Uses of Interface
org.apache.commons.rng.UniformRandomProvider

Packages that use UniformRandomProvider

Package	Description
org.apache.commons.rng	This package contains the library's interface to be used by client code that needs a generator of sequences of pseudo-random numbers that are uniformly distributed in a specified range.
org.apache.commons.rng.core	Base classes for the generation of uniformly distributed random numbers.
org.apache.commons.rng.core.source32	Concrete algorithms for int-based sources of randomness.
org.apache.commons.rng.core.source64	Concrete algorithms for long-based sources of randomness.
org.apache.commons.rng.core.util	This package contains utilities to combine/split primitive types.
org.apache.commons.rng.sampling	This package provides sampling utilities.
org.apache.commons.rng.sampling.distribution	This package contains classes for sampling from statistical distributions.
org.apache.commons.rng.sampling.shape	This package contains classes for sampling coordinates from shapes, for example a unit ball.
org.apache.commons.rng.simple	This package provides factory methods by which low-level classes implemented in module "commons-rng-core" are instantiated.
org.apache.commons.rng.simple.internal	Utilities for seed conversion.

Uses of UniformRandomProvider in org.apache.commons.rng

Subinterfaces of UniformRandomProvider in org.apache.commons.rng

Modifier and Type	Interface	Description
interface	ArbitrarilyJumpableUniformRandomProvider	Applies to generators that can be advanced an arbitrary number of steps of the output sequence in a single operation.
interface	JumpableUniformRandomProvider	Applies to generators that can be advanced a large number of steps of the output sequence in a single operation.
interface	LongJumpableUniformRandomProvider	Applies to generators that can be advanced a very large number of steps of the output sequence in a single operation.
interface	RestorableUniformRandomProvider	Applies to generators whose internal state can be saved and restored.
interface	SplittableUniformRandomProvider	Applies to generators that can be split into two objects (the original and a new instance) each of which implements the same interface (and can be recursively split indefinitely).

Methods in org.apache.commons.rng that return UniformRandomProvider

Modifier and Type	Method	Description
UniformRandomProvider	JumpableUniformRandomProvider.jump()	Creates a copy of the UniformRandomProvider and then advances the state of the current instance.

Methods in org.apache.commons.rng that return types with arguments of type UniformRandomProvider

Modifier and Type	Method	Description
default Stream<UniformRandomProvider>	JumpableUniformRandomProvider.jumps()	Returns an effectively unlimited stream of new random generators, each of which implements the UniformRandomProvider interface.
default Stream<UniformRandomProvider>	JumpableUniformRandomProvider.jumps(long streamSize)	Returns a stream producing the given streamSize number of new random generators, each of which implements the UniformRandomProvider interface.

Methods in org.apache.commons.rng with parameters of type UniformRandomProvider

Modifier and Type	Method	Description
SplittableUniformRandomProvider	SplittableUniformRandomProvider.split(UniformRandomProvider source)	Creates a new random generator, split off from this one, that implements the SplittableUniformRandomProvider interface.

Uses of UniformRandomProvider in org.apache.commons.rng.core

Classes in org.apache.commons.rng.core that implement UniformRandomProvider

Modifier and Type	Class	Description
class	BaseProvider	Base class with default implementation for common methods.

Uses of UniformRandomProvider in org.apache.commons.rng.core.source32

Classes in org.apache.commons.rng.core.source32 that implement UniformRandomProvider

