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120 changes: 120 additions & 0 deletions lib/node_modules/@stdlib/blas/base/ndarray/gscal/README.md
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<!--

@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.

-->

# gscal

> Multiply a one-dimensional ndarray by a scalar constant.

<section class="intro">

</section>

<!-- /.intro -->

<section class="usage">

## Usage

```javascript
var gscal = require( '@stdlib/blas/base/ndarray/gscal' );
```

#### gscal( arrays )

Multiplies a one-dimensional ndarray by a scalar constant.

```javascript
var vector = require( '@stdlib/ndarray/vector/ctor' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );

var x = vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ], 'generic' );

var alpha = scalar2ndarray( 5.0, {
'dtype': 'generic'
});

var y = gscal( [ x, alpha ] );
// returns <ndarray>[ 5.0, 10.0, 15.0, 20.0, 25.0 ]

var bool = ( y === x );
// returns true
```

The function has the following parameters:

- **arrays**: array-like object containing the following ndarrays:

- a one-dimensional input ndarray.
- a zero-dimensional ndarray containing a scalar constant.

</section>

<!-- /.usage -->

<section class="notes">

</section>

<!-- /.notes -->

<section class="examples">

## Examples

<!-- eslint no-undef: "error" -->

```javascript
var discreteUniform = require( '@stdlib/random/discrete-uniform' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
var ndarray2array = require( '@stdlib/ndarray/to-array' );
var gscal = require( '@stdlib/blas/base/ndarray/gscal' );

var opts = {
'dtype': 'generic'
};

var x = discreteUniform( [ 10 ], 0, 100, opts );
console.log( ndarray2array( x ) );

var alpha = scalar2ndarray( 5.0, opts );

var out = gscal( [ x, alpha ] );
console.log( ndarray2array( out ) );
```

</section>

<!-- /.examples -->

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

<section class="related">

</section>

<!-- /.related -->

<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->

<section class="links">

</section>

<!-- /.links -->
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/**
* @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 bench = require( '@stdlib/bench' );
var uniform = require( '@stdlib/random/uniform' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var pow = require( '@stdlib/math/base/special/pow' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
var format = require( '@stdlib/string/format' );
var pkg = require( './../package.json' ).name;
var gscal = require( './../lib' );


// VARIABLES //

var options = {
'dtype': 'generic'
};


// FUNCTIONS //

/**
* Creates a benchmark function.
*
* @private
* @param {PositiveInteger} len - array length
* @returns {Function} benchmark function
*/
function createBenchmark( len ) {
var alpha;
var x;

x = uniform( [ len ], -100.0, 100.0, options );
alpha = scalar2ndarray( 5.0, 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 = gscal( [ x, alpha ] );
if ( typeof z !== 'object' ) {
b.fail( 'should return an ndarray' );
}
}
b.toc();
if ( isnan( z.get( i%len ) ) ) {
b.fail( 'should not return NaN' );
}
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:len=%d', pkg, len ), f );
}
}

main();
32 changes: 32 additions & 0 deletions lib/node_modules/@stdlib/blas/base/ndarray/gscal/docs/repl.txt
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{{alias}}( arrays )
Multiplies a one-dimensional ndarray by a scalar constant.

If provided an empty input ndarray, the function returns the input ndarray
unchanged.

Parameters
----------
arrays: ArrayLikeObject<ndarray>
Array-like object containing the following ndarrays:

- a one-dimensional input/output ndarray.
- a zero-dimensional ndarray containing a scalar constant.

Returns
-------
out: ndarray
Input ndarray.

Examples
--------
> var x = {{alias:@stdlib/ndarray/vector/ctor}}( [ 4.0, 2.0, -3.0, 5.0, -1.0 ], 'generic' );
> var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 5.0, { 'dtype': 'generic' } );

> {{alias}}( [ x, alpha ] );
> x
<ndarray>[ 20.0, 10.0, -15.0, 25.0, -5.0 ]

See Also
--------

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/*
* @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.
*/

// TypeScript Version: 4.1

/// <reference types="@stdlib/types"/>

import { typedndarray } from '@stdlib/types/ndarray';

/**
* Multiplies a one-dimensional ndarray by a scalar constant.
*
* ## Notes
*
* - The function expects the following ndarrays:
*
* - a one-dimensional input ndarray.
* - a zero-dimensional ndarray containing a scalar constant.
*
* @param arrays - array-like object containing ndarrays
* @returns input ndarray
*
* @example
* var vector = require( '@stdlib/ndarray/vector/ctor' );
* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
*
* var x = vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ], 'generic' );
*
* var alpha = scalar2ndarray( 5.0, {
* 'dtype': 'generic'
* });
*
* var y = gscal( [ x, alpha ] );
* // returns <ndarray>[ 5.0, 10.0, 15.0, 20.0, 25.0 ]
*
* var bool = ( y === x );
* // returns true
*/
declare function gscal<T extends typedndarray<number> = typedndarray<number>>( arrays: [ T, typedndarray<number> ] ): T;


// EXPORTS //

export = gscal;
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/*
* @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.
*/

/* eslint-disable space-in-parens */

import zeros = require( '@stdlib/ndarray/zeros' );
import gscal = require( './index' );


// TESTS //

// The function returns an ndarray...
{
const x = zeros( [ 10 ], {
'dtype': 'generic'
});
const alpha = zeros( [], {
'dtype': 'generic'
});

gscal( [ x, alpha ] ); // $ExpectType genericndarray<number>
}

// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
{
gscal( '10' ); // $ExpectError
gscal( 10 ); // $ExpectError
gscal( true ); // $ExpectError
gscal( false ); // $ExpectError
gscal( null ); // $ExpectError
gscal( undefined ); // $ExpectError
gscal( [] ); // $ExpectError
gscal( {} ); // $ExpectError
gscal( ( x: number ): number => x ); // $ExpectError
}

// The compiler throws an error if the function is provided an unsupported number of arguments...
{
const x = zeros( [ 10 ], {
'dtype': 'generic'
});
const alpha = zeros( [], {
'dtype': 'generic'
});

gscal(); // $ExpectError
gscal( [ x, alpha ], {} ); // $ExpectError
}
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