Press n or j to go to the next uncovered block, b, p or k for the previous block.
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* @license Apache-2.0
*
* Copyright (c) 2018 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
'use strict';
/**
* Samples without replacement from a discrete set using custom probabilities.
*
* ## Notes
*
* - After each draw, the probabilities of the remaining observations are renormalized so that they sum to one.
*
* @private
* @param {ArrayLike} x - array-like object from which to sample
* @param {NonNegativeInteger} size - sample size
* @param {Function} rand - PRNG for generating uniformly distributed numbers
* @param {ProbabilityArray} probabilities - element probabilities
* @returns {Array} sample
*/
function renormalizing( x, size, rand, probabilities ) {
var probs;
var psum;
var out;
var N;
var i;
var j;
var k;
var u;
N = x.length;
probs = probabilities.slice();
out = [];
for ( i = 0; i < size; i++ ) {
u = rand();
psum = 0;
for ( j = 0; j < N; j++ ) {
psum += probs[ j ];
if ( u < psum ) {
break;
}
}
for ( k = 0; k < N; k++ ) {
if ( k === j ) {
continue;
}
probs[ k ] /= 1.0 - probs[ j ];
}
probs[ j ] = 0.0;
out.push( x[ j ] );
}
return out;
}
// EXPORTS //
module.exports = renormalizing;
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