Uses of Class
cern.jet.random.engine.RandomEngine

Packages that use RandomEngine
Package
Description
cern.colt.matrix.doublealgo
Double matrix algorithms such as print formatting, sorting, partitioning and statistics.
cern.jet.random
Large variety of probability distributions featuring high performance generation of random numbers, CDF's and PDF's.
cern.jet.random.engine
Engines generating strong uniformly distributed pseudo-random numbers; Needed by all JET probability distributions since they rely on uniform random numbers to generate random numbers from their own distribution.
cern.jet.random.sampling
Samples (picks) random subsets of data sequences.
cern.jet.stat.quantile
Scalable algorithms and data structures to compute approximate quantiles over very large data sequences.
hep.aida.bin
Multisets (bags) with efficient statistics operations defined upon; This package requires the Colt distribution.

  • Uses of RandomEngine in cern.colt.matrix.doublealgo

    Methods in cern.colt.matrix.doublealgo with parameters of type RandomEngine
    Modifier and Type
    Method
    Description
    static DoubleMatrix1D
    Statistic.viewSample(DoubleMatrix1D matrix, double fraction, RandomEngine randomGenerator)
    Constructs and returns a sampling view with a size of round(matrix.size() * fraction).
    static DoubleMatrix2D
    Statistic.viewSample(DoubleMatrix2D matrix, double rowFraction, double columnFraction, RandomEngine randomGenerator)
    Constructs and returns a sampling view with round(matrix.rows() * rowFraction) rows and round(matrix.columns() * columnFraction) columns.
    static DoubleMatrix3D
    Statistic.viewSample(DoubleMatrix3D matrix, double sliceFraction, double rowFraction, double columnFraction, RandomEngine randomGenerator)
    Constructs and returns a sampling view with round(matrix.slices() * sliceFraction) slices and round(matrix.rows() * rowFraction) rows and round(matrix.columns() * columnFraction) columns.

  • Uses of RandomEngine in cern.jet.random

    Fields in cern.jet.random declared as RandomEngine
    Modifier and Type
    Field
    Description
    protected RandomEngine
    AbstractDistribution.randomGenerator
     
    protected RandomEngine
    Benchmark.randomGenerator
     
    Methods in cern.jet.random that return RandomEngine
    Modifier and Type
    Method
    Description
    protected RandomEngine
    AbstractDistribution.getRandomGenerator()
    Returns the used uniform random number generator;
    static RandomEngine
    AbstractDistribution.makeDefaultGenerator()
    Constructs and returns a new uniform random number generation engine seeded with the current time.
    Methods in cern.jet.random with parameters of type RandomEngine
    Modifier and Type
    Method
    Description
    protected double
    Beta.b00(double a, double b, RandomEngine randomGenerator)
     
    protected double
    Beta.b01(double a, double b, RandomEngine randomGenerator)
     
    protected double
    Beta.b1prs(double p, double q, RandomEngine randomGenerator)
     
