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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!

reduce2d

NPM version Build Status Coverage Status

Reduce the number of dimensions by one of a two-dimensional nested array by applying a function against an accumulator and each element along the innermost dimension and returning the accumulation results as a one-dimensional array.

Usage

import reduce2d from 'https://cdn.jsdelivr.net/gh/stdlib-js/utils-reduce2d@deno/mod.js';

reduce2d( arr, initial, fcn[, thisArg] )

Reduces the number of dimensions by one of a two-dimensional nested array by applying a function against an accumulator and each element along the innermost dimension and returning the accumulation results as a one-dimensional array.

import naryFunction from 'https://cdn.jsdelivr.net/gh/stdlib-js/utils-nary-function@deno/mod.js';
import add from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-ops-add@deno/mod.js';

var arr = [
    [ 1, 2, 3 ],
    [ 4, 5, 6 ]
];

var out = reduce2d( arr, [ 0, 0 ], naryFunction( add, 2 ) );
// returns [ 6, 15 ]

The applied function is provided the following arguments:

  • accumulator: accumulated value.
  • value: array element.
  • indices: current array element indices.
  • arr: input array.

To set the this context when invoking the input function, provide a thisArg.

import add from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-ops-add@deno/mod.js';

function fcn( acc, v ) {
    this.count += 1;
    return add( acc, v );
}

var arr = [
    [ 1, 2, 3 ],
    [ 4, 5, 6 ]
];

var ctx = {
    'count': 0
};

var out = reduce2d( arr, [ 0, 0 ], fcn, ctx );
// returns [ 6, 15 ]

var cnt = ctx.count;
// returns 6

Notes

  • The function requires an array-like object containing an initial value for the accumulator for each reduction. The number of initial values must equal the size of the outermost input array dimension.

Examples

import filledarrayBy from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-filled-by@deno/mod.js';
var discreteUniform = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/random-base-discrete-uniform' ).factory;
import naryFunction from 'https://cdn.jsdelivr.net/gh/stdlib-js/utils-nary-function@deno/mod.js';
import add from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-ops-add@deno/mod.js';
import zeros from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@deno/mod.js';
import reduce2d from 'https://cdn.jsdelivr.net/gh/stdlib-js/utils-reduce2d@deno/mod.js';

function fill( i ) {
    var rand = discreteUniform( -10*(i+1), 10*(i+1) );
    return filledarrayBy( 10, 'float64', rand );
}

// Create a nested array of arrays:
var x = filledarrayBy( 10, 'generic', fill );

// Create an explicit binary function:
var f = naryFunction( add, 2 );

// Compute the sums along the innermost dimension...
var y = reduce2d( x, zeros( x.length ), f );

console.log( 'x:' );
console.log( x );

console.log( 'y:' );
console.log( y );

See Also

  • @stdlib/utils-map2d: apply a function to each nested element in an array of arrays and assign the result to a nested element in a new array of arrays.
  • @stdlib/utils-reduce: apply a function against an accumulator and each element in an array and return the accumulated result.

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 © 2016-2024. The Stdlib Authors.