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89 changes: 82 additions & 7 deletions lib/node_modules/@stdlib/lapack/base/dlacpy/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -188,21 +188,68 @@ console.log( ndarray2array( B, shape, strides, 0, order ) );
### Usage

```c
TODO
#include "stdlib/lapack/base/dlacpy.h"
```

#### TODO
#### c_dlacpy( order, uplo, M, N, \*A, LDA, \*B, LDB )

TODO.
Copies all or part of a matrix `A` to another matrix `B`.

```c
TODO
#include "stdlib/blas/base/shared.h"

double A[] = { 1.0, 2.0, 3.0, 4.0 };
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Suggested change
double A[] = { 1.0, 2.0, 3.0, 4.0 };
const double A[] = { 1.0, 2.0, 3.0, 4.0 };

This array is not mutated. Applies here and below.

double B[] = { 0.0, 0.0, 0.0, 0.0 };

c_dlacpy( CblasColMajor, CblasUpper, 2, 2, A, 2, B, 2 );
```

TODO
The function accepts the following arguments:

- **order**: `[in] CBLAS_LAYOUT` storage layout of `A` and `B`
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All these descriptions are missing ending periods.

- **uplo**: `[in] CBLAS_UPLO` specifies whether to copy the upper or lower triangular/trapezoidal part of matrix `A`
- **M**: `[in] CBLAS_INT` number of rows in matrix `A`
- **N**: `[in] CBLAS_INT` number of columns in matrix `A`
- **A**: `[in] double*` input matrix
- **LDA**: `[in] CBLAS_INT` stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`)
- **B**: `[in] double*` output matrix
- **LDB**: `[in] CBLAS_INT` stride of the first dimension of `B` (a.k.a., leading dimension of the matrix `B`)

```c
TODO
void c_dlacpy( const CBLAS_LAYOUT order, const CBLAS_UPLO uplo, const CBLAS_INT M, const CBLAS_INT N, double *A, const CBLAS_INT LDA, double *B, const CBLAS_INT LDB )
```

<!--lint disable maximum-heading-length-->

#### c_dlacpy_ndarray( uplo, M, N, \*A, strideA1, strideA2, offsetA, \*B, strideB1, strideB2, offsetB )

Copies all or part of a matrix `A` to another matrix `B` using alternative indexing semantics.

```c
#include "stdlib/blas/base/shared.h"

double A[] = { 1.0, 2.0, 3.0, 4.0, 5.0 };
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Why do these arrays have an odd number of elements?

double B[] = { 0.0, 0.0, 0.0, 0.0, 0.0 };

c_dlacpy_ndarray( CblasUpper, 2, 2, A, 2, 1, 1, B, 2, 1, 2 );
```

The function accepts the following arguments:

- **uplo**: `[in] CBLAS_UPLO` specifies whether to copy the upper or lower triangular/trapezoidal part of matrix `A`
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Periods.

- **M**: `[in] CBLAS_INT` number of rows in matrix `A`
- **N**: `[in] CBLAS_INT` number of columns in matrix `A`
- **A**: `[in] double*` input matrix
- **strideA1**: `[in] CBLAS_INT` stride of the first dimension of `A`
- **strideA2**: `[in] CBLAS_INT` stride of the second dimension of `A`
- **offsetB**: `[in] CBLAS_INT` starting index for `A`
- **B**: `[in] double*` output matrix
- **strideB1**: `[in] CBLAS_INT` stride of the first dimension of `B`
- **strideB2**: `[in] CBLAS_INT` stride of the second dimension of `B`
- **offsetB**: `[in] CBLAS_INT` starting index for `B`

```c
void c_dlacpy_ndarray( const CBLAS_UPLO uplo, const CBLAS_INT M, const CBLAS_INT N, double *A, const CBLAS_INT strideA1, const CBLAS_INT strideA2, const CBLAS_INT offsetA, double *B, const CBLAS_INT strideB1, const CBLAS_INT strideB2, const CBLAS_INT offsetB )
```

</section>
Expand All @@ -224,7 +271,35 @@ TODO
### Examples

```c
TODO
#include "stdlib/lapack/base/dlacpy.h"
#include "stdlib/blas/base/shared.h"

int main( void ) {
// Create strided arrays:
const double A[] = { 1.0, 0.0, 0.0, 2.0, 1.0, 0.0, 3.0, 2.0, 1.0 };
double B[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };

// Specify the number of elements along each dimension of `A`:
const int N = 3;

// Copies all or part of a matrix `A` to another matrix `B`:
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Suggested change
// Copies all or part of a matrix `A` to another matrix `B`:
// Copy the upper triangular part of a matrix `A` to another matrix `B`:

c_dlacpy( CblasColMajor, CblasUpper, N, N, A, N, B, N );

// Print the result:
for ( int i = 0; i < N*N; i++ ) {
printf( "B[ %i ] = %f\n", i, B[ i ] );
}

// Copies all or part of a matrix `A` to another matrix `B` using alternative indexing semantics:
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Suggested change
// Copies all or part of a matrix `A` to another matrix `B` using alternative indexing semantics:
// Copy the lower triangular part of a matrix `A` to another matrix `B` using alternative indexing semantics:

c_dlacpy_ndarray( CblasLower, N, N, A, 1, N, 0, B, 1, N, 0 );

// Print the result:
for ( int i = 0; i < N*N; i++ ) {
printf( "B[ %i ] = %f\n", i, B[ i ] );
}

return 0;
Comment on lines +300 to +301
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Suggested change
return 0;

This isn't needed.

}
```

