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cwxsy

Subtract elements of a single-precision complex floating-point strided array y from the corresponding elements of a single-precision complex floating-point strided array x and assign the results to elements in a single-precision complex floating-point strided array w.

This BLAS extension implements the operation

$$\mathbf{w} = \mathbf{x} - \mathbf{y}$$

Installation

npm install @stdlib/blas-ext-base-cwxsy

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 cwxsy = require( '@stdlib/blas-ext-base-cwxsy' );

cwxsy( N, x, strideX, y, strideY, w, strideW )

Subtracts elements of a single-precision complex floating-point strided array y from the corresponding elements of a single-precision complex floating-point strided array x and assigns the results to elements in a single-precision complex floating-point strided array w.

var Complex64Array = require( '@stdlib/array-complex64' );

var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
var y = new Complex64Array( [ 1.0, 3.0, -2.0, 1.0, 3.0, 4.0 ] );
var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

cwxsy( x.length, x, 1, y, 1, w, 1 );
// w => <Complex64Array>[ 0.0, -1.0, 5.0, 3.0, 2.0, 2.0 ]

The function has the following parameters:

• N: number of indexed elements.
• x: first input Complex64Array.
• strideX: stride length for x.
• y: second input Complex64Array.
• strideY: stride length for y.
• w: output Complex64Array.
• strideW: stride length for w.

The N and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to subtract every other element of y from every other element of x:

var Complex64Array = require( '@stdlib/array-complex64' );

var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
var y = new Complex64Array( [ 3.0, 1.0, 9.0, 10.0, -1.0, 2.0, 13.0, 14.0 ] );
var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

cwxsy( 2, x, 2, y, 2, w, 2 );
// w => <Complex64Array>[ -2.0, 1.0, 0.0, 0.0, 6.0, 4.0, 0.0, 0.0 ]

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

var Complex64Array = require( '@stdlib/array-complex64' );

// Initial arrays...
var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] );
var y0 = new Complex64Array( [ 7.0, 8.0, 9.0, 10.0, 6.0, 1.0, -2.0, 3.0, 10.0, 5.0 ] );
var w0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

// Create offset views...
var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); // start at 3rd element
var w1 = new Complex64Array( w0.buffer, w0.BYTES_PER_ELEMENT*2 ); // start at 3rd element

cwxsy( 3, x1, 1, y1, 1, w1, 1 );
// w0 => <Complex64Array>[ 0.0, 0.0, 0.0, 0.0, -3.0, 3.0, 7.0, 3.0, -3.0, 3.0 ]

cwxsy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, w, strideW, offsetW )

Subtracts elements of a single-precision complex floating-point strided array y from the corresponding elements of a single-precision complex floating-point strided array x and assigns the results to elements in a single-precision complex floating-point strided array w using alternative indexing semantics.

var Complex64Array = require( '@stdlib/array-complex64' );

var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
var y = new Complex64Array( [ 1.0, 3.0, -2.0, 1.0, 3.0, 4.0 ] );
var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

cwxsy.ndarray( x.length, x, 1, 0, y, 1, 0, w, 1, 0 );
// w => <Complex64Array>[ 0.0, -1.0, 5.0, 3.0, 2.0, 2.0 ]

The function has the following additional parameters:

• offsetX: starting index for x.
• offsetY: starting index for y.
• offsetW: starting index for w.

While typed array views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to subtract the last three elements of y from the last three elements of x:

var Complex64Array = require( '@stdlib/array-complex64' );

var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] );
var y = new Complex64Array( [ 11.0, 12.0, 13.0, 14.0, 8.0, 3.0, -1.0, 2.0, 12.0, 7.0 ] );
var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

cwxsy.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3, w, 1, w.length-3 );
// w => <Complex64Array>[ 0.0, 0.0, 0.0, 0.0, -3.0, 3.0, 8.0, 6.0, -3.0, 3.0 ]

Notes

• If N <= 0, both functions return w unchanged.

Examples

var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var Complex64Array = require( '@stdlib/array-complex64' );
var logEach = require( '@stdlib/console-log-each' );
var cwxsy = require( '@stdlib/blas-ext-base-cwxsy' );

var opts = {
    'dtype': 'float32'
};
var xbuf = discreteUniform( 20, -100, 100, opts );
var ybuf = discreteUniform( 20, -100, 100, opts );
var wbuf = discreteUniform( 20, -100, 100, opts );
var x = new Complex64Array( xbuf.buffer );
var y = new Complex64Array( ybuf.buffer );
var w = new Complex64Array( wbuf.buffer );

cwxsy( x.length, x, 1, y, 1, w, 1 );
logEach( '(%s) - (%s) = %s', x, y, w );

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C APIs

Usage

#include "stdlib/blas/ext/base/cwxsy.h"

stdlib_strided_cwxsy( N, *X, strideX, *Y, strideY, *W, strideW )

Subtracts elements of a single-precision complex floating-point strided array Y from the corresponding elements of a single-precision complex floating-point strided array X and assigns the results to elements in a single-precision complex floating-point strided array W.

