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About stdlib...

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gscal

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Multiply a vector by a scalar constant.

Usage

import gscal from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-base-gscal@deno/mod.js';

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

import { ndarray } from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-base-gscal@deno/mod.js';

gscal( N, alpha, x, stride )

Multiplies a vector by a scalar constant.

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

gscal( x.length, 5.0, x, 1 );
// x => [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ]

The function has the following parameters:

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

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

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

gscal( 4, 5.0, x, 2 );
// x => [ -10.0, 1.0, 15.0, -5.0, 20.0, 0.0, -5.0, -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@deno/mod.js';

// 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

// Scale every other value:
gscal( 3, 5.0, x1, 2 );
// x0 => <Float64Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]

If either N or stride is less than or equal to 0, the function returns x unchanged.

gscal.ndarray( N, alpha, x, stride, offset )

Multiplies a vector by a scalar constant using alternative indexing semantics.

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

gscal.ndarray( x.length, 5.0, x, 1, 0 );
// x => [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ]

The function has the following additional parameters:

  • offset: 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 multiply the last three elements:

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

gscal.ndarray( 3, 5.0, x, 1, x.length-3 );
// x => [ 1.0, -2.0, 3.0, -20.0, 25.0, -30.0 ]

Notes

  • If N <= 0, both functions return x unchanged.
  • gscal() corresponds to the BLAS level 1 function dscal with the exception that this implementation works with any array type, not just Float64Arrays. Depending on the environment, the typed versions (dscal, sscal, etc.) are likely to be significantly more performant.
  • Both functions support array-like objects having getter and setter accessors for array element access (e.g., @stdlib/array-base/accessor).

Examples

import discreteUniform from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-array-discrete-uniform@deno/mod.js';
import gscal from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-base-gscal@deno/mod.js';

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

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

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

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License

See LICENSE.

Copyright

Copyright © 2016-2025. The Stdlib Authors.