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MATH-1335 

Use new RNG API.
This commit is contained in:
Gilles 2016-05-11 13:54:06 +02:00
parent 6fc152e417
commit 0c9af5f450
4 changed files with 15 additions and 15 deletions
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18
src/main/java/org/apache/commons/math4/genetics/GeneticAlgorithm.java
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@ -18,8 +18,8 @@ package org.apache.commons.math4.genetics;
import org.apache.commons.math4.exception.OutOfRangeException;
import org.apache.commons.math4.exception.util.LocalizedFormats;
import org.apache.commons.math4.random.JDKRandomGenerator;
import org.apache.commons.math4.random.RandomGenerator;
import org.apache.commons.math4.rng.RandomSource;
import org.apache.commons.math4.rng.UniformRandomProvider;
/**
* Implementation of a genetic algorithm. All factors that govern the operation
@ -30,12 +30,12 @@ import org.apache.commons.math4.random.RandomGenerator;
public class GeneticAlgorithm {
/**
* Static random number generator shared by GA implementation classes. Set the randomGenerator seed to get
* reproducible results. Use {@link #setRandomGenerator(RandomGenerator)} to supply an alternative to the default
* JDK-provided PRNG.
* Static random number generator shared by GA implementation classes.
* Use {@link #setRandomGenerator(UniformRandomProvider)} to supply an
* alternative to the default PRNG, and/or select a specific seed.
*/
//@GuardedBy("this")
private static RandomGenerator randomGenerator = new JDKRandomGenerator();
private static UniformRandomProvider randomGenerator = RandomSource.create(RandomSource.WELL_19937_C);
/** the crossover policy used by the algorithm. */
private final CrossoverPolicy crossoverPolicy;
@ -90,7 +90,7 @@ public class GeneticAlgorithm {
*
* @param random random generator
*/
public static synchronized void setRandomGenerator(final RandomGenerator random) {
public static synchronized void setRandomGenerator(final UniformRandomProvider random) {
randomGenerator = random;
}
@ -99,7 +99,7 @@ public class GeneticAlgorithm {
*
* @return the static random generator shared by GA implementation classes
*/
public static synchronized RandomGenerator getRandomGenerator() {
public static synchronized UniformRandomProvider getRandomGenerator() {
return randomGenerator;
}
@ -148,7 +148,7 @@ public class GeneticAlgorithm {
public Population nextGeneration(final Population current) {
Population nextGeneration = current.nextGeneration();
RandomGenerator randGen = getRandomGenerator();
UniformRandomProvider randGen = getRandomGenerator();
while (nextGeneration.getPopulationSize() < nextGeneration.getPopulationLimit()) {
// select parent chromosomes

4
src/main/java/org/apache/commons/math4/genetics/NPointCrossover.java
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@ -24,7 +24,7 @@ import org.apache.commons.math4.exception.MathIllegalArgumentException;
import org.apache.commons.math4.exception.NotStrictlyPositiveException;
import org.apache.commons.math4.exception.NumberIsTooLargeException;
import org.apache.commons.math4.exception.util.LocalizedFormats;
import org.apache.commons.math4.random.RandomGenerator;
import org.apache.commons.math4.rng.UniformRandomProvider;
/**
* N-point crossover policy. For each iteration a random crossover point is
@ -142,7 +142,7 @@ public class NPointCrossover<T> implements CrossoverPolicy {
final List<T> child1Rep = new ArrayList<T>(length);
final List<T> child2Rep = new ArrayList<T>(length);
final RandomGenerator random = GeneticAlgorithm.getRandomGenerator();
final UniformRandomProvider random = GeneticAlgorithm.getRandomGenerator();
List<T> c1 = child1Rep;
List<T> c2 = child2Rep;

4
src/main/java/org/apache/commons/math4/genetics/OrderedCrossover.java
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@ -25,7 +25,7 @@ import java.util.Set;
import org.apache.commons.math4.exception.DimensionMismatchException;
import org.apache.commons.math4.exception.MathIllegalArgumentException;
import org.apache.commons.math4.exception.util.LocalizedFormats;
import org.apache.commons.math4.random.RandomGenerator;
import org.apache.commons.math4.rng.UniformRandomProvider;
import org.apache.commons.math4.util.FastMath;
/**
@ -103,7 +103,7 @@ public class OrderedCrossover<T> implements CrossoverPolicy {
final Set<T> child1Set = new HashSet<T>(length);
final Set<T> child2Set = new HashSet<T>(length);
final RandomGenerator random = GeneticAlgorithm.getRandomGenerator();
final UniformRandomProvider random = GeneticAlgorithm.getRandomGenerator();
// choose random points, making sure that lb < ub.
int a = random.nextInt(length);
int b;

4
src/main/java/org/apache/commons/math4/genetics/UniformCrossover.java
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@ -23,7 +23,7 @@ import org.apache.commons.math4.exception.DimensionMismatchException;
import org.apache.commons.math4.exception.MathIllegalArgumentException;
import org.apache.commons.math4.exception.OutOfRangeException;
import org.apache.commons.math4.exception.util.LocalizedFormats;
import org.apache.commons.math4.random.RandomGenerator;
import org.apache.commons.math4.rng.UniformRandomProvider;
/**
* Perform Uniform Crossover [UX] on the specified chromosomes. A fixed mixing
@ -115,7 +115,7 @@ public class UniformCrossover<T> implements CrossoverPolicy {
final List<T> child1Rep = new ArrayList<T>(length);
final List<T> child2Rep = new ArrayList<T>(length);
final RandomGenerator random = GeneticAlgorithm.getRandomGenerator();
final UniformRandomProvider random = GeneticAlgorithm.getRandomGenerator();
for (int index = 0; index < length; index++) {