001/*
002 * Java Genetic Algorithm Library (jenetics-8.3.0).
003 * Copyright (c) 2007-2025 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 java.util.random.RandomGenerator;
023
024import io.jenetics.stat.Sampler;
025import io.jenetics.stat.Samplers;
026import io.jenetics.util.DoubleRange;
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, defined by
031 * the {@link Shape} parameter of the mutator.
032 * <br>
033 * <img src="doc-files/gaussian-mutator-sigma.svg" alt="Sigma graph" width="500"/>
034 * <br>
035 *
036 * @param <G> the gene type
037 * @param <C> the allele type
038 *
039 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
040 * @since 1.0
041 * @version 8.3
042 */
043public class GaussianMutator<
044        G extends NumericGene<?, G>,
045        C extends Comparable<? super C>
046>
047        extends SamplerMutator<G, C>
048{
049
050        /**
051         * The parameters which define the <em>shape</em> of gaussian distribution
052         * of new gene values.
053         * <p>
054         * <b>shift</b><br>
055         * The {@code shift} value shifts the mean value of the distribution. Positive
056         * values shifts it right and negative values left. Its value
057         * must be within the range of {@code [-1, 1]}. This restriction ensures the
058         * numerical stability of the mutator. The actual µ value is calculated as
059         * follows: {@code µ = (shift + 1)*((max - min)/2)}.
060         * <br>
061         * <img src="doc-files/gaussian-mutator-shift.svg" alt="Shift graph" width="500"/>
062         * <br>
063         * <b>sigma</b><br>
064         * The {@code sigma} value <em>stretches</em> and <em>compresses</em>
065         * the distribution and must be within the range of {@code [0.1, 5]}. This
066         * restriction ensures the numerical stability of the mutator. The actual σ
067         * value is calculated as follows: {@code σ = ((max - min)/2)/sigma}.
068         * <br>
069         * <img src="doc-files/gaussian-mutator-sigma.svg" alt="Sigma graph" width="500"/>
070         * <br>
071         *
072         * @param shift the shift parameter, S, determining the mean value of the
073         *         created mutation value distribution
074         * @param sigma the sigma parameter, Σ, determining the standard deviation of
075         *        the created mutation value distribution
076         * @since 8.3
077         * @version 8.3
078         */
079        public record Shape(double shift, double sigma) implements Sampler {
080
081                /**
082                 * Create a new mutation distribution shape.
083                 *
084                 * @param shift the shift parameter, S, determining the mean value of the
085                 *         crated mutation value distribution
086                 * @param sigma the sigma parameter, Σ, determining the standard deviation of
087                 *        the created mutation value distribution
088                 * @throws IllegalArgumentException if {@code shift < -1 || shift > 1} of
089                 *         {@code sigma < 0.1 || sigma > 5}
090                 */
091                public Shape {
092                        if (shift < -1 || shift > 1) {
093                                throw new IllegalArgumentException(
094                                        "Shift must be  within the range [-1, 1]: " + shift
095                                );
096                        }
097                        if (sigma < 0.1 || sigma > 5) {
098                                throw new IllegalArgumentException(
099                                        "Sigma must be within the range [0.1, 5]: " + sigma
100                                );
101                        }
102                }
103
104                @Override
105                public double sample(final RandomGenerator random, final DoubleRange range) {
106                        final var sig = (range.max() - range.min())/2.0;
107                        final var mean = sig + sig*shift;
108                        final var stddev = sig/sigma;
109
110                        return Samplers.gaussian(mean, stddev).sample(random, range);
111                }
112
113                double stddev(final DoubleRange range) {
114                        return ((range.max() - range.min())/2.0)/sigma;
115                }
116
117                double mean(final DoubleRange range) {
118                        return (shift + 1)*((range.max() - range.min())/2.0);
119                }
120
121        }
122
123        /**
124         * The default shape of the mutator: {@code Shape[shift=0, sigma=1]}.
125         */
126        public static final Shape DEFAULT_SHAPE = new Shape(0, 1);
127
128        /**
129         * Create a new Gaussian mutator with the given parameter.
130         *
131         * @param probability the mutation probabilities
132         * @param shape the <em>shape</em> of the mutation value distribution
133         */
134        public GaussianMutator(final double probability, final Shape shape) {
135                super(probability, shape);
136        }
137
138        /**
139         * Create a new Gaussian mutator with the given mutation value distribution
140         * shape and the default mutation probability, {@link #DEFAULT_ALTER_PROBABILITY}.
141         *
142         * @param shape the mutation value distribution shape
143         */
144        public GaussianMutator(final Shape shape) {
145                this(DEFAULT_ALTER_PROBABILITY, shape);
146        }
147
148        /**
149         * Crate a new Gaussian mutator with the given mutation probability and the
150         * default shape, {@link #DEFAULT_SHAPE}.
151         *
152         * @param probability the mutation probability
153         */
154        public GaussianMutator(final double probability) {
155                this(probability, DEFAULT_SHAPE);
156        }
157
158        /**
159         * Create a new Gaussian mutator with the default mutation probability,
160         * {@link #DEFAULT_ALTER_PROBABILITY}, and default distribution shape,
161         * {@link #DEFAULT_SHAPE}.
162         */
163        public GaussianMutator() {
164                this(DEFAULT_ALTER_PROBABILITY, DEFAULT_SHAPE);
165        }
166
167}