01 /*
02 * Java Genetic Algorithm Library (jenetics-4.0.0).
03 * Copyright (c) 2007-2017 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.String.format;
23 import static io.jenetics.internal.math.base.clamp;
24
25 import java.util.Random;
26
27 import io.jenetics.internal.util.Hash;
28
29 /**
30 * The GaussianMutator class performs the mutation of a {@link NumericGene}.
31 * This mutator picks a new value based on a Gaussian distribution around the
32 * current value of the gene. The variance of the new value (before clipping to
33 * the allowed gene range) will be
34 * <p>
35 * <img
36 * src="doc-files/gaussian-mutator-var.gif"
37 * alt="\hat{\sigma }^2 = \left ( \frac{ g_{max} - g_{min} }{4}\right )^2"
38 * >
39 * </p>
40 * The new value will be cropped to the gene's boundaries.
41 *
42 *
43 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
44 * @since 1.0
45 * @version 4.0
46 */
47 public final class GaussianMutator<
48 G extends NumericGene<?, G>,
49 C extends Comparable<? super C>
50 >
51 extends Mutator<G, C>
52 {
53
54 public GaussianMutator(final double probability) {
55 super(probability);
56 }
57
58 public GaussianMutator() {
59 this(DEFAULT_ALTER_PROBABILITY);
60 }
61
62 @Override
63 protected G mutate(final G gene, final Random random) {
64 final double min = gene.getMin().doubleValue();
65 final double max = gene.getMax().doubleValue();
66 final double std = (max - min)*0.25;
67
68 final double value = gene.doubleValue();
69 final double gaussian = random.nextGaussian();
70 return gene.newInstance(clamp(gaussian*std + value, min, max));
71 }
72
73 @Override
74 public int hashCode() {
75 return Hash.of(getClass()).and(super.hashCode()).value();
76 }
77
78 @Override
79 public boolean equals(final Object obj) {
80 return obj instanceof GaussianMutator && super.equals(obj);
81 }
82
83 @Override
84 public String toString() {
85 return format(
86 "%s[p=%f]",
87 getClass().getSimpleName(),
88 _probability
89 );
90 }
91
92 }
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