    protected long
    Zeta.generateZeta(double ro, double pk, RandomEngine randomGenerator)
    Returns a zeta distributed random number.
    protected int
    HyperGeometric.hmdu(int N, int M, int n, RandomEngine randomGenerator)
    Returns a random number from the distribution.
    protected int
    HyperGeometric.hprs(int N, int M, int n, RandomEngine randomGenerator)
    Returns a random number from the distribution.
    static double
    Distributions.nextBurr1(double r, int nr, RandomEngine randomGenerator)
    Returns a random number from the Burr II, VII, VIII, X Distributions.
    static double
    Distributions.nextBurr2(double r, double k, int nr, RandomEngine randomGenerator)
    Returns a random number from the Burr III, IV, V, VI, IX, XII distributions.
    static double
    Distributions.nextCauchy(RandomEngine randomGenerator)
    Returns a cauchy distributed random number from the standard Cauchy distribution C(0,1).
    static double
    Distributions.nextErlang(double variance, double mean, RandomEngine randomGenerator)
    Returns an erlang distributed random number with the given variance and mean.
    static int
    Distributions.nextGeometric(double p, RandomEngine randomGenerator)
    Returns a discrete geometric distributed random number; Definition.
    protected int
    HyperGeometric.nextInt(int N, int M, int n, RandomEngine randomGenerator)
    Returns a random number from the distribution; bypasses the internal state.
    static double
    Distributions.nextLambda(double l3, double l4, RandomEngine randomGenerator)
    Returns a lambda distributed random number with parameters l3 and l4.
    static double
    Distributions.nextLaplace(RandomEngine randomGenerator)
    Returns a Laplace (Double Exponential) distributed random number from the standard Laplace distribution L(0,1).
    static double
    Distributions.nextLogistic(RandomEngine randomGenerator)
    Returns a random number from the standard Logistic distribution Log(0,1).
    static double
    Distributions.nextPowLaw(double alpha, double cut, RandomEngine randomGenerator)
    Returns a power-law distributed random number with the given exponent and lower cutoff.
    static double
    Distributions.nextTriangular(RandomEngine randomGenerator)
    Returns a random number from the standard Triangular distribution in (-1,1).
    static double
    Distributions.nextWeibull(double alpha, double beta, RandomEngine randomGenerator)
    Returns a weibull distributed random number.
    static int
    Distributions.nextZipfInt(double z, RandomEngine randomGenerator)
    Returns a zipfian distributed random number with the given skew.
    protected void
    AbstractDistribution.setRandomGenerator(RandomEngine randomGenerator)
    Sets the uniform random generator internally used.
    protected void
    Normal.setRandomGenerator(RandomEngine randomGenerator)
    Sets the uniform random generator internally used.
    static void
    Uniform.staticSetRandomEngine(RandomEngine randomGenerator)
    Sets the uniform random number generation engine shared by all static methods.
    Constructors in cern.jet.random with parameters of type RandomEngine
    Modifier
    Constructor
    Description
     
    Beta(double alpha, double beta, RandomEngine randomGenerator)
    Constructs a Beta distribution.
     
    Binomial(int n, double p, RandomEngine randomGenerator)
    Constructs a binomial distribution.
     
    BreitWigner(double mean, double gamma, double cut, RandomEngine randomGenerator)
    Constructs a BreitWigner distribution.
     
    BreitWignerMeanSquare(double mean, double gamma, double cut, RandomEngine randomGenerator)
    Constructs a mean-squared BreitWigner distribution.
     
    ChiSquare(double freedom, RandomEngine randomGenerator)
    Constructs a ChiSquare distribution.
     
    Empirical(double[] pdf, int interpolationType, RandomEngine randomGenerator)
    Constructs an Empirical distribution.
     
    EmpiricalWalker(double[] pdf, int interpolationType, RandomEngine randomGenerator)
    Constructs an Empirical distribution.
     
    Exponential(double lambda, RandomEngine randomGenerator)
    Constructs a Negative Exponential distribution.
     
    ExponentialPower(double tau, RandomEngine randomGenerator)
    Constructs an Exponential Power distribution.
     
    Gamma(double alpha, double lambda, RandomEngine randomGenerator)
    Constructs a Gamma distribution.
     
    Hyperbolic(double alpha, double beta, RandomEngine randomGenerator)
    Constructs a Beta distribution.
     
    HyperGeometric(int N, int s, int n, RandomEngine randomGenerator)
    Constructs a HyperGeometric distribution.
     
    Logarithmic(double p, RandomEngine randomGenerator)
    Constructs a Logarithmic distribution.
     
    NegativeBinomial(int n, double p, RandomEngine randomGenerator)
    Constructs a Negative Binomial distribution.
     
    Normal(double mean, double standardDeviation, RandomEngine randomGenerator)
    Constructs a normal (gauss) distribution.
     
    Poisson(double mean, RandomEngine randomGenerator)
    Constructs a poisson distribution.
     
    PoissonSlow(double mean, RandomEngine randomGenerator)
    Constructs a poisson distribution.
     
    StudentT(double freedom, RandomEngine randomGenerator)
    Constructs a StudentT distribution.
     
    Uniform(double min, double max, RandomEngine randomGenerator)
    Constructs a uniform distribution with the given minimum and maximum.
     
    Uniform(RandomEngine randomGenerator)
    Constructs a uniform distribution with min=0.0 and max=1.0.
     
    VonMises(double freedom, RandomEngine randomGenerator)
    Constructs a Von Mises distribution.
     
    Zeta(double ro, double pk, RandomEngine randomGenerator)
    Constructs a Zeta distribution.

