Uses of Interface
org.apache.commons.rng.UniformRandomProvider
Packages that use UniformRandomProvider
Package
Description
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.
Base classes for the
generation of uniformly distributed random numbers
.Concrete algorithms for
int
-based sources of randomness.Concrete algorithms for
long
-based sources of randomness.This package contains utilities to combine/split primitive types.
This package provides sampling utilities.
This package contains classes for sampling from statistical distributions.
This package contains classes for sampling coordinates from shapes, for example a unit ball.
This package provides
factory methods
by which low-level classes implemented in module "commons-rng-core"
are instantiated.Utilities for seed conversion.
-
Uses of UniformRandomProvider in org.apache.commons.rng
Subinterfaces of UniformRandomProvider in org.apache.commons.rngModifier and TypeInterfaceDescriptioninterface
Applies to generators that can be advanced a large number of steps of the output sequence in a single operation.interface
Applies to generators that can be advanced a very large number of steps of the output sequence in a single operation.interface
Applies to generators whose internal state can be saved and restored.interface
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 UniformRandomProviderModifier and TypeMethodDescriptionJumpableUniformRandomProvider.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 UniformRandomProviderModifier and TypeMethodDescriptiondefault Stream
<UniformRandomProvider> JumpableUniformRandomProvider.jumps()
Returns an effectively unlimited stream of new random generators, each of which implements theUniformRandomProvider
interface.default Stream
<UniformRandomProvider> JumpableUniformRandomProvider.jumps
(long streamSize) Returns a stream producing the givenstreamSize
number of new random generators, each of which implements theUniformRandomProvider
interface.Methods in org.apache.commons.rng with parameters of type UniformRandomProviderModifier and TypeMethodDescription(package private) static void
UniformRandomProviderSupport.nextBytes
(UniformRandomProvider source, byte[] bytes, int start, int len) Generates random bytes and places them into a user-supplied array.(package private) static double
UniformRandomProviderSupport.nextDouble
(UniformRandomProvider source, double bound) Generates adouble
value between 0 (inclusive) and the specified value (exclusive).(package private) static double
UniformRandomProviderSupport.nextDouble
(UniformRandomProvider source, double origin, double bound) Generates adouble
value between the specifiedorigin
(inclusive) and the specifiedbound
(exclusive).(package private) static float
UniformRandomProviderSupport.nextFloat
(UniformRandomProvider source, float bound) Generates afloat
value between 0 (inclusive) and the specified value (exclusive).(package private) static float
UniformRandomProviderSupport.nextFloat
(UniformRandomProvider source, float origin, float bound) Generates afloat
value between the specifiedorigin
(inclusive) and the specifiedbound
(exclusive).(package private) static int
UniformRandomProviderSupport.nextInt
(UniformRandomProvider source, int n) Generates anint
value between 0 (inclusive) and the specified value (exclusive).(package private) static int
UniformRandomProviderSupport.nextInt
(UniformRandomProvider source, int origin, int bound) Generates anint
value between the specifiedorigin
(inclusive) and the specifiedbound
(exclusive).(package private) static long
UniformRandomProviderSupport.nextLong
(UniformRandomProvider source, long n) Generates anlong
value between 0 (inclusive) and the specified value (exclusive).(package private) static long
UniformRandomProviderSupport.nextLong
(UniformRandomProvider source, long origin, long bound) Generates along
value between the specifiedorigin
(inclusive) and the specifiedbound
(exclusive).SplittableUniformRandomProvider.split
(UniformRandomProvider source) Creates a new random generator, split off from this one, that implements theSplittableUniformRandomProvider
interface. -
Uses of UniformRandomProvider in org.apache.commons.rng.core
Classes in org.apache.commons.rng.core that implement UniformRandomProviderModifier and TypeClassDescriptionclass
