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Jenetics - Java Genetic Algorithm Library
There is a newer version: 3.6.0
/*
 * 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.lang.String.format;
import static org.jenetics.internal.math.random.indexes;

import java.util.Random;

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

import org.jenetics.util.MSeq;
import org.jenetics.util.RandomRegistry;

/**
 * The GaussianMutator class performs the mutation of a {@link NumericGene}.
 * This mutator picks a new value based on a Gaussian distribution around the
 * current value of the gene. The variance of the new value (before clipping to
 * the allowed gene range) will be
 * 
 * 
 * 
 * The new value will be cropped to the gene's boundaries.
 *
 *
 * @author Franz Wilhelmstötter
 * @since 1.0
 * @version 3.0
 */
public final class GaussianMutator<
	G extends NumericGene,
	C extends Comparable
>
	extends Mutator
{

	public GaussianMutator(final double probability) {
		super(probability);
	}

	public GaussianMutator() {
		this(DEFAULT_ALTER_PROBABILITY);
	}

	@Override
	protected int mutate(final MSeq genes, final double p) {
		final Random random = RandomRegistry.getRandom();

		return (int)indexes(random, genes.length(), p)
			.peek(i -> genes.set(i, mutate(genes.get(i), random)))
			.count();
	}

	G mutate(final G gene, final Random random) {
		final double std =
			(gene.getMax().doubleValue() - gene.getMin().doubleValue())*0.25;

		return gene.newInstance(base.clamp(
			random.nextGaussian()*std + gene.doubleValue(),
			gene.getMin().doubleValue(),
			gene.getMax().doubleValue()
		));
	}

	@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 format(
			"%s[p=%f]",
			getClass().getSimpleName(),
			_probability
		);
	}

}