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123 changes: 123 additions & 0 deletions lib/node_modules/@stdlib/blas/ext/base/ndarray/gapxsum/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.

-->

# gapxsum

> Add a scalar constant to each element in a one-dimensional ndarray and compute the sum.

<section class="intro">

</section>

<!-- /.intro -->

<section class="usage">

## Usage

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

#### gapxsum( arrays )

Adds a scalar constant to each element in a one-dimensional ndarray and computes the sum.

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

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

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

var v = gapxsum( [ x, alpha ] );
// returns 30.0
```

The function has the following parameters:

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

- a one-dimensional input ndarray.
- a zero-dimensional ndarray containing the scalar constant to add.

</section>

<!-- /.usage -->

<section class="notes">

## Notes

- If provided an empty one-dimensional ndarray, the function returns `0.0`.

</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 gapxsum = require( '@stdlib/blas/ext/base/ndarray/gapxsum' );

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

var x = discreteUniform( [ 10 ], -50, 50, opts );
console.log( ndarray2array( x ) );

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

var v = gapxsum( [ x, alpha ] );
console.log( v );
```

</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 isnan = require( '@stdlib/math/base/assert/is-nan' );
var pow = require( '@stdlib/math/base/special/pow' );
var format = require( '@stdlib/string/format' );
var pkg = require( './../package.json' ).name;
var gapxsum = require( './../lib' );


// VARIABLES //

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


// FUNCTIONS //

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

x = uniform( [ len ], -10.0, 10.0, options );
alpha = scalar2ndarray( 5.0, 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 = gapxsum( [ x, alpha ] );
if ( isnan( v ) ) {
b.fail( 'should not return NaN' );
}
}
b.toc();
if ( isnan( v ) ) {
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();
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{{alias}}( arrays )
Adds a scalar constant to each element in a one-dimensional ndarray and
computes the sum.

If provided an empty ndarray, the function returns `0.0`.

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

- a one-dimensional input ndarray.
- a zero-dimensional ndarray containing the scalar constant to add.

Returns
-------
out: number
Sum.

Examples
--------
> var x = {{alias:@stdlib/ndarray/vector/ctor}}( [ 1.0, 2.0, 3.0 ], 'generic' );
> var opts = { 'dtype': 'generic' };
> var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 5.0, opts );
> {{alias}}( [ x, alpha ] )
21.0

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';

/**
* Adds a scalar constant to each element in a one-dimensional ndarray and computes the sum.
*
* ## Notes
*
* - The function expects the following ndarrays:
*
* - a one-dimensional input ndarray.
* - a zero-dimensional ndarray containing the scalar constant to add.
*
* @param arrays - array-like object containing ndarrays
* @returns sum
*
* @example
* var vector = require( '@stdlib/ndarray/vector/ctor' );
* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
*
* var x = vector( [ 1.0, 3.0, 4.0, 2.0 ], 'generic' );
*
* var alpha = scalar2ndarray( 5.0, {
* 'dtype': 'generic'
* });
*
* var v = gapxsum( [ x, alpha ] );
* // returns 30.0
*/
declare function gapxsum<T extends typedndarray<number> = typedndarray<number>>( arrays: [ T, typedndarray<number> ] ): number;


// EXPORTS //

export = gapxsum;
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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 scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
import gapxsum = require( './index' );


// TESTS //

// The function returns a number...
{
const x = zeros( [ 10 ], {
'dtype': 'generic'
});
const alpha = scalar2ndarray( 5.0, {
'dtype': 'generic'
});

gapxsum( [ x, alpha ] ); // $ExpectType number
}

// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
{
gapxsum( '10' ); // $ExpectError
gapxsum( 10 ); // $ExpectError
gapxsum( true ); // $ExpectError
gapxsum( false ); // $ExpectError
gapxsum( null ); // $ExpectError
gapxsum( undefined ); // $ExpectError
gapxsum( [] ); // $ExpectError
gapxsum( {} ); // $ExpectError
gapxsum( ( 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 = scalar2ndarray( 5.0, {
'dtype': 'generic'
});

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