Modifier and Type	Class	Description
class	AbstractWell	This abstract class implements the WELL class of pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
class	DotyHumphreySmallFastCounting32	Implement the Small, Fast, Counting (SFC) 32-bit generator of Chris Doty-Humphrey.
class	IntProvider	Base class for all implementations that provide an int-based source randomness.
class	ISAACRandom	A fast cryptographic pseudo-random number generator.
class	JDKRandom	A provider that uses the Random.nextInt() method of the JDK's Random class as the source of randomness.
class	JenkinsSmallFast32	Implement Bob Jenkins's small fast (JSF) 32-bit generator.
class	KISSRandom	Port from Marsaglia's "KISS" algorithm.
final class	L32X64Mix	A 32-bit all purpose generator.
class	MersenneTwister	This class implements a powerful pseudo-random number generator developed by Makoto Matsumoto and Takuji Nishimura during 1996-1997.
class	MiddleSquareWeylSequence	Middle Square Weyl Sequence Random Number Generator.
class	MultiplyWithCarry256	Port from Marsaglia's "Multiply-With-Carry" algorithm.
class	PcgMcgXshRr32	A Permuted Congruential Generator (PCG) that is composed of a 64-bit Multiplicative Congruential Generator (MCG) combined with the XSH-RR (xorshift; random rotate) output transformation to create 32-bit output.
class	PcgMcgXshRs32	A Permuted Congruential Generator (PCG) that is composed of a 64-bit Multiplicative Congruential Generator (MCG) combined with the XSH-RS (xorshift; random shift) output transformation to create 32-bit output.
class	PcgXshRr32	A Permuted Congruential Generator (PCG) that is composed of a 64-bit Linear Congruential Generator (LCG) combined with the XSH-RR (xorshift; random rotate) output transformation to create 32-bit output.
class	PcgXshRs32	A Permuted Congruential Generator (PCG) that is composed of a 64-bit Linear Congruential Generator (LCG) combined with the XSH-RS (xorshift; random shift) output transformation to create 32-bit output.
final class	Philox4x32	This class implements the Philox4x32 128-bit counter-based generator with 10 rounds.
class	Well1024a	This class implements the WELL1024a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
class	Well19937a	This class implements the WELL19937a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
class	Well19937c	This class implements the WELL19937c pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
class	Well44497a	This class implements the WELL44497a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
class	Well44497b	This class implements the WELL44497b pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
class	Well512a	This class implements the WELL512a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
class	XoRoShiRo64Star	A fast 32-bit generator suitable for float generation.
class	XoRoShiRo64StarStar	A fast all-purpose 32-bit generator.
class	XoShiRo128Plus	A fast 32-bit generator suitable for float generation.
class	XoShiRo128PlusPlus	A fast all-purpose 32-bit generator.
class	XoShiRo128StarStar	A fast all-purpose 32-bit generator.

Methods in org.apache.commons.rng.core.source32 that return UniformRandomProvider

Modifier and Type	Method	Description
UniformRandomProvider	L32X64Mix.jump()	Creates a copy of the UniformRandomProvider and then retreats the state of the current instance.
UniformRandomProvider	Philox4x32.jump()	Creates a copy of the UniformRandomProvider and then advances the state of the current instance.

Methods in org.apache.commons.rng.core.source32 with parameters of type UniformRandomProvider

Modifier and Type	Method	Description
SplittableUniformRandomProvider	L32X64Mix.split(UniformRandomProvider source)	Creates a new random generator, split off from this one, that implements the SplittableUniformRandomProvider interface.

Uses of UniformRandomProvider in org.apache.commons.rng.core.source64

Classes in org.apache.commons.rng.core.source64 that implement UniformRandomProvider