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 UniformRandomProviderModifier and TypeClassDescription(package private) class
This abstract class is a base for algorithms from the Permuted Congruential Generator (PCG) family that use an internal 64-bit Linear Congruential Generator (LCG) and output 32-bits per cycle.(package private) class
This abstract class is a base for algorithms from the Permuted Congruential Generator (PCG) family that use an internal 64-bit Multiplicative Congruential Generator (MCG) and output 32-bits per cycle.class
This abstract class implements the WELL class of pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.(package private) class
This abstract class is a base for algorithms from the Xor-Shift-Rotate family of 32-bit generators with 64-bits of state.(package private) class
This abstract class is a base for algorithms from the Xor-Shift-Rotate family of 32-bit generators with 128-bits of state.class
Implement the Small, Fast, Counting (SFC) 32-bit generator of Chris Doty-Humphrey.class
Base class for all implementations that provide anint
-based source randomness.class
A fast cryptographic pseudo-random number generator.class
A provider that uses theRandom.nextInt()
method of the JDK'sRandom
class as the source of randomness.class
Implement Bob Jenkins's small fast (JSF) 32-bit generator.class
Port from Marsaglia's "KISS" algorithm.final class
A 32-bit all purpose generator.class
This class implements a powerful pseudo-random number generator developed by Makoto Matsumoto and Takuji Nishimura during 1996-1997.class
Middle Square Weyl Sequence Random Number Generator.class
Port from Marsaglia's "Multiply-With-Carry" algorithm.class
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
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
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
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.class
This class implements the WELL1024a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.class
This class implements the WELL19937a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.class
This class implements the WELL19937c pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.class
This class implements the WELL44497a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.class
This class implements the WELL44497b pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.class
This class implements the WELL512a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.class
A fast 32-bit generator suitable forfloat
generation.class
A fast all-purpose 32-bit generator.class
A fast 32-bit generator suitable forfloat
generation.class
A fast all-purpose 32-bit generator.class
A fast all-purpose 32-bit generator.Methods in org.apache.commons.rng.core.source32 that return UniformRandomProviderModifier and TypeMethodDescriptionAbstractXoShiRo128.jump()
Creates a copy of the UniformRandomProvider and then advances the state of the current instance.L32X64Mix.jump()
Creates a copy of the UniformRandomProvider and then retreats the state of the current instance.Methods in org.apache.commons.rng.core.source32 with parameters of type UniformRandomProviderModifier and TypeMethodDescriptionprivate static SplittableUniformRandomProvider
L32X64Mix.create
(long seed, UniformRandomProvider source) Create a new instance using the givenseed
andsource
of randomness to initialise the instance.L32X64Mix.split
(UniformRandomProvider source) Creates a new random generator, split off from this one, that implements theSplittableUniformRandomProvider
interface. -
Uses of UniformRandomProvider in org.apache.commons.rng.core.source64
Classes in org.apache.commons.rng.core.source64 that implement UniformRandomProviderModifier and TypeClassDescription(package private) class
This abstract class is a base for algorithms from the LXM family of generators with a 128-bit LCG sub-generator.(package private) class
This abstract class is a base for algorithms from the LXM family of generators with a 64-bit LCG sub-generator.(package private) class
This abstract class is a base for algorithms from the LXM family of generators with a 64-bit LCG and 128-bit XBG sub-generator.(package private) class
This abstract class is a base for algorithms from the Xor-Shift-Rotate family of 64-bit generators with 1024-bits of state.(package private) class
