README.md

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mapReduce

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

Usage

import mapReduce from 'https://cdn.jsdelivr.net/gh/stdlib-js/utils-map-reduce@esm/index.mjs';

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.

import array from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-array@esm/index.mjs';

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).

  import Complex64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-complex64@esm/index.mjs';
  import Complex64 from 'https://cdn.jsdelivr.net/gh/stdlib-js/complex-float32-ctor@esm/index.mjs';
  import cceil from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-cceil@esm/index.mjs';
  import realf from 'https://cdn.jsdelivr.net/gh/stdlib-js/complex-float32-real@esm/index.mjs';
  import imagf from 'https://cdn.jsdelivr.net/gh/stdlib-js/complex-float32-imag@esm/index.mjs';
  
  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

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

import filledarrayBy from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-filled-by@esm/index.mjs';
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@esm/index.mjs';
import add from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-ops-add@esm/index.mjs';
import abs from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-abs@esm/index.mjs';
import array from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-array@esm/index.mjs';
import mapReduce from 'https://cdn.jsdelivr.net/gh/stdlib-js/utils-map-reduce@esm/index.mjs';

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 );

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

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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.

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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 © 2016-2024. The Stdlib Authors.