Modifier and Type	Class	Description
class	DotyHumphreySmallFastCounting64	Implement the Small, Fast, Counting (SFC) 64-bit generator of Chris Doty-Humphrey.
class	JenkinsSmallFast64	Implement Bob Jenkins's small fast (JSF) 64-bit generator.
class	L128X1024Mix	A 64-bit all purpose generator.
class	L128X128Mix	A 64-bit all purpose generator.
class	L128X256Mix	A 64-bit all purpose generator.
class	L64X1024Mix	A 64-bit all purpose generator.
class	L64X128Mix	A 64-bit all purpose generator.
class	L64X128StarStar	A 64-bit all purpose generator.
class	L64X256Mix	A 64-bit all purpose generator.
class	LongProvider	Base class for all implementations that provide a long-based source randomness.
class	MersenneTwister64	This class provides the 64-bits version of the originally 32-bits Mersenne Twister.
class	PcgRxsMXs64	A Permuted Congruential Generator (PCG) that is composed of a 64-bit Linear Congruential Generator (LCG) combined with the RXS-M-XS (random xorshift; multiply; xorshift) output transformation to create 64-bit output.
final class	Philox4x64	This class implements the Philox4x64 256-bit counter-based generator with 10 rounds.
class	SplitMix64	A fast RNG, with 64 bits of state, that can be used to initialize the state of other generators.
class	TwoCmres	Random number generator designed by Mark D. Overton.
class	XoRoShiRo1024PlusPlus	A large-state all-purpose 64-bit generator.
class	XoRoShiRo1024Star	A large-state 64-bit generator suitable for double generation.
class	XoRoShiRo1024StarStar	A large-state all-purpose 64-bit generator.
class	XoRoShiRo128Plus	A fast 64-bit generator suitable for double generation.
class	XoRoShiRo128PlusPlus	A fast all-purpose 64-bit generator.
class	XoRoShiRo128StarStar	A fast all-purpose 64-bit generator.
class	XorShift1024Star	A fast RNG implementing the XorShift1024* algorithm.
class	XorShift1024StarPhi	A fast RNG implementing the XorShift1024* algorithm.
class	XoShiRo256Plus	A fast 64-bit generator suitable for double generation.
class	XoShiRo256PlusPlus	A fast all-purpose 64-bit generator.
class	XoShiRo256StarStar	A fast all-purpose 64-bit generator.
class	XoShiRo512Plus	A fast 64-bit generator suitable for double generation.
class	XoShiRo512PlusPlus	A fast all-purpose generator.
class	XoShiRo512StarStar	A fast all-purpose generator.

Methods in org.apache.commons.rng.core.source64 that return UniformRandomProvider

Modifier and Type	Method	Description
UniformRandomProvider	L128X1024Mix.jump()	Creates a copy of the UniformRandomProvider and then retreats the state of the current instance.
UniformRandomProvider	L128X128Mix.jump()	Creates a copy of the UniformRandomProvider and then retreats the state of the current instance.
UniformRandomProvider	L128X256Mix.jump()	Creates a copy of the UniformRandomProvider and then retreats the state of the current instance.
UniformRandomProvider	L64X1024Mix.jump()	Creates a copy of the UniformRandomProvider and then retreats the state of the current instance.
UniformRandomProvider	L64X256Mix.jump()	Creates a copy of the UniformRandomProvider and then retreats the state of the current instance.
UniformRandomProvider	Philox4x64.jump()	Creates a copy of the UniformRandomProvider and then advances the state of the current instance.
UniformRandomProvider	XoRoShiRo128PlusPlus.jump()	Creates a copy of the UniformRandomProvider and then advances the state of the current instance.
UniformRandomProvider	XorShift1024Star.jump()	Creates a copy of the UniformRandomProvider and then advances the state of the current instance.

Methods in org.apache.commons.rng.core.source64 with parameters of type UniformRandomProvider

Modifier and Type	Method	Description
SplittableUniformRandomProvider	L128X1024Mix.split(UniformRandomProvider source)	Creates a new random generator, split off from this one, that implements the SplittableUniformRandomProvider interface.
SplittableUniformRandomProvider	L128X128Mix.split(UniformRandomProvider source)	Creates a new random generator, split off from this one, that implements the SplittableUniformRandomProvider interface.
SplittableUniformRandomProvider	L128X256Mix.split(UniformRandomProvider source)	Creates a new random generator, split off from this one, that implements the SplittableUniformRandomProvider interface.
SplittableUniformRandomProvider	L64X1024Mix.split(UniformRandomProvider source)	Creates a new random generator, split off from this one, that implements the SplittableUniformRandomProvider interface.
SplittableUniformRandomProvider	L64X128Mix.split(UniformRandomProvider source)	Creates a new random generator, split off from this one, that implements the SplittableUniformRandomProvider interface.
SplittableUniformRandomProvider	L64X128StarStar.split(UniformRandomProvider source)	Creates a new random generator, split off from this one, that implements the SplittableUniformRandomProvider interface.
SplittableUniformRandomProvider	L64X256Mix.split(UniformRandomProvider source)	Creates a new random generator, split off from this one, that implements the SplittableUniformRandomProvider interface.