This abstract class is a base for algorithms from the Xor-Shift-Rotate family of 64-bit generators with 128-bits of state.(package private) class
This abstract class is a base for algorithms from the Xor-Shift-Rotate family of 64-bit generators with 256-bits of state.(package private) class
This abstract class is a base for algorithms from the Xor-Shift-Rotate family of 64-bit generators with 512-bits of state.class
Implement the Small, Fast, Counting (SFC) 64-bit generator of Chris Doty-Humphrey.class
Implement Bob Jenkins's small fast (JSF) 64-bit generator.class
A 64-bit all purpose generator.class
A 64-bit all purpose generator.class
A 64-bit all purpose generator.class
A 64-bit all purpose generator.class
A 64-bit all purpose generator.class
A 64-bit all purpose generator.class
A 64-bit all purpose generator.class
Base class for all implementations that provide along
-based source randomness.class
This class provides the 64-bits version of the originally 32-bitsMersenne Twister
.class
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.class
A fast RNG, with 64 bits of state, that can be used to initialize the state of other generators.class
Random number generator designed by Mark D. Overton.class
A large-state all-purpose 64-bit generator.class
A large-state 64-bit generator suitable fordouble
generation.class
A large-state all-purpose 64-bit generator.class
A fast 64-bit generator suitable fordouble
generation.class
A fast all-purpose 64-bit generator.class
A fast all-purpose 64-bit generator.class
A fast RNG implementing theXorShift1024*
algorithm.class
A fast RNG implementing theXorShift1024*
algorithm.class
A fast 64-bit generator suitable fordouble
generation.class
A fast all-purpose 64-bit generator.class
A fast all-purpose 64-bit generator.class
A fast 64-bit generator suitable fordouble
generation.class
A fast all-purpose generator.class
A fast all-purpose generator.Methods in org.apache.commons.rng.core.source64 that return UniformRandomProviderModifier and TypeMethodDescriptionAbstractL128.jump()
Creates a copy of the UniformRandomProvider and then retreats the state of the current instance.AbstractL64.jump()
Creates a copy of the UniformRandomProvider and then retreats the state of the current instance.AbstractL64X128.jump()
Creates a copy of the UniformRandomProvider and then retreats the state of the current instance.AbstractXoRoShiRo1024.jump()
Creates a copy of the UniformRandomProvider and then advances the state of the current instance.AbstractXoRoShiRo128.jump()
Creates a copy of the UniformRandomProvider and then advances the state of the current instance.AbstractXoShiRo256.jump()
Creates a copy of the UniformRandomProvider and then advances the state of the current instance.AbstractXoShiRo512.jump()
Creates a copy of the UniformRandomProvider and then advances the state of the current instance.L128X1024Mix.jump()
Creates a copy of the UniformRandomProvider and then retreats the state of the current instance.L128X128Mix.jump()
Creates a copy of the UniformRandomProvider and then retreats the state of the current instance.L128X256Mix.jump()
Creates a copy of the UniformRandomProvider and then retreats the state of the current instance.L64X1024Mix.jump()
Creates a copy of the UniformRandomProvider and then retreats the state of the current instance.L64X256Mix.jump()
Creates a copy of the UniformRandomProvider and then retreats the state of the current instance.XoRoShiRo128PlusPlus.jump()
Creates a copy of the UniformRandomProvider and then advances the state of the current instance.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 UniformRandomProviderModifier and TypeMethodDescriptionprivate static SplittableUniformRandomProvider
L128X1024Mix.create
(long seed, UniformRandomProvider source) Create a new instance using the givenseed
andsource
of randomness to initialise the instance.private static SplittableUniformRandomProvider
L128X128Mix.create
(long seed, UniformRandomProvider source) Create a new instance using the givenseed
andsource
of randomness to initialise the instance.private static SplittableUniformRandomProvider
L128X256Mix.create
(long seed, UniformRandomProvider source) Create a new instance using the givenseed
andsource
of randomness to initialise the instance.private static SplittableUniformRandomProvider
L64X1024Mix.create
