001 /*
002 * Java Genetic Algorithm Library (jenetics-4.3.0).
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 import static io.jenetics.internal.util.Hashes.hash;
024
025 import java.io.Serializable;
026 import java.util.Objects;
027 import java.util.function.Function;
028
029 /**
030 * Implements an exponential fitness scaling, whereby all fitness values are
031 * modified the following way.
032 * <p><img src="doc-files/exponential-scaler.gif"
033 * alt="f_s=\left(a\cdot f+b \rigth)^c"
034 * >.</p>
035 *
036 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
037 * @since 1.0
038 * @version 2.0
039 */
040 public final class ExponentialScaler
041 implements
042 Function<Double, Double>,
043 Serializable
044 {
045 private static final long serialVersionUID = 2L;
046
047 public static final ExponentialScaler SQR_SCALER = new ExponentialScaler(2);
048 public static final ExponentialScaler SQRT_SCALER = new ExponentialScaler(0.5);
049
050 private final double _a;
051 private final double _b;
052 private final double _c;
053
054 /**
055 * Create a new FitnessScaler.
056 *
057 * @param a <pre>fitness = (<strong>a</strong> * fitness + b) ^ c</pre>
058 * @param b <pre>fitness = (a * fitness + <strong>b</strong>) ^ c</pre>
059 * @param c <pre>fitness = (a * fitness + b) ^ <strong>c</strong></pre>
060 */
061 public ExponentialScaler(final double a, final double b, final double c) {
062 _a = a;
063 _b = b;
064 _c = c;
065 }
066
067 /**
068 * Create a new FitnessScaler.
069 *
070 * @param b <pre>fitness = (1 * fitness + <strong>b</strong>) ^ c</pre>
071 * @param c <pre>fitness = (1 * fitness + b) ^ <strong>c</strong></pre>
072 */
073 public ExponentialScaler(final double b, final double c) {
074 this(1.0, b, c);
075 }
076
077 /**
078 * Create a new FitnessScaler.
079 *
080 * @param c <pre>fitness = (1 * fitness + 0) ^ <strong>c</strong></pre>
081 */
082 public ExponentialScaler(final double c) {
083 this(1.0, 0.0, c);
084 }
085
086
087 @Override
088 public Double apply(final Double value) {
089 return Math.pow(_a*value + _b, _c);
090 }
091
092 @Override
093 public int hashCode() {
094 return hash(_a, hash(_b, hash(_c)));
095 }
096
097 @Override
098 public boolean equals(final Object obj) {
099 return obj == this ||
100 obj instanceof ExponentialScaler &&
101 Objects.equals(((ExponentialScaler) obj)._a, _a) &&
102 Objects.equals(((ExponentialScaler)obj)._b, _b) &&
103 Objects.equals(((ExponentialScaler)obj)._c, _c);
104 }
105
106 @Override
107 public String toString() {
108 return format(
109 "%s[a=%f, b=%f, c=%f]",
110 getClass().getSimpleName(), _a, _b, _c
111 );
112 }
113 }
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