Package org.apache.commons.math3.random

Examples of org.apache.commons.math3.random.RandomGenerator.nextDouble()

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  public void testVersusHashSet() {
    FastIDSet actual = new FastIDSet(1);
    Collection<Integer> expected = new HashSet<Integer>(1000000);
    RandomGenerator r = RandomManager.getRandom();
    for (int i = 0; i < 1000000; i++) {
      double d = r.nextDouble();
      Integer key = r.nextInt(100);
      if (d < 0.4) {
        assertEquals(expected.contains(key), actual.contains(key));
      } else {
        if (d < 0.7) {
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  public void testVersusHashMap() {
    FastByIDFloatMap actual = new FastByIDFloatMap();
    Map<Long,Float> expected = Maps.newHashMapWithExpectedSize(1000000);
    RandomGenerator r = RandomManager.getRandom();
    for (int i = 0; i < 1000000; i++) {
      double d = r.nextDouble();
      Long key = (long) r.nextInt(100);
      if (d < 0.4) {
        Number expectedValue = expected.get(key);
        float actualValue = actual.get(key);
        if (expectedValue == null) {
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  public void testVersusHashMap() {
    FastByIDMap<String> actual = new FastByIDMap<String>();
    Map<Long, String> expected = Maps.newHashMapWithExpectedSize(1000000);
    RandomGenerator r = RandomManager.getRandom();
    for (int i = 0; i < 1000000; i++) {
      double d = r.nextDouble();
      Long key = (long) r.nextInt(100);
      if (d < 0.4) {
        assertEquals(expected.get(key), actual.get(key));
      } else {
        if (d < 0.7) {
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  private static void assignVectorsParallel(FastByIDMap<float[]> vectors, double samplingRate, Node[][] map) {
    boolean doSample = samplingRate < 1.0;
    RandomGenerator random = RandomManager.getRandom();
    for (FastByIDMap.MapEntry<float[]> entry : vectors.entrySet()) {
      if (doSample && random.nextDouble() > samplingRate) {
        continue;
      }
      float[] V = entry.getValue();
      int[] bmuCoordinates = findBestMatchingUnit(V, map);
      if (bmuCoordinates != null) {
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  private static RealMatrix randomSymmetricMatrix(int dimension) {
    RandomGenerator random = RandomManager.getRandom();
    RealMatrix symmetric = new Array2DRowRealMatrix(dimension, dimension);
    for (int j = 0; j < dimension; j++) {
      // Diagonal
      symmetric.setEntry(j, j, random.nextDouble());
      for (int k = j + 1; k < dimension; k++) {
        // Off-diagonal
        double d = random.nextDouble();
        symmetric.setEntry(j, k, d);
        symmetric.setEntry(k, j, d);         
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    for (int j = 0; j < dimension; j++) {
      // Diagonal
      symmetric.setEntry(j, j, random.nextDouble());
      for (int k = j + 1; k < dimension; k++) {
        // Off-diagonal
        double d = random.nextDouble();
        symmetric.setEntry(j, k, d);
        symmetric.setEntry(k, j, d);         
      }
    }
    return symmetric;
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        while (nextGeneration.getPopulationSize() < nextGeneration.getPopulationLimit()) {
            // select parent chromosomes
            ChromosomePair pair = getSelectionPolicy().select(current);

            // crossover?
            if (randGen.nextDouble() < getCrossoverRate()) {
                // apply crossover policy to create two offspring
                pair = getCrossoverPolicy().crossover(pair.getFirst(), pair.getSecond());
            }

            // mutation?
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                // apply crossover policy to create two offspring
                pair = getCrossoverPolicy().crossover(pair.getFirst(), pair.getSecond());
            }

            // mutation?
            if (randGen.nextDouble() < getMutationRate()) {
                // apply mutation policy to the chromosomes
                pair = new ChromosomePair(
                    getMutationPolicy().mutate(pair.getFirst()),
                    getMutationPolicy().mutate(pair.getSecond()));
            }
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        final RandomGenerator random = GeneticAlgorithm.getRandomGenerator();

        for (int index = 0; index < length; index++) {

            if (random.nextDouble() < ratio) {
                // swap the bits -> take other parent
                child1Rep.add(parent2Rep.get(index));
                child2Rep.add(parent1Rep.get(index));
            } else {
                child1Rep.add(parent1Rep.get(index));
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        RandomGenerator random = new Well1024a(0x49914cdd9f0b8db5l);
        final UnivariateDifferentiableFunction id = FunctionUtils.compose((UnivariateDifferentiableFunction) g,
                                                                (UnivariateDifferentiableFunction) f);

        for (int i = 0; i < 10; i++) {
            final double x = lo + random.nextDouble() * (hi - lo);
            Assert.assertEquals(x, id.value(new DerivativeStructure(1, 1, 0, x)).getValue(), EPS);
        }

        Assert.assertEquals(lo, id.value(new DerivativeStructure(1, 1, 0, lo)).getValue(), EPS);
        Assert.assertEquals(hi, id.value(new DerivativeStructure(1, 1, 0, hi)).getValue(), EPS);
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