(long seed, UniformRandomProvider source) Create a new instance using the givenseed
andsource
of randomness to initialise the instance.private static SplittableUniformRandomProvider
L64X128Mix.create
(long seed, UniformRandomProvider source) Create a new instance using the givenseed
andsource
of randomness to initialise the instance.private static SplittableUniformRandomProvider
L64X128StarStar.create
(long seed, UniformRandomProvider source) Create a new instance using the givenseed
andsource
of randomness to initialise the instance.private static SplittableUniformRandomProvider
L64X256Mix.create
(long seed, UniformRandomProvider source) Create a new instance using the givenseed
andsource
of randomness to initialise the instance.L128X1024Mix.split
(UniformRandomProvider source) Creates a new random generator, split off from this one, that implements theSplittableUniformRandomProvider
interface.L128X128Mix.split
(UniformRandomProvider source) Creates a new random generator, split off from this one, that implements theSplittableUniformRandomProvider
interface.L128X256Mix.split
(UniformRandomProvider source) Creates a new random generator, split off from this one, that implements theSplittableUniformRandomProvider
interface.L64X1024Mix.split
(UniformRandomProvider source) Creates a new random generator, split off from this one, that implements theSplittableUniformRandomProvider
interface.L64X128Mix.split
(UniformRandomProvider source) Creates a new random generator, split off from this one, that implements theSplittableUniformRandomProvider
interface.L64X128StarStar.split
(UniformRandomProvider source) Creates a new random generator, split off from this one, that implements theSplittableUniformRandomProvider
interface.L64X256Mix.split
(UniformRandomProvider source) Creates a new random generator, split off from this one, that implements theSplittableUniformRandomProvider
interface. -
Uses of UniformRandomProvider in org.apache.commons.rng.core.util
Methods in org.apache.commons.rng.core.util with parameters of type UniformRandomProviderModifier and TypeMethodDescriptionRandomStreams.SeededObjectFactory.create
(long seed, UniformRandomProvider source) Creates the object.(package private) static long
RandomStreams.createSeed
(UniformRandomProvider rng) Creates a seed to prepend to a counter. -
Uses of UniformRandomProvider in org.apache.commons.rng.sampling
Fields in org.apache.commons.rng.sampling declared as UniformRandomProviderModifier and TypeFieldDescriptionprivate final UniformRandomProvider
CollectionSampler.rng
RNG.private final UniformRandomProvider
CombinationSampler.rng
RNG.private final UniformRandomProvider
PermutationSampler.rng
RNG.private final UniformRandomProvider
UnitSphereSampler.UnitSphereSampler1D.rng
The source of randomness.Methods in org.apache.commons.rng.sampling with parameters of type UniformRandomProviderModifier and TypeMethodDescriptionCompositeSamplers.Builder.build
(UniformRandomProvider rng) Builds the composite sampler.CompositeSamplers.SamplerBuilder.build
(UniformRandomProvider rng) Builds the composite sampler.private static <T extends SharedStateSampler<T>>
List<T> CompositeSamplers.copy
(List<T> samplers, UniformRandomProvider rng) Create a copy instance of each sampler in the list of samplers using the given uniform random provider as the source of randomness.CompositeSamplers.DiscreteProbabilitySamplerFactory.create
(UniformRandomProvider rng, double[] probabilities) Creates the sampler.private DiscreteSampler
CompositeSamplers.SamplerBuilder.createDiscreteSampler
(UniformRandomProvider rng, double[] weights) Creates the discrete sampler of the enumerated probability distribution.private static SharedStateDiscreteSampler
DiscreteProbabilityCollectionSampler.createSampler
(UniformRandomProvider rng, double[] probabilities) Creates the sampler of the enumerated probability distribution.static UnitSphereSampler
UnitSphereSampler.of
(UniformRandomProvider rng, int dimension) Create a unit sphere sampler for the given dimension.(package private) static int[]
SubsetSamplerUtils.partialSample
(int[] domain, int steps, UniformRandomProvider rng, boolean upper) Perform a partial Fisher-Yates shuffle of the domain in-place and return either the upper fully shuffled section or the remaining lower partially shuffled section.static <T> List