Uses of UniformRandomProvider in org.apache.commons.rng.core.util

Methods in org.apache.commons.rng.core.util with parameters of type UniformRandomProvider

Modifier and Type	Method	Description
T	RandomStreams.SeededObjectFactory.create(long seed, UniformRandomProvider source)	Creates the object.

Uses of UniformRandomProvider in org.apache.commons.rng.sampling

Methods in org.apache.commons.rng.sampling with parameters of type UniformRandomProvider

Modifier and Type	Method	Description
S	CompositeSamplers.Builder.build(UniformRandomProvider rng)	Builds the composite sampler.
DiscreteSampler	CompositeSamplers.DiscreteProbabilitySamplerFactory.create(UniformRandomProvider rng, double[] probabilities)	Creates the sampler.
static UnitSphereSampler	UnitSphereSampler.of(UniformRandomProvider rng, int dimension)	Create a unit sphere sampler for the given dimension.
static <T> List<T>	ListSampler.sample(UniformRandomProvider rng, List<T> collection, int k)	Generates a list of size k whose entries are selected randomly, without repetition, from the items in the given collection.
static boolean[]	ArraySampler.shuffle(UniformRandomProvider rng, boolean[] array)	Shuffles the entries of the given array.
static boolean[]	ArraySampler.shuffle(UniformRandomProvider rng, boolean[] array, int from, int to)	Shuffles the entries of the given array in the range [from, to).
static byte[]	ArraySampler.shuffle(UniformRandomProvider rng, byte[] array)	Shuffles the entries of the given array.
static byte[]	ArraySampler.shuffle(UniformRandomProvider rng, byte[] array, int from, int to)	Shuffles the entries of the given array in the range [from, to).
static char[]	ArraySampler.shuffle(UniformRandomProvider rng, char[] array)	Shuffles the entries of the given array.
static char[]	ArraySampler.shuffle(UniformRandomProvider rng, char[] array, int from, int to)	Shuffles the entries of the given array in the range [from, to).
static double[]	ArraySampler.shuffle(UniformRandomProvider rng, double[] array)	Shuffles the entries of the given array.
static double[]	ArraySampler.shuffle(UniformRandomProvider rng, double[] array, int from, int to)	Shuffles the entries of the given array in the range [from, to).
static float[]	ArraySampler.shuffle(UniformRandomProvider rng, float[] array)	Shuffles the entries of the given array.
static float[]	ArraySampler.shuffle(UniformRandomProvider rng, float[] array, int from, int to)	Shuffles the entries of the given array in the range [from, to).
static int[]	ArraySampler.shuffle(UniformRandomProvider rng, int[] array)	Shuffles the entries of the given array.
static int[]	ArraySampler.shuffle(UniformRandomProvider rng, int[] array, int from, int to)	Shuffles the entries of the given array in the range [from, to).
static long[]	ArraySampler.shuffle(UniformRandomProvider rng, long[] array)	Shuffles the entries of the given array.
static long[]	ArraySampler.shuffle(UniformRandomProvider rng, long[] array, int from, int to)	Shuffles the entries of the given array in the range [from, to).
static short[]	ArraySampler.shuffle(UniformRandomProvider rng, short[] array)	Shuffles the entries of the given array.
static short[]	ArraySampler.shuffle(UniformRandomProvider rng, short[] array, int from, int to)	Shuffles the entries of the given array in the range [from, to).
static <T> T[]	ArraySampler.shuffle(UniformRandomProvider rng, T[] array)	Shuffles the entries of the given array.
static <T> T[]	ArraySampler.shuffle(UniformRandomProvider rng, T[] array, int from, int to)	Shuffles the entries of the given array in the range [from, to).
static <T> void	ListSampler.shuffle(UniformRandomProvider rng, List<T> list)	Shuffles the entries of the given array, using the Fisher-Yates algorithm.
static <T> void	ListSampler.shuffle(UniformRandomProvider rng, List<T> list, int start, boolean towardHead)	Shuffles the entries of the given array, using the Fisher-Yates algorithm.
static void	PermutationSampler.shuffle(UniformRandomProvider rng, int[] list)	Shuffles the entries of the given array.
static void	PermutationSampler.shuffle(UniformRandomProvider rng, int[] list, int start, boolean towardHead)	Shuffles the entries of the given array, using the Fisher-Yates algorithm.
CollectionSampler<T>	CollectionSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
CombinationSampler	CombinationSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
DiscreteProbabilityCollectionSampler<T>	DiscreteProbabilityCollectionSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
PermutationSampler	PermutationSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
R	SharedStateSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
UnitSphereSampler	UnitSphereSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.

