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Apply a function against an accumulator and each element in an array and return the accumulated result.
npm install @stdlib/utils-reduce
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var reduce = require( '@stdlib/utils-reduce' );
Applies a function against an accumulator and each element in an array and returns the accumulated result.
function sum( accumulator, value ) {
return accumulator + value;
}
var arr = [ 1, 2, 3, 4 ];
var out = reduce( arr, 0, sum );
// returns 10
The function accepts both array-like objects and ndarray
-like objects.
var array = require( '@stdlib/ndarray-array' );
function sum( accumulator, value ) {
return accumulator + value;
}
var opts = {
'dtype': 'generic'
};
var arr = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ], opts );
var out = reduce( arr, 0, sum );
// returns 21
The applied function is provided the following arguments:
- accumulator: accumulated value.
- value: array element.
- index: element index.
- arr: input array.
To set the this
context when invoking the input function, provide a thisArg
.
function sum( accumulator, value ) {
this.count += 1;
return accumulator + value;
}
var arr = [ 1, 2, 3, 4 ];
var ctx = {
'count': 0
};
var out = reduce( arr, 0, sum, ctx );
// returns 10
var mean = out / ctx.count;
// returns 2.5
-
For input arrays, the function differs from
Array.prototype.reduce
in the following ways:- The function requires an
initial
value for theaccumulator
. Theinitial
value is used during the first invocation of thereducer
function. - The function does not skip the first array element.
- The function does not skip
undefined
elements. - The function does not support dynamic array-like objects (i.e., array-like objects whose
length
changes during execution).
- The function requires an
-
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 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( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); var v = reduce( x, new Complex64( 0.0, 0.0 ), sum ); // returns <Complex64> var re = realf( v ); // returns 16.0 var im = imagf( v ); // returns 20.0
-
For
ndarray
-like objects, the function performs a reduction over the entire inputndarray
(i.e., higher-orderndarray
dimensions are flattened to a single-dimension). -
When applying a function to
ndarray
-like objects, performance will be best forndarray
-like objects which are single-segment contiguous.
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 array = require( '@stdlib/ndarray-array' );
var reduce = require( '@stdlib/utils-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 binary function:
var f = naryFunction( add, 2 );
// Compute the sum:
var out = reduce( x, 0, f );
console.log( 'x:' );
console.log( x.data );
console.log( 'sum: %d', out );
@stdlib/utils-for-each
: invoke a function for each element in a collection.@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-async/reduce
: apply a function against an accumulator and each element in a collection and return the accumulated result.@stdlib/utils-reduce-right
: apply a function against an accumulator and each element in an array while iterating from right to left and return the accumulated result.
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.
See LICENSE.
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