<T> ListSampler.sample
(UniformRandomProvider rng, List<T> collection, int k) Generates a list of sizek
whose entries are selected randomly, without repetition, from the items in the givencollection
.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.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.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.CompositeSamplers.SharedStateContinuousSamplerFactory.CompositeSharedStateContinuousSampler.withUniformRandomProvider
(UniformRandomProvider rng) CompositeSamplers.SharedStateDiscreteProbabilitySampler.withUniformRandomProvider
(UniformRandomProvider rng) CompositeSamplers.SharedStateDiscreteSamplerFactory.CompositeSharedStateDiscreteSampler.withUniformRandomProvider
(UniformRandomProvider rng) CompositeSamplers.SharedStateLongSamplerFactory.CompositeSharedStateLongSampler.withUniformRandomProvider
(UniformRandomProvider rng) CompositeSamplers.SharedStateObjectSamplerFactory.CompositeSharedStateObjectSampler.withUniformRandomProvider
(UniformRandomProvider rng) 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.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.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.UnitSphereSampler1D.withUniformRandomProvider
(UniformRandomProvider rng) UnitSphereSampler.UnitSphereSampler2D.withUniformRandomProvider
(UniformRandomProvider rng) UnitSphereSampler.UnitSphereSampler3D.withUniformRandomProvider
(UniformRandomProvider rng) UnitSphereSampler.UnitSphereSamplerND.withUniformRandomProvider
(UniformRandomProvider rng) 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 UniformRandomProviderModifierConstructorDescriptionCollectionSampler
(UniformRandomProvider rng, Collection<T> collection) Creates a sampler.private
CollectionSampler
(UniformRandomProvider rng, CollectionSampler<T> source) CombinationSampler
(UniformRandomProvider rng, int n, int k) Creates a generator of combinations.private
CombinationSampler
(UniformRandomProvider rng, CombinationSampler source) DiscreteProbabilityCollectionSampler
(UniformRandomProvider rng, List<T> collection, double[] probabilities) Creates a sampler.DiscreteProbabilityCollectionSampler
(UniformRandomProvider rng, Map<T, Double> collection) Creates a sampler.private
DiscreteProbabilityCollectionSampler
(UniformRandomProvider rng, DiscreteProbabilityCollectionSampler<T> source) PermutationSampler
(UniformRandomProvider rng, int n, int k) Creates a generator of permutations.private
PermutationSampler
(UniformRandomProvider rng, PermutationSampler source) UnitSphereSampler
(int dimension, UniformRandomProvider rng) Deprecated.(package private)
(package private)
(package private)
(package private)
UnitSphereSamplerND
(UniformRandomProvider rng, int dimension) -
Uses of UniformRandomProvider in org.apache.commons.rng.sampling.distribution
Fields in org.apache.commons.rng.sampling.distribution declared as UniformRandomProviderModifier and TypeFieldDescriptionprivate final UniformRandomProvider
AhrensDieterExponentialSampler.rng
Underlying source of randomness.protected final UniformRandomProvider
AhrensDieterMarsagliaTsangGammaSampler.BaseGammaSampler.rng
Underlying source of randomness.protected final UniformRandomProvider
AliasMethodDiscreteSampler.rng
Underlying source of randomness.private final UniformRandomProvider
BoxMullerGaussianSampler.rng
Deprecated.Underlying source of randomness.private final UniformRandomProvider
BoxMullerNormalizedGaussianSampler.rng
Underlying source of randomness.protected final UniformRandomProvider
ChengBetaSampler.BaseChengBetaSampler.rng
Underlying source of randomness.private final UniformRandomProvider
ContinuousUniformSampler.rng
Underlying source of randomness.private final UniformRandomProvider
DirichletSampler.rng
RNG (used for the toString() method).protected final UniformRandomProvider
DiscreteUniformSampler.AbstractDiscreteUniformSampler.rng
Underlying source of randomness.private final UniformRandomProvider
FastLoadedDiceRollerDiscreteSampler.FLDRSampler.rng
Underlying source of randomness.private final UniformRandomProvider
GeometricSampler.GeometricExponentialSampler.rng
Underlying source of randomness.private final UniformRandomProvider
GuideTableDiscreteSampler.rng
Underlying source of randomness.private final UniformRandomProvider
InverseTransformContinuousSampler.rng
