01 /*
02 * Java Genetic Algorithm Library (jenetics-6.3.0).
03 * Copyright (c) 2007-2021 Franz Wilhelmstötter
04 *
05 * Licensed under the Apache License, Version 2.0 (the "License");
06 * you may not use this file except in compliance with the License.
07 * You may obtain a copy of the License at
08 *
09 * http://www.apache.org/licenses/LICENSE-2.0
10 *
11 * Unless required by applicable law or agreed to in writing, software
12 * distributed under the License is distributed on an "AS IS" BASIS,
13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 * See the License for the specific language governing permissions and
15 * limitations under the License.
16 *
17 * Author:
18 * Franz Wilhelmstötter (franz.wilhelmstoetter@gmail.com)
19 */
20 package io.jenetics;
21
22 import static java.lang.Math.nextDown;
23 import static java.lang.String.format;
24 import static io.jenetics.internal.math.Basics.clamp;
25
26 import java.util.Random;
27
28 /**
29 * The GaussianMutator class performs the mutation of a {@link NumericGene}.
30 * This mutator picks a new value based on a Gaussian distribution around the
31 * current value of the gene. The variance of the new value (before clipping to
32 * the allowed gene range) will be
33 * <p>
34 * <img
35 * src="doc-files/gaussian-mutator-var.svg"
36 * alt="\hat{\sigma }^2 = \left ( \frac{ g_{max} - g_{min} }{4}\right )^2"
37 * >
38 * </p>
39 * The new value will be cropped to the gene's boundaries.
40 *
41 *
42 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
43 * @since 1.0
44 * @version 6.1
45 */
46 public class GaussianMutator<
47 G extends NumericGene<?, G>,
48 C extends Comparable<? super C>
49 >
50 extends Mutator<G, C>
51 {
52
53 public GaussianMutator(final double probability) {
54 super(probability);
55 }
56
57 public GaussianMutator() {
58 this(DEFAULT_ALTER_PROBABILITY);
59 }
60
61 @Override
62 protected G mutate(final G gene, final Random random) {
63 return gene.isValid() ? mutate0(gene, random) : gene;
64 }
65
66 private G mutate0(final G gene, final Random random) {
67 final double min = gene.min().doubleValue();
68 final double max = gene.max().doubleValue();
69 final double std = (max - min)*0.25;
70
71 final double value = gene.doubleValue();
72 final double gaussian = random.nextGaussian();
73 return gene.newInstance(clamp(gaussian*std + value, min, nextDown(max)));
74 }
75
76 @Override
77 public String toString() {
78 return format("%s[p=%f]", getClass().getSimpleName(), _probability);
79 }
80
81 }
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