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134 changes: 134 additions & 0 deletions lib/node_modules/@stdlib/blas/ext/base/ndarray/dcusumkbn/README.md
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<!--

@license Apache-2.0

Copyright (c) 2025 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.

-->

# dcusumkbn

> Compute the cumulative sum of one-dimensional double-precision floating-point ndarray using an improved Kahan–Babuška algorithm.

<section class="intro">

</section>

<!-- /.intro -->

<section class="usage">

## Usage

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

#### dcusumkbn( arrays )

Computes the cumulative sum of one-dimensional double-precision floating-point ndarray using an improved Kahan–Babuška algorithm.

```javascript
var Float64Array = require( '@stdlib/array/float64' );
var ndarray2array = require( '@stdlib/ndarray/to-array' );
var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' );
var ndarray = require( '@stdlib/ndarray/base/ctor' );

var xbuf = new Float64Array( [ 1.0, 3.0, 4.0, 2.0 ] );
var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );

var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );
var y = new ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );

var initial = scalar2ndarray( 0.0, 'float64', 'row-major' );

var v = dcusumkbn( [ x, y, initial ] );
// returns <ndarray>

var bool = ( v === y );
// returns true

var arr = ndarray2array( v );
// returns [ 1.0, 4.0, 8.0, 10.0 ]
```

The function has the following parameters:

- **arrays**: array-like object containing a one-dimensional input ndarray, a one-dimensional output ndarray, and a zero-dimensional ndarray containing the initial sum.

</section>

<!-- /.usage -->

<section class="notes">

## Notes

- If provided an empty one-dimensional input ndarray, the function returns the output ndarray unchanged.

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

```javascript
var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var ndarray = require( '@stdlib/ndarray/base/ctor' );
var zerosLike = require( '@stdlib/ndarray/zeros-like' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
var ndarray2array = require( '@stdlib/ndarray/to-array' );
var dcusumkbn = require( '@stdlib/blas/ext/base/ndarray/dcusumkbn' );

var xbuf = discreteUniform( 10, -50, 50, {
'dtype': 'float64'
});
var x = new ndarray( 'float64', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
console.log( ndarray2array( x ) );

var y = zerosLike( x );
console.log( ndarray2array( y ) );

var initial = scalar2ndarray( 100.0, {
'dtype': 'float64'
});

var v = dcusumkbn( [ x, y, initial ] );
console.log( ndarray2array( 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) 2025 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 zeros = require( '@stdlib/array/zeros' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var pow = require( '@stdlib/math/base/special/pow' );
var ndarray = require( '@stdlib/ndarray/base/ctor' );
var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' );
var pkg = require( './../package.json' ).name;
var dcusumkbn = require( './../lib' );


// VARIABLES //

var options = {
'dtype': 'float64'
};


// FUNCTIONS //

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

xbuf = uniform( len, -10.0, 10.0, options );
x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' );

initial = scalar2ndarray( 0.0, options.dtype, 'row-major' );

ybuf = zeros( len, options.dtype );
y = new ndarray( options.dtype, ybuf, [ len ], [ 1 ], 0, 'row-major' );

return benchmark;

function benchmark( b ) {
var v;
var i;

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
v = dcusumkbn( [ x, y, initial ] );
if ( typeof v !== 'object' ) {
b.fail( 'should return an ndarray' );
}
}
b.toc();
if ( isnan( v.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( pkg+':len='+len, f );
}
}

main();
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{{alias}}( arrays )
Computes the cumulative sum of one-dimensional double-precision
floating-point ndarray using an improved Kahan–Babuška algorithm.

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

Parameters
----------
arrays: ArrayLikeObject<ndarray>
Array-like object containing a one-dimensional input ndarray, a one-
dimensional output ndarray, and a zero-dimensional ndarray containing
the initial sum.

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

Examples
--------
> var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] );
> var ybuf = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0 ] );
> var dt = 'float64';
> var sh = [ xbuf.length ];
> var st = [ 1 ];
> var oo = 0;
> var ord = 'row-major';
> var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, st, oo, ord );
> var y = new {{alias:@stdlib/ndarray/ctor}}( dt, ybuf, sh, st, oo, ord );
> var s = {{alias:@stdlib/ndarray/from-scalar}}( 0.0, { 'dtype': dt } );
> {{alias}}( [ x, y, s ] );
> {{alias:@stdlib/ndarray/to-array}}( y )
[ 1.0, -1.0, 1.0 ]

See Also
--------

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/*
* @license Apache-2.0
*
* Copyright (c) 2025 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 { float64ndarray } from '@stdlib/types/ndarray';

/**
* Computes the cumulative sum of one-dimensional double-precision floating-point ndarray using an improved Kahan–Babuška algorithm.
*
* @param arrays - array-like object containing an input ndarray, an output ndarray, and ndarray containing the initial sum
* @returns output ndarray
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
* var ndarray2array = require( '@stdlib/ndarray/to-array' );
* var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' );
* var ndarray = require( '@stdlib/ndarray/base/ctor' );
*
* var xbuf = new Float64Array( [ 1.0, 3.0, 4.0, 2.0 ] );
* var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
*
* var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );
* var y = new ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );
*
* var initial = scalar2ndarray( 0.0, 'float64', 'row-major' );
*
* var v = dcusumkbn( [ x, y, initial ] );
* // returns <ndarray>
*
* var bool = ( v === y );
* // returns true
*
* var arr = ndarray2array( v );
* // returns [ 1.0, 4.0, 8.0, 10.0 ]
*/
declare function dcusumkbn( arrays: [ float64ndarray, float64ndarray, float64ndarray ] ): float64ndarray;


// EXPORTS //

export = dcusumkbn;
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