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daxpy

Multiply a one-dimensional double-precision floating-point ndarray x by a constant alpha and add the result to a one-dimensional double-precision floating-point ndarray y.

Installation

npm install @stdlib/blas-base-ndarray-daxpy

Alternatively,

• To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
• If you are using Deno, visit the deno branch (see README for usage intructions).
• For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).

The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.

To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

Usage

var daxpy = require( '@stdlib/blas-base-ndarray-daxpy' );

daxpy( arrays )

Multiplies a one-dimensional double-precision floating-point ndarray x by a constant alpha and adds the result to a one-dimensional double-precision floating-point ndarray y.

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

var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
var x = new ndarray( 'float64', xbuf, [ 5 ], [ 1 ], 0, 'row-major' );

var ybuf = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );
var y = new ndarray( 'float64', ybuf, [ 5 ], [ 1 ], 0, 'row-major' );

var alpha = scalar2ndarray( 5.0, 'float64', 'row-major' );
var z = daxpy( [ x, y, alpha ] );
// returns <ndarray>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]

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

The function has the following parameters:

• arrays: array-like object containing an input ndarray, an output ndarray, and a zero-dimensional ndarray containing a scalar constant.

Examples

var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var scalar2ndarray = require( '@stdlib/ndarray-from-scalar' );
var ndarray = require( '@stdlib/ndarray-base-ctor' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var daxpy = require( '@stdlib/blas-base-ndarray-daxpy' );

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

var xbuf = discreteUniform( 10, 0, 100, opts );
var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
console.log( ndarray2array( x ) );

var ybuf = discreteUniform( xbuf.length, 0, 10, opts );
var y = new ndarray( opts.dtype, ybuf, [ ybuf.length ], [ 1 ], 0, 'row-major' );
console.log( ndarray2array( y ) );

var alpha = scalar2ndarray( 5.0, opts );
var out = daxpy( [ x, y, alpha ] );
console.log( ndarray2array( out ) );

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Notice

This package is part of stdlib, a standard library for JavaScript and Node.js, 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 © 2016-2026. The Stdlib Authors.