Uses of Class
cern.jet.random.engine.RandomEngine
Packages that use RandomEngine
Package
Description
Double matrix algorithms such as print formatting, sorting, partitioning and statistics.
Large variety of probability distributions featuring high performance generation
of random numbers, CDF's and PDF's.
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.
Samples (picks) random subsets of data sequences.
Scalable algorithms and data structures to compute approximate quantiles over very large data sequences.
Multisets (bags) with efficient statistics operations defined upon; This package
requires the Colt distribution.
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Uses of RandomEngine in cern.colt.matrix.doublealgo
Methods in cern.colt.matrix.doublealgo with parameters of type RandomEngineModifier and TypeMethodDescriptionstatic 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 RandomEngineModifier and TypeFieldDescriptionprotected RandomEngine
AbstractDistribution.randomGenerator
protected RandomEngine
Benchmark.randomGenerator
Methods in cern.jet.random that return RandomEngineModifier and TypeMethodDescriptionprotected 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 RandomEngineModifier and TypeMethodDescriptionprotected 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.private static void
Beta.xstaticSetRandomGenerator
(RandomEngine randomGenerator) Sets the uniform random number generated shared by all static methods.private static void
Binomial.xstaticSetRandomGenerator
(RandomEngine randomGenerator) Sets the uniform random number generated shared by all static methods.private static void
BreitWigner.xstaticSetRandomGenerator
(RandomEngine randomGenerator) Sets the uniform random number generated shared by all static methods.private static void
BreitWignerMeanSquare.xstaticSetRandomGenerator
(RandomEngine randomGenerator) Sets the uniform random number generated shared by all static methods.private static void
ChiSquare.xstaticSetRandomGenerator
(RandomEngine randomGenerator) Sets the uniform random number generated shared by all static methods.private static void
Exponential.xstaticSetRandomGenerator
(RandomEngine randomGenerator) Sets the uniform random number generated shared by all static methods.private static void
ExponentialPower.xstaticSetRandomGenerator
(RandomEngine randomGenerator) Sets the uniform random number generated shared by all static methods.private static void
Gamma.xstaticSetRandomGenerator
(RandomEngine randomGenerator) Sets the uniform random number generated shared by all static methods.private static void
Hyperbolic.xstaticSetRandomGenerator
(RandomEngine randomGenerator) Sets the uniform random number generated shared by all static methods.private static void
HyperGeometric.xstaticSetRandomGenerator
(RandomEngine randomGenerator) Sets the uniform random number generated shared by all static methods.private static void
Logarithmic.xstaticSetRandomGenerator
(RandomEngine randomGenerator) Sets the uniform random number generated shared by all static methods.private static void
NegativeBinomial.xstaticSetRandomGenerator
(RandomEngine randomGenerator) Sets the uniform random number generated shared by all static methods.private static void
Normal.xstaticSetRandomGenerator
(RandomEngine randomGenerator) Sets the uniform random number generated shared by all static methods.private static void
Poisson.xstaticSetRandomGenerator
(RandomEngine randomGenerator) Sets the uniform random number generated shared by all static methods.private static void
PoissonSlow.xstaticSetRandomGenerator
(RandomEngine randomGenerator) Sets the uniform random number generated shared by all static methods.private static void
StudentT.xstaticSetRandomGenerator
(RandomEngine randomGenerator) Sets the uniform random number generated shared by all static methods.private static void
VonMises.xstaticSetRandomGenerator
(RandomEngine randomGenerator) Sets the uniform random number generated shared by all static methods.private static void
Zeta.xstaticSetRandomGenerator
(RandomEngine randomGenerator) Sets the uniform random number generated shared by all static methods.Constructors in cern.jet.random with parameters of type RandomEngineModifierConstructorDescriptionBeta
(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.engineModifier and TypeClassDescriptionclass
Quick medium quality uniform pseudo-random number generator.class
MersenneTwister (MT19937) is one of the strongest uniform pseudo-random number generators known so far; at the same time it is quick.class
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 RandomEngineModifier and TypeMethodDescriptionstatic 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 RandomEngineModifier and TypeMethodDescriptionstatic 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
Fields in cern.jet.random.sampling declared as RandomEngineMethods in cern.jet.random.sampling that return RandomEngineModifier and TypeMethodDescriptionRandomSamplingAssistant.getRandomGenerator()
Returns the used random generator.Methods in cern.jet.random.sampling with parameters of type RandomEngineModifier and TypeMethodDescriptionprotected 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 RandomEngineModifierConstructorDescriptionRandomSampler
(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 RandomEngineModifier and TypeMethodDescriptionstatic 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.Constructors in cern.jet.stat.quantile with parameters of type RandomEngineModifierConstructorDescriptionKnownDoubleQuantileEstimator
(int b, int k, long N, double samplingRate, RandomEngine generator) Constructs an approximate quantile finder with b buffers, each having k elements.UnknownDoubleQuantileEstimator
(int b, int k, int h, double precomputeEpsilon, RandomEngine generator) Constructs an approximate quantile finder with b buffers, each having k elements. -
Uses of RandomEngine in hep.aida.bin
Methods in hep.aida.bin with parameters of type RandomEngineModifier and TypeMethodDescriptionvoid
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.sampleBootstrap
(DynamicBin1D other, int resamples, RandomEngine randomGenerator, BinBinFunction1D function) Generic bootstrap resampling.Constructors in hep.aida.bin with parameters of type RandomEngineModifierConstructorDescriptionQuantileBin1D
(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.