Underlying source of randomness.private final UniformRandomProvider
InverseTransformDiscreteSampler.rng
Underlying source of randomness.private final UniformRandomProvider
InverseTransformParetoSampler.rng
Underlying source of randomness.private final UniformRandomProvider
KempSmallMeanPoissonSampler.rng
Underlying source of randomness.private final UniformRandomProvider
LargeMeanPoissonSampler.rng
Underlying source of randomness.private final UniformRandomProvider
LevySampler.rng
RNG (used for the toString() method).private final UniformRandomProvider
MarsagliaNormalizedGaussianSampler.rng
Underlying source of randomness.protected final UniformRandomProvider
MarsagliaTsangWangDiscreteSampler.AbstractMarsagliaTsangWangDiscreteSampler.rng
Underlying source of randomness.private final UniformRandomProvider
RejectionInversionZipfSampler.RejectionInversionZipfSamplerImpl.rng
Underlying source of randomness.private final UniformRandomProvider
SamplerBase.rng
Deprecated.RNG.private final UniformRandomProvider
SmallMeanPoissonSampler.rng
Underlying source of randomness.private final UniformRandomProvider
StableSampler.rng
Underlying source of randomness.private final UniformRandomProvider
TSampler.rng
Source of randomness.protected final UniformRandomProvider
UniformLongSampler.rng
Underlying source of randomness.private final UniformRandomProvider
ZigguratNormalizedGaussianSampler.rng
Underlying source of randomness.private final UniformRandomProvider
ZigguratSampler.rng
Underlying source of randomness.Methods in org.apache.commons.rng.sampling.distribution with parameters of type UniformRandomProviderModifier and TypeMethodDescriptionprivate static StableSampler
StableSampler.create
(UniformRandomProvider rng, double alpha, double beta) Creates a standardized sampler of a stable distribution with zero location and unit scale.private static SharedStateDiscreteSampler
MarsagliaTsangWangDiscreteSampler.Binomial.createBinomialDistributionSampler
(UniformRandomProvider rng, int trials, double probabilityOfSuccess) Creates the Binomial distribution sampler.private static SharedStateDiscreteSampler
MarsagliaTsangWangDiscreteSampler.Binomial.createBinomialDistributionSamplerFromRange
(UniformRandomProvider rng, int trials, double p, boolean useInversion, double p0, int begin, int end) Creates the Binomial distribution sampler using only the probability values forX
between the begin and the end (inclusive).private static SharedStateDiscreteSampler
MarsagliaTsangWangDiscreteSampler.Poisson.createPoissonDistributionFromX0
(UniformRandomProvider rng, double mean) Creates the Poisson distribution by computing probabilities recursively fromX=0
.private static SharedStateDiscreteSampler
MarsagliaTsangWangDiscreteSampler.Poisson.createPoissonDistributionFromXMode
(UniformRandomProvider rng, double mean) Creates the Poisson distribution by computing probabilities recursively upward and downward fromX=mode
, the location of the largest p-value.PoissonSamplerCache.createPoissonSampler
(UniformRandomProvider rng, double mean) private static SharedStateContinuousSampler
DirichletSampler.createSampler
(UniformRandomProvider rng, double alpha) Creates a gamma sampler for a category with the given concentration parameter.private static FastLoadedDiceRollerDiscreteSampler
FastLoadedDiceRollerDiscreteSampler.createSampler
(UniformRandomProvider rng, long[] frequencies, int[] offsets, int[] indices, BigInteger m) Creates the sampler.private static FastLoadedDiceRollerDiscreteSampler
FastLoadedDiceRollerDiscreteSampler.createSampler
(UniformRandomProvider rng, long[] frequencies, int[] indices, long m) Creates the sampler.private static SharedStateDiscreteSampler
MarsagliaTsangWangDiscreteSampler.createSampler
(UniformRandomProvider rng, String distributionName, int[] prob, int offset) Create a new instance for probabilitiesp(i)
where the sample valuex
isi + offset
.PoissonSamplerCache.createSharedStateSampler
(UniformRandomProvider rng, double mean) Creates a new Poisson sampler.private static DiscreteUniformSampler.AbstractDiscreteUniformSampler
DiscreteUniformSampler.createZeroBoundedSampler
(UniformRandomProvider rng, int upper) Create a new sampler for the range0
inclusive toupper
inclusive.private static UniformLongSampler
UniformLongSampler.createZeroBoundedSampler
