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About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

gapx

NPM version Build Status Coverage Status

Add a scalar constant to each element in a strided array.

Usage

import gapx from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-ext-base-gapx@esm/index.mjs';

You can also import the following named exports from the package:

import { ndarray } from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-ext-base-gapx@esm/index.mjs';

gapx( N, alpha, x, strideX )

Adds a scalar constant to each element in a strided array.

var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];

gapx( x.length, 5.0, x, 1 );
// x => [ 3.0, 6.0, 8.0, 0.0, 9.0, 5.0, 4.0, 2.0 ]

The function has the following parameters:

  • N: number of indexed elements.
  • alpha: scalar constant.
  • x: input Array or typed array.
  • strideX: stride length.

The N and stride parameters determine which elements in the strided array are accessed at runtime. For example, to add a constant to every other element:

var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];

gapx( 4, 5.0, x, 2 );
// x => [ 3.0, 1.0, 8.0, -5.0, 9.0, 0.0, 4.0, -3.0 ]

Note that indexing is relative to the first index. To introduce an offset, use typed array views.

import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@esm/index.mjs';

// Initial array...
var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );

// Create an offset view...
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

// Add a constant to every other element...
gapx( 3, 5.0, x1, 2 );
// x0 => <Float64Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]

gapx.ndarray( N, alpha, x, strideX, offsetX )

Adds a scalar constant to each element in a strided array using alternative indexing semantics.

var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];

gapx.ndarray( x.length, 5.0, x, 1, 0 );
// x => [ 3.0, 6.0, 8.0, 0.0, 9.0, 5.0, 4.0, 2.0 ]

The function has the following additional parameters:

  • offsetX: starting index.

While typed array views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements:

var x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];

gapx.ndarray( 3, 5.0, x, 1, x.length-3 );
// x => [ 1.0, -2.0, 3.0, 1.0, 10.0, -1.0 ]

Notes

  • If N <= 0, both functions return x unchanged.
  • Both functions support array-like objects having getter and setter accessors for array element access (e.g., @stdlib/array-base/accessor)
  • Depending on the environment, the typed versions (dapx, sapx, etc.) are likely to be significantly more performant.

Examples

<!DOCTYPE html>
<html lang="en">
<body>
<script type="module">

import discreteUniform from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-array-discrete-uniform@esm/index.mjs';
import gapx from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-ext-base-gapx@esm/index.mjs';

var x = discreteUniform( 10, -100, 100, {
    'dtype': 'float64'
});
console.log( x );

gapx( x.length, 5.0, x, 1 );
console.log( x );

</script>
</body>
</html>

See Also

Notice

This package is part of stdlib, a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.

For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.

Community

Chat

License

See LICENSE.

Copyright

Copyright © 2016-2025. The Stdlib Authors.