@stdlib/blas-base-dscal
Advanced tools
Multiply a double-precision floating-point vector by a constant.
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!
Multiply a double-precision floating-point vector
xby a constantalpha.
npm install @stdlib/blas-base-dscal
var dscal = require( '@stdlib/blas-base-dscal' );
Multiplies a double-precision floating-point vector x by a constant alpha.
var Float64Array = require( '@stdlib/array-float64' );
var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );
dscal( x.length, 5.0, x, 1 );
// x => <Float64Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ]
The function has the following parameters:
Float64Array.The N and stride parameters determine which elements in x are accessed at runtime. For example, to multiply every other value by a constant
var Float64Array = require( '@stdlib/array-float64' );
var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );
dscal( 4, 5.0, x, 2 );
// x => <Float64Array>[ -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.
var Float64Array = require( '@stdlib/array-float64' );
// 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...
dscal( 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.
Multiplies a double-precision floating-point vector x by a constant alpha using alternative indexing semantics.
var Float64Array = require( '@stdlib/array-float64' );
var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );
dscal.ndarray( x.length, 5.0, x, 1, 0 );
// x => <Float64Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ]
The function has the following additional parameters:
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 of x by a constant
var Float64Array = require( '@stdlib/array-float64' );
var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );
dscal.ndarray( 3, 5.0, x, 1, x.length-3 );
// x => <Float64Array>[ 1.0, -2.0, 3.0, -20.0, 25.0, -30.0 ]
var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var dscal = require( '@stdlib/blas-base-dscal' );
var opts = {
'dtype': 'float64'
};
var x = discreteUniform( 10, -100, 100, opts );
console.log( x );
dscal( x.length, 5.0, x, 1 );
console.log( x );
#include "stdlib/blas/base/dscal.h"
Multiplies each element of a double-precision floating-point vector by a constant.
double x[] = { 1.0, 2.0, 3.0, 4.0 };
c_dscal( 4, 5.0, x, 1 );
The function accepts the following arguments:
[in] CBLAS_INT number of indexed elements.[in] double scalar constant.[inout] double* input array.[in] CBLAS_INT index increment for X.void c_dscal( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT stride );
#include "stdlib/blas/base/dscal.h"
#include <stdio.h>
int main( void ) {
// Create a strided array:
double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 };
// Specify the number of elements:
const int N = 8;
// Specify a stride:
const int strideX = 1;
// Scale the vector:
c_dscal( N, 5.0, x, strideX );
// Print the result:
for ( int i = 0; i < 8; i++ ) {
printf( "x[ %i ] = %lf\n", i, x[ i ] );
}
}
@stdlib/blas-base/daxpy: multiply a vector x by a constant and add the result to y.@stdlib/blas-base/gscal: multiply a vector by a constant.@stdlib/blas-base/sscal: multiply a single-precision floating-point vector by a constant.@stdlib/blas-base/saxpy: multiply a vector x by a constant and add the result to y.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.
See LICENSE.
Copyright © 2016-2024. The Stdlib Authors.
0.3.0 (2024-07-27)
<section class="features">757ce66 - add support for specifying integer size5c514c7 - specify integer type to match CBLASd04dcbd - docs: remove private annotations in C comments (by Philipp Burckhardt)aea56c1 - docs: fix signature (by Athan Reines)6226f32 - docs: update signatures (by Athan Reines)c313ca8 - refactor: support building with API suffix (by Athan Reines)5c514c7 - fix: specify integer type to match CBLAS (by Athan Reines)757ce66 - feat: add support for specifying integer size (by Athan Reines)38464b7 - docs: remove comments (by Athan Reines)f1576ec - docs: remove comments (by Athan Reines)c8aa78f - build: add separate configurations for benchmarks and examples (by Athan Reines)0244027 - chore: add missing trailing newlines (by Philipp Burckhardt)A total of 2 people contributed to this release. Thank you to the following contributors:
FAQs
Multiply a double-precision floating-point vector by a constant.
We found that @stdlib/blas-base-dscal demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 4 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Application Security
/Security News
Socket CEO Feross Aboukhadijeh and a16z partner Joel de la Garza discuss vibe coding, AI-driven software development, and how the rise of LLMs, despite their risks, still points toward a more secure and innovative future.
Research
/Security News
Threat actors hijacked Toptal’s GitHub org, publishing npm packages with malicious payloads that steal tokens and attempt to wipe victim systems.
Research
/Security News
Socket researchers investigate 4 malicious npm and PyPI packages with 56,000+ downloads that install surveillance malware.