Multiply a double-precision floating-point vector by a constant.
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> Multiply a double-precision floating-point vector x by a constant alpha.
``bash`
npm install @stdlib/blas-base-dscal
`javascript`
var dscal = require( '@stdlib/blas-base-dscal' );
#### dscal( N, alpha, x, stride )
Multiplies a double-precision floating-point vector x by a constant alpha.
`javascript
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 =>
`
The function has the following parameters:
- N: number of indexed elements.
- alpha: scalar constant.
- x: input [Float64Array][@stdlib/array/float64].
- stride: index increment.
The N and stride parameters determine which elements in x are accessed at runtime. For example, to multiply every other value by a constant
`javascript
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 =>
`
Note that indexing is relative to the first index. To introduce an offset, use [typed array][mdn-typed-array] views.
`javascript
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 =>
`
If N is less than or equal to 0, the function returns x unchanged.
#### dscal.ndarray( N, alpha, x, stride, offset )
Multiplies a double-precision floating-point vector x by a constant alpha using alternative indexing semantics.
`javascript
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 =>
`
The function has the following additional parameters:
- offset: starting index.
While [typed array][mdn-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
`javascript
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 =>
`
- If N <= 0, both functions return x unchanged.dscal()
- corresponds to the [BLAS][blas] level 1 function [dscal][dscal].
`javascript
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 );
`
*
`c`
#include "stdlib/blas/base/dscal.h"
#### c_dscal( N, alpha, \*X, stride )
Multiplies each element of a double-precision floating-point vector by a constant.
`c
double x[] = { 1.0, 2.0, 3.0, 4.0 };
c_dscal( 4, 5.0, x, 1 );
`
The function accepts the following arguments:
- N: [in] CBLAS_INT number of indexed elements.[in] double
- alpha: scalar constant.[inout] double*
- X: input array.[in] CBLAS_INT
- stride: index increment for X.
`c`
void c_dscal( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT stride );
#### c_dscal_ndarray( N, alpha, \*X, stride, offset )
Multiplies each element of a double-precision floating-point vector by a constant using alternative indexing semantics.
`c
double x[] = { 1.0, 2.0, 3.0, 4.0 };
c_dscal_ndarray( 4, 5.0, x, 1, 0 );
`
The function accepts the following arguments:
- N: [in] CBLAS_INT number of indexed elements.[in] double
- alpha: scalar constant.[inout] double*
- X: input array.[in] CBLAS_INT
- stride: index increment for X.[in] CBLAS_INT
- offset: starting index for X.
`c`
void c_dscal_ndarray( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT stride, const CBLAS_INT offset );
`c
#include "stdlib/blas/base/dscal.h"
#include
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 stride = 1;
// Scale the vector:
c_dscal( N, 5.0, x, stride );
// Print the result:
for ( int i = 0; i < 8; i++ ) {
printf( "x[ %i ] = %lf\n", i, x[ i ] );
}
// Scale the vector:
c_dscal_ndarray( N, 5.0, x, -stride, N-1 );
// Print the result:
for ( int i = 0; i < 8; i++ ) {
printf( "x[ %i ] = %lf\n", i, x[ i ] );
}
}
`
*
- [@stdlib/blas-base/daxpy][@stdlib/blas/base/daxpy]: multiply a vector x by a constant and add the result to y.
- [@stdlib/blas-base/gscal][@stdlib/blas/base/gscal]: multiply a vector by a scalar constant.
- [@stdlib/blas-base/sscal][@stdlib/blas/base/sscal]: multiply a single-precision floating-point vector by a constant.
- [@stdlib/blas-base/saxpy][@stdlib/blas/base/saxpy]: multiply a vector x by a constant and add the result to y.
*
This package is part of [stdlib][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][stdlib], see the main project [repository][stdlib].
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---
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Copyright © 2016-2026. The Stdlib [Authors][stdlib-authors].
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[umd]: https://github.com/umdjs/umd
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[deno-url]: https://github.com/stdlib-js/blas-base-dscal/tree/deno
[deno-readme]: https://github.com/stdlib-js/blas-base-dscal/blob/deno/README.md
[umd-url]: https://github.com/stdlib-js/blas-base-dscal/tree/umd
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[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/blas-base-dscal/main/LICENSE
[blas]: http://www.netlib.org/blas
[dscal]: http://www.netlib.org/lapack/explore-html/de/da4/group__double__blas__level1.html
[@stdlib/array/float64]: https://www.npmjs.com/package/@stdlib/array-float64
[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
[@stdlib/blas/base/daxpy]: https://www.npmjs.com/package/@stdlib/blas-base-daxpy
[@stdlib/blas/base/gscal]: https://www.npmjs.com/package/@stdlib/blas-base-gscal
[@stdlib/blas/base/sscal]: https://www.npmjs.com/package/@stdlib/blas-base-sscal
[@stdlib/blas/base/saxpy]: https://www.npmjs.com/package/@stdlib/blas-base-saxpy