001 /*
002 * Java Genetic Algorithm Library (jenetics-4.1.0).
003 * Copyright (c) 2007-2018 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 */
020 package io.jenetics;
021
022 import static java.lang.String.format;
023
024 import java.io.Serializable;
025 import java.util.Objects;
026 import java.util.function.Function;
027
028 /**
029 * Implements an exponential fitness scaling, whereby all fitness values are
030 * modified the following way.
031 * <p><img src="doc-files/exponential-scaler.gif"
032 * alt="f_s=\left(a\cdot f+b \rigth)^c"
033 * >.</p>
034 *
035 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
036 * @since 1.0
037 * @version 2.0
038 */
039 public final class ExponentialScaler
040 implements
041 Function<Double, Double>,
042 Serializable
043 {
044 private static final long serialVersionUID = 2L;
045
046 public static final ExponentialScaler SQR_SCALER = new ExponentialScaler(2);
047 public static final ExponentialScaler SQRT_SCALER = new ExponentialScaler(0.5);
048
049 private final double _a;
050 private final double _b;
051 private final double _c;
052
053 /**
054 * Create a new FitnessScaler.
055 *
056 * @param a <pre>fitness = (<strong>a</strong> * fitness + b) ^ c</pre>
057 * @param b <pre>fitness = (a * fitness + <strong>b</strong>) ^ c</pre>
058 * @param c <pre>fitness = (a * fitness + b) ^ <strong>c</strong></pre>
059 */
060 public ExponentialScaler(final double a, final double b, final double c) {
061 _a = a;
062 _b = b;
063 _c = c;
064 }
065
066 /**
067 * Create a new FitnessScaler.
068 *
069 * @param b <pre>fitness = (1 * fitness + <strong>b</strong>) ^ c</pre>
070 * @param c <pre>fitness = (1 * fitness + b) ^ <strong>c</strong></pre>
071 */
072 public ExponentialScaler(final double b, final double c) {
073 this(1.0, b, c);
074 }
075
076 /**
077 * Create a new FitnessScaler.
078 *
079 * @param c <pre>fitness = (1 * fitness + 0) ^ <strong>c</strong></pre>
080 */
081 public ExponentialScaler(final double c) {
082 this(1.0, 0.0, c);
083 }
084
085
086 @Override
087 public Double apply(final Double value) {
088 return Math.pow(_a*value + _b, _c);
089 }
090
091 @Override
092 public int hashCode() {
093 int hash = 17;
094 hash += 31*Double.hashCode(_a) + 37;
095 hash += 31*Double.hashCode(_b) + 37;
096 hash += 31*Double.hashCode(_c) + 37;
097 return hash;
098 }
099
100 @Override
101 public boolean equals(final Object obj) {
102 return obj == this ||
103 obj instanceof ExponentialScaler &&
104 Objects.equals(((ExponentialScaler) obj)._a, _a) &&
105 Objects.equals(((ExponentialScaler)obj)._b, _b) &&
106 Objects.equals(((ExponentialScaler)obj)._c, _c);
107 }
108
109 @Override
110 public String toString() {
111 return format(
112 "%s[a=%f, b=%f, c=%f]",
113 getClass().getSimpleName(), _a, _b, _c
114 );
115 }
116 }
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