</section>
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,114 @@
/**
* @license Apache-2.0
*
* Copyright (c) 2025 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

'use strict';

// MODULES //

var resolve = require( 'path' ).resolve;
var bench = require( '@stdlib/bench' );
var uniform = require( '@stdlib/random/array/uniform' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var pow = require( '@stdlib/math/base/special/pow' );
var floor = require( '@stdlib/math/base/special/floor' );
var tryRequire = require( '@stdlib/utils/try-require' );
var pkg = require( './../package.json' ).name;


// VARIABLES //

var dlacpy = tryRequire( resolve( __dirname, './../lib/dlacpy.native.js' ) );
var opts = {
'skip': ( dlacpy instanceof Error )
};


// FUNCTIONS //

/**
* Creates a benchmark function.
*
* @private
* @param {PositiveInteger} N - number of elements along each dimension
* @returns {Function} benchmark function
*/
function createBenchmark( N ) {
var options;
var A;
var B;

options = {
'dtype': 'float64'
};

A = uniform( N*N, -10.0, 10.0, options );
B = uniform( N*N, -10.0, 10.0, options );
return benchmark;

/**
* Benchmark function.
*
* @private
* @param {Benchmark} b - benchmark instance
*/
function benchmark( b ) {
var z;
var i;

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
z = dlacpy( 'column-major', 'all', N, N, A, N, B, N );
if ( isnan( z[ i%z.length ] ) ) {
b.fail( 'should not return NaN' );
}
}
b.toc();
if ( isnan( z[ i%z.length ] ) ) {
b.fail( 'should not return NaN' );
}
b.pass( 'benchmark finished' );
b.end();
}
}


// MAIN //

/**
* Main execution sequence.
*
* @private
*/
function main() {
var min;
var max;
var N;
var f;
var i;

min = 1; // 10^min
max = 6; // 10^max

for ( i = min; i <= max; i++ ) {
N = floor( pow( pow( 10, i ), 1.0/2.0 ) );
f = createBenchmark( N );
bench( pkg+':native::order=column-major,size='+(N*N), opts, f );
}
}

main();
Original file line number Diff line number Diff line change
@@ -0,0 +1,114 @@
/**
* @license Apache-2.0
*
* Copyright (c) 2025 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

'use strict';

// MODULES //

var resolve = require( 'path' ).resolve;
var bench = require( '@stdlib/bench' );
var uniform = require( '@stdlib/random/array/uniform' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var pow = require( '@stdlib/math/base/special/pow' );
var floor = require( '@stdlib/math/base/special/floor' );
var tryRequire = require( '@stdlib/utils/try-require' );
var pkg = require( '@stdlib/lapack/base/dlacpy/package.json' ).name;


// VARIABLES //

var dlacpy = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
var opts = {
'skip': ( dlacpy instanceof Error )
};


// FUNCTIONS //

/**
* Creates a benchmark function.
*
* @private
* @param {PositiveInteger} N - number of elements along each dimension
* @returns {Function} benchmark function
*/
function createBenchmark( N ) {
var options;
var A;
var B;

options = {
'dtype': 'float64'
};

A = uniform( N*N, -10.0, 10.0, options );
B = uniform( N*N, -10.0, 10.0, options );
return benchmark;

/**
* Benchmark function.
*
* @private
* @param {Benchmark} b - benchmark instance
*/
function benchmark( b ) {
var z;
var i;

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
z = dlacpy( 'all', N, N, A, 1, N, 0, B, 1, N, 0 );
if ( isnan( z[ i%z.length ] ) ) {
b.fail( 'should not return NaN' );
}
}
b.toc();
if ( isnan( z[ i%z.length ] ) ) {
b.fail( 'should not return NaN' );
}
b.pass( 'benchmark finished' );
b.end();
}
}


// MAIN //

/**
* Main execution sequence.
*
* @private
*/
function main() {
var min;
var max;
var N;
var f;
var i;

min = 1; // 10^min
max = 6; // 10^max

for ( i = min; i <= max; i++ ) {
N = floor( pow( pow( 10, i ), 1.0/2.0 ) );
f = createBenchmark( N );
bench( pkg+'::native:ndarray:order=column-major,size='+(N*N), opts, f );
}
}

main();
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