Skip to content
Open
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
135 changes: 135 additions & 0 deletions lib/node_modules/@stdlib/blas/ext/base/ndarray/dapxsumkbn/README.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,135 @@
<!--

@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.

-->

# dapxsumkbn

> Add a scalar constant to each element in a one-dimensional double-precision floating-point ndarray and compute the sum using an improved Kahan–Babuška algorithm.

<section class="intro">

</section>

<!-- /.intro -->

<section class="usage">

## Usage

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

#### dapxsumkbn( arrays )

Adds a scalar constant to each element in a one-dimensional double-precision floating-point ndarray and computes the sum using an improved Kahan–Babuška algorithm.

```javascript
var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );

var x = new Float64Vector( [ 1.0, -2.0, 2.0 ] );

var alpha = scalar2ndarray( 5.0, {
'dtype': 'float64'
});

var v = dapxsumkbn( [ x, alpha ] );
// returns 16.0
```

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

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

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

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

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

</section>

<!-- /.examples -->

<section class="references">

## References

- Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." _Zeitschrift Für Angewandte Mathematik Und Mechanik_ 54 (1): 39–51. doi:[10.1002/zamm.19740540106][@neumaier:1974a].

</section>

<!-- /.references -->

<!-- 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">

[@neumaier:1974a]: https://doi.org/10.1002/zamm.19740540106

</section>

<!-- /.links -->
Original file line number Diff line number Diff line change
@@ -0,0 +1,108 @@
/**
* @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 dapxsumkbn = require( './../lib' );


// VARIABLES //

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


// 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 ], -100.0, 100.0, 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 = dapxsumkbn( [ 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();
Original file line number Diff line number Diff line change
@@ -0,0 +1,32 @@

{{alias}}( arrays )
Adds a scalar constant to each element in a one-dimensional double-precision
floating-point ndarray and computes the sum using an improved Kahan–Babuška
algorithm.

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 buf = [ 1.0, -2.0, 2.0 ];
> var x = new {{alias:@stdlib/ndarray/vector/float64}}( buf );
> var opts = { 'dtype': 'float64' };
> var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 5.0, opts );
> {{alias}}( [ x, alpha ] )
16.0

See Also
--------
Original file line number Diff line number Diff line change
@@ -0,0 +1,56 @@
/*
* @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 { float64ndarray, typedndarray } from '@stdlib/types/ndarray';

/**
* Adds a scalar constant to each element in a one-dimensional double-precision floating-point ndarray and computes the sum using an improved Kahan–Babuška algorithm.
*
* ## 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 Float64Vector = require( '@stdlib/ndarray/vector/float64' );
* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
*
* var x = new Float64Vector( [ 1.0, -2.0, 2.0 ] );
*
* var alpha = scalar2ndarray( 5.0, {
* 'dtype': 'float64'
* });
*
* var v = dapxsumkbn( [ x, alpha ] );
* // returns 16.0
*/
declare function dapxsumkbn( arrays: [ float64ndarray, typedndarray<number> ] ): number;


// EXPORTS //

export = dapxsumkbn;
Original file line number Diff line number Diff line change
@@ -0,0 +1,64 @@
/*
* @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 dapxsumkbn = require( './index' );


// TESTS //

// The function returns a number...
{
const x = zeros( [ 10 ], {
'dtype': 'float64'
});
const alpha = scalar2ndarray( 5.0, {
'dtype': 'float64'
});

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

// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
{
dapxsumkbn( '10' ); // $ExpectError
dapxsumkbn( 5 ); // $ExpectError
dapxsumkbn( true ); // $ExpectError
dapxsumkbn( false ); // $ExpectError
dapxsumkbn( null ); // $ExpectError
dapxsumkbn( undefined ); // $ExpectError
dapxsumkbn( [] ); // $ExpectError
dapxsumkbn( {} ); // $ExpectError
dapxsumkbn( ( 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': 'float64'
});
const alpha = scalar2ndarray( 5.0, {
'dtype': 'float64'
});

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