-forge/linux-64/pyamg-4.2.3-py39hcf8a7be_2.conda#f7a209fe66831b3e3d216b90c2fc9d8a diff --git a/build_tools/azure/ubuntu_atlas_lock.txt b/build_tools/azure/ubuntu_atlas_lock.txt index 9f5973a1ccd53..e5233159eb8b6 100644 --- a/build_tools/azure/ubuntu_atlas_lock.txt +++ b/build_tools/azure/ubuntu_atlas_lock.txt @@ -8,7 +8,7 @@ attrs==22.2.0 # via pytest cython==0.29.33 # via -r build_tools/azure/ubuntu_atlas_requirements.txt -exceptiongroup==1.1.0 +exceptiongroup==1.1.1 # via pytest execnet==1.9.0 # via pytest-xdist @@ -22,12 +22,12 @@ pluggy==1.0.0 # via pytest py==1.11.0 # via pytest-forked -pytest==7.2.1 +pytest==7.2.2 # via # -r build_tools/azure/ubuntu_atlas_requirements.txt # pytest-forked # pytest-xdist -pytest-forked==1.4.0 +pytest-forked==1.6.0 # via pytest-xdist pytest-xdist==2.5.0 # via -r build_tools/azure/ubuntu_atlas_requirements.txt diff --git a/build_tools/circle/doc_environment.yml b/build_tools/circle/doc_environment.yml index ac12c221f317c..0c441a5266906 100644 --- a/build_tools/circle/doc_environment.yml +++ b/build_tools/circle/doc_environment.yml @@ -27,6 +27,5 @@ dependencies: - sphinx-prompt - plotly - pooch + - sphinxext-opengraph - pip - - pip: - - sphinxext-opengraph diff --git a/build_tools/circle/doc_linux-64_conda.lock b/build_tools/circle/doc_linux-64_conda.lock index 0ea1329d35098..74d96ab9de6bb 100644 --- a/build_tools/circle/doc_linux-64_conda.lock +++ b/build_tools/circle/doc_linux-64_conda.lock @@ -1,6 +1,6 @@ # Generated by conda-lock. # platform: linux-64 -# input_hash: ab71a4d47c35d849da7211030836aa7c50d7363575d5a9b000dff69b667208f0 +# input_hash: e94308f010347872a13f1dc0dcc6b19de98bc55b7a0f75b0102c299b78e8b31d @EXPLICIT https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2#d7c89558ba9fa0495403155b64376d81 https://conda.anaconda.org/conda-forge/linux-64/ca-certificates-2022.12.7-ha878542_0.conda#ff9f73d45c4a07d6f424495288a26080 @@ -36,11 +36,10 @@ https://conda.anaconda.org/conda-forge/linux-64/dav1d-1.0.0-h166bdaf_1.tar.bz2#e https://conda.anaconda.org/conda-forge/linux-64/expat-2.5.0-h27087fc_0.tar.bz2#c4fbad8d4bddeb3c085f18cbf97fbfad https://conda.anaconda.org/conda-forge/linux-64/fftw-3.3.10-nompi_hf0379b8_106.conda#d7407e695358f068a2a7f8295cde0567 https://conda.anaconda.org/conda-forge/linux-64/gettext-0.21.1-h27087fc_0.tar.bz2#14947d8770185e5153fdd04d4673ed37 -https://conda.anaconda.org/conda-forge/linux-64/giflib-5.2.1-h36c2ea0_2.tar.bz2#626e68ae9cc5912d6adb79d318cf962d +https://conda.anaconda.org/conda-forge/linux-64/giflib-5.2.1-h0b41bf4_3.conda#96f3b11872ef6fad973eac856cd2624f https://conda.anaconda.org/conda-forge/linux-64/graphite2-1.3.13-h58526e2_1001.tar.bz2#8c54672728e8ec6aa6db90cf2806d220 https://conda.anaconda.org/conda-forge/linux-64/gstreamer-orc-0.4.33-h166bdaf_0.tar.bz2#879c93426c9d0b84a9de4513fbce5f4f https://conda.anaconda.org/conda-forge/linux-64/icu-70.1-h27087fc_0.tar.bz2#87473a15119779e021c314249d4b4aed -https://conda.anaconda.org/conda-forge/linux-64/jpeg-9e-h166bdaf_2.tar.bz2#ee8b844357a0946870901c7c6f418268 https://conda.anaconda.org/conda-forge/linux-64/jxrlib-1.1-h7f98852_2.tar.bz2#8e787b08fe19986d99d034b839df2961 https://conda.anaconda.org/conda-forge/linux-64/keyutils-1.6.1-h166bdaf_0.tar.bz2#30186d27e2c9fa62b45fb1476b7200e3 https://conda.anaconda.org/conda-forge/linux-64/lame-3.100-h166bdaf_1003.tar.bz2#a8832b479f93521a9e7b5b743803be51 @@ -52,39 +51,41 @@ https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.17-h0b41bf4_0.conda https://conda.anaconda.org/conda-forge/linux-64/libev-4.33-h516909a_1.tar.bz2#6f8720dff19e17ce5d48cfe7f3d2f0a3 https://conda.anaconda.org/conda-forge/linux-64/libffi-3.4.2-h7f98852_5.tar.bz2#d645c6d2ac96843a2bfaccd2d62b3ac3 https://conda.anaconda.org/conda-forge/linux-64/libiconv-1.17-h166bdaf_0.tar.bz2#b62b52da46c39ee2bc3c162ac7f1804d -https://conda.anaconda.org/conda-forge/linux-64/libjpeg-turbo-2.1.4-h166bdaf_0.tar.bz2#b4f717df2d377410b462328bf0e8fb7d +https://conda.anaconda.org/conda-forge/linux-64/libjpeg-turbo-2.1.5.1-h0b41bf4_0.conda#1edd9e67bdb90d78cea97733ff6b54e6 https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.0-h7f98852_0.tar.bz2#39b1328babf85c7c3a61636d9cd50206 https://conda.anaconda.org/conda-forge/linux-64/libogg-1.3.4-h7f98852_1.tar.bz2#6e8cc2173440d77708196c5b93771680 https://conda.anaconda.org/conda-forge/linux-64/libopenblas-0.3.21-pthreads_h78a6416_3.tar.bz2#8c5963a49b6035c40646a763293fbb35 https://conda.anaconda.org/conda-forge/linux-64/libopus-1.3.1-h7f98852_1.tar.bz2#15345e56d527b330e1cacbdf58676e8f https://conda.anaconda.org/conda-forge/linux-64/libsanitizer-11.3.0-h239ccf8_19.tar.bz2#d17fd55aed84ab6592c5419b6600501c https://conda.anaconda.org/conda-forge/linux-64/libtool-2.4.7-h27087fc_0.conda#f204c8ba400ec475452737094fb81d52 -https://conda.anaconda.org/conda-forge/linux-64/libudev1-252-h166bdaf_0.tar.bz2#174243089ec111479298a5b7099b64b5 +https://conda.anaconda.org/conda-forge/linux-64/libudev1-253-h0b41bf4_0.conda#6c2addbd9aa4ee47c76d50c9f0df8cd6 https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.32.1-h7f98852_1000.tar.bz2#772d69f030955d9646d3d0eaf21d859d -https://conda.anaconda.org/conda-forge/linux-64/libwebp-base-1.2.4-h166bdaf_0.tar.bz2#ac2ccf7323d21f2994e4d1f5da664f37 +https://conda.anaconda.org/conda-forge/linux-64/libwebp-base-1.3.0-h0b41bf4_0.conda#0d4a7508d8c6c65314f2b9c1f56ad408 https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.2.13-h166bdaf_4.tar.bz2#f3f9de449d32ca9b9c66a22863c96f41 https://conda.anaconda.org/conda-forge/linux-64/libzopfli-1.0.3-h9c3ff4c_0.tar.bz2#c66fe2d123249af7651ebde8984c51c2 https://conda.anaconda.org/conda-forge/linux-64/lz4-c-1.9.4-hcb278e6_0.conda#318b08df404f9c9be5712aaa5a6f0bb0 https://conda.anaconda.org/conda-forge/linux-64/mpg123-1.31.2-hcb278e6_0.conda#08efb1e1813f1a151b7a945b972a049b https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.3-h27087fc_1.tar.bz2#4acfc691e64342b9dae57cf2adc63238 https://conda.anaconda.org/conda-forge/linux-64/nspr-4.35-h27087fc_0.conda#da0ec11a6454ae19bff5b02ed881a2b1 -https://conda.anaconda.org/conda-forge/linux-64/openssl-3.0.7-h0b41bf4_2.conda#45758f4ece9c8b7b5f99328bd5caae51 +https://conda.anaconda.org/conda-forge/linux-64/openssl-3.0.8-h0b41bf4_0.conda#e043403cd18faf815bf7705ab6c1e092 https://conda.anaconda.org/conda-forge/linux-64/pixman-0.40.0-h36c2ea0_0.tar.bz2#660e72c82f2e75a6b3fe6a6e75c79f19 https://conda.anaconda.org/conda-forge/linux-64/pthread-stubs-0.4-h36c2ea0_1001.tar.bz2#22dad4df6e8630e8dff2428f6f6a7036 -https://conda.anaconda.org/conda-forge/linux-64/snappy-1.1.9-hbd366e4_2.tar.bz2#48018e187dacc6002d3ede9c824238ac +https://conda.anaconda.org/conda-forge/linux-64/snappy-1.1.10-h9fff704_0.conda#e6d228cd0bb74a51dd18f5bfce0b4115 +https://conda.anaconda.org/conda-forge/linux-64/xkeyboard-config-2.38-h0b41bf4_0.conda#9ac34337e5101a87e5d91da05d84aa48 https://conda.anaconda.org/conda-forge/linux-64/xorg-kbproto-1.0.7-h7f98852_1002.tar.bz2#4b230e8381279d76131116660f5a241a https://conda.anaconda.org/conda-forge/linux-64/xorg-libice-1.0.10-h7f98852_0.tar.bz2#d6b0b50b49eccfe0be0373be628be0f3 https://conda.anaconda.org/conda-forge/linux-64/xorg-libxau-1.0.9-h7f98852_0.tar.bz2#bf6f803a544f26ebbdc3bfff272eb179 https://conda.anaconda.org/conda-forge/linux-64/xorg-libxdmcp-1.1.3-h7f98852_0.tar.bz2#be93aabceefa2fac576e971aef407908 https://conda.anaconda.org/conda-forge/linux-64/xorg-renderproto-0.11.1-h7f98852_1002.tar.bz2#06feff3d2634e3097ce2fe681474b534 -https://conda.anaconda.org/conda-forge/linux-64/xorg-xextproto-7.3.0-h7f98852_1002.tar.bz2#1e15f6ad85a7d743a2ac68dae6c82b98 +https://conda.anaconda.org/conda-forge/linux-64/xorg-xextproto-7.3.0-h0b41bf4_1003.conda#bce9f945da8ad2ae9b1d7165a64d0f87 +https://conda.anaconda.org/conda-forge/linux-64/xorg-xf86vidmodeproto-2.3.1-h7f98852_1002.tar.bz2#3ceea9668625c18f19530de98b15d5b0 https://conda.anaconda.org/conda-forge/linux-64/xorg-xproto-7.0.31-h7f98852_1007.tar.bz2#b4a4381d54784606820704f7b5f05a15 https://conda.anaconda.org/conda-forge/linux-64/xz-5.2.6-h166bdaf_0.tar.bz2#2161070d867d1b1204ea749c8eec4ef0 