MATH-1335

Use new RNG API.

src/main/java/org/apache/commons/math4/genetics/GeneticAlgorithm.java

@@ -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.rng.RandomSource;
-import org.apache.commons.math4.random.RandomGenerator;
+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
+     * Static random number generator shared by GA implementation classes.
-     * reproducible results. Use {@link #setRandomGenerator(RandomGenerator)} to supply an alternative to the default
+     * Use {@link #setRandomGenerator(UniformRandomProvider)} to supply an
-     * JDK-provided PRNG.
+     * 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

src/main/java/org/apache/commons/math4/genetics/NPointCrossover.java

@@ -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;

src/main/java/org/apache/commons/math4/genetics/OrderedCrossover.java

@@ -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;

src/main/java/org/apache/commons/math4/genetics/UniformCrossover.java

@@ -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++) {