Constructors in org.apache.commons.rng.sampling with parameters of type UniformRandomProvider

Modifier	Constructor	Description
	CollectionSampler(UniformRandomProvider rng, Collection<T> collection)	Creates a sampler.
	CombinationSampler(UniformRandomProvider rng, int n, int k)	Creates a generator of combinations.
	DiscreteProbabilityCollectionSampler(UniformRandomProvider rng, List<T> collection, double[] probabilities)	Creates a sampler.
	DiscreteProbabilityCollectionSampler(UniformRandomProvider rng, Map<T,Double> collection)	Creates a sampler.
	PermutationSampler(UniformRandomProvider rng, int n, int k)	Creates a generator of permutations.
	UnitSphereSampler(int dimension, UniformRandomProvider rng)	Deprecated. Use UnitSphereSampler.of(UniformRandomProvider, int).

Uses of UniformRandomProvider in org.apache.commons.rng.sampling.distribution

Fields in org.apache.commons.rng.sampling.distribution declared as UniformRandomProvider

Modifier and Type	Field	Description
protected final UniformRandomProvider	AliasMethodDiscreteSampler.rng	Underlying source of randomness.
protected final UniformRandomProvider	ContinuousUniformSampler.rng	Underlying source of randomness.
protected final UniformRandomProvider	UniformLongSampler.rng	Underlying source of randomness.

Methods in org.apache.commons.rng.sampling.distribution with parameters of type UniformRandomProvider