https://conda.anaconda.org/conda-forge/linux-64/yaml-0.2.5-h7f98852_2.tar.bz2#4cb3ad778ec2d5a7acbdf254eb1c42ae https://conda.anaconda.org/conda-forge/linux-64/zfp-1.0.0-h27087fc_3.tar.bz2#0428af0510c3fafedf1c66b43102a34b https://conda.anaconda.org/conda-forge/linux-64/zlib-ng-2.0.6-h166bdaf_0.tar.bz2#8650e4fb44c4a618e5ab3e1e19607e32 https://conda.anaconda.org/conda-forge/linux-64/gcc_impl_linux-64-11.3.0-hab1b70f_19.tar.bz2#89ac16d36e66ccb9ca5d34c9217e5799 -https://conda.anaconda.org/conda-forge/linux-64/jack-1.9.21-h583fa2b_2.conda#7b36a10b58964d4444fcba44244710c5 +https://conda.anaconda.org/conda-forge/linux-64/jack-1.9.22-h11f4161_0.conda#504fa9e712b99494a9cf4630e3ca7d78 https://conda.anaconda.org/conda-forge/linux-64/libavif-0.11.1-h5cdd6b5_0.tar.bz2#2040f9067e8852606208cafa66c3563f https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-16_linux64_openblas.tar.bz2#d9b7a8639171f6c6fa0a983edabcfe2b https://conda.anaconda.org/conda-forge/linux-64/libbrotlidec-1.0.9-h166bdaf_8.tar.bz2#4ae4d7795d33e02bd20f6b23d91caf82 @@ -94,7 +95,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libedit-3.1.20191231-he28a2e2_2. https://conda.anaconda.org/conda-forge/linux-64/libevent-2.1.10-h28343ad_4.tar.bz2#4a049fc560e00e43151dc51368915fdd https://conda.anaconda.org/conda-forge/linux-64/libflac-1.4.2-h27087fc_0.tar.bz2#7daf72d8e2a8e848e11d63ed6d1026e0 https://conda.anaconda.org/conda-forge/linux-64/libgpg-error-1.46-h620e276_0.conda#27e745f6f2e4b757e95dd7225fbe6bdb -https://conda.anaconda.org/conda-forge/linux-64/libnghttp2-1.51.0-hff17c54_0.conda#dd682f0b6d65e75b2bc868fc8e93d87e +https://conda.anaconda.org/conda-forge/linux-64/libnghttp2-1.52.0-h61bc06f_0.conda#613955a50485812985c059e7b269f42e https://conda.anaconda.org/conda-forge/linux-64/libpng-1.6.39-h753d276_0.conda#e1c890aebdebbfbf87e2c917187b4416 https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.40.0-h753d276_0.tar.bz2#2e5f9a37d487e1019fd4d8113adb2f9f https://conda.anaconda.org/conda-forge/linux-64/libssh2-1.10.0-hf14f497_3.tar.bz2#d85acad4b47dff4e3def14a769a97906 @@ -112,7 +113,7 @@ https://conda.anaconda.org/conda-forge/linux-64/zlib-1.2.13-h166bdaf_4.tar.bz2#4 https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.2-h3eb15da_6.conda#6b63daed8feeca47be78f323e793d555 https://conda.anaconda.org/conda-forge/linux-64/blosc-1.21.3-hafa529b_0.conda#bcf0664a2dbbbb86cbd4c1e6ff10ddd6 https://conda.anaconda.org/conda-forge/linux-64/brotli-bin-1.0.9-h166bdaf_8.tar.bz2#e5613f2bc717e9945840ff474419b8e4 -https://conda.anaconda.org/conda-forge/linux-64/c-blosc2-2.6.1-hf91038e_0.conda#332b553e1a0d22c318756ffcd370384c +https://conda.anaconda.org/conda-forge/linux-64/c-blosc2-2.7.1-hf91038e_0.conda#3a19cba20d395f47b60b13251eb4e267 https://conda.anaconda.org/conda-forge/linux-64/freetype-2.12.1-hca18f0e_1.conda#e1232042de76d24539a436d37597eb06 https://conda.anaconda.org/conda-forge/linux-64/gcc-11.3.0-h02d0930_11.tar.bz2#6037ebe5f1e3054519ce78b11eec9cd4 https://conda.anaconda.org/conda-forge/linux-64/gcc_linux-64-11.3.0-he6f903b_11.tar.bz2#25f76cb82e483ce96d118b9edffd12c9 @@ -125,18 +126,17 @@ https://conda.anaconda.org/conda-forge/linux-64/libglib-2.74.1-h606061b_1.tar.bz https://conda.anaconda.org/conda-forge/linux-64/liblapack-3.9.0-16_linux64_openblas.tar.bz2#955d993f41f9354bf753d29864ea20ad https://conda.anaconda.org/conda-forge/linux-64/libllvm15-15.0.7-hadd5161_0.conda#70cbb0c2033665f2a7339bf0ec51a67f https://conda.anaconda.org/conda-forge/linux-64/libsndfile-1.2.0-hb75c966_0.conda#c648d19cd9c8625898d5d370414de7c7 -https://conda.anaconda.org/conda-forge/linux-64/libtiff-4.5.0-h6adf6a1_2.conda#2e648a34072eb39d7c4fc2a9981c5f0c -https://conda.anaconda.org/conda-forge/linux-64/libxkbcommon-1.0.3-he3ba5ed_0.tar.bz2#f9dbabc7e01c459ed7a1d1d64b206e9b +https://conda.anaconda.org/conda-forge/linux-64/libtiff-4.5.0-hddfeb54_5.conda#d2343e6594c2a4a654a475a6131ef20d +https://conda.anaconda.org/conda-forge/linux-64/libxkbcommon-1.5.0-h79f4944_1.conda#04a39cdd663f295653fc143851830563 https://conda.anaconda.org/conda-forge/linux-64/mysql-libs-8.0.32-hd7da12d_0.conda#b05d7ea8b76f1172d5fe4f30e03277ea -https://conda.anaconda.org/conda-forge/linux-64/nss-3.82-he02c5a1_0.conda#f8d7f11d19e4cb2207eab159fd4c0152 -https://conda.anaconda.org/conda-forge/linux-64/python-3.9.15-hba424b6_0_cpython.conda#7b9485fce17fac2dd4aca6117a9936c2 +https://conda.anaconda.org/conda-forge/linux-64/nss-3.89-he45b914_0.conda#2745719a58eeaab6657256a3f142f099 +https://conda.anaconda.org/conda-forge/linux-64/python-3.9.16-h2782a2a_0_cpython.conda#95c9b7c96a7fd7342e0c9d0a917b8f78 https://conda.anaconda.org/conda-forge/linux-64/xcb-util-0.4.0-h166bdaf_0.tar.bz2#384e7fcb3cd162ba3e4aed4b687df566 https://conda.anaconda.org/conda-forge/linux-64/xcb-util-keysyms-0.4.0-h166bdaf_0.tar.bz2#637054603bb7594302e3bf83f0a99879 https://conda.anaconda.org/conda-forge/linux-64/xcb-util-renderutil-0.3.9-h166bdaf_0.tar.bz2#732e22f1741bccea861f5668cf7342a7 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remove_from(alist, to_remove): "sphinx-prompt", "plotly", "pooch", + "sphinxext-opengraph", + "pip", ], - "pip_dependencies": ["sphinxext-opengraph"], "package_constraints": { "python": "3.9", # XXX: sphinx > 6.0 does not correctly generate searchindex.js diff --git a/examples/calibration/plot_calibration_curve.py b/examples/calibration/plot_calibration_curve.py index 3ba7c2c6404c7..5f8ad621bc7a8 100644 --- a/examples/calibration/plot_calibration_curve.py +++ b/examples/calibration/plot_calibration_curve.py @@ -78,7 +78,7 @@ # %% fig = plt.figure(figsize=(10, 10)) gs = GridSpec(4, 2) -colors = plt.cm.get_cmap("Dark2") +colors = plt.get_cmap("Dark2") ax_calibration_curve = fig.add_subplot(gs[:2, :2]) calibration_displays = {} diff --git a/examples/calibration/plot_compare_calibration.py b/examples/calibration/plot_compare_calibration.py index 026737ee0e455..cd4782122a07b 100644 --- a/examples/calibration/plot_compare_calibration.py +++ b/examples/calibration/plot_compare_calibration.py @@ -109,7 +109,7 @@ def predict_proba(self, X): fig = plt.figure(figsize=(10, 10)) gs = GridSpec(4, 2) -colors = plt.cm.get_cmap("Dark2") +colors = plt.get_cmap("Dark2") ax_calibration_curve = fig.add_subplot(gs[:2, :2]) calibration_displays = {} diff --git a/examples/svm/plot_svm_margin.py b/examples/svm/plot_svm_margin.py index 9f52881f1faf2..43cef2544721c 100644 --- a/examples/svm/plot_svm_margin.py +++ b/examples/svm/plot_svm_margin.py @@ -20,7 +20,6 @@ import numpy as np import matplotlib.pyplot as plt -from matplotlib import cm from sklearn import svm # we create 40 separable points @@ -65,10 +64,10 @@ facecolors="none", zorder=10, edgecolors="k", - cmap=cm.get_cmap("RdBu"), + cmap=plt.get_cmap("RdBu"), ) plt.scatter( - X[:, 0], X[:, 1], c=Y, zorder=10, cmap=cm.get_cmap("RdBu"), edgecolors="k" + X[:, 0], X[:, 1], c=Y, zorder=10, cmap=plt.get_cmap("RdBu"), edgecolors="k" ) plt.axis("tight") @@ -82,7 +81,7 @@ Z = clf.decision_function(xy).reshape(XX.shape) # Put the result into a contour plot - plt.contourf(XX, YY, Z, cmap=cm.get_cmap("RdBu"), alpha=0.5, linestyles=["-"]) + plt.contourf(XX, YY, Z, cmap=plt.get_cmap("RdBu"), alpha=0.5, linestyles=["-"]) plt.xlim(x_min, x_max) plt.ylim(y_min, y_max) diff --git a/sklearn/_min_dependencies.py b/sklearn/_min_dependencies.py index b06c7fb47afb4..c2314528f5745 100644 --- a/sklearn/_min_dependencies.py +++ b/sklearn/_min_dependencies.py @@ -51,7 +51,7 @@ "plotly": ("5.10.0", "docs, examples"), # XXX: Pin conda-lock to the latest released version (needs manual update # from time to time) - "conda-lock": ("1.3.0", "maintenance"), + "conda-lock": ("1.4.0", "maintenance"), } diff --git a/sklearn/metrics/_plot/tests/test_confusion_matrix_display.py b/sklearn/metrics/_plot/tests/test_confusion_matrix_display.py index fd70be4fbc07e..48b7a44f39ea8 100644 --- a/sklearn/metrics/_plot/tests/test_confusion_matrix_display.py +++ b/sklearn/metrics/_plot/tests/test_confusion_matrix_display.py @@ -333,10 +333,7 @@ def test_confusion_matrix_with_unknown_labels(pyplot, constructor_name): def test_colormap_max(pyplot): """Check that the max color is used