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scasum

Compute the sum of the absolute values of the real and imaginary components of a single-precision complex floating-point vector.

Installation

npm install @stdlib/blas-base-scasum

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

scasum( N, cx, strideX )

Computes the sum of the absolute values of the real and imaginary components of a single-precision complex floating-point vector.

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

var cx = new Complex64Array( [ 0.3, 0.1, 0.5, 0.0, 0.0, 0.5, 0.0, 0.2 ] );

var out = scasum( 4, cx, 1 );
// returns ~1.6

The function has the following parameters:

• N: number of indexed elements.
• cx: input Complex64Array.
• strideX: index increment for cx.

The N and stride parameters determine which elements in the strided array are accessed at runtime. For example, to traverse every other value,

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

var cx = new Complex64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );

var out = scasum( 2, cx, 2 );
// returns 7.0

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

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

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

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

// Compute the L2-out:
var out = scasum( 2, cx1, 1 );
// returns 18.0

scasum.ndarray( N, cx, strideX, offset )

Computes the sum of the absolute values of the real and imaginary components of a single-precision complex floating-point vector using alternative indexing semantics.

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

var cx = new Complex64Array( [ 0.3, 0.1, 0.5, 0.0, 0.0, 0.5, 0.0, 0.2 ] );

var out = scasum.ndarray( 4, cx, 1, 0 );
// returns ~1.6

The function has the following additional parameters:

• offsetX: starting index.

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 start from the second index,

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

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

var out = scasum.ndarray( 2, cx, 1, 1 );
// returns 18.0

Notes

• If N <= 0, both functions return 0.0.
• scasum() corresponds to the BLAS level 1 function scasum.

Examples

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

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

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

// Compute the sum of the absolute values of real and imaginary components:
var out = scasum( cx.length, cx, 1 );
console.log( out );

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C APIs

Usage

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

c_scasum( N, *CX, strideX )

Computes the sum of the absolute values of the real and imaginary components of a single-precision complex floating-point vector.

const float cx[] = { 0.3f, 0.1f, 0.5f, 0.0f, 0.0f, 0.5f, 0.0f, 0.2f };

float out = c_scasum( 4, (void *)cx, 1 );
// returns 1.6f

The function accepts the following arguments:

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

float c_scasum( const CBLAS_INT N, const void *CX, const CBLAS_INT strideX );

c_scasum_ndarray( N, *CX, strideX, offsetX )

Computes the sum of the absolute values of the real and imaginary components of a single-precision complex floating-point vector using alternative indexing semantics.

const float cx[] = { 0.3f, 0.1f, 0.5f, 0.0f, 0.0f, 0.5f, 0.0f, 0.2f };

float out = c_scasum_ndarray( 4, (void *)cx, 1, 0 );
// returns 1.6f

The function accepts the following arguments:

• N: [in] CBLAS_INT number of indexed elements.
• CX: [in] void* input array.
• strideX: [in] CBLAS_INT index increment for CX.
• offsetX: [in] CBLAS_INT starting index for CX.

float c_scasum_ndarray( const CBLAS_INT N, const void *CX, const CBLAS_INT strideX, const CBLAS_INT offsetX );  

Examples

#include "stdlib/blas/base/scasum.h"
#include <stdio.h>

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

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

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

    // Compute the sum of the absolute values of real and imaginary components:
    float out = c_scasum( N, (void *)cx, strideX );

    // Print the result:
    printf( "out: %f\n", out );

    // Compute the sum of the absolute values of real and imaginary components using alternative indexing semantics:
    out = c_scasum_ndarray( N, (void *)cx, -strideX, N-1 );

    // Print the result:
    printf( "out: %f\n", out );
}

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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 © 2016-2024. The Stdlib Authors.