Examples of org.apache.commons.math.random.RandomDataImpl

org.apache.commons.math.random.RandomDataImpl
Implements the {@link RandomData} interface using a {@link RandomGenerator}instance to generate non-secure data and a {@link java.security.SecureRandom}instance to provide data for the nextSecureXxx methods. If no RandomGenerator is provided in the constructor, the default is to use a generator based on {@link java.util.Random}. To plug in a different implementation, either implement RandomGenerator directly or extend {@link AbstractRandomGenerator}.
Supports reseeding the underlying pseudo-random number generator (PRNG). The SecurityProvider and Algorithm used by the SecureRandom instance can also be reset.

For details on the default PRNGs, see {@link java.util.Random} and{@link java.security.SecureRandom}.

Usage Notes:
- Instance variables are used to maintain RandomGenerator and SecureRandom instances used in data generation. Therefore, to generate a random sequence of values or strings, you should use just one RandomDataImpl instance repeatedly.
- The "secure" methods are *much* slower. These should be used only when a cryptographically secure random sequence is required. A secure random sequence is a sequence of pseudo-random values which, in addition to being well-dispersed (so no subsequence of values is an any more likely than other subsequence of the the same length), also has the additional property that knowledge of values generated up to any point in the sequence does not make it any easier to predict subsequent values.
- When a new RandomDataImpl is created, the underlying random number generators are not initialized. If you do not explicitly seed the default non-secure generator, it is seeded with the current time in milliseconds on first use. The same holds for the secure generator. If you provide a RandomGenerator to the constructor, however, this generator is not reseeded by the constructor nor is it reseeded on first use.
- The reSeed and reSeedSecure methods delegate to the corresponding methods on the underlying RandomGenerator and SecureRandom instances. Therefore, reSeed(long) fully resets the initial state of the non-secure random number generator (so that reseeding with a specific value always results in the same subsequent random sequence); whereas reSeedSecure(long) does not reinitialize the secure random number generator (so secure sequences started with calls to reseedSecure(long) won't be identical).
- This implementation is not synchronized.
@version $Revision: 1061496 $ $Date: 2011-01-20 21:32:16 +0100 (jeu. 20 janv. 2011) $

    public void testWithInitialCapacity() {
        
        ResizableDoubleArray eDA2 = new ResizableDoubleArray(2);
        assertEquals("Initial number of elements should be 0", 0, eDA2.getNumElements());
        
        RandomData randomData = new RandomDataImpl();
        int iterations = randomData.nextInt(100, 1000);
        
        for( int i = 0; i < iterations; i++) {
            eDA2.addElement( i );
        }

View Full Code Here

    public void testWithInitialCapacityAndExpansionFactor() {
        
        ResizableDoubleArray eDA3 = new ResizableDoubleArray(3, 3.0f, 3.5f);
        assertEquals("Initial number of elements should be 0", 0, eDA3.getNumElements() );
        
        RandomData randomData = new RandomDataImpl();
        int iterations = randomData.nextInt(100, 3000);
        
        for( int i = 0; i < iterations; i++) {
            eDA3.addElement( i );
        }

View Full Code Here

        double[] test1 = {5,4,3,2,1};
        double[] test2 = {5,2,1,3,4,0};
        double[] test3 = {1};
        int[] testi = null;
        double[] test4 = null;
        RandomData rd = new RandomDataImpl();
        tstGetSortedValues(test1);
        tstGetSortedValues(test2);
        tstGetSortedValues(test3);
        for (int i = 0; i < 10; i++) {
            testi = rd.nextPermutation(10,6);
            test4 = new double[6];
            for (int j = 0; j < testi.length; j++) {
                test4[j] = (double) testi[j];
            }
            tstGetSortedValues(test4);
        }
        for (int i = 0; i < 10; i++) {
            testi = rd.nextPermutation(10,5);
            test4 = new double[5];
            for (int j = 0; j < testi.length; j++) {
                test4[j] = (double) testi[j];
            }
            tstGetSortedValues(test4);

View Full Code Here

        assertEquals("Q1",1,u.getPercentile(25),10E-12);
        assertEquals("Q3",1,u.getPercentile(75),10E-12);
        assertEquals("Q2",1,u.getPercentile(50),10E-12);
        
        u.clear();
        RandomData rd = new RandomDataImpl();
        int[] testi = rd.nextPermutation(100,100); // will contain 0-99
        for (int j = 0; j < testi.length; j++) {
            u.addValue((double) testi[j]);  //OK, laugh at me for the cast
        }
        for (int i = 1; i < 100; i++) {
            assertEquals("percentile " + i,