for the color of the text.""" - - from matplotlib import cm - - gray = cm.get_cmap("gray", 1024) + gray = pyplot.get_cmap("gray", 1024) confusion_matrix = np.array([[1.0, 0.0], [0.0, 1.0]]) disp = ConfusionMatrixDisplay(confusion_matrix) From a40da6d6a18344b6d00820245ab0dc95edf93816 Mon Sep 17 00:00:00 2001 From: zeeshan lone <56621467+still-learning-ev@users.noreply.github.com> Date: Wed, 15 Mar 2023 20:48:26 +0530 Subject: [PATCH 2/9] MAINT Added Parameter Validation for metrics.mean_gamma_deviance (#25853) --- sklearn/metrics/_regression.py | 7 +++++++ sklearn/tests/test_public_functions.py | 1 + 2 files changed, 8 insertions(+) diff --git a/sklearn/metrics/_regression.py b/sklearn/metrics/_regression.py index 70a3303a4770d..d4337cad59984 100644 --- a/sklearn/metrics/_regression.py +++ b/sklearn/metrics/_regression.py @@ -1186,6 +1186,13 @@ def mean_poisson_deviance(y_true, y_pred, *, sample_weight=None): return mean_tweedie_deviance(y_true, y_pred, sample_weight=sample_weight, power=1) +@validate_params( + { + "y_true": ["array-like"], + "y_pred": ["array-like"], + "sample_weight": ["array-like", None], + } +) def mean_gamma_deviance(y_true, y_pred, *, sample_weight=None): """Mean Gamma deviance regression loss. diff --git a/sklearn/tests/test_public_functions.py b/sklearn/tests/test_public_functions.py index a9fff191b06a7..84c15bf25c389 100644 --- a/sklearn/tests/test_public_functions.py +++ b/sklearn/tests/test_public_functions.py @@ -152,6 +152,7 @@ def _check_function_param_validation( "sklearn.metrics.max_error", "sklearn.metrics.mean_absolute_error", "sklearn.metrics.mean_absolute_percentage_error", + "sklearn.metrics.mean_gamma_deviance", "sklearn.metrics.mean_pinball_loss", "sklearn.metrics.mean_squared_error", "sklearn.metrics.mean_tweedie_deviance", From 530dfc9631b2135412a048b5ec7cf01d155b6067 Mon Sep 17 00:00:00 2001 From: Benedek Harsanyi <80836204+hbenedek@users.noreply.github.com> Date: Wed, 15 Mar 2023 16:33:20 +0100 Subject: [PATCH 3/9] MAINT Parameters validation for feature_selection.mutual_info_regression (#25850) --- sklearn/feature_selection/_mutual_info.py | 10 ++++++++++ sklearn/tests/test_public_functions.py | 1 + 2 files changed, 11 insertions(+) diff --git a/sklearn/feature_selection/_mutual_info.py b/sklearn/feature_selection/_mutual_info.py index f353d78acf4c4..9cacfc3890784 100644 --- a/sklearn/feature_selection/_mutual_info.py +++ b/sklearn/feature_selection/_mutual_info.py @@ -311,6 +311,16 @@ def _estimate_mi( return np.array(mi) +@validate_params( + { + "X": ["array-like", "sparse matrix"], + "y": ["array-like"], + "discrete_features": [StrOptions({"auto"}), "boolean", "array-like"], + "n_neighbors": [Interval(Integral, 1, None, closed="left")], + "copy": ["boolean"], + "random_state": ["random_state"], + } +) def mutual_info_regression( X, y, *, discrete_features="auto", n_neighbors=3, copy=True, random_state=None ): diff --git a/sklearn/tests/test_public_functions.py b/sklearn/tests/test_public_functions.py index 84c15bf25c389..ea1b64cda62f9 100644 --- a/sklearn/tests/test_public_functions.py +++ b/sklearn/tests/test_public_functions.py @@ -125,6 +125,7 @@ def _check_function_param_validation( "sklearn.feature_selection.f_classif", "sklearn.feature_selection.f_regression", "sklearn.feature_selection.mutual_info_classif", + "sklearn.feature_selection.mutual_info_regression", "sklearn.feature_selection.r_regression", "sklearn.linear_model.orthogonal_mp", "sklearn.metrics.accuracy_score", From 36bb7e56ab73dc4a56457c5f4a7c8af2a65124a1 Mon Sep 17 00:00:00 2001 From: Pooja Subramaniam Date: Wed, 15 Mar 2023 19:10:29 +0100 Subject: [PATCH 4/9] MAINT parameter validation metrics.class_likelihood_ratios (#25863) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> --- sklearn/metrics/_classification.py | 9 +++++++++ sklearn/tests/test_public_functions.py | 1 + 2 files changed, 10 insertions(+) diff --git a/sklearn/metrics/_classification.py b/sklearn/metrics/_classification.py index 9aba3f57a54e6..5fb5c0c3e69e6 100644 --- a/sklearn/metrics/_classification.py +++ b/sklearn/metrics/_classification.py @@ -1761,6 +1761,15 @@ def precision_recall_fscore_support( return precision, recall, f_score, true_sum +@validate_params( + { + "y_true": ["array-like", "sparse matrix"], + "y_pred": ["array-like", "sparse matrix"], + "labels": ["array-like", None], + "sample_weight": ["array-like", None], + "raise_warning": ["boolean"], + } +) def class_likelihood_ratios( y_true, y_pred, diff --git a/sklearn/tests/test_public_functions.py b/sklearn/tests/test_public_functions.py index ea1b64cda62f9..b15685eaf122f 100644 --- a/sklearn/tests/test_public_functions.py +++ b/sklearn/tests/test_public_functions.py @@ -133,6 +133,7 @@ def _check_function_param_validation( "sklearn.metrics.average_precision_score", "sklearn.metrics.balanced_accuracy_score", "sklearn.metrics.brier_score_loss", + "sklearn.metrics.class_likelihood_ratios", "sklearn.metrics.cluster.contingency_matrix", "sklearn.metrics.cohen_kappa_score", "sklearn.metrics.confusion_matrix", From 9d558355748ce56718242e5a611a5e6611d6ec67 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?J=C3=A9r=C3=A9mie=20du=20Boisberranger?= <34657725+jeremiedbb@users.noreply.github.com> Date: Wed, 15 Mar 2023 19:44:09 +0100 Subject: [PATCH 5/9] MAINT Ensure disjoint interval constraints (#25797) --- sklearn/cluster/_optics.py | 15 +- sklearn/cluster/tests/test_optics.py | 2 +- sklearn/decomposition/_pca.py | 3 +- sklearn/ensemble/_bagging.py | 7 +- sklearn/ensemble/_forest.py | 3 +- .../gradient_boosting.py | 3 +- sklearn/ensemble/_iforest.py | 3 +- sklearn/feature_extraction/image.py | 7 +- sklearn/feature_extraction/text.py | 7 +- sklearn/feature_selection/_rfe.py | 7 +- sklearn/feature_selection/_sequential.py | 3 +- sklearn/linear_model/_ransac.py | 3 +- sklearn/model_selection/_split.py | 5 +- sklearn/preprocessing/_encoders.py | 5 +- sklearn/tests/test_public_functions.py | 18 +- sklearn/tree/_classes.py | 7 +- sklearn/utils/_param_validation.py | 165 +++++------------- sklearn/utils/estimator_checks.py | 20 ++- sklearn/utils/tests/test_param_validation.py | 83 ++++----- 19 files changed, 168 insertions(+), 198 deletions(-) diff --git a/sklearn/cluster/_optics.py b/sklearn/cluster/_optics.py index fb8daa4db1226..0dd5fb7f7daad 100755 --- a/sklearn/cluster/_optics.py +++ b/sklearn/cluster/_optics.py @@ -20,6 +20,7 @@ from ..metrics.pairwise import _VALID_METRICS from ..utils import gen_batches, get_chunk_n_rows from ..utils._param_validation import Interval, HasMethods, StrOptions, validate_params +from ..utils._param_validation import RealNotInt from ..utils.validation import check_memory from ..neighbors import NearestNeighbors from ..base import BaseEstimator, ClusterMixin @@ -233,7 +234,7 @@ class OPTICS(ClusterMixin, BaseEstimator): _parameter_constraints: dict = { "min_samples": [ Interval(Integral, 2, None, closed="left"), - Interval(Real, 0, 1, closed="both"), + Interval(RealNotInt, 0, 1, closed="both"), ], "max_eps": [Interval(Real, 0, None, closed="both")], "metric": [StrOptions(set(_VALID_METRICS) | {"precomputed"}), callable], @@ -245,7 +246,7 @@ class OPTICS(ClusterMixin, BaseEstimator): "predecessor_correction": ["boolean"], "min_cluster_size": [ Interval(Integral, 2, None, closed="left"), - Interval(Real, 0, 1, closed="right"), + Interval(RealNotInt, 0, 1, closed="right"), None, ], "algorithm": [StrOptions({"auto", "brute", "ball_tree", "kd_tree"})], @@ -431,7 +432,7 @@ def _compute_core_distances_(X, neighbors, min_samples, working_memory): "X": [np.ndarray, "sparse matrix"], "min_samples": [ Interval(Integral, 2, None, closed="left"), - Interval(Real, 0, 1, closed="both"), + Interval(RealNotInt, 0, 1, closed="both"), ], "max_eps": [Interval(Real, 0, None, closed="both")], "metric": [StrOptions(set(_VALID_METRICS) | {"precomputed"}), callable], @@ -723,12 +724,12 @@ def cluster_optics_dbscan(*, reachability, core_distances, ordering, eps): "predecessor": [np.ndarray], "ordering": [np.ndarray], "min_samples": [ - Interval(Integral, 