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Scale a single-precision complex floating-point vector by a single-precision floating-point constant.

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csscal

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Scale a single-precision complex floating-point vector by a single-precision floating-point constant.

Usage

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

csscal( N, alpha, x, strideX )

Scales a single-precision complex floating-point vector by a single-precision floating-point constant.

import Complex64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-complex64@deno/mod.js';

var x = new Complex64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );

csscal( 3, 2.0, x, 1 );
// x => <Complex64Array>[ 2.0, 2.0, 2.0, 2.0, 2.0, 2.0 ]

The function has the following parameters:

  • N: number of indexed elements.
  • alpha: scalar constant.
  • x: input Complex64Array.
  • strideX: stride length for x.

The N and stride parameters determine which elements in x are scaled by alpha. For example, to scale every other element in x by alpha,

import Complex64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-complex64@deno/mod.js';

var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );

csscal( 2, 2.0, x, 2 );
// x => <Complex64Array>[ 2.0, 4.0, 3.0, 4.0, 10.0, 12.0, 7.0, 8.0 ]

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

import Complex64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-complex64@deno/mod.js';

// Initial array:
var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );

// Create an offset view:
var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

// Scale every element in `x1`:
csscal( 3, 2.0, x1, 1 );
// x0 => <Complex64Array>[ 1.0, 2.0, 6.0, 8.0, 10.0, 12.0, 14.0, 16.0 ]

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

Scales a single-precision complex floating-point vector by a single-precision floating-point constant using alternative indexing semantics.

import Complex64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-complex64@deno/mod.js';

var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );

csscal.ndarray( 3, 2.0, x, 1, 0 );
// x => <Complex64Array>[ 2.0, 4.0, 6.0, 8.0, 10.0, 12.0 ]

The function has the following additional parameters:

  • offsetX: starting index for x.

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 scale every other element in the input strided array starting from the second element,

import Complex64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-complex64@deno/mod.js';

var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );

csscal.ndarray( 2, 2.0, x, 2, 1 );
// x => <Complex64Array>[ 1.0, 2.0, 6.0, 8.0, 5.0, 6.0, 14.0, 16.0 ]

Notes

  • If N <= 0, both functions return x unchanged.
  • csscal() corresponds to the BLAS level 1 function csscal.

Examples

import discreteUniform from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-base-discrete-uniform@deno/mod.js';
import filledarrayBy from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-filled-by@deno/mod.js';
import Complex64 from 'https://cdn.jsdelivr.net/gh/stdlib-js/complex-float32-ctor@deno/mod.js';
import csscal from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-base-csscal@deno/mod.js';

function rand() {
    return new Complex64( discreteUniform( 0, 10 ), discreteUniform( -5, 5 ) );
}

var x = filledarrayBy( 10, 'complex64', rand );
console.log( x.toString() );

csscal( x.length, 2.0, x, 1 );
console.log( x.toString() );

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.

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License

See LICENSE.

Copyright

Copyright © 2016-2025. The Stdlib Authors.