View Full Code Here

    FragmentPenalty fragmentPenalty = new PowerFragmentPenalty(power,powerCoefficient);
    //define partition prior
    FragmentPartitionPrior fragPrior = new FragmentPartitionPrior(fragmentPenalty);
    //define tuning distribution
    RandomGenerator rg = new Well44497b();
    RandomDataImpl rng = new RandomDataImpl(rg);
    common.TuningDistribution tuningDistribution = new PoissonTuningDistribution(rng,poisson);
    //initial jumping weights
    double[] initJumpWeight = new double[n];
    java.util.Arrays.fill(initJumpWeight, 10);
    //------------------------------------------------------------------------------------

View Full Code Here

public class Test {
  public static void main(String[] args) throws MathException {
    int[][] grid = new int[5][5];
    double[][] data = new double[5][5];
    RandomGenerator rg = new Well44497b(20111013);
    RandomDataImpl rng = new RandomDataImpl(rg);
    initializeGrid2(grid);
    initializeData(data, rng);
    printGrid(grid);
//    System.out.println(rng.nextInt(0, 4));
//    System.out.println(rng.nextInt(0, 4));

View Full Code Here


public class RunMCMC {
  public static void main(String[] args){
    //-------------- random number generator -----------------
    RandomGenerator rg = new Well44497b();
    RandomDataImpl rng = new RandomDataImpl(rg);
    //--------------- initial data points ----------------
    
    //-----initial currentPartition and proposedPartition---------
    
    //partition prior

View Full Code Here

    //define partition prior
//    PartitionPrior partitionPrior = new DistPartitionPrior(locs,3,fragmentPenalty,sizePenalty);
    PartitionPrior fragPrior = new FragmentPartitionPrior(fragmentPenalty);
    //define tuning distribution
    RandomGenerator rg = new Well44497b();
    RandomDataImpl rng = new RandomDataImpl(rg);
    TuningDistribution tuningDistribution = new PoissonTuningDistribution(rng,1);
    //initial jumping weights
    double[] initJumpWeight = new double[n];
    java.util.Arrays.fill(initJumpWeight, 10);
    double variance = 0.1;

View Full Code Here

    FragmentPenalty fragmentPenalty = new PowerFragmentPenalty(power,powerCoefficient);
    //define partition prior
    FragmentPartitionPrior fragPrior = new FragmentPartitionPrior(fragmentPenalty);
    //define tuning distribution
    RandomGenerator rg = new Well44497b();
    RandomDataImpl rng = new RandomDataImpl(rg);
    common.TuningDistribution tuningDistribution = new PoissonTuningDistribution(rng,poisson);
    //initial jumping weights
    double[] initJumpWeight = new double[n];
    java.util.Arrays.fill(initJumpWeight, 10);
    //------------------------------------------------------------------------------------

View Full Code Here

    FragmentPenalty fragmentPenalty = new PowerFragmentPenalty(power,powerCoefficient);
    //define partition prior
    FragmentPartitionPrior fragPrior = new FragmentPartitionPrior(fragmentPenalty);
    //define tuning distribution
    RandomGenerator rg = new Well44497b();
    RandomDataImpl rng = new RandomDataImpl(rg);
    common.TuningDistribution tuningDistribution = new PoissonTuningDistribution(rng,poisson);
    //initial jumping weights
    double[] initJumpWeight = new double[n];
    java.util.Arrays.fill(initJumpWeight, 10);
    //------------------------------------------------------------------------------------

View Full Code Here

0 1 2 3 4 5 6

TOP

Related Classes of org.apache.commons.math.random.RandomDataImpl

br.com.six2six.bfgex.RandomGen

complex1.RunMCMC

cu.repsystestbed.util.DefaultArffFeedbackGenerator

normal1.RunSimpleMCMC

normal2.RunMCMC

normal2.RunSimpleMCMC

org.apache.accumulo.test.randomwalk.concurrent.Config

org.apache.commons.math.distribution.BetaDistributionImpl

org.apache.commons.math.distribution.BinomialDistributionImpl

org.apache.commons.math.distribution.CauchyDistributionImpl

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.