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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.

Usage

import dmap2 from 'https://cdn.jsdelivr.net/gh/stdlib-js/strided-base-dmap2@esm/index.mjs';

You can also import the following named exports from the package:

import { ndarray } from 'https://cdn.jsdelivr.net/gh/stdlib-js/strided-base-dmap2@esm/index.mjs';

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.

import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@esm/index.mjs';
import add from 'https://cdn.jsdelivr.net/gh/stdlib-js/number-float64-base-add@esm/index.mjs';

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,

import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@esm/index.mjs';
import add from 'https://cdn.jsdelivr.net/gh/stdlib-js/number-float64-base-add@esm/index.mjs';

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.

import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@esm/index.mjs';
import add from 'https://cdn.jsdelivr.net/gh/stdlib-js/number-float64-base-add@esm/index.mjs';

// 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.

import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@esm/index.mjs';
import add from 'https://cdn.jsdelivr.net/gh/stdlib-js/number-float64-base-add@esm/index.mjs';

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,

import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@esm/index.mjs';
import add from 'https://cdn.jsdelivr.net/gh/stdlib-js/number-float64-base-add@esm/index.mjs';

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

<!DOCTYPE html>
<html lang="en">
<body>
<script type="module">

var discreteUniform = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/random-base-discrete-uniform' ).factory;
import filledarrayBy from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-filled-by@esm/index.mjs';
import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@esm/index.mjs';
import add from 'https://cdn.jsdelivr.net/gh/stdlib-js/number-float64-base-add@esm/index.mjs';
import dmap2 from 'https://cdn.jsdelivr.net/gh/stdlib-js/strided-base-dmap2@esm/index.mjs';

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 );

</script>
</body>
</html>

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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.

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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.

Community

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License

See LICENSE.

Copyright

Copyright © 2016-2025. The Stdlib Authors.