1, None, closed="neither"), - Interval(Real, 0, 1, closed="both"), + Interval(Integral, 2, None, closed="left"), + Interval(RealNotInt, 0, 1, closed="both"), ], "min_cluster_size": [ - Interval(Integral, 1, None, closed="neither"), - Interval(Real, 0, 1, closed="both"), + Interval(Integral, 2, None, closed="left"), + Interval(RealNotInt, 0, 1, closed="both"), None, ], "xi": [Interval(Real, 0, 1, closed="both")], diff --git a/sklearn/cluster/tests/test_optics.py b/sklearn/cluster/tests/test_optics.py index 48ebd11751ef3..38c92f855b746 100644 --- a/sklearn/cluster/tests/test_optics.py +++ b/sklearn/cluster/tests/test_optics.py @@ -197,7 +197,7 @@ def test_minimum_number_of_sample_check(): # Compute OPTICS X = [[1, 1]] - clust = OPTICS(max_eps=5.0 * 0.3, min_samples=10, min_cluster_size=1) + clust = OPTICS(max_eps=5.0 * 0.3, min_samples=10, min_cluster_size=1.0) # Run the fit with pytest.raises(ValueError, match=msg): diff --git a/sklearn/decomposition/_pca.py b/sklearn/decomposition/_pca.py index 789b38c9cd455..e8c302fc47129 100644 --- a/sklearn/decomposition/_pca.py +++ b/sklearn/decomposition/_pca.py @@ -27,6 +27,7 @@ from ..utils.extmath import stable_cumsum from ..utils.validation import check_is_fitted from ..utils._param_validation import Interval, StrOptions +from ..utils._param_validation import RealNotInt def _assess_dimension(spectrum, rank, n_samples): @@ -363,7 +364,7 @@ class PCA(_BasePCA): _parameter_constraints: dict = { "n_components": [ Interval(Integral, 0, None, closed="left"), - Interval(Real, 0, 1, closed="neither"), + Interval(RealNotInt, 0, 1, closed="neither"), StrOptions({"mle"}), None, ], diff --git a/sklearn/ensemble/_bagging.py b/sklearn/ensemble/_bagging.py index d10f89102ea82..c4fb966aacac3 100644 --- a/sklearn/ensemble/_bagging.py +++ b/sklearn/ensemble/_bagging.py @@ -8,7 +8,7 @@ import numbers import numpy as np from abc import ABCMeta, abstractmethod -from numbers import Integral, Real +from numbers import Integral from warnings import warn from functools import partial @@ -22,6 +22,7 @@ from ..utils.multiclass import check_classification_targets from ..utils.random import sample_without_replacement from ..utils._param_validation import Interval, HasMethods, StrOptions +from ..utils._param_validation import RealNotInt from ..utils.validation import has_fit_parameter, check_is_fitted, _check_sample_weight from ..utils._tags import _safe_tags from ..utils.parallel import delayed, Parallel @@ -248,11 +249,11 @@ class BaseBagging(BaseEnsemble, metaclass=ABCMeta): "n_estimators": [Interval(Integral, 1, None, closed="left")], "max_samples": [ Interval(Integral, 1, None, closed="left"), - Interval(Real, 0, 1, closed="right"), + Interval(RealNotInt, 0, 1, closed="right"), ], "max_features": [ Interval(Integral, 1, None, closed="left"), - Interval(Real, 0, 1, closed="right"), + Interval(RealNotInt, 0, 1, closed="right"), ], "bootstrap": ["boolean"], "bootstrap_features": ["boolean"], diff --git a/sklearn/ensemble/_forest.py b/sklearn/ensemble/_forest.py index c84468536b64b..c33d833aeb95f 100644 --- a/sklearn/ensemble/_forest.py +++ b/sklearn/ensemble/_forest.py @@ -74,6 +74,7 @@ class calls the ``fit`` method of each sub-estimator on random samples ) from ..utils.validation import _num_samples from ..utils._param_validation import Interval, StrOptions +from ..utils._param_validation import RealNotInt __all__ = [ @@ -206,7 +207,7 @@ class BaseForest(MultiOutputMixin, BaseEnsemble, metaclass=ABCMeta): "warm_start": ["boolean"], "max_samples": [ None, - Interval(Real, 0.0, 1.0, closed="right"), + Interval(RealNotInt, 0.0, 1.0, closed="right"), Interval(Integral, 1, None, closed="left"), ], } diff --git a/sklearn/ensemble/_hist_gradient_boosting/gradient_boosting.py b/sklearn/ensemble/_hist_gradient_boosting/gradient_boosting.py index 6014fc845b8a6..6396d1d43f631 100644 --- a/sklearn/ensemble/_hist_gradient_boosting/gradient_boosting.py +++ b/sklearn/ensemble/_hist_gradient_boosting/gradient_boosting.py @@ -26,6 +26,7 @@ _check_monotonic_cst, ) from ...utils._param_validation import Interval, StrOptions +from ...utils._param_validation import RealNotInt from ...utils._openmp_helpers import _openmp_effective_n_threads from ...utils.multiclass import check_classification_targets from ...metrics import check_scoring @@ -99,7 +100,7 @@ class BaseHistGradientBoosting(BaseEstimator, ABC): ], "n_iter_no_change": [Interval(Integral, 1, None, closed="left")], "validation_fraction": [ - Interval(Real, 0, 1, closed="neither"), + Interval(RealNotInt, 0, 1, closed="neither"), Interval(Integral, 1, None, closed="left"), None, ], diff --git a/sklearn/ensemble/_iforest.py b/sklearn/ensemble/_iforest.py index 4e5422c50e614..4d6c1c3f0b7f9 100644 --- a/sklearn/ensemble/_iforest.py +++ b/sklearn/ensemble/_iforest.py @@ -17,6 +17,7 @@ get_chunk_n_rows, ) from ..utils._param_validation import Interval, StrOptions +from ..utils._param_validation import RealNotInt from ..utils.validation import check_is_fitted, _num_samples from ..base import OutlierMixin @@ -206,7 +207,7 @@ class IsolationForest(OutlierMixin, BaseBagging): "max_samples": [ StrOptions({"auto"}), Interval(Integral, 1, None, closed="left"), - Interval(Real, 0, 1, closed="right"), + Interval(RealNotInt, 0, 1, closed="right"), ], "contamination": [ StrOptions({"auto"}), diff --git a/sklearn/feature_extraction/image.py b/sklearn/feature_extraction/image.py index ec7c9dfec90ea..06cbe3b423276 100644 --- a/sklearn/feature_extraction/image.py +++ b/sklearn/feature_extraction/image.py @@ -18,6 +18,7 @@ from ..base import BaseEstimator, TransformerMixin from ..utils import check_array, check_random_state from ..utils._param_validation import Hidden, Interval, validate_params +from ..utils._param_validation import RealNotInt __all__ = [ "PatchExtractor", @@ -343,8 +344,8 @@ def _extract_patches(arr, patch_shape=8, extraction_step=1): "image": [np.ndarray], "patch_size": [tuple, list], "max_patches": [ - Interval(Real, left=0, right=1, closed="neither"), - Interval(Integral, left=1, right=None, closed="left"), + Interval(RealNotInt, 0, 1, closed="neither"), + Interval(Integral, 1, None, closed="left"), None, ], "random_state": ["random_state"], @@ -542,7 +543,7 @@ class PatchExtractor(TransformerMixin, BaseEstimator): "patch_size": [tuple, None], "max_patches": [ None, - Interval(Real, 0, 1, closed="neither"), + Interval(RealNotInt, 0, 1, closed="neither"), Interval(Integral, 1, None, closed="left"), ], "random_state": ["random_state"], diff --git a/sklearn/feature_extraction/text.py b/sklearn/feature_extraction/text.py index 0160bfeaa539f..9d56d2d1bf2dd 100644 --- a/sklearn/feature_extraction/text.py +++ b/sklearn/feature_extraction/text.py @@ -15,7 +15,7 @@ from collections import defaultdict from collections.abc import Mapping from functools import partial -from numbers import Integral, Real +from numbers import Integral from operator import itemgetter import re import unicodedata @@ -32,6 +32,7 @@ from ..utils import _IS_32BIT from ..exceptions import NotFittedError from ..utils._param_validation import StrOptions, Interval, HasMethods +from ..utils._param_validation import RealNotInt __all__ = [ @@ -1148,11 +1149,11 @@ class CountVectorizer(_VectorizerMixin, BaseEstimator): "ngram_range": [tuple], "analyzer": [StrOptions({"word", "char", "char_wb"}), callable], "max_df": [ - Interval(Real, 0, 1, closed="both"), + Interval(RealNotInt, 0, 1, closed="both"), Interval(Integral, 1, None, closed="left"), ], "min_df": [ - Interval(Real, 0, 1, closed="both"), + Interval(RealNotInt, 0, 1, closed="both"), Interval(Integral, 1, None, closed="left"), ], "max_features": [Interval(Integral, 1, None, closed="left"), None], diff --git a/sklearn/feature_selection/_rfe.py b/sklearn/feature_selection/_rfe.py index d105ba1ae3567..214ac9e0c30cf 100644 --- a/sklearn/feature_selection/_rfe.py +++ b/sklearn/feature_selection/_rfe.py @@ -7,13 +7,14 @@ """Recursive feature elimination for feature ranking""" import numpy as np -from numbers import Integral, Real +from numbers import Integral from joblib