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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!

dmap

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

Usage

import dmap from 'https://cdn.jsdelivr.net/gh/stdlib-js/strided-base-dmap@deno/mod.js';

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

import { ndarray } from 'https://cdn.jsdelivr.net/gh/stdlib-js/strided-base-dmap@deno/mod.js';

dmap( N, x, strideX, y, strideY, fcn )

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

import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';
import abs from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-abs@deno/mod.js';

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

// Compute the absolute values in-place:
dmap( x.length, x, 1, x, 1, abs );
// x => <Float64Array>[ 2.0, 1.0, 3.0, 5.0, 4.0, 0.0, 1.0, 3.0 ]

The function accepts the following arguments:

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

The N and stride parameters determine which elements in x and y 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@deno/mod.js';
import abs from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-abs@deno/mod.js';

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

dmap( 3, x, 2, y, -1, abs );
// y => <Float64Array>[ 5.0, 3.0, 1.0, 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@deno/mod.js';
import abs from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-abs@deno/mod.js';

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

dmap( 3, x1, -2, y1, 1, abs );
// y0 => <Float64Array>[ 0.0, 0.0, 0.0, 6.0, 4.0, 2.0 ]

dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )

Applies a unary function to a double-precision floating-point strided input array 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@deno/mod.js';
import abs from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-abs@deno/mod.js';

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

dmap.ndarray( x.length, x, 1, 0, y, 1, 0, abs );
// y => <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]

The function accepts the following additional arguments:

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

While typed array views mandate a view offset based on the underlying buffer, the offsetX and offsetY 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@deno/mod.js';
import abs from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-abs@deno/mod.js';

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

dmap.ndarray( 3, x, 2, 1, y, -1, y.length-1, abs );
// y => <Float64Array>[ 0.0, 0.0, 0.0, 6.0, 4.0, 2.0 ]

Examples

import round from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-round@deno/mod.js';
import randu from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-base-randu@deno/mod.js';
import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';
import dmap from 'https://cdn.jsdelivr.net/gh/stdlib-js/strided-base-dmap@deno/mod.js';

function scale( x ) {
    return x * 10.0;
}

var x = new Float64Array( 10 );
var y = new Float64Array( 10 );

var i;
for ( i = 0; i < x.length; i++ ) {
    x[ i ] = round( (randu()*200.0) - 100.0 );
}
console.log( x );
console.log( y );

dmap.ndarray( x.length, x, 1, 0, y, -1, y.length-1, scale );
console.log( y );

See Also

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

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.

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License

See LICENSE.

Copyright

Copyright © 2016-2025. The Stdlib Authors.