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146 changes: 146 additions & 0 deletions lib/node_modules/@stdlib/blas/ext/base/ndarray/saxpby/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.

-->

# saxpby

> Multiply a one-dimensional single-precision floating-point ndarray by a scalar constant and add the result to a second one-dimensional single-precision floating-point ndarray multiplied by a scalar constant.

<section class="intro">

This BLAS extension implements the operation

<!-- <equation class="equation" label="eq:axpby" align="center" raw="\mathbf{y} = \alpha \mathbf{x} + \beta \mathbf{y}" alt="Equation for axpby operation."> -->

```math
\mathbf{y} = \alpha \mathbf{x} + \beta \mathbf{y}
```

<!-- </equation> -->

</section>

<!-- /.intro -->

<section class="usage">

## Usage

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

#### saxpby( arrays )

Multiplies a one-dimensional single-precision floating-point ndarray by a scalar constant and adds the result to a second one-dimensional single-precision floating-point ndarray multiplied by a scalar constant.

```javascript
var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );

var x = new Float32Vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
var y = new Float32Vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] );

var alpha = scalar2ndarray( 5.0, {
'dtype': 'float32'
});

var beta = scalar2ndarray( 2.0, {
'dtype': 'float32'
});

saxpby( [ x, y, alpha, beta ] );
// y => <ndarray>[ 9.0, 16.0, 23.0, 30.0, 37.0 ]
```

The function has the following parameters:

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

- a one-dimensional input ndarray.
- a one-dimensional output ndarray.
- a zero-dimensional ndarray containing the constant by which to multiply the input ndarray.
- a zero-dimensional ndarray containing the constant by which to multiply the output ndarray.

</section>

<!-- /.usage -->

<section class="notes">

## Notes

- The output ndarray is modified **in-place** (i.e., the output ndarray is **mutated**).

</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 ndarraylike2scalar = require( '@stdlib/ndarray/ndarraylike2scalar' );
var saxpby = require( '@stdlib/blas/ext/base/ndarray/saxpby' );

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

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

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

var alpha = scalar2ndarray( 5.0, opts );
console.log( 'Alpha: %d', ndarraylike2scalar( alpha ) );

var beta = scalar2ndarray( 2.0, opts );
console.log( 'Beta: %d', ndarraylike2scalar( beta ) );

saxpby( [ x, y, alpha, beta ] );
console.log( ndarray2array( y ) );
```

</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 scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
var pow = require( '@stdlib/math/base/special/pow' );
var format = require( '@stdlib/string/format' );
var pkg = require( './../package.json' ).name;
var saxpby = require( './../lib' );


// VARIABLES //

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


// FUNCTIONS //

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

x = uniform( [ len ], -100.0, 100.0, options );
y = uniform( [ len ], -100.0, 100.0, options );
alpha = scalar2ndarray( 5.0, options );
beta = scalar2ndarray( 2.0, options );
return benchmark;

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

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
out = saxpby( [ x, y, alpha, beta ] );
if ( typeof out !== 'object' ) {
b.fail( 'should return an ndarray' );
}
}
b.toc();
if ( typeof out !== '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:len=%d', pkg, len ), f );
}
}

main();
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{{alias}}( arrays )
Multiplies a one-dimensional single-precision floating-point ndarray by a
scalar constant and adds the result to a second one-dimensional single-
precision floating-point ndarray multiplied by a scalar constant.

The output ndarray is modified *in-place* (i.e., the output ndarray is
*mutated*).

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

- a one-dimensional input ndarray.
- a one-dimensional output ndarray.
- a zero-dimensional ndarray containing the constant by which to
multiply the input ndarray.
- a zero-dimensional ndarray containing the constant by which to
multiply the output ndarray.

Returns
-------
out: ndarray
Output ndarray.

Examples
--------
> var xbuf = [ 1.0, 2.0, 3.0, 4.0 ];
> var x = new {{alias:@stdlib/ndarray/vector/float32}}( xbuf );
> var ybuf = [ 2.0, 3.0, 4.0, 5.0 ];
> var y = new {{alias:@stdlib/ndarray/vector/float32}}( ybuf );
> var opts = { 'dtype': 'float32' };
> var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 5.0, opts );
> var beta = {{alias:@stdlib/ndarray/from-scalar}}( 2.0, opts );
> {{alias}}( [ x, y, alpha, beta ] )
<ndarray>[ 9.0, 16.0, 23.0, 30.0 ]

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 { float32ndarray, typedndarray } from '@stdlib/types/ndarray';

/**
* Multiplies a one-dimensional single-precision floating-point ndarray by a scalar constant and adds the result to a second one-dimensional single-precision floating-point ndarray multiplied by a scalar constant.
*
* ## Notes
*
* - The function expects the following ndarrays:
*
* - a one-dimensional input ndarray.
* - a one-dimensional output ndarray.
* - a zero-dimensional ndarray containing the scalar constant by which to multiply the input ndarray.
* - a zero-dimensional ndarray containing the scalar constant by which to multiply the output ndarray.
*
* @param arrays - array-like object containing ndarrays
* @returns output ndarray
*
* @example
* var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
*
* var x = new Float32Vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
* var y = new Float32Vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] );
*
* var alpha = scalar2ndarray( 5.0, {
* 'dtype': 'float32'
* });
*
* var beta = scalar2ndarray( 2.0, {
* 'dtype': 'float32'
* });
*
* var out = saxpby( [ x, y, alpha, beta ] );
* // returns <ndarray>[ 9.0, 16.0, 23.0, 30.0, 37.0 ]
*/
declare function saxpby( arrays: [ float32ndarray, float32ndarray, typedndarray<number>, typedndarray<number> ] ): float32ndarray;


// EXPORTS //

export = saxpby;
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