import effective_n_jobs from ..utils.metaestimators import available_if from ..utils.metaestimators import _safe_split from ..utils._param_validation import HasMethods, Interval +from ..utils._param_validation import RealNotInt from ..utils._tags import _safe_tags from ..utils.validation import check_is_fitted from ..utils.parallel import delayed, Parallel @@ -187,12 +188,12 @@ class RFE(SelectorMixin, MetaEstimatorMixin, BaseEstimator): "estimator": [HasMethods(["fit"])], "n_features_to_select": [ None, - Interval(Real, 0, 1, closed="right"), + Interval(RealNotInt, 0, 1, closed="right"), Interval(Integral, 0, None, closed="neither"), ], "step": [ Interval(Integral, 0, None, closed="neither"), - Interval(Real, 0, 1, closed="neither"), + Interval(RealNotInt, 0, 1, closed="neither"), ], "verbose": ["verbose"], "importance_getter": [str, callable], diff --git a/sklearn/feature_selection/_sequential.py b/sklearn/feature_selection/_sequential.py index 91ea7bdc719b9..e983c55de7d25 100644 --- a/sklearn/feature_selection/_sequential.py +++ b/sklearn/feature_selection/_sequential.py @@ -10,6 +10,7 @@ from ._base import SelectorMixin from ..base import BaseEstimator, MetaEstimatorMixin, clone from ..utils._param_validation import HasMethods, Hidden, Interval, StrOptions +from ..utils._param_validation import RealNotInt from ..utils._tags import _safe_tags from ..utils.validation import check_is_fitted from ..model_selection import cross_val_score @@ -154,7 +155,7 @@ class SequentialFeatureSelector(SelectorMixin, MetaEstimatorMixin, BaseEstimator "estimator": [HasMethods(["fit"])], "n_features_to_select": [ StrOptions({"auto", "warn"}, deprecated={"warn"}), - Interval(Real, 0, 1, closed="right"), + Interval(RealNotInt, 0, 1, closed="right"), Interval(Integral, 0, None, closed="neither"), Hidden(None), ], diff --git a/sklearn/linear_model/_ransac.py b/sklearn/linear_model/_ransac.py index ff58e067cde35..472f2275ffa6b 100644 --- a/sklearn/linear_model/_ransac.py +++ b/sklearn/linear_model/_ransac.py @@ -15,6 +15,7 @@ from ._base import LinearRegression from ..utils.validation import has_fit_parameter from ..utils._param_validation import Interval, Options, StrOptions, HasMethods, Hidden +from ..utils._param_validation import RealNotInt from ..exceptions import ConvergenceWarning _EPSILON = np.spacing(1) @@ -236,7 +237,7 @@ class RANSACRegressor( "estimator": [HasMethods(["fit", "score", "predict"]), None], "min_samples": [ Interval(Integral, 1, None, closed="left"), - Interval(Real, 0, 1, closed="both"), + Interval(RealNotInt, 0, 1, closed="both"), None, ], "residual_threshold": [Interval(Real, 0, None, closed="left"), None], diff --git a/sklearn/model_selection/_split.py b/sklearn/model_selection/_split.py index 5c3854cfc9d3b..dded962a350d8 100644 --- a/sklearn/model_selection/_split.py +++ b/sklearn/model_selection/_split.py @@ -29,6 +29,7 @@ from ..utils.validation import check_array from ..utils.multiclass import type_of_target from ..utils._param_validation import validate_params, Interval +from ..utils._param_validation import RealNotInt __all__ = [ "BaseCrossValidator", @@ -2464,12 +2465,12 @@ def check_cv(cv=5, y=None, *, classifier=False): @validate_params( { "test_size": [ - Interval(numbers.Real, 0, 1, closed="neither"), + Interval(RealNotInt, 0, 1, closed="neither"), Interval(numbers.Integral, 1, None, closed="left"), None, ], "train_size": [ - Interval(numbers.Real, 0, 1, closed="neither"), + Interval(RealNotInt, 0, 1, closed="neither"), Interval(numbers.Integral, 1, None, closed="left"), None, ], diff --git a/sklearn/preprocessing/_encoders.py b/sklearn/preprocessing/_encoders.py index 4c3e80771c35a..7df0584ba9d5b 100644 --- a/sklearn/preprocessing/_encoders.py +++ b/sklearn/preprocessing/_encoders.py @@ -3,7 +3,7 @@ # License: BSD 3 clause import numbers -from numbers import Integral, Real +from numbers import Integral import warnings import numpy as np @@ -14,6 +14,7 @@ from ..utils.validation import check_is_fitted from ..utils.validation import _check_feature_names_in from ..utils._param_validation import Interval, StrOptions, Hidden +from ..utils._param_validation import RealNotInt from ..utils._mask import _get_mask from ..utils._encode import _encode, _check_unknown, _unique, _get_counts @@ -493,7 +494,7 @@ class OneHotEncoder(_BaseEncoder): "max_categories": [Interval(Integral, 1, None, closed="left"), None], "min_frequency": [ Interval(Integral, 1, None, closed="left"), - Interval(Real, 0, 1, closed="neither"), + Interval(RealNotInt, 0, 1, closed="neither"), None, ], "sparse": [Hidden(StrOptions({"deprecated"})), "boolean"], # deprecated diff --git a/sklearn/tests/test_public_functions.py b/sklearn/tests/test_public_functions.py index b15685eaf122f..a81264e2e6ccd 100644 --- a/sklearn/tests/test_public_functions.py +++ b/sklearn/tests/test_public_functions.py @@ -1,5 +1,6 @@ from importlib import import_module from inspect import signature +from numbers import Integral, Real import pytest @@ -7,6 +8,7 @@ from sklearn.utils._param_validation import generate_valid_param from sklearn.utils._param_validation import make_constraint from sklearn.utils._param_validation import InvalidParameterError +from sklearn.utils._param_validation import Interval def _get_func_info(func_module): @@ -70,6 +72,20 @@ def _check_function_param_validation( # This parameter is not validated continue + # Mixing an interval of reals and an interval of integers must be avoided. + if any( + isinstance(constraint, Interval) and constraint.type == Integral + for constraint in constraints + ) and any( + isinstance(constraint, Interval) and constraint.type == Real + for constraint in constraints + ): + raise ValueError( + f"The constraint for parameter {param_name} of {func_name} can't have a" + " mix of intervals of Integral and Real types. Use the type" + " RealNotInt instead of Real." + ) + match = ( rf"The '{param_name}' parameter of {func_name} must be .* Got .* instead." ) @@ -85,7 +101,7 @@ def _check_function_param_validation( for constraint in constraints: try: - bad_value = generate_invalid_param_val(constraint, constraints) + bad_value = generate_invalid_param_val(constraint) except NotImplementedError: continue diff --git a/sklearn/tree/_classes.py b/sklearn/tree/_classes.py index 6e01b8b49e594..e0e341d9a89f6 100644 --- a/sklearn/tree/_classes.py +++ b/sklearn/tree/_classes.py @@ -38,6 +38,7 @@ from ..utils.multiclass import check_classification_targets from ..utils.validation import check_is_fitted from ..utils._param_validation import Hidden, Interval, StrOptions +from ..utils._param_validation import RealNotInt from ._criterion import Criterion from ._splitter import Splitter @@ -99,16 +100,16 @@ class BaseDecisionTree(MultiOutputMixin, BaseEstimator, metaclass=ABCMeta): "max_depth": [Interval(Integral, 1, None, closed="left"), None], "min_samples_split": [ Interval(Integral, 2, None, closed="left"), - Interval("real_not_int", 0.0, 1.0, closed="right"), + Interval(RealNotInt, 0.0, 1.0, closed="right"), ], "min_samples_leaf": [ Interval(Integral, 1, None, closed="left"), - Interval("real_not_int", 0.0, 1.0, closed="neither"), + Interval(RealNotInt, 0.0, 1.0, closed="neither"), ], "min_weight_fraction_leaf": [Interval(Real, 0.0, 0.5, closed="both")], "max_features": [ Interval(Integral, 1, None, closed="left"), - Interval("real_not_int", 0.0, 1.0, closed="right"), + Interval(RealNotInt, 0.0, 1.0, closed="right"), StrOptions({"auto", "sqrt", "log2"}, deprecated={"auto"}), None, ], diff --git a/sklearn/utils/_param_validation.py b/sklearn/utils/_param_validation.py index 8d23f0b23b6eb..4370817094be8 100644 --- a/sklearn/utils/_param_validation.py +++ b/sklearn/utils/_param_validation.py @@ -207,6 +207,18 @@ def wrapper(*args, **kwargs): return decorator +class RealNotInt(Real): + """A type that represents reals that are not instances of int. + + Behaves like float, but also works with values extracted from numpy arrays. + isintance(1, RealNotInt) -> False + isinstance(1.0, RealNotInt) -> True + """ + + +RealNotInt.register(float) + + def _type_name(t): """Convert type into human readable string.""" module = t.