(UniformRandomProvider rng, long upper) Create a new sampler for the range0
inclusive toupper
inclusive.(package private) static NormalizedGaussianSampler
InternalUtils.newNormalizedGaussianSampler
(NormalizedGaussianSampler sampler, UniformRandomProvider rng) Create a new instance of the given sampler usingSharedStateSampler.withUniformRandomProvider(UniformRandomProvider)
.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>
SBoxMullerNormalizedGaussianSampler.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.FastLoadedDiceRollerDiscreteSampler.of
(UniformRandomProvider rng, double[] weights) Creates a sampler.FastLoadedDiceRollerDiscreteSampler.of
(UniformRandomProvider rng, double[] weights, int alpha) Creates a sampler.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 givenprobabilities
.static SharedStateDiscreteSampler
GuideTableDiscreteSampler.of
(UniformRandomProvider rng, double[] probabilities, double alpha) Create a new sampler for an enumerated distribution using the givenprobabilities
.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>
SMarsagliaNormalizedGaussianSampler.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 ofn
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>
SZigguratNormalizedGaussianSampler.of
(UniformRandomProvider rng) Create a new normalised Gaussian sampler.static ZigguratSampler.Exponential
ZigguratSampler.Exponential.of
(UniformRandomProvider rng) Create a new exponential sampler withmean = 1
.static ZigguratSampler.Exponential
ZigguratSampler.Exponential.of
(UniformRandomProvider rng, double mean) Create a new exponential sampler with the specifiedmean
.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.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.AhrensDieterMarsagliaTsangGammaSampler.AhrensDieterGammaSampler.withUniformRandomProvider
(UniformRandomProvider rng) AhrensDieterMarsagliaTsangGammaSampler.MarsagliaTsangGammaSampler.withUniformRandomProvider
(UniformRandomProvider rng) 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.AliasMethodDiscreteSampler.SmallTableAliasMethodDiscreteSampler.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.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.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.ChengBetaSampler.ChengBBBetaSampler.withUniformRandomProvider
(UniformRandomProvider rng) ChengBetaSampler.ChengBCBetaSampler.withUniformRandomProvider
(UniformRandomProvider rng) 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.ContinuousUniformSampler.OpenIntervalContinuousUniformSampler.withUniformRandomProvider
(UniformRandomProvider rng) 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.DirichletSampler.GeneralDirichletSampler.withUniformRandomProvider
(UniformRandomProvider rng) DirichletSampler.SymmetricDirichletSampler.withUniformRandomProvider
(UniformRandomProvider rng) 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.DiscreteUniformSampler.FixedDiscreteUniformSampler.withUniformRandomProvider
(UniformRandomProvider rng) DiscreteUniformSampler.LargeRangeDiscreteUniformSampler.withUniformRandomProvider
(UniformRandomProvider rng) DiscreteUniformSampler.OffsetDiscreteUniformSampler.withUniformRandomProvider
(UniformRandomProvider rng) DiscreteUniformSampler.PowerOf2RangeDiscreteUniformSampler.withUniformRandomProvider
(UniformRandomProvider rng) DiscreteUniformSampler.SmallRangeDiscreteUniformSampler.withUniformRandomProvider
(UniformRandomProvider rng) 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.FastLoadedDiceRollerDiscreteSampler.FixedValueDiscreteSampler.withUniformRandomProvider
(UniformRandomProvider rng) FastLoadedDiceRollerDiscreteSampler.FLDRSampler.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.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.GeometricSampler.GeometricExponentialSampler.withUniformRandomProvider
(UniformRandomProvider rng) GeometricSampler.GeometricP1Sampler.withUniformRandomProvider
(UniformRandomProvider rng) 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.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.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.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.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.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.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.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.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.MarsagliaTsangWangDiscreteSampler.Binomial.MarsagliaTsangWangFixedResultBinomialSampler.withUniformRandomProvider