Modifier and Type	Method	Description
DiscreteSampler	PoissonSamplerCache.createPoissonSampler(UniformRandomProvider rng, double mean)	Deprecated. Use PoissonSamplerCache.createSharedStateSampler(UniformRandomProvider, double).
SharedStateDiscreteSampler	PoissonSamplerCache.createSharedStateSampler(UniformRandomProvider rng, double mean)	Creates a new Poisson sampler.
static SharedStateContinuousSampler	AhrensDieterExponentialSampler.of(UniformRandomProvider rng, double mean)	Create a new exponential distribution sampler.
static SharedStateContinuousSampler	AhrensDieterMarsagliaTsangGammaSampler.of(UniformRandomProvider rng, double alpha, double theta)	Creates a new gamma distribution sampler.
static SharedStateDiscreteSampler	AliasMethodDiscreteSampler.of(UniformRandomProvider rng, double[] probabilities)	Creates a sampler.
static SharedStateDiscreteSampler	AliasMethodDiscreteSampler.of(UniformRandomProvider rng, double[] probabilities, int alpha)	Creates a sampler.
static <S extends NormalizedGaussianSampler & SharedStateContinuousSampler> S	BoxMullerNormalizedGaussianSampler.of(UniformRandomProvider rng)	Create a new normalised Gaussian sampler.
static SharedStateContinuousSampler	ChengBetaSampler.of(UniformRandomProvider rng, double alpha, double beta)	Creates a new beta distribution sampler.
static SharedStateContinuousSampler	ContinuousUniformSampler.of(UniformRandomProvider rng, double lo, double hi)	Creates a new continuous uniform distribution sampler.
static SharedStateContinuousSampler	ContinuousUniformSampler.of(UniformRandomProvider rng, double lo, double hi, boolean excludeBounds)	Creates a new continuous uniform distribution sampler.
static DirichletSampler	DirichletSampler.of(UniformRandomProvider rng, double... alpha)	Creates a new Dirichlet distribution sampler.
static SharedStateDiscreteSampler	DiscreteUniformSampler.of(UniformRandomProvider rng, int lower, int upper)	Creates a new discrete uniform distribution sampler.
static FastLoadedDiceRollerDiscreteSampler	FastLoadedDiceRollerDiscreteSampler.of(UniformRandomProvider rng, double[] weights)	Creates a sampler.
static FastLoadedDiceRollerDiscreteSampler	FastLoadedDiceRollerDiscreteSampler.of(UniformRandomProvider rng, double[] weights, int alpha)	Creates a sampler.
static FastLoadedDiceRollerDiscreteSampler	FastLoadedDiceRollerDiscreteSampler.of(UniformRandomProvider rng, long[] frequencies)	Creates a sampler.
static SharedStateDiscreteSampler	GeometricSampler.of(UniformRandomProvider rng, double probabilityOfSuccess)	Creates a new geometric distribution sampler.
static SharedStateDiscreteSampler	GuideTableDiscreteSampler.of(UniformRandomProvider rng, double[] probabilities)	Create a new sampler for an enumerated distribution using the given probabilities.
static SharedStateDiscreteSampler	GuideTableDiscreteSampler.of(UniformRandomProvider rng, double[] probabilities, double alpha)	Create a new sampler for an enumerated distribution using the given probabilities.
static SharedStateContinuousSampler	InverseTransformContinuousSampler.of(UniformRandomProvider rng, ContinuousInverseCumulativeProbabilityFunction function)	Create a new inverse-transform continuous sampler.
static SharedStateDiscreteSampler	InverseTransformDiscreteSampler.of(UniformRandomProvider rng, DiscreteInverseCumulativeProbabilityFunction function)	Create a new inverse-transform discrete sampler.
static SharedStateContinuousSampler	InverseTransformParetoSampler.of(UniformRandomProvider rng, double scale, double shape)	Creates a new Pareto distribution sampler.
static SharedStateDiscreteSampler	KempSmallMeanPoissonSampler.of(UniformRandomProvider rng, double mean)	Creates a new sampler for the Poisson distribution.
static SharedStateDiscreteSampler	LargeMeanPoissonSampler.of(UniformRandomProvider rng, double mean)	Creates a new Poisson distribution sampler.
static LevySampler	LevySampler.of(UniformRandomProvider rng, double location, double scale)	Create a new Lévy distribution sampler.
static <S extends NormalizedGaussianSampler & SharedStateContinuousSampler> S	MarsagliaNormalizedGaussianSampler.of(UniformRandomProvider rng)	Create a new normalised Gaussian sampler.
static SharedStateDiscreteSampler	MarsagliaTsangWangDiscreteSampler.Binomial.of(UniformRandomProvider rng, int trials, double probabilityOfSuccess)	Creates a sampler for the Binomial distribution.
static SharedStateDiscreteSampler	MarsagliaTsangWangDiscreteSampler.Enumerated.of(UniformRandomProvider rng, double[] probabilities)	Creates a sampler for an enumerated distribution of n values each with an associated probability.