  • Uses of RandomEngine in cern.jet.random.engine

    Subclasses of RandomEngine in cern.jet.random.engine
    Modifier and Type
    Class
    Description
    class 
    DRand
    Quick medium quality uniform pseudo-random number generator.
    class 
    MersenneTwister
    MersenneTwister (MT19937) is one of the strongest uniform pseudo-random number generators known so far; at the same time it is quick.
    class 
    MersenneTwister64
    Same as MersenneTwister except that method raw() returns 64 bit random numbers instead of 32 bit random numbers.
    Methods in cern.jet.random.engine that return RandomEngine
    Modifier and Type
    Method
    Description
    static RandomEngine
    RandomEngine.makeDefault()
    Constructs and returns a new uniform random number engine seeded with the current time.
    Methods in cern.jet.random.engine with parameters of type RandomEngine
    Modifier and Type
    Method
    Description
    static void
    Benchmark.test(int size, RandomEngine randomEngine)
    Prints the first size random numbers generated by the given engine.

  • Uses of RandomEngine in cern.jet.random.sampling

    Methods in cern.jet.random.sampling that return RandomEngine
    Modifier and Type
    Method
    Description
    RandomEngine
    RandomSamplingAssistant.getRandomGenerator()
    Returns the used random generator.
    Methods in cern.jet.random.sampling with parameters of type RandomEngine
    Modifier and Type
    Method
    Description
    protected static void
    RandomSampler.rejectMethodD(long n, long N, int count, long low, long[] values, int fromIndex, RandomEngine randomGenerator)
    Efficiently computes a sorted random set of count elements from the interval [low,low+N-1].
    static void
    RandomSampler.sample(long n, long N, int count, long low, long[] values, int fromIndex, RandomEngine randomGenerator)
    Efficiently computes a sorted random set of count elements from the interval [low,low+N-1].
    protected static void
    RandomSampler.sampleMethodA(long n, long N, int count, long low, long[] values, int fromIndex, RandomEngine randomGenerator)
    Computes a sorted random set of count elements from the interval [low,low+N-1].
    protected static void
    RandomSampler.sampleMethodD(long n, long N, int count, long low, long[] values, int fromIndex, RandomEngine randomGenerator)
    Efficiently computes a sorted random set of count elements from the interval [low,low+N-1].
    Constructors in cern.jet.random.sampling with parameters of type RandomEngine
    Modifier
    Constructor
    Description
     
    RandomSampler(long n, long N, long low, RandomEngine randomGenerator)
    Constructs a random sampler that computes and delivers sorted random sets in blocks.
     
    RandomSamplingAssistant(long n, long N, RandomEngine randomGenerator)
    Constructs a random sampler that samples n random elements from an input sequence of N elements.
     
    WeightedRandomSampler(int weight, RandomEngine randomGenerator)
    Chooses exactly one random element from successive blocks of weight input elements each.

  • Uses of RandomEngine in cern.jet.stat.quantile

    Methods in cern.jet.stat.quantile with parameters of type RandomEngine
    Modifier and Type
    Method
    Description
    static DoubleQuantileFinder
    QuantileFinderFactory.newDoubleQuantileFinder(boolean known_N, long N, double epsilon, double delta, int quantiles, RandomEngine generator)
    Returns a quantile finder that minimizes the amount of memory needed under the user provided constraints.

  • Uses of RandomEngine in hep.aida.bin

    Methods in hep.aida.bin with parameters of type RandomEngine
    Modifier and Type
    Method
    Description
    void
    DynamicBin1D.sample(int n, boolean withReplacement, RandomEngine randomGenerator, DoubleBuffer buffer)
    Uniformly samples (chooses) n random elements with or without replacement from the contained elements and adds them to the given buffer.
    DynamicBin1D
    DynamicBin1D.sampleBootstrap(DynamicBin1D other, int resamples, RandomEngine randomGenerator, BinBinFunction1D function)
    Generic bootstrap resampling.
    Constructors in hep.aida.bin with parameters of type RandomEngine
    Modifier
    Constructor
    Description
     
    QuantileBin1D(boolean known_N, long N, double epsilon, double delta, int quantiles, RandomEngine randomGenerator)
    Equivalent to new QuantileBin1D(known_N, N, epsilon, delta, quantiles, randomGenerator, false, false, 2).
     
    QuantileBin1D(boolean known_N, long N, double epsilon, double delta, int quantiles, RandomEngine randomGenerator, boolean hasSumOfLogarithms, boolean hasSumOfInversions, int maxOrderForSumOfPowers)
    Constructs and returns an empty bin that, under the given constraints, minimizes the amount of memory needed.