Example usage for org.apache.commons.math.random RandomGenerator nextDouble

Introduction

In this page you can find the example usage for org.apache.commons.math.random RandomGenerator nextDouble.

Prototype

double nextDouble();

Source Link

Document

Returns the next pseudorandom, uniformly distributed double value between 0.0 and 1.0 from this random number generator's sequence.

Usage

From source file:de.tud.kom.p2psim.impl.network.modular.st.latency.NormalDistributionLatency.java

/**
 * Precompute the delays.// ww  w .  j  a v  a2s  .co m
 * 
 * @param size
 *            The number of delays, which should be computed and stored in
 *            delays.
 */
private void createDelays(int size) {

    if (propagationMeanDelay < standardDeviation) {
        log.warn(
                "Bad Configuration! It is possible, that huge delays are negative and consequently this values will be set to the mean delay value.");
    }

    log.info("Create " + size + " precomputed delays");
    RandomGenerator randGen = Simulator.getRandom();
    delays = new Vector<Long>(size);
    for (int i = 0; i < size; i++) {
        long delay = 0;
        try {
            delay = (long) normalDistribution.inverseCumulativeProbability(randGen.nextDouble());
        } catch (MathException e) {
            log.error("MathException, check your parameteres for NormalDistributionLatency class...", e);
            throw new RuntimeException();
        }
        if (delay <= 0) {
            log.debug("Set delay to propagationMeanDelay (" + propagationMeanDelay
                    + ") because it has the value " + delay);
            delay = propagationMeanDelay;
        }
        delays.add(delay);
    }
    log.info("Finished, to create delays");
}

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From source file:lfsom.visualization.clustering.LFSKMeans.java

/**
 * Calculate random centroids for each cluster.
 *///from w  w  w  .  j av  a2s . c  o m
private void initClustersRandomly() {
    RandomGenerator rg = new JDKRandomGenerator();
    // FIXME: this is for testing purposes only
    rg.setSeed(RANDOM_SEED);
    // for each cluster
    for (int clusterIndex = 0; clusterIndex < k; clusterIndex++) {
        // for each of its attributes
        double[] centroid = new double[numberOfAttributes];
        for (int attributeIndex = 0; attributeIndex < numberOfAttributes; attributeIndex++) {
            centroid[attributeIndex] = differences[attributeIndex] * rg.nextDouble()
                    + minValues[attributeIndex];
        }
        clusters[clusterIndex] = new LFSCluster(centroid);
    }
    System.out.println("initial centroids: ");
    // printCentroids();
}

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From source file:org.peerfact.impl.network.modular.common.PingErToolkitTest.java

@Test
public void test1() {
    double avgRtt = 243.23d;
    double minRtt = 193.7d;
    double dVar = 10.78;

    long startTime = System.nanoTime();
    JitterParameter result = PingErToolkit.getJitterParameterFrom(avgRtt, minRtt, dVar);
    log.debug("Calculation lasted " + (System.nanoTime() - startTime) * 0.000001 + " ms");

    LognormalDist testDist = new LognormalDist(1, 0.6);

    RandomGenerator rand = new JDKRandomGenerator();

    for (int i = 0; i < 100; i++) {
        log.debug(testDist.inverseF(rand.nextDouble()));
    }//from  w  w  w  .jav  a  2 s.c  o m

    log.debug(result);
}

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