Example usage for org.apache.commons.math3.distribution UniformRealDistribution UniformRealDistribution

Introduction

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

Prototype

public UniformRealDistribution() 

Source Link

Document

Create a standard uniform real distribution with lower bound (inclusive) equal to zero and upper bound (exclusive) equal to one.

Usage

From source file:it.cnr.isti.smartfed.federation.generation.AbstractGenerator.java

public AbstractGenerator(long seed) {
    distribution = new UniformRealDistribution();
    type = GenerationType.UNIFORM;
    this.resetSeed(seed);
}

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From source file:com.vsthost.rnd.StructuralTest.java

@Test
public void isItRunningAtAll() {
    // Create an instance of a problem:
    Problem problem = new Problem(new double[] { -1, -1 }, new double[] { 1, 1 });

    // Define an objective:
    Objective objective = candidate -> Math.abs(SillyFormula(candidate[0], candidate[1]));

    // Define an empty strategy:
    Strategy strategy = (population, problem1, objective1) -> {
    };/*from   w  w  w  .j  a  v  a2  s. c o m*/

    // Initialize a population:
    Population population = new Population(100, 2, new double[] { -1, -1 }, new double[] { 1, 1 },
            new UniformRealDistribution());

    // Define the diagnostics:
    Diagnostics diagnostics = new Diagnostics(true, true);

    // Define the DE instance:
    DEoptim DEoptim = new DEoptim(10, problem, objective, strategy, population, diagnostics);

    // Run it:
    DEoptim.evolve();
}

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From source file:it.cnr.isti.smartfed.federation.generation.ApplicationGenerator.java

/**
 * Return an application whose cloudlets are assigned to vertex with 
 * an uniform distribution. /*from   w  w w.j  av  a 2s  . c  o m*/
 * @param userId
 * @param numVertex
 * @param numCloudlet
 * @return
 */
public Application getApplication(int userId, int numVertex, int numCloudlet) {
    UniformRealDistribution urd = new UniformRealDistribution();
    urd.reseedRandomGenerator(this.seed);
    return this.getApplication(userId, numVertex, numCloudlet, urd);
}

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From source file:com.vsthost.rnd.SandboxStrategyTest.java

@Test
public void isItEvolving() {
    // Create an instance of a problem:
    Problem problem = new Problem(new double[] { -1, -1 }, new double[] { 1, 1 });

    // Define an objective:
    Objective objective = candidate -> Math.abs(SillyFormula(candidate[0], candidate[1]));

    // Define a strategy:
    Strategy strategy = new SandboxStrategy(0.75, 0.8, 0.1, new MersenneTwister());

    // Initialize a population:
    Population population = new Population(20, 2, new double[] { -1, -1 }, new double[] { 1, 1 },
            new UniformRealDistribution());

    // Define the diagnostics:
    Diagnostics diagnostics = new Diagnostics(true, true);

    // Define the DE instance:
    DEoptim DEoptim = new DEoptim(50, problem, objective, strategy, population, diagnostics);

    // Run it:/*from w  w  w .  ja  v  a2s  .com*/
    DEoptim.evolve();

    // Compare the first score to the best:
    assertTrue(diagnostics.getEntries().get(0).score >= diagnostics.getBestScore());
}

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From source file:it.cnr.isti.smartfed.papers.qbrokage.ApplicationGenerator.java

public Application getApplication(int userId, int numVertex, int numCloudlet) {
    UniformRealDistribution urd = new UniformRealDistribution();
    urd.reseedRandomGenerator(this.seed);
    return this.getApplication(userId, numVertex, numCloudlet, urd);
}

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From source file:com.vsthost.rnd.StructuralTest.java

@Test
public void isItEvolving() {
    // Create an instance of a problem:
    Problem problem = new Problem(new double[] { -1, -1 }, new double[] { 1, 1 });

    // Define an objective:
    Objective objective = candidate -> Math.abs(SillyFormula(candidate[0], candidate[1]));

    // Define a strategy:
    Strategy strategy = new SimpleStrategy(0.75, 0.8, new MersenneTwister());

    // Initialize a population:
    Population population = new Population(10, 2, new double[] { -1, -1 }, new double[] { 1, 1 },
            new UniformRealDistribution());

    // Define the diagnostics:
    Diagnostics diagnostics = new Diagnostics(true, true);

    // Define the DE instance:
    DEoptim DEoptim = new DEoptim(50, problem, objective, strategy, population, diagnostics);

    // Run it://  www.  j a  v a  2 s.  com
    DEoptim.evolve();

    // Compare the first score to the best:
    assertTrue(diagnostics.getEntries().get(0).score >= diagnostics.getBestScore());
}

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From source file:it.cnr.isti.smartfed.federation.generation.DatacenterGenerator.java

/**
 * Generates the list of datacenters by assigning hosts to datacenters according
 * to a uniform distribution. If a datacenter will result with 0 hosts, it will not
 * be created./*from   ww w .j  av  a2 s .  c o  m*/
 * 
 * @param numOfDatacenters
 * @param numHost
 * @return
 */
public List<FederationDatacenter> getDatacenters(int numOfDatacenters, int numHost) {
    UniformRealDistribution urd = new UniformRealDistribution();
    urd.reseedRandomGenerator(this.seed);

    return getDatacenters(numOfDatacenters, numHost, urd);
}

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From source file:com.github.tteofili.looseen.yay.SGM.java

private RealMatrix[] initWeights() {
    int[] conf = new int[] { configuration.inputs, configuration.vectorSize, configuration.outputs };
    int[] layers = new int[conf.length];
    System.arraycopy(conf, 0, layers, 0, layers.length);
    int weightsCount = layers.length - 1;

    RealMatrix[] initialWeights = new RealMatrix[weightsCount];

    for (int i = 0; i < weightsCount; i++) {
        RealMatrix matrix = MatrixUtils.createRealMatrix(layers[i + 1], layers[i]);

        UniformRealDistribution uniformRealDistribution = new UniformRealDistribution();
        double[] vs = uniformRealDistribution.sample(matrix.getRowDimension() * matrix.getColumnDimension());
        int r = 0;
        int c = 0;
        for (double v : vs) {
            matrix.setEntry(r % matrix.getRowDimension(), c % matrix.getColumnDimension(), v);
            r++;/*from w w  w  .  ja  va2 s .  c  o  m*/
            c++;
        }

        initialWeights[i] = matrix;
    }
    return initialWeights;

}

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