__module__ @@ -364,10 +376,10 @@ class Interval(_Constraint): Parameters ---------- - type : {numbers.Integral, numbers.Real, "real_not_int"} + type : {numbers.Integral, numbers.Real, RealNotInt} The set of numbers in which to set the interval. - If "real_not_int", only reals that don't have the integer type + If RealNotInt, only reals that don't have the integer type are allowed. For example 1.0 is allowed but 1 is not. left : float or int or None @@ -405,9 +417,9 @@ def __init__(self, type, left, right, *, closed): self._check_params() def _check_params(self): - if self.type not in (Integral, Real, "real_not_int"): + if self.type not in (Integral, Real, RealNotInt): raise ValueError( - "type must be either numbers.Integral, numbers.Real or 'real_not_int'." + "type must be either numbers.Integral, numbers.Real or RealNotInt." f" Got {self.type} instead." ) @@ -459,13 +471,8 @@ def __contains__(self, val): return False return True - def _has_valid_type(self, val): - if self.type == "real_not_int": - return isinstance(val, Real) and not isinstance(val, Integral) - return isinstance(val, self.type) - def is_satisfied_by(self, val): - if not self._has_valid_type(val): + if not isinstance(val, self.type): return False return val in self @@ -476,6 +483,13 @@ def __str__(self): left_bound = "-inf" if self.left is None else self.left right_bound = "inf" if self.right is None else self.right right_bracket = "]" if self.closed in ("right", "both") else ")" + + # better repr if the bounds were given as integers + if not self.type == Integral and isinstance(self.left, Real): + left_bound = float(left_bound) + if not self.type == Integral and isinstance(self.right, Real): + right_bound = float(right_bound) + return ( f"{type_str} in the range " f"{left_bracket}{left_bound}, {right_bound}{right_bracket}" @@ -718,7 +732,7 @@ def __init__(self, constraint): self.constraint = constraint -def generate_invalid_param_val(constraint, constraints=None): +def generate_invalid_param_val(constraint): """Return a value that does not satisfy the constraint. Raises a NotImplementedError if there exists no invalid value for this constraint. @@ -730,10 +744,6 @@ def generate_invalid_param_val(constraint, constraints=None): constraint : _Constraint instance The constraint to generate a value for. - constraints : list of _Constraint instances or None, default=None - The list of all constraints for this parameter. If None, the list only - containing `constraint` is used. - Returns ------- val : object @@ -757,116 +767,31 @@ def generate_invalid_param_val(constraint, constraints=None): if isinstance(constraint, _CVObjects): return "not a cv object" - if not isinstance(constraint, Interval): - raise NotImplementedError - - # constraint is an interval - constraints = [constraint] if constraints is None else constraints - return _generate_invalid_param_val_interval(constraint, constraints) + if isinstance(constraint, Interval) and constraint.type is Integral: + if constraint.left is not None: + return constraint.left - 1 + if constraint.right is not None: + return constraint.right + 1 + # There's no integer outside (-inf, +inf) + raise NotImplementedError -def _generate_invalid_param_val_interval(interval, constraints): - """Return a value that does not satisfy an interval constraint. - - Generating an invalid value for an integer interval depends on the other constraints - since an int is a real, meaning that it can be valid for a real interval. - Assumes that there can be at most 2 interval constraints: one integer interval - and/or one real interval. - - This is only useful for testing purpose. - - Parameters - ---------- - interval : Interval instance - The interval to generate a value for. - - constraints : list of _Constraint instances - The list of all constraints for this parameter. - - Returns - ------- - val : object - A value that does not satisfy the interval constraint. - """ - if interval.type is Real: - # generate a non-integer value such that it can't be valid even if there's also - # an integer interval constraint. - if interval.left is None and interval.right is None: - if interval.closed in ("left", "neither"): - return np.inf - elif interval.closed in ("right", "neither"): - return -np.inf - else: - raise NotImplementedError + if isinstance(constraint, Interval) and constraint.type in (Real, RealNotInt): + if constraint.left is not None: + return constraint.left - 1e-6 + if constraint.right is not None: + return constraint.right + 1e-6 - if interval.left is not None: - return np.floor(interval.left) - 0.5 - else: # right is not None - return np.ceil(interval.right) + 0.5 + # bounds are -inf, +inf + if constraint.closed in ("right", "neither"): + return -np.inf + if constraint.closed in ("left", "neither"): + return np.inf - else: # interval.type is Integral - if interval.left is None and interval.right is None: - raise NotImplementedError + # interval is [-inf, +inf] + return np.nan - # We need to check if there's also a real interval constraint to generate a - # value that is not valid for any of the 2 interval constraints. - real_intervals = [ - i for i in constraints if isinstance(i, Interval) and i.type is Real - ] - real_interval = real_intervals[0] if real_intervals else None - - if real_interval is None: - # Only the integer interval constraint -> easy - if interval.left is not None: - return interval.left - 1 - else: # interval.right is not None - return interval.right + 1 - - # There's also a real interval constraint. Try to find a value left to both or - # right to both or in between them. - - # redefine left and right bounds to be smallest and largest valid integers in - # both intervals. - int_left = interval.left - if int_left is not None and interval.closed in ("right", "neither"): - int_left = int_left + 1 - - int_right = interval.right - if int_right is not None and interval.closed in ("left", "neither"): - int_right = int_right - 1 - - real_left = real_interval.left - if real_interval.left is not None: - real_left = int(np.ceil(real_interval.left)) - if real_interval.closed in ("right", "neither"): - real_left = real_left + 1 - - real_right = real_interval.right - if real_interval.right is not None: - real_right = int(np.floor(real_interval.right)) - if real_interval.closed in ("left", "neither"): - real_right = real_right - 1 - - if int_left is not None and real_left is not None: - # there exists an int left to both intervals - return min(int_left, real_left) - 1 - - if int_right is not None and real_right is not None: - # there exists an int right to both intervals - return max(int_right, real_right) + 1 - - if int_left is not None: - if real_right is not None and int_left - real_right >= 2: - # there exists an int between the 2 intervals - return int_left - 1 - else: - raise NotImplementedError - else: # int_right is not None - if real_left is not None and real_left - int_right >= 2: - # there exists an int between the 2 intervals - return int_right + 1 - else: - raise NotImplementedError + raise NotImplementedError def generate_valid_param(constraint): diff --git a/sklearn/utils/estimator_checks.py b/sklearn/utils/estimator_checks.py index 14aaf8b40e8e0..d38473693efd0 100644 --- a/sklearn/utils/estimator_checks.py +++ b/sklearn/utils/estimator_checks.py @@ -4,7 +4,7 @@ from copy import deepcopy from functools import partial, wraps from inspect import signature -from numbers import Real +from numbers import Real, Integral import numpy as np from scipy import sparse @@ -1434,7 +1434,7 @@ def check_fit2d_1sample(name, estimator_orig): # min_cluster_size cannot be less than the data size for OPTICS. if name == "OPTICS": - estimator.set_params(min_samples=1) + estimator.set_params(min_samples=1.0) # perplexity cannot be more than the number of samples for TSNE. if name == "TSNE": @@ -4155,6 +4155,20 @@ def check_param_validation(name, estimator_orig): # This parameter is not validated continue + # Mixing an interval of reals and an interval of integers must be avoided. + if any( + isinstance(constraint, Interval) and constraint.type == Integral + for constraint in constraints + ) and any( + isinstance(constraint, Interval) and constraint.type == Real + for constraint in constraints + ): + raise ValueError( + f"The constraint for parameter {param_name} of {name} can't have a mix" + " of intervals of Integral and Real types. Use the type RealNotInt" + " instead of Real." + ) + match = rf"The '{param_name}' parameter of {name} must be .