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

const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
const float y[] = { 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f };
float w[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f };

stdlib_strided_cwxsy( 4, (const stdlib_complex64_t *)x, 1, (const stdlib_complex64_t *)y, 1, (stdlib_complex64_t *)w, 1 );

The function accepts the following arguments:

• N: [in] CBLAS_INT number of indexed elements.
• X: [in] stdlib_complex64_t* first input array.
• strideX: [in] CBLAS_INT stride length for X.
• Y: [in] stdlib_complex64_t* second input array.
• strideY: [in] CBLAS_INT stride length for Y.
• W: [out] stdlib_complex64_t* output array.
• strideW: [in] CBLAS_INT stride length for W.

void stdlib_strided_cwxsy( const CBLAS_INT N, const stdlib_complex64_t *X, const CBLAS_INT strideX, const stdlib_complex64_t *Y, const CBLAS_INT strideY, stdlib_complex64_t *W, const CBLAS_INT strideW );

stdlib_strided_cwxsy_ndarray( N, *X, strideX, offsetX, *Y, strideY, offsetY, *W, strideW, offsetW )

Subtracts elements of a single-precision complex floating-point strided array Y from the corresponding elements of a single-precision complex floating-point strided array X and assigns the results to elements in a single-precision complex floating-point strided array W using alternative indexing semantics.

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

const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
const float y[] = { 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f };
float w[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f };

stdlib_strided_cwxsy_ndarray( 4, (const stdlib_complex64_t *)x, 1, 0, (const stdlib_complex64_t *)y, 1, 0, (stdlib_complex64_t *)w, 1, 0 );

The function accepts the following arguments:

• N: [in] CBLAS_INT number of indexed elements.
• X: [in] stdlib_complex64_t* first input array.
• strideX: [in] CBLAS_INT stride length for X.
• offsetX: [in] CBLAS_INT starting index for X.
• Y: [in] stdlib_complex64_t* second input array.
• strideY: [in] CBLAS_INT stride length for Y.
• offsetY: [in] CBLAS_INT starting index for Y.
• W: [out] stdlib_complex64_t* output array.
• strideW: [in] CBLAS_INT stride length for W.
• offsetW: [in] CBLAS_INT starting index for W.

void stdlib_strided_cwxsy_ndarray( const CBLAS_INT N, const stdlib_complex64_t *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const stdlib_complex64_t *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY, stdlib_complex64_t *W, const CBLAS_INT strideW, const CBLAS_INT offsetW );

Examples

#include "stdlib/blas/ext/base/cwxsy.h"
#include "stdlib/complex/float32/ctor.h"
#include "stdlib/complex/float32/real.h"
#include "stdlib/complex/float32/imag.h"
#include <stdio.h>

int main( void ) {
    // Create strided arrays:
    const stdlib_complex64_t x[] = {
        stdlib_complex64( 1.0f, 2.0f ),
        stdlib_complex64( 3.0f, 4.0f ),
        stdlib_complex64( 5.0f, 6.0f ),
        stdlib_complex64( 7.0f, 8.0f )
    };
    const stdlib_complex64_t y[] = {
        stdlib_complex64( 2.0f, 3.0f ),
        stdlib_complex64( 4.0f, 5.0f ),
        stdlib_complex64( 6.0f, 7.0f ),
        stdlib_complex64( 8.0f, 9.0f )
    };
    stdlib_complex64_t w[] = {
        stdlib_complex64( 0.0f, 0.0f ),
        stdlib_complex64( 0.0f, 0.0f ),
        stdlib_complex64( 0.0f, 0.0f ),
        stdlib_complex64( 0.0f, 0.0f )
    };

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

    // Specify strides:
    const int strideX = 1;
    const int strideY = 1;
    const int strideW = 1;

    // Subtract elements of `y` from the corresponding elements of `x` and assign the results to elements in `w`:
    stdlib_strided_cwxsy( N, x, strideX, y, strideY, w, strideW );

    // Print the result:
    for ( int i = 0; i < N; i++ ) {
        printf( "w[ %i ] = %f + %fi\n", i, stdlib_complex64_real( w[ i ] ), stdlib_complex64_imag( w[ i ] ) );
    }
}

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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.