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176 changes: 176 additions & 0 deletions lib/node_modules/@stdlib/blas/ext/base/ndarray/dwhere/README.md
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Expand Up @@ -111,6 +111,182 @@ console.log( ndarray2array( out ) );

<!-- /.examples -->

<!-- C interface documentation. -->

* * *

<section class="c">

## C APIs

<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->

<section class="intro">

</section>

<!-- /.intro -->

<!-- C usage documentation. -->

<section class="usage">

### Usage

```c
#include "stdlib/blas/ext/base/ndarray/dwhere.h"
```

#### stdlib_blas_ext_dwhere( arrays )

Takes elements from one of two one-dimensional double-precision floating-point ndarrays depending on a condition.

```c
#include "stdlib/ndarray/ctor.h"
#include "stdlib/ndarray/dtypes.h"
#include "stdlib/ndarray/index_modes.h"
#include "stdlib/ndarray/orders.h"
#include "stdlib/ndarray/base/bytes_per_element.h"
#include <stdint.h>
#include <stdbool.h>

// Create data buffers:
const uint8_t dataC[] = { 1, 0, 1, 0 };
const double dataX[] = { 1.0, 2.0, 3.0, 4.0 };
const double dataY[] = { 5.0, 6.0, 7.0, 8.0 };
double dataOut[] = { 0.0, 0.0, 0.0, 0.0 };

int64_t shape[] = { 4 };
int64_t stridesC[] = { STDLIB_NDARRAY_BOOL_BYTES_PER_ELEMENT };
int64_t strides[] = { STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT };
int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR };

struct ndarray *c = stdlib_ndarray_allocate( STDLIB_NDARRAY_BOOL, (uint8_t *)dataC, 1, shape, stridesC, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes );
struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataX, 1, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes );
struct ndarray *y = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataY, 1, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes );
struct ndarray *out = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataOut, 1, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes );

// Perform computation:
const struct ndarray *arrays[] = { c, x, y, out };
stdlib_blas_ext_dwhere( arrays );

// Free allocated memory:
stdlib_ndarray_free( c );
stdlib_ndarray_free( x );
stdlib_ndarray_free( y );
stdlib_ndarray_free( out );
```

The function accepts the following arguments:

- **arrays**: `[in] struct ndarray**` list containing the following ndarrays:

- `[in] struct ndarray*` a one-dimensional condition ndarray.
- `[in] struct ndarray*` first one-dimensional input ndarray.
- `[in] struct ndarray*` second one-dimensional input ndarray.
- `[out] struct ndarray*` a one-dimensional output ndarray.

```c
void stdlib_blas_ext_dwhere( const struct ndarray *arrays[] );
```

