Examples with MersenneTwister cern.jet.random.engine.MersenneTwister used on opensource projects

Example 1 with MersenneTwister

use of cern.jet.random.engine.MersenneTwister in project processdash by dtuma.

the class ConfidenceIntervalSum method runSimulation.

protected void runSimulation() {
    u = new MersenneTwister();
    super.runSimulation();
}

Example 2 with MersenneTwister

use of cern.jet.random.engine.MersenneTwister in project processdash by dtuma.

the class EVScheduleConfidenceIntervals method runSimulation.

private void runSimulation() {
    long start = System.currentTimeMillis();
    RandomEngine random = new MersenneTwister();
    int sampleCount = Settings.getInt("ev.simulationSize", BOOTSTRAP_SIZE);
    if (USE_RATIO && indivDates == null) {
        double factor = Math.exp(0.75 * Math.log(randomObjects.size()));
        sampleCount = (int) (sampleCount / factor);
        if (sampleCount < 100)
            sampleCount = 100;
    }
    for (int i = 0; i < sampleCount; i++) runOneTest(random);
    cost.samplesDone();
    date.samplesDone();
    if (optimizedDate != null)
        optimizedDate.samplesDone();
    if (indivDates != null)
        for (int i = 0; i < indivDates.length; i++) indivDates[i].samplesDone();
    long finish = System.currentTimeMillis();
    long elapsed = finish - start;
    System.out.println("schedule simulation took " + elapsed + " ms.");
    if (optimizedDate != null)
        date.debug = true;
}

Example 3 with MersenneTwister

use of cern.jet.random.engine.MersenneTwister in project processdash by dtuma.

the class LognormalConfidenceInterval method generateBootstrapSamples.

private double[] generateBootstrapSamples() {
    RandomEngine u = new MersenneTwister();
    Normal normal = new Normal(0, 1, u);
    ChiSquare chisquare = new ChiSquare(numSamples - 1, u);
    int bootstrapSize = Settings.getInt("logCI.bootstrapSize", 2000);
    double[] samples = new double[bootstrapSize];
    for (int i = bootstrapSize; i-- > 0; ) samples[i] = generateBootstrapSample(normal, chisquare, numSamples, logstd);
    Arrays.sort(samples);
    return samples;
}

Example 4 with MersenneTwister

use of cern.jet.random.engine.MersenneTwister in project Gemma by PavlidisLab.

the class ComBat method plot.

/**
 * Make diagnostic plots.
 * FIXME: As in the original ComBat, this only graphs the first batch's statistics. In principle we can (and perhaps
 * should) examine these plots for all the batches.
 *
 * @param filePrefix file prefix
 */
public void plot(String filePrefix) {
    if (this.gammaHat == null)
        throw new IllegalArgumentException("You must call 'run' first");
    /*
         * View the distribution of gammaHat, which we assume will have a normal distribution
         */
    DoubleMatrix1D ghr = gammaHat.viewRow(0);
    int NUM_HIST_BINS = 100;
    Histogram gammaHatHist = new Histogram("GammaHat", NUM_HIST_BINS, ghr);
    XYSeries ghplot = gammaHatHist.plot();
    Normal rn = new Normal(this.gammaBar.get(0), Math.sqrt(this.t2.get(0)), new MersenneTwister());
    Histogram ghtheoryT = new Histogram("Gamma", NUM_HIST_BINS, gammaHatHist.min(), gammaHatHist.max());
    for (int i = 0; i < 10000; i++) {
        double n = rn.nextDouble();
        ghtheoryT.fill(n);
    }
    XYSeries ghtheory = ghtheoryT.plot();
    File tmpfile;
    try {
        tmpfile = File.createTempFile(filePrefix + ".gammahat.histogram.", ".png");
        ComBat.log.info(tmpfile);
    } catch (IOException e) {
        throw new RuntimeException(e);
    }
    try (OutputStream os = new FileOutputStream(tmpfile)) {
        this.writePlot(os, ghplot, ghtheory);
        /*
             * View the distribution of deltaHat, which we assume has an inverse gamma distribution
             */
        DoubleMatrix1D dhr = deltaHat.viewRow(0);
        Histogram deltaHatHist = new Histogram("DeltaHat", NUM_HIST_BINS, dhr);
        XYSeries dhplot = deltaHatHist.plot();
        Gamma g = new Gamma(aPrior.get(0), bPrior.get(0), new MersenneTwister());
        Histogram deltaHatT = new Histogram("Delta", NUM_HIST_BINS, deltaHatHist.min(), deltaHatHist.max());
        for (int i = 0; i < 10000; i++) {
            double invg = 1.0 / g.nextDouble();
            deltaHatT.fill(invg);
        }
        XYSeries dhtheory = deltaHatT.plot();
        tmpfile = File.createTempFile(filePrefix + ".deltahat.histogram.", ".png");
        ComBat.log.info(tmpfile);
        try (OutputStream os2 = new FileOutputStream(tmpfile)) {
            this.writePlot(os2, dhplot, dhtheory);
        }
    } catch (IOException e) {
        throw new RuntimeException(e);
    }
}

Example 5 with MersenneTwister

use of cern.jet.random.engine.MersenneTwister in project tetrad by cmu-phil.

the class NormalityTests method getNormal.

/**
 * Generates an ideal Normal distribution for some variable.
 *
 * @return Ideal Normal distribution for a variable.
 */
private static Normal getNormal(DataSet dataSet, Variable variable) {
    double[] paramsForNormal = normalParams(dataSet, variable);
    double mean = paramsForNormal[0];
    double sd = paramsForNormal[1];
    return new Normal(mean, sd, new MersenneTwister());
}