Example usage for org.apache.commons.math3.random Well1024a Well1024a

Introduction

In this page you can find the example usage for org.apache.commons.math3.random Well1024a Well1024a.

Prototype

public Well1024a() 

Source Link

Document

Creates a new random number generator.

Usage

From source file:com.ibm.bi.dml.runtime.util.PoissonPRNGenerator.java

public void setup(double mean, long sd) {
    seed = sd;/*w  w w . j  ava2s  .  c  om*/

    SynchronizedRandomGenerator srg = new SynchronizedRandomGenerator(new Well1024a());
    srg.setSeed(seed);
    _pdist = new PoissonDistribution(srg, _mean, PoissonDistribution.DEFAULT_EPSILON,
            PoissonDistribution.DEFAULT_MAX_ITERATIONS);
}

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From source file:com.milaboratory.core.io.util.AbstractRandomAccessReaderTest.java

@Test
public void test3() throws Exception {
    RandomGenerator rnd = new Well1024a();
    File tempFile = createRandomFile(rnd.nextLong());
    String[] allLines = getAllLines(tempFile);
    for (int step = 5; step < 10; step += 2) {
        for (int start = 1; start <= step; ++start) {
            FileIndex index = buildIndex(tempFile, step, start);
            StringReader reader = new StringReader(index, tempFile);
            for (int i = 0; i < allLines.length; ++i) {
                int p = rnd.nextInt(allLines.length);
                Assert.assertEquals(allLines[p], reader.take(p));
            }//from w  w  w  .  ja  v a2  s . c om
        }
    }
    tempFile.delete();
}

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From source file:com.ibm.bi.dml.runtime.matrix.data.LibMatrixDatagen.java

/**
 * A matrix of random numbers is generated by using multiple seeds, one for each 
 * block. Such block-level seeds are produced via Well equidistributed long-period linear 
 * generator (Well1024a). For a given seed, this function sets up the block-level seeds.
 * /*from   w  w w .ja v a2s.c  o m*/
 * This function is invoked from both CP (RandCPInstruction.processInstruction()) 
 * as well as MR (RandMR.java while setting up the Rand job).
 * 
 * @param seed
 * @return
 */
public static Well1024a setupSeedsForRand(long seed) {
    long lSeed = (seed == DataGenOp.UNSPECIFIED_SEED ? DataGenOp.generateRandomSeed() : seed);
    LOG.trace("Setting up RandSeeds with initial seed = " + lSeed + ".");

    Random random = new Random(lSeed);
    Well1024a bigrand = new Well1024a();
    //random.setSeed(lSeed);
    int[] seeds = new int[32];
    for (int s = 0; s < seeds.length; s++)
        seeds[s] = random.nextInt();
    bigrand.setSeed(seeds);

    return bigrand;
}

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From source file:com.milaboratory.core.io.sequence.fastq.RandomAccessFastqReaderTest.java

@Test
public void test3() throws Exception {
    File sample = new File(
            SingleFastqReaderTest.class.getClassLoader().getResource("sequences/sample_r1.fastq").toURI());
    RandomGenerator rnd = new Well1024a();
    for (int step = 1; step < 5; ++step) {
        SingleRead[] reads = allReads(sample);
        FileIndex index = buildeIndex(sample, step);
        RandomAccessFastqReader rreader = new RandomAccessFastqReader(sample, index, true);
        for (int i = 0; i < 100; ++i) {
            int p = rnd.nextInt(reads.length);
            SingleRead actual = rreader.take(p);
            Assert.assertEquals(reads[p].getId(), actual.getId());
            Assert.assertEquals(reads[p].getData(), actual.getData());
            Assert.assertEquals(reads[p].getDescription(), actual.getDescription());
        }//  w w w .j a  v a2 s  . co m
    }
}

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From source file:org.briljantframework.benchmark.DataFrameSortPerformance.java

@Setup(Level.Iteration)
public void setupDataFrame() {
    DataFrame.Builder builder = new MixedDataFrame.Builder();
    UniformRandomGenerator gen = new UniformRandomGenerator(new Well1024a());
    for (int i = 0; i < 1000_000; i++) {
        builder.setRecord(String.valueOf(i), Vector.of(gen.nextNormalizedDouble(), i, 20.0, 30.0));
    }//w  w w .j  a  v  a2  s.  c  om
    builder.setColumnIndex("First", "Second", "Third", "Fourth");
    dataFrame = builder.build();
}

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From source file:org.briljantframework.benchmark.VectorSortPerformance.java

@Setup(Level.Iteration)
public void setupDataFrame() {
    Vector.Builder builder = Vector.Builder.of(Double.class);
    UniformRandomGenerator gen = new UniformRandomGenerator(new Well1024a());
    for (int i = 0; i < 1000_000; i++) {
        builder.add(gen.nextNormalizedDouble());
    }//  ww w .j a  va  2s  .  c o  m
    vector = builder.build();
}

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From source file:org.optaplanner.core.impl.solver.random.DefaultRandomFactory.java

@Override
public Random createRandom() {
    switch (randomType) {
    case JDK:/*from w  w w. j  a v  a 2 s  .com*/
        return randomSeed == null ? new Random() : new Random(randomSeed);
    case MERSENNE_TWISTER:
        return new RandomAdaptor(randomSeed == null ? new MersenneTwister() : new MersenneTwister(randomSeed));
    case WELL512A:
        return new RandomAdaptor(randomSeed == null ? new Well512a() : new Well512a(randomSeed));
    case WELL1024A:
        return new RandomAdaptor(randomSeed == null ? new Well1024a() : new Well1024a(randomSeed));
    case WELL19937A:
        return new RandomAdaptor(randomSeed == null ? new Well19937a() : new Well19937a(randomSeed));
    case WELL19937C:
        return new RandomAdaptor(randomSeed == null ? new Well19937c() : new Well19937c(randomSeed));
    case WELL44497A:
        return new RandomAdaptor(randomSeed == null ? new Well44497a() : new Well44497a(randomSeed));
    case WELL44497B:
        return new RandomAdaptor(randomSeed == null ? new Well44497b() : new Well44497b(randomSeed));
    default:
        throw new IllegalStateException("The randomType (" + randomType + ") is not implemented.");
    }
}

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