001 /*
002 * Java Genetic Algorithm Library (jenetics-1.5.0).
003 * Copyright (c) 2007-2013 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.util.object.eq;
024 import static org.jenetics.util.object.hashCodeOf;
025
026 import java.io.Serializable;
027
028 import javolution.lang.Immutable;
029
030 import org.jscience.mathematics.number.Float64;
031
032 import org.jenetics.util.Function;
033
034 /**
035 * Implements an exponential fitness scaling, whereby all fitness values are
036 * modified the following way.
037 * <p><img src="doc-files/exponential-scaler.gif"
038 * alt="f_s=\left(a\cdot f+b \rigth)^c"
039 * >.</p>
040 *
041 * @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
042 * @since 1.0
043 * @version 1.0 — <em>$Date: 2013-11-28 $</em>
044 */
045 public final class ExponentialScaler
046 implements
047 Function<Float64, Float64>,
048 Serializable,
049 Immutable
050 {
051 private static final long serialVersionUID = 1L;
052
053 public static final ExponentialScaler SQR_SCALER = new ExponentialScaler(2);
054 public static final ExponentialScaler SQRT_SCALER = new ExponentialScaler(0.5);
055
056 private final double _a;
057 private final double _b;
058 private final double _c;
059
060 /**
061 * Create a new FitnessScaler.
062 *
063 * @param a <pre>fitness = (<strong>a</strong> * fitness + b) ^ c</pre>
064 * @param b <pre>fitness = (a * fitness + <strong>b</strong>) ^ c</pre>
065 * @param c <pre>fitness = (a * fitness + b) ^ <strong>c</strong></pre>
066 */
067 public ExponentialScaler(final double a, final double b, final double c) {
068 _a = a;
069 _b = b;
070 _c = c;
071 }
072
073 /**
074 * Create a new FitnessScaler.
075 *
076 * @param b <pre>fitness = (1 * fitness + <strong>b</strong>) ^ c</pre>
077 * @param c <pre>fitness = (1 * fitness + b) ^ <strong>c</strong></pre>
078 */
079 public ExponentialScaler(final double b, final double c) {
080 this(1.0, b, c);
081 }
082
083 /**
084 * Create a new FitnessScaler.
085 *
086 * @param c <pre>fitness = (1 * fitness + 0) ^ <strong>c</strong></pre>
087 */
088 public ExponentialScaler(final double c) {
089 this(0.0, c);
090 }
091
092
093 @Override
094 public Float64 apply(final Float64 value) {
095 return Float64.valueOf(Math.pow((_a*value.doubleValue() + _b), _c));
096 }
097
098 @Override
099 public int hashCode() {
100 return hashCodeOf(getClass()).and(_a).and(_b).and(_c).value();
101 }
102
103 @Override
104 public boolean equals(final Object obj) {
105 if (obj == this) {
106 return true;
107 }
108 if (obj == null || obj.getClass() != getClass()) {
109 return false;
110 }
111
112 final ExponentialScaler selector = (ExponentialScaler)obj;
113 return eq(_a, selector._a) && eq(_b, selector._b) && eq(_c, selector._c);
114 }
115
116 @Override
117 public String toString() {
118 return format(
119 "%s[a=%f, b=%f, c=%f]",
120 getClass().getSimpleName(), _a, _b, _c
121 );
122 }
123 }
|