Examples of MersenneTwisterRNG

org.uncommons.maths.random.MersenneTwisterRNG
ath.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html" target="_top">Mersenne Twister algorithm developed by Makoto Matsumoto and Takuji Nishimura.

This is a very fast random number generator with good statistical properties (it passes the full DIEHARD suite). This is the best RNG for most experiments. If a non-linear generator is required, use the slower {@link AESCounterRNG} RNG.
This PRNG is deterministic, which can be advantageous for testing purposes since the output is repeatable. If multiple instances of this class are created with the same seed they will all have identical output.

This code is translated from the original C version and assumes that we will always seed from an array of bytes. I don't pretend to know the meanings of the magic numbers or how it works, it just does.

NOTE: Because instances of this class require 128-bit seeds, it is not possible to seed this RNG using the {@link #setSeed(long)} method inheritedfrom {@link Random}. Calls to this method will have no effect. Instead the seed must be set by a constructor.
@author Makoto Matsumoto and Takuji Nishimura (original C version) @author Daniel Dyer (Java port)

Examples of org.uncommons.maths.random.MersenneTwisterRNG

  public void testTrainingTestingSets() throws IOException {
    int n = 20;


    for (int nloop = 0; nloop < n; nloop++) {
      long datasetSize = 100;
      MersenneTwisterRNG rng = new MersenneTwisterRNG();
      byte[] seed = rng.getSeed();
      double threshold = rng.nextDouble();


      JobConf conf = new JobConf();
      RndLineRecordReader rndReader;
      Set<Long> dataset = new HashSet<Long>();
      LongWritable key = new LongWritable();

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Examples of org.uncommons.maths.random.MersenneTwisterRNG


  public void testStoreJobParameters() {
    int n = 20;


    for (int nloop = 0; nloop < n; nloop++) {
      MersenneTwisterRNG rng = new MersenneTwisterRNG();


      byte[] seed = rng.getSeed();
      double threshold = rng.nextDouble();
      boolean training = rng.nextBoolean();


      DatasetSplit split = new DatasetSplit(seed, threshold);
      split.setTraining(training);


      JobConf conf = new JobConf();

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Examples of org.uncommons.maths.random.MersenneTwisterRNG


public class CDMahoutEvaluatorTest extends TestCase {


  public void testEvaluate() throws Exception {
    int nbrules = 100;
    Random rng = new MersenneTwisterRNG();
    int target = 1;


    // random rules
    List<Rule> rules = new ArrayList<Rule>();
    for (int index = 0; index < nbrules; index++) {

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Examples of org.uncommons.maths.random.MersenneTwisterRNG


  Random rng;


  @Override
  protected void setUp() {
    rng = new MersenneTwisterRNG();
  }

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Examples of org.uncommons.maths.random.MersenneTwisterRNG

        dataset, target, split);
    // Selection Strategy
    SelectionStrategy<? super CDRule> selection = new RouletteWheelSelection();


    EvolutionEngine<CDRule> engine = new SequentialEvolutionEngine<CDRule>(factory,
        pipeline, evaluator, selection, new MersenneTwisterRNG());


    engine.addEvolutionObserver(new EvolutionObserver<CDRule>() {
      @Override
      public void populationUpdate(PopulationData<? extends CDRule> data) {
        log.info("Generation {}", data.getGenerationNumber());

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Examples of org.uncommons.maths.random.MersenneTwisterRNG


  private UncommonDistributions() {
  }


  public static void init(byte[] seed) {
    random = new MersenneTwisterRNG(seed);
  }

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Examples of org.uncommons.maths.random.MersenneTwisterRNG

   *         cities once.
   */
  @Override
  public List<String> calculateShortestRoute(Collection<String> cities,
      final ProgressListener progressListener) {
    Random rng = new MersenneTwisterRNG();


    // Set-up evolution pipeline (cross-over followed by mutation).
    List<EvolutionaryOperator<? super List<?>>> operators = new ArrayList<EvolutionaryOperator<? super List<?>>>(
        2);
    if (crossover) {

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Examples of org.uncommons.maths.random.MersenneTwisterRNG

    this.threshold = threshold;
    this.training = true;
  }


  public DatasetSplit(double threshold) {
    this(new MersenneTwisterRNG().getSeed(), threshold);
  }

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Examples of org.uncommons.maths.random.MersenneTwisterRNG


      this.reader = reader;


      DatasetSplit split = new DatasetSplit(conf);


      rng = new MersenneTwisterRNG(split.getSeed());
      threshold = split.getThreshold();
      training = split.isTraining();
    }

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Examples of org.uncommons.maths.random.MersenneTwisterRNG

   * <br>
   * Make sure that evaluate() is not called twice for the same population.
   */
  public void testEvaluateSamePopulation() {
    STFitnessEvaluatorMock<Integer> mock = new STFitnessEvaluatorMock<Integer>();
    Random rng = new MersenneTwisterRNG();


    int size = 100;
    List<Integer> population = randomInts(size, rng);


    List<Double> evaluations = randomFloats(size, rng);

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