static SharedStateDiscreteSampler	MarsagliaTsangWangDiscreteSampler.Poisson.of(UniformRandomProvider rng, double mean)	Creates a sampler for the Poisson distribution.
static SharedStateDiscreteSampler	PoissonSampler.of(UniformRandomProvider rng, double mean)	Creates a new Poisson distribution sampler.
static SharedStateDiscreteSampler	RejectionInversionZipfSampler.of(UniformRandomProvider rng, int numberOfElements, double exponent)	Creates a new Zipf distribution sampler.
static SharedStateDiscreteSampler	SmallMeanPoissonSampler.of(UniformRandomProvider rng, double mean)	Creates a new sampler for the Poisson distribution.
static StableSampler	StableSampler.of(UniformRandomProvider rng, double alpha, double beta)	Creates a standardized sampler of a stable distribution with zero location and unit scale.
static StableSampler	StableSampler.of(UniformRandomProvider rng, double alpha, double beta, double gamma, double delta)	Creates a sampler of a stable distribution.
static TSampler	TSampler.of(UniformRandomProvider rng, double degreesOfFreedom)	Create a new t distribution sampler.
static UniformLongSampler	UniformLongSampler.of(UniformRandomProvider rng, long lower, long upper)	Creates a new discrete uniform distribution sampler.
static <S extends NormalizedGaussianSampler & SharedStateContinuousSampler> S	ZigguratNormalizedGaussianSampler.of(UniformRandomProvider rng)	Create a new normalised Gaussian sampler.
static ZigguratSampler.Exponential	ZigguratSampler.Exponential.of(UniformRandomProvider rng)	Create a new exponential sampler with mean = 1.
static ZigguratSampler.Exponential	ZigguratSampler.Exponential.of(UniformRandomProvider rng, double mean)	Create a new exponential sampler with the specified mean.
static ZigguratSampler.NormalizedGaussian	ZigguratSampler.NormalizedGaussian.of(UniformRandomProvider rng)	Create a new normalised Gaussian sampler.
static DirichletSampler	DirichletSampler.symmetric(UniformRandomProvider rng, int k, double alpha)	Creates a new symmetric Dirichlet distribution sampler using the same concentration parameter for each category.
SharedStateContinuousSampler	AhrensDieterExponentialSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateContinuousSampler	AhrensDieterMarsagliaTsangGammaSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateDiscreteSampler	AliasMethodDiscreteSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateContinuousSampler	BoxMullerNormalizedGaussianSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateContinuousSampler	ChengBetaSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateContinuousSampler	ContinuousUniformSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
abstract DirichletSampler	DirichletSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateDiscreteSampler	DiscreteUniformSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
abstract FastLoadedDiceRollerDiscreteSampler	FastLoadedDiceRollerDiscreteSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateContinuousSampler	GaussianSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateDiscreteSampler	GuideTableDiscreteSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateContinuousSampler	InverseTransformContinuousSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateDiscreteSampler	InverseTransformDiscreteSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateContinuousSampler	InverseTransformParetoSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateDiscreteSampler	KempSmallMeanPoissonSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateDiscreteSampler	LargeMeanPoissonSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
LevySampler	LevySampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateContinuousSampler	LogNormalSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateContinuousSampler	MarsagliaNormalizedGaussianSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateDiscreteSampler	PoissonSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateDiscreteSampler	RejectionInversionZipfSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateDiscreteSampler	SmallMeanPoissonSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
abstract StableSampler	StableSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
abstract TSampler	TSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
abstract UniformLongSampler	UniformLongSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateContinuousSampler	ZigguratNormalizedGaussianSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
ZigguratSampler.Exponential	ZigguratSampler.Exponential.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
ZigguratSampler.NormalizedGaussian	ZigguratSampler.NormalizedGaussian.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.

