ExponentialScaler.java
/*
* Java Genetic Algorithm Library (@__identifier__@).
* Copyright (c) @__year__@ Franz Wilhelmstötter
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* Author:
* Franz Wilhelmstötter (franz.wilhelmstoetter@gmx.at)
*/
package org.jenetics;
import static java.lang.String.format;
import static org.jenetics.internal.util.object.eq;
import java.io.Serializable;
import javolution.lang.Immutable;
import org.jscience.mathematics.number.Float64;
import org.jenetics.internal.util.HashBuilder;
import org.jenetics.util.Function;
/**
* Implements an exponential fitness scaling, whereby all fitness values are
* modified the following way.
* <p><img src="doc-files/exponential-scaler.gif"
* alt="f_s=\left(a\cdot f+b \rigth)^c"
* >.</p>
*
* @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
* @since 1.0
* @version 1.0 — <em>$Date: 2014-03-05 $</em>
*
* @deprecated Will be removed in next major version, respectively replaced with
* a variant which will be parametrized with {@code Double}s.
*/
@Deprecated
public final class ExponentialScaler
implements
Function<Float64, Float64>,
Serializable,
Immutable
{
private static final long serialVersionUID = 1L;
public static final ExponentialScaler SQR_SCALER = new ExponentialScaler(2);
public static final ExponentialScaler SQRT_SCALER = new ExponentialScaler(0.5);
private final double _a;
private final double _b;
private final double _c;
/**
* Create a new FitnessScaler.
*
* @param a <pre>fitness = (<strong>a</strong> * fitness + b) ^ c</pre>
* @param b <pre>fitness = (a * fitness + <strong>b</strong>) ^ c</pre>
* @param c <pre>fitness = (a * fitness + b) ^ <strong>c</strong></pre>
*/
public ExponentialScaler(final double a, final double b, final double c) {
_a = a;
_b = b;
_c = c;
}
/**
* Create a new FitnessScaler.
*
* @param b <pre>fitness = (1 * fitness + <strong>b</strong>) ^ c</pre>
* @param c <pre>fitness = (1 * fitness + b) ^ <strong>c</strong></pre>
*/
public ExponentialScaler(final double b, final double c) {
this(1.0, b, c);
}
/**
* Create a new FitnessScaler.
*
* @param c <pre>fitness = (1 * fitness + 0) ^ <strong>c</strong></pre>
*/
public ExponentialScaler(final double c) {
this(0.0, c);
}
@Override
public Float64 apply(final Float64 value) {
return Float64.valueOf(Math.pow((_a*value.doubleValue() + _b), _c));
}
@Override
public int hashCode() {
return HashBuilder.of(getClass()).and(_a).and(_b).and(_c).value();
}
@Override
public boolean equals(final Object obj) {
if (obj == this) {
return true;
}
if (obj == null || obj.getClass() != getClass()) {
return false;
}
final ExponentialScaler selector = (ExponentialScaler)obj;
return eq(_a, selector._a) && eq(_b, selector._b) && eq(_c, selector._c);
}
@Override
public String toString() {
return format(
"%s[a=%f, b=%f, c=%f]",
getClass().getSimpleName(), _a, _b, _c
);
}
}