Revert back to java.util.Random
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@ -5,7 +5,7 @@ import eva2.tools.math.RNG;
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import eva2.util.annotation.Description;
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import java.util.Arrays;
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import java.security.SecureRandom;
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import java.util.Random;
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/**
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* Fletcher-Powell function with up to 2^n optima from Shir&Baeck, PPSN 2006,
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@ -40,7 +40,7 @@ public class F19Problem extends AbstractProblemDouble implements
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public void initializeProblem() {
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super.initializeProblem();
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// create static random data
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SecureRandom rand = new SecureRandom();
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Random rand = new Random();
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rand.setSeed(randSeed);
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alphas = RNG.randomDoubleArray(rand, -Math.PI, Math.PI, dim);
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A = RNG.randomIntArray(rand, -100, 100, dim * dim);
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@ -4,7 +4,7 @@ import eva2.tools.EVAERROR;
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import java.util.ArrayList;
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import java.util.BitSet;
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import java.security.SecureRandom;
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import java.util.Random;
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/**
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* Random number generator used across all optimizations
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@ -12,7 +12,7 @@ import java.security.SecureRandom;
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*/
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public class RNG {
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private static SecureRandom random;
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private static Random random;
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private static long randomSeed;
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/**
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@ -20,7 +20,7 @@ public class RNG {
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*/
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static {
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randomSeed = System.currentTimeMillis();
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random = new SecureRandom();
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random = new Random();
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random.setSeed(randomSeed);
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}
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@ -33,7 +33,7 @@ public class RNG {
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if (randomSeed == 0) {
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setRandomSeed();
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} else {
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random = new SecureRandom();
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random = new Random();
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random.setSeed(randomSeed);
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}
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}
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@ -51,14 +51,14 @@ public class RNG {
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*/
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public static void setRandomSeed() {
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randomSeed = System.currentTimeMillis();
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random = new SecureRandom();
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random = new Random();
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random.setSeed(randomSeed);
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}
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/**
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*
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*/
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public static void setRandom(SecureRandom baseRandom) {
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public static void setRandom(Random baseRandom) {
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random = baseRandom;
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}
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@ -141,7 +141,7 @@ public class RNG {
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* @param hi Upper bound.
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* @return int
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*/
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public static int randomInt(SecureRandom rand, int lo, int hi) {
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public static int randomInt(Random rand, int lo, int hi) {
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if (hi < lo) {
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System.err.println("Invalid boundary values! Returning zero.");
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return -1;
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@ -196,7 +196,7 @@ public class RNG {
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return (hi - lo) * random.nextDouble() + lo;
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}
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public static double randomDouble(SecureRandom rand, double lo, double hi) {
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public static double randomDouble(Random rand, double lo, double hi) {
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return (hi - lo) * rand.nextDouble() + lo;
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}
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@ -239,7 +239,7 @@ public class RNG {
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return result;
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}
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public static double[] randomDoubleArray(SecureRandom rand, double lower, double upper, int size) {
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public static double[] randomDoubleArray(Random rand, double lower, double upper, int size) {
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double[] result = new double[size];
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for (int i = 0; i < result.length; i++) {
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result[i] = RNG.randomDouble(rand, lower, upper);
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@ -262,9 +262,9 @@ public class RNG {
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* Create a uniform random integer vector within the given bounds
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* (inclusive) in every dimension.
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*
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* @param n
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* @param lower
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* @param upper
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* @param size
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* @return
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*/
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public static int[] randomIntArray(int lower, int upper, int size) {
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@ -275,7 +275,7 @@ public class RNG {
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return result;
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}
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public static int[] randomIntArray(SecureRandom rand, int lower, int upper, int size) {
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public static int[] randomIntArray(Random rand, int lower, int upper, int size) {
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int[] result = new int[size];
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for (int i = 0; i < result.length; i++) {
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result[i] = RNG.randomInt(rand, lower, upper);
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@ -448,7 +448,6 @@ public class RNG {
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/**
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* Create a normalized random vector with gaussian random double entries.
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*
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* @param n
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* @return
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*/
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public static double[] gaussianVector(double dev, double[] result,
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