* Got .* instead." err_msg = ( f"{name} does not raise an informative error message when the " @@ -4188,7 +4202,7 @@ def check_param_validation(name, estimator_orig): for constraint in constraints: try: - bad_value = generate_invalid_param_val(constraint, constraints) + bad_value = generate_invalid_param_val(constraint) except NotImplementedError: continue diff --git a/sklearn/utils/tests/test_param_validation.py b/sklearn/utils/tests/test_param_validation.py index ce8f9cdf939fd..bfbbf2a1b29df 100644 --- a/sklearn/utils/tests/test_param_validation.py +++ b/sklearn/utils/tests/test_param_validation.py @@ -29,6 +29,7 @@ from sklearn.utils._param_validation import generate_valid_param from sklearn.utils._param_validation import validate_params from sklearn.utils._param_validation import InvalidParameterError +from sklearn.utils._param_validation import RealNotInt # Some helpers for the tests @@ -219,75 +220,75 @@ def test_generate_invalid_param_val(constraint): [ ( Interval(Integral, None, 3, closed="right"), - Interval(Real, -5, 5, closed="both"), + Interval(RealNotInt, -5, 5, closed="both"), ), ( Interval(Integral, None, 3, closed="right"), - Interval(Real, -5, 5, closed="neither"), + Interval(RealNotInt, -5, 5, closed="neither"), ), ( Interval(Integral, None, 3, closed="right"), - Interval(Real, 4, 5, closed="both"), + Interval(RealNotInt, 4, 5, closed="both"), ), ( Interval(Integral, None, 3, closed="right"), - Interval(Real, 5, None, closed="left"), + Interval(RealNotInt, 5, None, closed="left"), ), ( Interval(Integral, None, 3, closed="right"), - Interval(Real, 4, None, closed="neither"), + Interval(RealNotInt, 4, None, closed="neither"), ), ( Interval(Integral, 3, None, closed="left"), - Interval(Real, -5, 5, closed="both"), + Interval(RealNotInt, -5, 5, closed="both"), ), ( Interval(Integral, 3, None, closed="left"), - Interval(Real, -5, 5, closed="neither"), + Interval(RealNotInt, -5, 5, closed="neither"), ), ( Interval(Integral, 3, None, closed="left"), - Interval(Real, 1, 2, closed="both"), + Interval(RealNotInt, 1, 2, closed="both"), ), ( Interval(Integral, 3, None, closed="left"), - Interval(Real, None, -5, closed="left"), + Interval(RealNotInt, None, -5, closed="left"), ), ( Interval(Integral, 3, None, closed="left"), - Interval(Real, None, -4, closed="neither"), + Interval(RealNotInt, None, -4, closed="neither"), ), ( Interval(Integral, -5, 5, closed="both"), - Interval(Real, None, 1, closed="right"), + Interval(RealNotInt, None, 1, closed="right"), ), ( Interval(Integral, -5, 5, closed="both"), - Interval(Real, 1, None, closed="left"), + Interval(RealNotInt, 1, None, closed="left"), ), ( Interval(Integral, -5, 5, closed="both"), - Interval(Real, -10, -4, closed="neither"), + Interval(RealNotInt, -10, -4, closed="neither"), ), ( Interval(Integral, -5, 5, closed="both"), - Interval(Real, -10, -4, closed="right"), + Interval(RealNotInt, -10, -4, closed="right"), ), ( Interval(Integral, -5, 5, closed="neither"), - Interval(Real, 6, 10, closed="neither"), + Interval(RealNotInt, 6, 10, closed="neither"), ), ( Interval(Integral, -5, 5, closed="neither"), - Interval(Real, 6, 10, closed="left"), + Interval(RealNotInt, 6, 10, closed="left"), ), ( Interval(Integral, 2, None, closed="left"), - Interval(Real, 0, 1, closed="both"), + Interval(RealNotInt, 0, 1, closed="both"), ), ( Interval(Integral, 1, None, closed="left"), - Interval(Real, 0, 1, closed="both"), + Interval(RealNotInt, 0, 1, closed="both"), ), ], ) @@ -295,42 +296,34 @@ def test_generate_invalid_param_val_2_intervals(integer_interval, real_interval) """Check that the value generated for an interval constraint does not satisfy any of the interval constraints. """ - bad_value = generate_invalid_param_val( - real_interval, constraints=[real_interval, integer_interval] - ) + bad_value = generate_invalid_param_val(constraint=real_interval) assert not real_interval.is_satisfied_by(bad_value) assert not integer_interval.is_satisfied_by(bad_value) - bad_value = generate_invalid_param_val( - integer_interval, constraints=[real_interval, integer_interval] - ) + bad_value = generate_invalid_param_val(constraint=integer_interval) assert not real_interval.is_satisfied_by(bad_value) assert not integer_interval.is_satisfied_by(bad_value) @pytest.mark.parametrize( - "constraints", + "constraint", [ - [_ArrayLikes()], - [_InstancesOf(list)], - [_Callables()], - [_NoneConstraint()], - [_RandomStates()], - [_SparseMatrices()], - [_Booleans()], - [Interval(Real, None, None, closed="both")], - [ - Interval(Integral, 0, None, closed="left"), - Interval(Real, None, 0, closed="neither"), - ], + _ArrayLikes(), + _InstancesOf(list), + _Callables(), + _NoneConstraint(), + _RandomStates(), + _SparseMatrices(), + _Booleans(), + Interval(Integral, None, None, closed="neither"), ], ) -def test_generate_invalid_param_val_all_valid(constraints): +def test_generate_invalid_param_val_all_valid(constraint): """Check that the function raises NotImplementedError when there's no invalid value for the constraint. """ with pytest.raises(NotImplementedError): - generate_invalid_param_val(constraints[0], constraints=constraints) + generate_invalid_param_val(constraint) @pytest.mark.parametrize( @@ -665,7 +658,15 @@ def fit(self, X=None, y=None): def test_interval_real_not_int(): - """Check for the type "real_not_int" in the Interval constraint.""" - constraint = Interval("real_not_int", 0, 1, closed="both") + """Check for the type RealNotInt in the Interval constraint.""" + constraint = Interval(RealNotInt, 0, 1, closed="both") assert constraint.is_satisfied_by(1.0) assert not constraint.is_satisfied_by(1) + + +def test_real_not_int(): + """Check for the RealNotInt type.""" + assert isinstance(1.0, RealNotInt) + assert not isinstance(1, RealNotInt) + assert isinstance(np.float64(1), RealNotInt) + assert not isinstance(np.int64(1), RealNotInt) From f4fbb2891390c9386eb485cf9d86df27048741a3 Mon Sep 17 00:00:00 2001 From: Pooja Subramaniam Date: Wed, 15 Mar 2023 20:23:27 +0100 Subject: [PATCH 6/9] MAINT Parameters validation for utils.gen_batches (#25864) --- sklearn/tests/test_public_functions.py | 1 + sklearn/utils/__init__.py | 14 ++++++++------ sklearn/utils/tests/test_utils.py | 14 -------------- 3 files changed, 9 insertions(+), 20 deletions(-) diff --git a/sklearn/tests/test_public_functions.py b/sklearn/tests/test_public_functions.py index a81264e2e6ccd..7f8fe0f2717ab 100644 --- a/sklearn/tests/test_public_functions.py +++ b/sklearn/tests/test_public_functions.py @@ -189,6 +189,7 @@ def _check_function_param_validation( "sklearn.model_selection.train_test_split", "sklearn.random_projection.johnson_lindenstrauss_min_dim", "sklearn.svm.l1_min_c", + "sklearn.utils.gen_batches", ] diff --git a/sklearn/utils/__init__.py b/sklearn/utils/__init__.py index 923c08d44c6f4..0b3119c0bfa03 100644 --- a/sklearn/utils/__init__.py +++ b/sklearn/utils/__init__.py @@ -39,6 +39,7 @@ ) from .. import get_config from ._bunch import Bunch +from ._param_validation import validate_params, Interval # Do not deprecate parallel_backend and register_parallel_backend as they are @@ -725,6 +726,13 @@ def _chunk_generator(gen, chunksize): return +@validate_params( + { + "n": [Interval(numbers.Integral, 1, None, closed="left")], + "batch_size": [Interval(numbers.Integral, 1, None, closed="left")], + "min_batch_size": [Interval(numbers.Integral, 0, None, closed="left")], + } +) def gen_batches(n, batch_size, *, min_batch_size=0): """Generator to create slices containing `batch_size` elements from 0 to `n`. @@ -762,12 +770,6 @@ def