@stdlib/blas-base-cscal v0.0.2

cscal

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

Installation

npm install @stdlib/blas-base-cscal

Usage

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

cscal( N, ca, cx, strideX )

Scales values from cx by ca.

var Complex64Array = require( '@stdlib/array-complex64' );
var Complex64 = require( '@stdlib/complex-float32-ctor' );
var realf = require( '@stdlib/complex-float32-real' );
var imagf = require( '@stdlib/complex-float32-imag' );

var cx = new Complex64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );
var ca = new Complex64( 2.0, 0.0 );

cscal( 3, ca, cx, 1 );

var z = cx.get( 0 );
// returns <Complex64>

var re = realf( z );
// returns 2.0

var im = imagf( z );
// returns 2.0

The function has the following parameters:

• N: number of indexed elements.
• ca: scalar Complex64 constant.
• cx: input Complex64Array.
• strideX: index increment for cx.

The N and stride parameters determine how values from cx are scaled by ca. For example, to scale every other value in cx by ca,

var Complex64Array = require( '@stdlib/array-complex64' );
var Complex64 = require( '@stdlib/complex-float32-ctor' );
var realf = require( '@stdlib/complex-float32-real' );
var imagf = require( '@stdlib/complex-float32-imag' );

var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
var ca = new Complex64( 2.0, 0.0 );

cscal( 2, ca, cx, 2 );

var z = cx.get( 2 );
// returns <Complex64>

var re = realf( z );
// returns 10.0

var im = imagf( z );
// returns 12.0

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

var Complex64Array = require( '@stdlib/array-complex64' );
var Complex64 = require( '@stdlib/complex-float32-ctor' );
var realf = require( '@stdlib/complex-float32-real' );
var imagf = require( '@stdlib/complex-float32-imag' );

// Initial array:
var cx0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );

// Define a scalar constant:
var ca = new Complex64( 2.0, 2.0 );

// Create an offset view:
var cx1 = new Complex64Array( cx0.buffer, cx0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

// Scales every other value from `cx1` by `ca`...
cscal( 3, ca, cx1, 1 );

var z = cx0.get( 1 );
// returns <Complex64>

var re = realf( z );
// returns -2.0

var im = imagf( z );
// returns 14.0

cscal.ndarray( N, ca, cx, strideX, offsetX )

Scales values from cx by ca using alternative indexing semantics.

var Complex64Array = require( '@stdlib/array-complex64' );
var Complex64 = require( '@stdlib/complex-float32-ctor' );
var realf = require( '@stdlib/complex-float32-real' );
var imagf = require( '@stdlib/complex-float32-imag' );

var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
var ca = new Complex64( 2.0, 2.0 );

cscal.ndarray( 3, ca, cx, 1, 0 );

var z = cx.get( 0 );
// returns <Complex64>

var re = realf( z );
// returns -2.0

var im = imagf( z );
// returns 6.0

The function has the following additional parameters:

• offsetX: starting index for cx.

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 value in the input strided array starting from the second element,

var Complex64Array = require( '@stdlib/array-complex64' );
var Complex64 = require( '@stdlib/complex-float32-ctor' );
var realf = require( '@stdlib/complex-float32-real' );
var imagf = require( '@stdlib/complex-float32-imag' );

var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
var ca = new Complex64( 2.0, 2.0 );

cscal.ndarray( 2, ca, cx, 2, 1 );

var z = cx.get( 3 );
// returns <Complex64>

var re = realf( z );
// returns -2.0

var im = imagf( z );
// returns 30.0

Notes

• If N <= 0 or strideX <= 0 , both functions return cx unchanged.
• cscal() corresponds to the BLAS level 1 function cscal.

Examples

var discreteUniform = require( '@stdlib/random-base-discrete-uniform' );
var filledarrayBy = require( '@stdlib/array-filled-by' );
var Complex64 = require( '@stdlib/complex-float32-ctor' );
var cscal = require( '@stdlib/blas-base-cscal' );

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

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

var ca = new Complex64( 2.0, 2.0 );
console.log( ca.toString() );

// Scale elements from `cx` by `ca`:
cscal( cx.length, ca, cx, 1 );
console.log( cx.get( cx.length-1 ).toString() );

C APIs

Usage

#include "stdlib/blas/base/cscal.h"

c_cscal( N, ca, *CX, strideX )

Scales values from CX by ca.

#include "stdlib/complex/float32/ctor.h"

float cx[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
const stdlib_complex64_t ca = stdlib_complex64( 2.0f, 2.0f );

c_dscal( 4, ca, (void *)cx, 1 );

The function accepts the following arguments:

• N: [in] CBLAS_INT number of indexed elements.
• ca: [in] stdlib_complex64_t scalar constant.
• CX: [inout] void* input array.
• strideX: [in] CBLAS_INT index increment for CX.

void c_dscal( const CBLAS_INT N, const stdlib_complex64_t ca, void *CX, const CBLAS_INT strideX );

Examples

#include "stdlib/blas/base/cscal.h"
#include "stdlib/complex/float32/ctor.h"
#include <stdio.h>

int main( void ) {
    // Create a strided array of interleaved real and imaginary components:
    float cx[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };

    // Create a complex scalar:
    const stdlib_complex64_t ca = stdlib_complex64( 2.0f, 2.0f );

    // Specify the number of elements:
    const int N = 4;

    // Specify stride length:
    const int strideX = 1;

    // Scale the elements of the array:
    c_cscal( N, ca, (void *)cx, strideX );

    // Print the result:
    for ( int i = 0; i < N; i++ ) {
        printf( "cx[ %i ] = %f + %fj\n", i, cx[ i*2 ], cx[ (i*2)+1 ] );
    }
}

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

License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.