001/*
002 * Java Genetic Algorithm Library (jenetics-7.1.0).
003 * Copyright (c) 2007-2022 Franz Wilhelmstötter
004 *
005 * Licensed under the Apache License, Version 2.0 (the "License");
006 * you may not use this file except in compliance with the License.
007 * You may obtain a copy of the License at
008 *
009 *      http://www.apache.org/licenses/LICENSE-2.0
010 *
011 * Unless required by applicable law or agreed to in writing, software
012 * distributed under the License is distributed on an "AS IS" BASIS,
013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
014 * See the License for the specific language governing permissions and
015 * limitations under the License.
016 *
017 * Author:
018 *    Franz Wilhelmstötter (franz.wilhelmstoetter@gmail.com)
019 */
020package io.jenetics;
021
022import static java.lang.Math.nextDown;
023import static java.lang.String.format;
024import static io.jenetics.internal.math.Basics.clamp;
025
026import java.util.random.RandomGenerator;
027
028/**
029 * The GaussianMutator class performs the mutation of a {@link NumericGene}.
030 * This mutator picks a new value based on a Gaussian distribution around the
031 * current value of the gene. The variance of the new value (before clipping to
032 * the allowed gene range) will be
033 * <p>
034 * <img
035 *     src="doc-files/gaussian-mutator-var.svg"
036 *     alt="\hat{\sigma }^2 = \left ( \frac{ g_{max} - g_{min} }{4}\right )^2"
037 * >
038 * </p>
039 * The new value will be cropped to the gene's boundaries.
040 *
041 *
042 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
043 * @since 1.0
044 * @version 6.1
045 */
046public class GaussianMutator<
047        G extends NumericGene<?, G>,
048        C extends Comparable<? super C>
049>
050        extends Mutator<G, C>
051{
052
053        public GaussianMutator(final double probability) {
054                super(probability);
055        }
056
057        public GaussianMutator() {
058                this(DEFAULT_ALTER_PROBABILITY);
059        }
060
061        @Override
062        protected G mutate(final G gene, final RandomGenerator random) {
063                return gene.isValid() ? mutate0(gene, random) : gene;
064        }
065
066        private G mutate0(final G gene, final RandomGenerator random) {
067                final double min = gene.min().doubleValue();
068                final double max = gene.max().doubleValue();
069                final double std = (max - min)*0.25;
070
071                final double value = gene.doubleValue();
072                final double gaussian = random.nextGaussian();
073                return gene.newInstance(clamp(gaussian*std + value, min, nextDown(max)));
074        }
075
076        @Override
077        public String toString() {
078                return format("%s[p=%f]", getClass().getSimpleName(), _probability);
079        }
080
081}