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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!

mapReduce

NPM version Build Status Coverage Status

Perform a single-pass map-reduce operation against each element in an array and return the accumulated result.

Installation

npm install @stdlib/utils-map-reduce

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 mapReduce = require( '@stdlib/utils-map-reduce' );

mapReduce( arr, initial, mapper, reducer[, thisArg ] )

Performs a map-reduce operation against each element in an array and returns the accumulated result.

function square( value ) {
    return value * value;
}

function sum( accumulator, value ) {
    return accumulator + value;
}

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

var out = mapReduce( arr, 0, square, sum );
// returns 30

The function accepts both array-like objects and ndarray-like objects.

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

function square( value ) {
    return value * value;
}

function sum( accumulator, value ) {
    return accumulator + value;
}

var opts = {
    'dtype': 'generic'
};
var arr = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ], opts );

var out = mapReduce( arr, 0, square, sum );
// returns 91

The mapping function is provided the following arguments:

  • value: array element.
  • index: element index.
  • arr: input array.

The reducing function is provided the following arguments:

  • accumulator: accumulated value.
  • value: result of applying the mapping function to the current array element.
  • index: element index.
  • arr: input array.

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

function square( value ) {
    return value * value;
}

function sum( accumulator, value ) {
    this.count += 1;
    return accumulator + value;
}

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

var ctx = {
    'count': 0
};

var out = mapReduce( arr, 0, square, sum, ctx );
// returns 30

var mean = out / ctx.count;
// returns 7.5

Notes

  • The function supports array-like objects exposing getters and setters for array element access (e.g., Complex64Array, Complex128Array, etc).

    var Complex64Array = require( '@stdlib/array-complex64' );
    var Complex64 = require( '@stdlib/complex-float32-ctor' );
    var cceil = require( '@stdlib/math-base-special-cceil' );
    var realf = require( '@stdlib/complex-float32-real' );
    var imagf = require( '@stdlib/complex-float32-imag' );
    
    function sum( acc, z ) {
        var re1 = realf( acc );
        var im1 = imagf( acc );
        var re2 = realf( z );
        var im2 = imagf( z );
        return new Complex64( re1+re2, im1+im2 );
    }
    
    var x = new Complex64Array( [ 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5 ] );
    
    var v = mapReduce( x, new Complex64( 0.0, 0.0 ), cceil, sum );
    // returns <Complex64>
    
    var re = realf( v );
    // returns 20.0
    
    var im = imagf( v );
    // returns 24.0
  • For ndarray-like objects, the function performs a single-pass map-reduce operation over the entire input ndarray (i.e., higher-order ndarray dimensions are flattened to a single-dimension).

  • When applying a function to ndarray-like objects, performance will be best for ndarray-like objects which are single-segment contiguous.

Examples

var filledarrayBy = require( '@stdlib/array-filled-by' );
var discreteUniform = require( '@stdlib/random-base-discrete-uniform' ).factory;
var naryFunction = require( '@stdlib/utils-nary-function' );
var add = require( '@stdlib/math-base-ops-add' );
var abs = require( '@stdlib/math-base-special-abs' );
var array = require( '@stdlib/ndarray-array' );
var mapReduce = require( '@stdlib/utils-map-reduce' );

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

// Create a two-dimensional ndarray (i.e., a matrix):
var x = array( filledarrayBy( 10, 'generic', fill ), {
    'dtype': 'generic',
    'flatten': true
});

// Create an explicit unary function:
var f1 = naryFunction( abs, 1 );

// Create an explicit binary function:
var f2 = naryFunction( add, 2 );

// Compute the sum of absolute values:
var out = mapReduce( x, 0, f1, f2 );

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

console.log( 'sum: %d', out );

See Also

  • @stdlib/utils-map: apply a function to each element in an array and assign the result to an element in an output array.
  • @stdlib/utils-map-reduce-right: perform a single-pass map-reduce operation against each element in an array while iterating from right to left and return the accumulated result.
  • @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 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.

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License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.