Constructors in org.apache.commons.rng.sampling.distribution with parameters of type UniformRandomProvider

Modifier	Constructor	Description
	AhrensDieterExponentialSampler(UniformRandomProvider rng, double mean)	Create an instance.
	AhrensDieterMarsagliaTsangGammaSampler(UniformRandomProvider rng, double alpha, double theta)	This instance delegates sampling.
	BoxMullerGaussianSampler(UniformRandomProvider rng, double mean, double standardDeviation)	Deprecated. Create an instance.
	BoxMullerLogNormalSampler(UniformRandomProvider rng, double mu, double sigma)	Deprecated. Create an instance.
	BoxMullerNormalizedGaussianSampler(UniformRandomProvider rng)	Create an instance.
	ChengBetaSampler(UniformRandomProvider rng, double alpha, double beta)	Creates a sampler instance.
	ContinuousUniformSampler(UniformRandomProvider rng, double lo, double hi)	Create an instance.
	DiscreteUniformSampler(UniformRandomProvider rng, int lower, int upper)	This instance delegates sampling.
	InverseTransformContinuousSampler(UniformRandomProvider rng, ContinuousInverseCumulativeProbabilityFunction function)	Create an instance.
	InverseTransformDiscreteSampler(UniformRandomProvider rng, DiscreteInverseCumulativeProbabilityFunction function)	Create an instance.
	InverseTransformParetoSampler(UniformRandomProvider rng, double scale, double shape)	Create an instance.
	LargeMeanPoissonSampler(UniformRandomProvider rng, double mean)	Create an instance.
	MarsagliaNormalizedGaussianSampler(UniformRandomProvider rng)	Create an instance.
	PoissonSampler(UniformRandomProvider rng, double mean)	This instance delegates sampling.
	RejectionInversionZipfSampler(UniformRandomProvider rng, int numberOfElements, double exponent)	This instance delegates sampling.
protected	SamplerBase(UniformRandomProvider rng)	Deprecated. Create an instance.
	SmallMeanPoissonSampler(UniformRandomProvider rng, double mean)	Create an instance.
	ZigguratNormalizedGaussianSampler(UniformRandomProvider rng)	Create an instance.

Uses of UniformRandomProvider in org.apache.commons.rng.sampling.shape

Methods in org.apache.commons.rng.sampling.shape with parameters of type UniformRandomProvider

Modifier and Type	Method	Description
static BoxSampler	BoxSampler.of(UniformRandomProvider rng, double[] a, double[] b)	Create a box sampler with bounds a and b.
static LineSampler	LineSampler.of(UniformRandomProvider rng, double[] a, double[] b)	Create a line sampler with vertices a and b.
static TetrahedronSampler	TetrahedronSampler.of(UniformRandomProvider rng, double[] a, double[] b, double[] c, double[] d)	Create a tetrahedron sampler with vertices a, b, c and d.
static TriangleSampler	TriangleSampler.of(UniformRandomProvider rng, double[] a, double[] b, double[] c)	Create a triangle sampler with vertices a, b and c.
static UnitBallSampler	UnitBallSampler.of(UniformRandomProvider rng, int dimension)	Create a unit n-ball sampler for the given dimension.
abstract BoxSampler	BoxSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
abstract LineSampler	LineSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
TetrahedronSampler	TetrahedronSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
abstract TriangleSampler	TriangleSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
abstract UnitBallSampler	UnitBallSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.

Uses of UniformRandomProvider in org.apache.commons.rng.simple

Classes in org.apache.commons.rng.simple that implement UniformRandomProvider

Modifier and Type	Class	Description
final class	JDKRandomWrapper	Wraps a Random instance to implement UniformRandomProvider.

Methods in org.apache.commons.rng.simple that return UniformRandomProvider

Modifier and Type	Method	Description
static UniformRandomProvider	ThreadLocalRandomSource.current(RandomSource source)	Returns the current thread's copy of the given source.
static UniformRandomProvider	RandomSource.unrestorable(UniformRandomProvider delegate)	Wraps the given delegate generator in a new instance that only provides access to the UniformRandomProvider methods.

Methods in org.apache.commons.rng.simple with parameters of type UniformRandomProvider

Modifier and Type	Method	Description
byte[]	RandomSource.createSeed(UniformRandomProvider rng)	Creates a seed suitable for the implementing class represented by this random source using the supplied source of randomness.
static UniformRandomProvider	RandomSource.unrestorable(UniformRandomProvider delegate)	Wraps the given delegate generator in a new instance that only provides access to the UniformRandomProvider methods.

Uses of UniformRandomProvider in org.apache.commons.rng.simple.internal

Methods in org.apache.commons.rng.simple.internal with parameters of type UniformRandomProvider

Modifier and Type	Method	Description
protected byte[]	ProviderBuilder.RandomSourceInternal.createByteArraySeed(UniformRandomProvider source)	Creates a byte[] seed using the provided source of randomness.
final byte[]	ProviderBuilder.RandomSourceInternal.createSeedBytes(UniformRandomProvider source)	Creates a seed suitable for the implementing class represented by this random source using the supplied source of randomness.