Create an iterator which iteratively computes a moving sum.
For a window of size W
, the moving sum is defined as
npm install @stdlib/stats-iter-msum
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var itermsum = require( '@stdlib/stats-iter-msum' );
Returns an iterator which iteratively computes a moving sum. The W
parameter defines the number of iterated values over which to compute the moving sum.
var array2iterator = require( '@stdlib/array-to-iterator' );
var arr = array2iterator( [ 2.0, 1.0, 3.0, -7.0, -5.0 ] );
var it = itermsum( arr, 3 );
// Fill the window...
var s = it.next().value; // [2.0]
// returns 2.0
s = it.next().value; // [2.0, 1.0]
// returns 3.0
s = it.next().value; // [2.0, 1.0, 3.0]
// returns 6.0
// Window begins sliding...
s = it.next().value; // [1.0, 3.0, -7.0]
// returns -3.0
s = it.next().value; // [3.0, -7.0, -5.0]
// returns -9.0
- If an iterated value is non-numeric (including
NaN
), the function returnsNaN
for at leastW-1
future invocations. If non-numeric iterated values are possible, you are advised to provide aniterator
which type checks and handles non-numeric values accordingly. - As
W
values are needed to fill the window buffer, the firstW-1
returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all previously iterated values.
var runif = require( '@stdlib/random-iter-uniform' );
var itermsum = require( '@stdlib/stats-iter-msum' );
// Create an iterator for generating uniformly distributed pseudorandom numbers:
var rand = runif( -10.0, 10.0, {
'seed': 1234,
'iter': 100
});
// Create an iterator for iteratively computing a moving sum:
var it = itermsum( rand, 3 );
// Perform manual iteration...
var v;
while ( true ) {
v = it.next();
if ( v.done ) {
break;
}
if ( typeof v.value === 'number' ) {
console.log( 'sum: %d', v.value );
}
}
@stdlib/stats/iter/mmean
: create an iterator which iteratively computes a moving arithmetic mean.@stdlib/stats/iter/sum
: compute the sum of all iterated values.
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.
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See LICENSE.
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