107 lines
2.4 KiB
JavaScript
107 lines
2.4 KiB
JavaScript
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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2018 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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// MODULES //
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var floor = require( '@stdlib/math/base/special/floor' );
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// MAIN //
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/**
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* Samples with replacement and non-uniform probabilities using Vose's [alias method][alias-method].
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*
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* ## References
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*
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* - Vose, Michael D. 1991. "A linear algorithm for generating random numbers with a given distribution." _IEEE Transactions on Software Engineering_ 17 (9): 972–75. doi:[10.1109/32.92917][@vose:1991].
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*
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* [alias-method]: http://keithschwarz.com/darts-dice-coins/
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* [@vose:1991]: https://doi.org/10.1109/32.92917
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*
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*
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* @private
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* @param {ArrayLike} x - array-like object from which to sample
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* @param {NonNegativeInteger} size - sample size
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* @param {Function} rand - PRNG for generating uniformly distributed numbers
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* @param {ProbabilityArray} probabilities - element probabilities
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* @returns {Array} sample
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*/
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function vose( x, size, rand, probabilities ) {
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var small;
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var large;
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var probs;
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var alias;
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var out;
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var N;
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var p;
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var g;
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var i;
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var l;
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probs = probabilities.slice();
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N = x.length;
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small = [];
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large = [];
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for ( i = 0; i < N; i++ ) {
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probs[ i ] *= N;
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if ( probs[ i ] < 1.0 ) {
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small.push( i );
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} else {
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large.push( i );
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}
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}
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alias = new Array( N );
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p = new Array( N );
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while ( small.length !== 0 && large.length !== 0 ) {
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l = small.shift();
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g = large.shift();
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p[ l ] = probs[ l ];
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alias[ l ] = g;
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probs[ g ] = probs[ g ] + probs[ l ] - 1.0;
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if ( probs[ g ] < 1.0 ) {
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small.push( g );
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} else {
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large.push( g );
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}
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}
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for ( i = 0; i < large.length; i++ ) {
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p[ large[ i ] ] = 1.0;
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}
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for ( i = 0; i < small.length; i++ ) {
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p[ small[ i ] ] = 1.0;
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}
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out = new Array( size );
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for ( i = 0; i < size; i++ ) {
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l = floor( N*rand() );
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if ( rand() < p[ l ] ) {
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out[ i ] = x[ l ];
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} else {
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out[ i ] = x[ alias[ l ] ];
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}
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}
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return out;
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}
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// EXPORTS //
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module.exports = vose;
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