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.
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 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

Fields in cern.jet.random.sampling declared as RandomEngine

Modifier and Type	Field	Description
(package private) RandomEngine	RandomSampler.my_RandomGenerator

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.

Constructors in cern.jet.stat.quantile with parameters of type RandomEngine

Modifier	Constructor	Description
	KnownDoubleQuantileEstimator(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 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.