MeanAlterer.java
/*
* Java Genetic Algorithm Library (@__identifier__@).
* Copyright (c) @__year__@ 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 (franz.wilhelmstoetter@gmx.at)
*/
package org.jenetics;
import static java.lang.String.format;
import java.util.Random;
import javolution.lang.Immutable;
import org.jenetics.internal.util.HashBuilder;
import org.jenetics.util.ISeq;
import org.jenetics.util.MSeq;
import org.jenetics.util.Mean;
import org.jenetics.util.RandomRegistry;
import org.jenetics.util.Seq;
/**
* <p>
* The order ({@link #getOrder()}) of this Recombination implementation is two.
* </p>
*
* @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
* @since 1.0
* @version 1.0 — <em>$Date: 2014-02-27 $</em>
*/
public final class MeanAlterer<G extends Gene<?, G> & Mean<G>>
extends Recombinator<G>
implements Immutable
{
/**
* Constructs an alterer with a given recombination probability.
*
* @param probability the crossover probability.
* @throws IllegalArgumentException if the {@code probability} is not in the
* valid range of {@code [0, 1]}.
*/
public MeanAlterer(final double probability) {
super(probability, 2);
}
/**
* Create a new alterer with alter probability of {@code 0.05}.
*/
public MeanAlterer() {
this(0.05);
}
@Override
protected <C extends Comparable<? super C>> int recombine(
final Population<G, C> population,
final int[] individuals,
final int generation
) {
final Random random = RandomRegistry.getRandom();
final Phenotype<G, C> pt1 = population.get(individuals[0]);
final Phenotype<G, C> pt2 = population.get(individuals[1]);
final Genotype<G> gt1 = pt1.getGenotype();
final Genotype<G> gt2 = pt2.getGenotype();
final int cindex = random.nextInt(gt1.length());
final MSeq<Chromosome<G>> c1 = gt1.toSeq().copy();
final ISeq<Chromosome<G>> c2 = gt2.toSeq();
// Calculate the mean value of the gene array.
final MSeq<G> mean = mean(
c1.get(cindex).toSeq().copy(),
c2.get(cindex).toSeq()
);
c1.set(cindex, c1.get(cindex).newInstance(mean.toISeq()));
population.set(
individuals[0],
pt1.newInstance(gt1.newInstance(c1.toISeq()), generation)
);
return 1;
}
private static <G extends Gene<?, G> & Mean<G>>
MSeq<G> mean(final MSeq<G> a, final Seq<G> b) {
for (int i = a.length(); --i >= 0;) {
a.set(i, a.get(i).mean(b.get(i)));
}
return a;
}
@Override
public int hashCode() {
return HashBuilder.of(getClass()).and(super.hashCode()).value();
}
@Override
public boolean equals(final Object obj) {
return obj == this || obj instanceof MeanAlterer<?> && super.equals(obj);
}
@Override
public String toString() {
return format("%s[p=%f]", getClass().getSimpleName(), _probability);
}
}