01 /*
02 * Java Genetic Algorithm Library (jenetics-4.3.0).
03 * Copyright (c) 2007-2018 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 /**
28 * The GaussianMutator class performs the mutation of a {@link NumericGene}.
29 * This mutator picks a new value based on a Gaussian distribution around the
30 * current value of the gene. The variance of the new value (before clipping to
31 * the allowed gene range) will be
32 * <p>
33 * <img
34 * src="doc-files/gaussian-mutator-var.gif"
35 * alt="\hat{\sigma }^2 = \left ( \frac{ g_{max} - g_{min} }{4}\right )^2"
36 * >
37 * </p>
38 * The new value will be cropped to the gene's boundaries.
39 *
40 *
41 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
42 * @since 1.0
43 * @version 4.0
44 */
45 public final class GaussianMutator<
46 G extends NumericGene<?, G>,
47 C extends Comparable<? super C>
48 >
49 extends Mutator<G, C>
50 {
51
52 public GaussianMutator(final double probability) {
53 super(probability);
54 }
55
56 public GaussianMutator() {
57 this(DEFAULT_ALTER_PROBABILITY);
58 }
59
60 @Override
61 protected G mutate(final G gene, final Random random) {
62 final double min = gene.getMin().doubleValue();
63 final double max = gene.getMax().doubleValue();
64 final double std = (max - min)*0.25;
65
66 final double value = gene.doubleValue();
67 final double gaussian = random.nextGaussian();
68 return gene.newInstance(clamp(gaussian*std + value, min, max));
69 }
70
71 @Override
72 public String toString() {
73 return format("%s[p=%f]", getClass().getSimpleName(), _probability);
74 }
75
76 }
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