Example usage for org.apache.commons.math3.distribution MultivariateNormalDistribution reseedRandomGenerator

Introduction

In this page you can find the example usage for org.apache.commons.math3.distribution MultivariateNormalDistribution reseedRandomGenerator.

Prototype

public void reseedRandomGenerator(long seed) 

Source Link

Usage

From source file:com.datumbox.framework.core.statistics.distributions.ContinuousDistributions.java

/**
 * Samples from Multinomial Normal Distribution.
 * /*from www. j  ava  2  s . co  m*/
 * @param mean
 * @param covariance
 * @return              A multinomialGaussianSample from the Multinomial Normal Distribution
 */
public static double[] multinomialGaussianSample(double[] mean, double[][] covariance) {
    MultivariateNormalDistribution gaussian = new MultivariateNormalDistribution(mean, covariance);
    gaussian.reseedRandomGenerator(RandomGenerator.getThreadLocalRandom().nextLong());
    return gaussian.sample();
}

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From source file:com.datumbox.framework.statistics.distributions.ContinuousDistributions.java

/**
 * Samples from Multinomial Normal Distribution.
 * /* w w w . jav  a2  s.  c  o  m*/
 * @param mean
 * @param covariance
 * @return              A multinomialGaussianSample from the Multinomial Normal Distribution
 */
public static double[] multinomialGaussianSample(double[] mean, double[][] covariance) {
    MultivariateNormalDistribution gaussian = new MultivariateNormalDistribution(mean, covariance);
    gaussian.reseedRandomGenerator(RandomValue.randomGenerator.nextLong());
    return gaussian.sample();
}

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From source file:es.csic.iiia.planes.generator.HotspotFactory.java

@Override
public MultivariateNormalDistribution buildDistribution(Configuration config, Random r) {
    final double w = config.getWidth();
    final double h = config.getHeight();
    double maxd = interpolator.value(config.getHotspotRadius(), config.getHotspotFreedomDegrees());
    double factor = 1 / maxd;

    if (covDistribution == null) {
        RealMatrix m = new Array2DRowRealMatrix(new double[][] { { factor, 0 }, { 0, factor } });
        covDistribution = new InverseWishartDistribution(m, config.getHotspotFreedomDegrees());
        covDistribution.reseedRandomGenerator(r.nextLong());
    }/*from   ww w.  ja v  a2s. c  o  m*/

    double[] means = new double[] { r.nextInt(config.getWidth()), r.nextInt(config.getHeight()), };
    double[][] covariance = getCovarianceMatrix();
    MultivariateNormalDistribution distribution = new MultivariateNormalDistribution(means, covariance);
    distribution.reseedRandomGenerator(r.nextLong());
    return distribution;
}

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