gen_batches(n, batch_size, *, min_batch_size=0): >>> list(gen_batches(7, 3, min_batch_size=2)) [slice(0, 3, None), slice(3, 7, None)] """ - if not isinstance(batch_size, numbers.Integral): - raise TypeError( - "gen_batches got batch_size=%s, must be an integer" % batch_size - ) - if batch_size <= 0: - raise ValueError("gen_batches got batch_size=%s, must be positive" % batch_size) start = 0 for _ in range(int(n // batch_size)): end = start + batch_size diff --git a/sklearn/utils/tests/test_utils.py b/sklearn/utils/tests/test_utils.py index 848985f267c92..a000394bbee28 100644 --- a/sklearn/utils/tests/test_utils.py +++ b/sklearn/utils/tests/test_utils.py @@ -17,7 +17,6 @@ from sklearn.utils import check_random_state from sklearn.utils import _determine_key_type from sklearn.utils import deprecated -from sklearn.utils import gen_batches from sklearn.utils import _get_column_indices from sklearn.utils import resample from sklearn.utils import safe_mask @@ -56,19 +55,6 @@ def test_make_rng(): check_random_state("some invalid seed") -def test_gen_batches(): - # Make sure gen_batches errors on invalid batch_size - - assert_array_equal(list(gen_batches(4, 2)), [slice(0, 2, None), slice(2, 4, None)]) - msg_zero = "gen_batches got batch_size=0, must be positive" - with pytest.raises(ValueError, match=msg_zero): - next(gen_batches(4, 0)) - - msg_float = "gen_batches got batch_size=0.5, must be an integer" - with pytest.raises(TypeError, match=msg_float): - next(gen_batches(4, 0.5)) - - def test_deprecated(): # Test whether the deprecated decorator issues appropriate warnings # Copied almost verbatim from https://docs.python.org/library/warnings.html From cae0b77ff6a4d3d9e112c2d5b5500e3c44207d1c Mon Sep 17 00:00:00 2001 From: Rushil Desai Date: Thu, 16 Mar 2023 02:53:22 +0530 Subject: [PATCH 7/9] TST use global_random_seed in test_dict_vectorizer.py (#24533) --- sklearn/feature_extraction/tests/test_dict_vectorizer.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/sklearn/feature_extraction/tests/test_dict_vectorizer.py b/sklearn/feature_extraction/tests/test_dict_vectorizer.py index 613b7eeee4f4e..c8b9aaa8b5c8a 100644 --- a/sklearn/feature_extraction/tests/test_dict_vectorizer.py +++ b/sklearn/feature_extraction/tests/test_dict_vectorizer.py @@ -145,10 +145,10 @@ def test_unseen_or_no_features(): v.transform([]) -def test_deterministic_vocabulary(): +def test_deterministic_vocabulary(global_random_seed): # Generate equal dictionaries with different memory layouts items = [("%03d" % i, i) for i in range(1000)] - rng = Random(42) + rng = Random(global_random_seed) d_sorted = dict(items) rng.shuffle(items) d_shuffled = dict(items) From a473525b013273d5b0bd34c8ec01439025b0442d Mon Sep 17 00:00:00 2001 From: Xiao Yuan Date: Thu, 16 Mar 2023 05:30:46 +0800 Subject: [PATCH 8/9] TST use global_random_seed in test_pls.py (#24526) Co-authored-by: jeremiedbb --- sklearn/cross_decomposition/tests/test_pls.py | 30 +++++++++++-------- 1 file changed, 18 insertions(+), 12 deletions(-) diff --git a/sklearn/cross_decomposition/tests/test_pls.py b/sklearn/cross_decomposition/tests/test_pls.py index aff2b76034b0b..55ef8b482d58e 100644 --- a/sklearn/cross_decomposition/tests/test_pls.py +++ b/sklearn/cross_decomposition/tests/test_pls.py @@ -484,31 +484,35 @@ def test_n_components_upper_bounds(Estimator): @pytest.mark.parametrize("n_samples, n_features", [(100, 10), (100, 200)]) -@pytest.mark.parametrize("seed", range(10)) -def test_singular_value_helpers(n_samples, n_features, seed): +def test_singular_value_helpers(n_samples, n_features, global_random_seed): # Make sure SVD and power method give approximately the same results - X, Y = make_regression(n_samples, n_features, n_targets=5, random_state=seed) + X, Y = make_regression( + n_samples, n_features, n_targets=5, random_state=global_random_seed + ) u1, v1, _ = _get_first_singular_vectors_power_method(X, Y, norm_y_weights=True) u2, v2 = _get_first_singular_vectors_svd(X, Y) _svd_flip_1d(u1, v1) _svd_flip_1d(u2, v2) - rtol = 1e-1 - assert_allclose(u1, u2, rtol=rtol) - assert_allclose(v1, v2, rtol=rtol) + rtol = 1e-3 + # Setting atol because some coordinates are very close to zero + assert_allclose(u1, u2, atol=u2.max() * rtol) + assert_allclose(v1, v2, atol=v2.max() * rtol) -def test_one_component_equivalence(): +def test_one_component_equivalence(global_random_seed): # PLSSVD, PLSRegression and PLSCanonical should all be equivalent when # n_components is 1 - X, Y = make_regression(100, 10, n_targets=5, random_state=0) + X, Y = make_regression(100, 10, n_targets=5, random_state=global_random_seed) svd = PLSSVD(n_components=1).fit(X, Y).transform(X) reg = PLSRegression(n_components=1).fit(X, Y).transform(X) canonical = PLSCanonical(n_components=1).fit(X, Y).transform(X) - assert_allclose(svd, reg, rtol=1e-2) - assert_allclose(svd, canonical, rtol=1e-2) + rtol = 1e-3 + # Setting atol because some entries are very close to zero + assert_allclose(svd, reg, atol=reg.max() * rtol) + assert_allclose(svd, canonical, atol=canonical.max() * rtol) def test_svd_flip_1d(): @@ -526,9 +530,11 @@ def test_svd_flip_1d(): assert_allclose(v, [-1, -2, -3]) -def test_loadings_converges(): +def test_loadings_converges(global_random_seed): """Test that CCA converges. Non-regression test for #19549.""" - X, y = make_regression(n_samples=200, n_features=20, n_targets=20, random_state=20) + X, y = make_regression( + n_samples=200, n_features=20, n_targets=20, random_state=global_random_seed + ) cca = CCA(n_components=10, max_iter=500) From b397b8f2d952a26344cc062ff912c663f4afa6d5 Mon Sep 17 00:00:00 2001 From: Omar Salman Date: Thu, 16 Mar 2023 03:23:57 +0500 Subject: [PATCH 9/9] TST use global_random_seed in test_gpc.py (#24600) Co-authored-by: jeremiedbb --- sklearn/gaussian_process/tests/test_gpc.py | 18 ++++++++++-------- 1 file changed, 10 insertions(+), 8 deletions(-) diff --git a/sklearn/gaussian_process/tests/test_gpc.py b/sklearn/gaussian_process/tests/test_gpc.py index 2173f77c161c1..aefdb2e8ff0e2 100644 --- a/sklearn/gaussian_process/tests/test_gpc.py +++ b/sklearn/gaussian_process/tests/test_gpc.py @@ -118,11 +118,11 @@ def test_lml_gradient(kernel): assert_almost_equal(lml_gradient, lml_gradient_approx, 3) -def test_random_starts(): +def test_random_starts(global_random_seed): # Test that an increasing number of random-starts of GP fitting only # increases the log marginal likelihood of the chosen theta. n_samples, n_features = 25, 2 - rng = np.random.RandomState(0) + rng = np.random.RandomState(global_random_seed) X = rng.randn(n_samples, n_features) * 2 - 1 y = (np.sin(X).sum(axis=1) + np.sin(3 * X).sum(axis=1)) > 0 @@ -132,7 +132,9 @@ def test_random_starts(): last_lml = -np.inf for n_restarts_optimizer in range(5): gp = GaussianProcessClassifier( - kernel=kernel, n_restarts_optimizer=n_restarts_optimizer, random_state=0 + kernel=kernel, + n_restarts_optimizer=n_restarts_optimizer, + random_state=global_random_seed, ).fit(X, y) lml = gp.log_marginal_likelihood(gp.kernel_.theta) assert lml > last_lml - np.finfo(np.float32).eps @@ -140,11 +142,11 @@ def test_random_starts(): @pytest.mark.parametrize("kernel", non_fixed_kernels) -def test_custom_optimizer(kernel): +def test_custom_optimizer(kernel, global_random_seed): # Test that GPC can use externally defined optimizers. # Define a dummy optimizer that simply tests 10 random hyperparameters def optimizer(obj_func, initial_theta, bounds): - rng = np.random.RandomState(0) + rng = np.random.RandomState(global_random_seed) theta_opt, func_min = initial_theta, obj_func( initial_theta, eval_gradient=False ) @@ -160,9 +162,9 @@ def optimizer(obj_func, initial_theta, bounds): gpc = GaussianProcessClassifier(kernel=kernel, optimizer=optimizer) gpc.fit(X, y_mc) # Checks that optimizer improved marginal likelihood - assert gpc.log_marginal_likelihood(gpc.kernel_.theta) > gpc.log_marginal_likelihood( - kernel.theta - ) + assert gpc.log_marginal_likelihood( + gpc.kernel_.theta + ) >= gpc.log_marginal_likelihood(kernel.theta) @pytest.mark.parametrize("kernel", kernels)