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125 changes: 125 additions & 0 deletions lib/node_modules/@stdlib/blas/base/ndarray/cscal/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.

-->

# cscal

> Multiply a one-dimensional single-precision complex floating-point ndarray by a scalar constant.

<section class="intro">

</section>

<!-- /.intro -->

<section class="usage">

## Usage

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

#### cscal( arrays )

Multiplies a one-dimensional single-precision complex floating-point ndarray by a scalar constant.

```javascript
var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' );
var Complex64 = require( '@stdlib/complex/float32/ctor' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );

var x = new Complex64Vector( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );

var alpha = scalar2ndarray( new Complex64( 2.0, 0.0 ), {
'dtype': 'complex64'
});

var y = cscal( [ x, alpha ] );
// returns <ndarray>[ <Complex64>[ 2.0, 4.0 ], <Complex64>[ 6.0, 8.0 ], <Complex64>[ 10.0, 12.0 ] ]

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/array/discrete-uniform' );
var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' );
var Complex64 = require( '@stdlib/complex/float32/ctor' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
var ndarray2array = require( '@stdlib/ndarray/to-array' );
var cscal = require( '@stdlib/blas/base/ndarray/cscal' );

var opts = {
'dtype': 'float32'
};

var x = new Complex64Vector( discreteUniform( 10, 0, 100, opts ) );
console.log( ndarray2array( x ) );

var alpha = scalar2ndarray( new Complex64( 2.0, 0.0 ), {
'dtype': 'complex64'
});

var out = cscal( [ 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/array/uniform' );
var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
var realf = require( '@stdlib/complex/float32/real' );
var pow = require( '@stdlib/math/base/special/pow' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' );
var Complex64 = require( '@stdlib/complex/float32/ctor' );
var format = require( '@stdlib/string/format' );
var pkg = require( './../package.json' ).name;
var cscal = require( './../lib' );


// VARIABLES //

var options = {
'dtype': 'complex64'
};


// FUNCTIONS //

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

xbuf = uniform( len*2, -100.0, 100.0, {
'dtype': 'float32'
});
x = new Complex64Vector( xbuf.buffer );

alpha = scalar2ndarray( new Complex64( 0.8, 0.6 ), 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 = cscal( [ x, alpha ] );
if ( typeof z !== 'object' ) {
b.fail( 'should return an ndarray' );
}
}
b.toc();
if ( isnanf( realf( 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();
34 changes: 34 additions & 0 deletions lib/node_modules/@stdlib/blas/base/ndarray/cscal/docs/repl.txt
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{{alias}}( arrays )
Multiplies a one-dimensional single-precision complex floating-point 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 ndarray.
- a zero-dimensional ndarray containing a scalar constant.

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

Examples
--------
> var x = new {{alias:@stdlib/ndarray/vector/complex64}}( [ 4.0, 2.0, -3.0, 5.0 ] );
> var ca = new {{alias:@stdlib/complex/float32/ctor}}( 2.0, 0.0 );
> var alpha = {{alias:@stdlib/ndarray/from-scalar}}( ca, { 'dtype': 'complex64' } );

> {{alias}}( [ x, alpha ] );
> x
<ndarray>[ <Complex64>[ 8.0, 4.0 ], <Complex64>[ -6.0, 10.0 ] ]

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 { complex64ndarray } from '@stdlib/types/ndarray';

/**
* Multiplies a one-dimensional single-precision complex floating-point 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 Complex64Vector = require( '@stdlib/ndarray/vector/complex64' );
* var Complex64 = require( '@stdlib/complex/float32/ctor' );
* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
*
* var x = new Complex64Vector( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
*
* var alpha = scalar2ndarray( new Complex64( 2.0, 0.0 ), {
* 'dtype': 'complex64'
* });
*
* var y = cscal( [ x, alpha ] );
* // returns <ndarray>[ <Complex64>[ 2.0, 4.0 ], <Complex64>[ 6.0, 8.0 ], <Complex64>[ 10.0, 12.0 ] ]
*
* var bool = ( y === x );
* // returns true
*/
declare function cscal( arrays: [ complex64ndarray, complex64ndarray ] ): complex64ndarray;


// EXPORTS //

export = cscal;
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