@stdlib/strided-base-dmap2

About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

dmap2

Apply a binary function to double-precision floating-point strided input arrays and assign results to a double-precision floating-point strided output array.

Installation

npm install @stdlib/strided-base-dmap2

Usage

var dmap2 = require( '@stdlib/strided-base-dmap2' );

dmap2( N, x, strideX, y, strideY, z, strideZ, fcn )

Applies a binary function to double-precision floating-point strided input arrays and assigns results to a double-precision floating-point strided output array.

var Float64Array = require( '@stdlib/array-float64' );
var add = require( '@stdlib/number-float64-base-add' );

var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );
var y = new Float64Array( [ 2.0, 1.0, 3.0, -2.0, 4.0, 1.0, -1.0, 3.0 ] );
var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

dmap2( x.length, x, 1, y, 1, z, 1, add );
// z => <Float64Array>[ 0.0, 2.0, 6.0, -7.0, 8.0, 1.0, -2.0, 0.0 ]

The function accepts the following arguments:

• N: number of indexed elements.
• x: input Float64Array.
• strideX: index increment for x.
• y: input Float64Array.
• strideY: index increment for y.
• z: output Float64Array.
• strideZ: index increment for z.
• fcn: function to apply.

The N and stride parameters determine which strided array elements are accessed at runtime. For example, to index every other value in x and to index the first N elements of y in reverse order,

var Float64Array = require( '@stdlib/array-float64' );
var add = require( '@stdlib/number-float64-base-add' );

var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] );
var y = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] );
var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

dmap2( 3, x, 2, y, -1, z, 1, add );
// z => <Float64Array>[ 1.0, -2.0, -4.0, 0.0, 0.0, 0.0 ]

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

var Float64Array = require( '@stdlib/array-float64' );
var add = require( '@stdlib/number-float64-base-add' );

// Initial arrays...
var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] );
var y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] );
var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

// Create offset views...
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element
var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 ); // start at 3rd element

dmap2( 3, x1, -2, y1, 1, z1, 1, add );
// z0 => <Float64Array>[ 0.0, 0.0, -4.0, -1.0, 1.0, 0.0 ]

dmap2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, z, strideZ, offsetZ, fcn )

Applies a binary function to double-precision floating-point strided input arrays and assigns results to a double-precision floating-point strided output array using alternative indexing semantics.

var Float64Array = require( '@stdlib/array-float64' );
var add = require( '@stdlib/number-float64-base-add' );

var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0, -5.0 ] );
var y = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0 ] );
var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );

dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, add );
// z => <Float64Array>[ 0.0, -1.0, -1.0, -2.0, -2.0 ]

The function accepts the following additional arguments:

• offsetX: starting index for x.
• offsetY: starting index for y.
• offsetZ: starting index for z.

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 index every other value in x starting from the second value and to index the last N elements in y in reverse order,

var Float64Array = require( '@stdlib/array-float64' );
var add = require( '@stdlib/number-float64-base-add' );

var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] );
var y = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] );
var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

dmap2.ndarray( 3, x, 2, 1, y, -1, y.length-1, z, 1, 3, add );
// z => <Float64Array>[ 0.0, 0.0, 0.0, 1.0, -1.0, -4.0 ]

Examples

var discreteUniform = require( '@stdlib/random-base-discrete-uniform' ).factory;
var filledarrayBy = require( '@stdlib/array-filled-by' );
var Float64Array = require( '@stdlib/array-float64' );
var add = require( '@stdlib/number-float64-base-add' );
var dmap2 = require( '@stdlib/strided-base-dmap2' );

var x = filledarrayBy( 10, 'float64', discreteUniform( -100, 100 ) );
console.log( x );

var y = filledarrayBy( x.length, 'float64', discreteUniform( -100, 100 ) );
console.log( y );

var z = new Float64Array( x.length );
console.log( z );

dmap2.ndarray( x.length, x, 1, 0, y, -1, y.length-1, z, 1, 0, add );
console.log( z );

C APIs

Usage

#include "stdlib/strided/base/dmap2.h"

stdlib_strided_dmap2( N, *X, strideX, *Y, strideY, *Z, strideZ, fcn )

Applies a binary function to double-precision floating-point strided input arrays and assigns results to a double-precision floating-point strided output array.

#include <stdint.h>

static double add( const double x, const double y ) {
    return x + y;
}

double X[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 };
double Y[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 };
double Z[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };

int64_t N = 6;

stdlib_strided_dmap2( N, X, 1, Y, 1, Z, 1, add );

The function accepts the following arguments:

• N: [in] int64_t number of indexed elements.
• X: [in] double* input array.
• strideX [in] int64_t index increment for X.
• Y: [in] double* input array.
• strideY: [in] int64_t index increment for Y.
• Z: [out] double* output array.
• strideZ: [in] int64_t index increment for Z.
• fcn: [in] double (*fcn)( double, double ) binary function to apply.

void stdlib_strided_dmap2( const int64_t N, const double *X, const int64_t strideX, const double *Y, const int64_t strideY, double *Z, const int64_t strideZ, double (*fcn)( double, double ) );

Examples

#include "stdlib/strided/base/dmap2.h"
#include <stdint.h>
#include <stdio.h>
#include <inttypes.h>

// Define a callback:
static double add( const double x, const double y ) {
    return x + y;
}

int main( void ) {
    // Create input strided arrays:
    double X[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 };
    double Y[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 };

    // Create an output strided array:
    double Z[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };

    // Specify the number of elements:
    int64_t N = 6;

    // Define the strides:
    int64_t strideX = 1;
    int64_t strideY = -1;
    int64_t strideZ = 1;

    // Apply the callback:
    stdlib_strided_dmap2( N, X, strideX, Y, strideY, Z, strideZ, add );

    // Print the results:
    for ( int64_t i = 0; i < N; i++ ) {
        printf( "Z[ %"PRId64" ] = %lf\n", i, Z[ i ] );
    }
}

See Also

• @stdlib/strided-base/smap2: apply a binary function to single-precision floating-point strided input arrays and assign results to a single-precision floating-point strided output array.
• @stdlib/strided-base/binary: apply a binary callback to elements in strided input arrays and assign results to elements in a strided output array.

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 © 2016-2026. The Stdlib Authors.