</section>

<!-- /.usage -->

<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->

<section class="notes">

</section>

<!-- /.notes -->

<!-- C API usage examples. -->

<section class="examples">

### Examples

```c
#include "stdlib/blas/ext/base/ndarray/dwhere.h"
#include "stdlib/ndarray/ctor.h"
#include "stdlib/ndarray/dtypes.h"
#include "stdlib/ndarray/index_modes.h"
#include "stdlib/ndarray/orders.h"
#include "stdlib/ndarray/base/bytes_per_element.h"
#include <stdint.h>
#include <stdbool.h>
#include <stdlib.h>
#include <stdio.h>

int main( void ) {
// Create data buffers:
const uint8_t dataC[] = { 1, 0, 1, 0 };
const double dataX[] = { 1.0, 2.0, 3.0, 4.0 };
const double dataY[] = { 5.0, 6.0, 7.0, 8.0 };
double dataOut[] = { 0.0, 0.0, 0.0, 0.0 };

// Specify the number of array dimensions:
const int64_t ndims = 1;

// Specify the array shape:
int64_t shape[] = { 4 };

// Specify the array strides:
int64_t stridesC[] = { STDLIB_NDARRAY_BOOL_BYTES_PER_ELEMENT };
int64_t strides[] = { STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT };

// Specify the byte offset:
const int64_t offset = 0;

// Specify the array order:
const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR;

// Specify the index mode:
const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR;

// Specify the subscript index modes:
int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR };
const int64_t nsubmodes = 1;

// Create ndarrays:
struct ndarray *c = stdlib_ndarray_allocate( STDLIB_NDARRAY_BOOL, (uint8_t *)dataC, ndims, shape, stridesC, offset, order, imode, nsubmodes, submodes );
struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataX, ndims, shape, strides, offset, order, imode, nsubmodes, submodes );
struct ndarray *y = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataY, ndims, shape, strides, offset, order, imode, nsubmodes, submodes );
struct ndarray *out = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)dataOut, ndims, shape, strides, offset, order, imode, nsubmodes, submodes );
if ( c == NULL || x == NULL || y == NULL || out == NULL ) {
fprintf( stderr, "Error allocating memory.\n" );
exit( 1 );
}

// Define a list of ndarrays:
const struct ndarray *arrays[] = { c, x, y, out };

// Perform computation:
stdlib_blas_ext_dwhere( arrays );

// Print the result:
for ( int i = 0; i < 4; i++ ) {
printf( "out[ %i ] = %lf\n", i, dataOut[ i ] );
}

// Free allocated memory:
stdlib_ndarray_free( c );
stdlib_ndarray_free( x );
stdlib_ndarray_free( y );
stdlib_ndarray_free( out );
}
```

</section>

<!-- /.examples -->

</section>

<!-- /.c -->

<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->

<section class="related">
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,7 @@ var BooleanVector = require( '@stdlib/ndarray/vector/bool' );
var pow = require( '@stdlib/math/base/special/pow' );
var format = require( '@stdlib/string/format' );
var pkg = require( './../package.json' ).name;
var dwhere = require( './../lib' );
var dwhere = require( './../lib/main.js' );


// VARIABLES //
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Original file line number Diff line number Diff line change
@@ -0,0 +1,121 @@
/**
* @license Apache-2.0
*
* Copyright (c) 2026 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 bernoulli = require( '@stdlib/random/array/bernoulli' );
var uniform = require( '@stdlib/random/uniform' );
var BooleanVector = require( '@stdlib/ndarray/vector/bool' );
var pow = require( '@stdlib/math/base/special/pow' );
var format = require( '@stdlib/string/format' );
var tryRequire = require( '@stdlib/utils/try-require' );
var pkg = require( './../package.json' ).name;


// VARIABLES //

var dwhere = tryRequire( resolve( __dirname, './../lib/native.js' ) );
var opts = {
'skip': ( dwhere instanceof Error )
};
var options = {
'dtype': 'float64'
};


// FUNCTIONS //

/**
* Creates a benchmark function.
*
* @private
* @param {PositiveInteger} len - ndarray length
* @returns {Function} benchmark function
*/
function createBenchmark( len ) {
var condition;
var cbuf;
var out;
var x;
var y;

cbuf = bernoulli( len, 0.5, {
'dtype': 'uint8'
});
condition = new BooleanVector( cbuf.buffer );
out = uniform( [ len ], -100.0, 100.0, options );
x = uniform( [ len ], -100.0, 100.0, options );
y = uniform( [ len ], -100.0, 100.0, options );
return benchmark;

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

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
v = dwhere( [ condition, x, y, out ] );
if ( typeof v !== 'object' ) {
b.fail( 'should return an ndarray' );
}
}
b.toc();
if ( typeof v !== 'object' ) {
b.fail( 'should return an ndarray' );
}
b.pass( 'benchmark finished' );
b.end();
}
}


// MAIN //

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

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

for ( i = min; i <= max; i++ ) {
len = pow( 10, i );
f = createBenchmark( len );
bench( format( '%s::native:len=%d', pkg, len ), opts, f );
}
}

main();
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