001 /*
002 * Java Genetic Algorithm Library (jenetics-3.8.0).
003 * Copyright (c) 2007-2017 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@gmx.at)
019 */
020 package org.jenetics;
021
022 import static java.lang.String.format;
023 import static org.jenetics.internal.util.Equality.eq;
024
025 import java.io.Serializable;
026 import java.util.function.Function;
027
028 import org.jenetics.internal.util.Hash;
029
030 /**
031 * Implements an exponential fitness scaling, whereby all fitness values are
032 * modified the following way.
033 * <p><img src="doc-files/exponential-scaler.gif"
034 * alt="f_s=\left(a\cdot f+b \rigth)^c"
035 * >.</p>
036 *
037 * @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
038 * @since 1.0
039 * @version 2.0
040 */
041 public final class ExponentialScaler
042 implements
043 Function<Double, Double>,
044 Serializable
045 {
046 private static final long serialVersionUID = 2L;
047
048 public static final ExponentialScaler SQR_SCALER = new ExponentialScaler(2);
049 public static final ExponentialScaler SQRT_SCALER = new ExponentialScaler(0.5);
050
051 private final double _a;
052 private final double _b;
053 private final double _c;
054
055 /**
056 * Create a new FitnessScaler.
057 *
058 * @param a <pre>fitness = (<strong>a</strong> * fitness + b) ^ c</pre>
059 * @param b <pre>fitness = (a * fitness + <strong>b</strong>) ^ c</pre>
060 * @param c <pre>fitness = (a * fitness + b) ^ <strong>c</strong></pre>
061 */
062 public ExponentialScaler(final double a, final double b, final double c) {
063 _a = a;
064 _b = b;
065 _c = c;
066 }
067
068 /**
069 * Create a new FitnessScaler.
070 *
071 * @param b <pre>fitness = (1 * fitness + <strong>b</strong>) ^ c</pre>
072 * @param c <pre>fitness = (1 * fitness + b) ^ <strong>c</strong></pre>
073 */
074 public ExponentialScaler(final double b, final double c) {
075 this(1.0, b, c);
076 }
077
078 /**
079 * Create a new FitnessScaler.
080 *
081 * @param c <pre>fitness = (1 * fitness + 0) ^ <strong>c</strong></pre>
082 */
083 public ExponentialScaler(final double c) {
084 this(1.0, 0.0, c);
085 }
086
087
088 @Override
089 public Double apply(final Double value) {
090 return Math.pow(_a*value + _b, _c);
091 }
092
093 @Override
094 public int hashCode() {
095 return Hash.of(getClass())
096 .and(_a)
097 .and(_b)
098 .and(_c).value();
099 }
100
101 @Override
102 public boolean equals(final Object obj) {
103 return obj instanceof ExponentialScaler &&
104 eq(((ExponentialScaler)obj)._a, _a) &&
105 eq(((ExponentialScaler)obj)._b, _b) &&
106 eq(((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 }
|