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/*
 * Java Genetic Algorithm Library (jenetics-3.1.0).
 * Copyright (c) 2007-2015 Franz Wilhelmstötter
 *
 * 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.
 *
 * Author:
 *    Franz Wilhelmstötter ([email protected])
 */
package org.jenetics;

import static java.util.Objects.requireNonNull;

import org.jenetics.internal.util.Equality;
import org.jenetics.internal.util.Hash;

import org.jenetics.util.RandomRegistry;

/**
 * {@code StochasticUniversalSelector} is a method for selecting a
 * population according to some given probability in a way that minimize chance
 * fluctuations. It can be viewed as a type of roulette game where now we have
 * P equally spaced points which we spin.
 *
 * 

* Selector *

* * The figure above shows how the stochastic-universal selection works; n * is the number of individuals to select. * * @see * Wikipedia: Stochastic universal sampling * * * @author Franz Wilhelmstötter * @since 1.0 * @version 2.0 */ public class StochasticUniversalSelector< G extends Gene, N extends Number & Comparable > extends RouletteWheelSelector { public StochasticUniversalSelector() { } /** * This method sorts the population in descending order while calculating the * selection probabilities. (The method {@link Population#populationSort()} is called * by this method.) */ @Override public Population select( final Population population, final int count, final Optimize opt ) { requireNonNull(population, "Population"); if (count < 0) { throw new IllegalArgumentException( "Selection count must be greater or equal then zero, but was " + count ); } final Population selection = new Population<>(count); if (count == 0) { return selection; } final double[] probabilities = probabilities(population, count, opt); assert (population.size() == probabilities.length); //Calculating the equally spaces random points. final double delta = 1.0/count; final double[] points = new double[count]; points[0] = RandomRegistry.getRandom().nextDouble()*delta; for (int i = 1; i < count; ++i) { points[i] = delta*i; } int j = 0; double prop = 0; for (int i = 0; i < count; ++i) { while (points[i] > prop) { prop += probabilities[j]; ++j; } selection.add(population.get(j%population.size())); } return selection; } @Override protected double[] probabilities( final Population population, final int count ) { population.populationSort(); return super.probabilities(population, count); } @Override public int hashCode() { return Hash.of(getClass()).and(super.hashCode()).value(); } @Override public boolean equals(final Object obj) { return Equality.of(this, obj).test(super::equals); } @Override public String toString() { return getClass().getSimpleName(); } }




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