(UniformRandomProvider rng) MarsagliaTsangWangDiscreteSampler.Binomial.MarsagliaTsangWangInversionBinomialSampler.withUniformRandomProvider
(UniformRandomProvider rng) MarsagliaTsangWangDiscreteSampler.MarsagliaTsangWangBase64Int16DiscreteSampler.withUniformRandomProvider
(UniformRandomProvider rng) MarsagliaTsangWangDiscreteSampler.MarsagliaTsangWangBase64Int32DiscreteSampler.withUniformRandomProvider
(UniformRandomProvider rng) MarsagliaTsangWangDiscreteSampler.MarsagliaTsangWangBase64Int8DiscreteSampler.withUniformRandomProvider
(UniformRandomProvider rng) 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.RejectionInversionZipfSampler.RejectionInversionZipfSamplerImpl.withUniformRandomProvider
(UniformRandomProvider rng) 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.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.StableSampler.Alpha1CMSStableSampler.withUniformRandomProvider
(UniformRandomProvider rng) StableSampler.Beta0CMSStableSampler.withUniformRandomProvider
(UniformRandomProvider rng) StableSampler.Beta0WeronStableSampler.withUniformRandomProvider
(UniformRandomProvider rng) StableSampler.CauchyStableSampler.withUniformRandomProvider
(UniformRandomProvider rng) StableSampler.CMSStableSampler.withUniformRandomProvider
(UniformRandomProvider rng) StableSampler.GaussianStableSampler.withUniformRandomProvider
(UniformRandomProvider rng) StableSampler.LevyStableSampler.withUniformRandomProvider
(UniformRandomProvider rng) StableSampler.TransformedStableSampler.withUniformRandomProvider
(UniformRandomProvider rng) StableSampler.WeronStableSampler.withUniformRandomProvider
(UniformRandomProvider rng) 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.TSampler.NormalTSampler.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.TSampler.StudentsTSampler.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.UniformLongSampler.FixedUniformLongSampler.withUniformRandomProvider
(UniformRandomProvider rng) UniformLongSampler.LargeRangeUniformLongSampler.withUniformRandomProvider
(UniformRandomProvider rng) UniformLongSampler.OffsetUniformLongSampler.withUniformRandomProvider
(UniformRandomProvider rng) UniformLongSampler.PowerOf2RangeUniformLongSampler.withUniformRandomProvider
(UniformRandomProvider rng) UniformLongSampler.SmallRangeUniformLongSampler.withUniformRandomProvider
(UniformRandomProvider rng) 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.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.ExponentialMean.withUniformRandomProvider
(UniformRandomProvider rng) 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.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 UniformRandomProviderModifierConstructorDescription(package private)
(package private)
AbstractMarsagliaTsangWangDiscreteSampler
(UniformRandomProvider rng, String distributionName) (package private)
AbstractMarsagliaTsangWangDiscreteSampler
(UniformRandomProvider rng, MarsagliaTsangWangDiscreteSampler.AbstractMarsagliaTsangWangDiscreteSampler source) AhrensDieterExponentialSampler
(UniformRandomProvider rng, double mean) private
(package private)
AhrensDieterGammaSampler
(UniformRandomProvider rng, double alpha, double theta) (package private)
AhrensDieterGammaSampler
(UniformRandomProvider rng, AhrensDieterMarsagliaTsangGammaSampler.AhrensDieterGammaSampler source) AhrensDieterMarsagliaTsangGammaSampler
(UniformRandomProvider rng, double alpha, double theta) This instance delegates sampling.private
AliasMethodDiscreteSampler
(UniformRandomProvider rng, long[] probability, int[] alias) Creates a sampler.(package private)
Alpha1CMSStableSampler
(UniformRandomProvider rng, double beta) (package private)
(package private)
BaseChengBetaSampler
(UniformRandomProvider rng, boolean aIsAlphaShape, double a, double b) private
(package private)
BaseGammaSampler
(UniformRandomProvider rng, double alpha, double theta) (package private)
BaseGammaSampler
(UniformRandomProvider rng, AhrensDieterMarsagliaTsangGammaSampler.BaseGammaSampler source) (package private)
(package private)
Beta0CMSStableSampler
(UniformRandomProvider rng, double alpha) (package private)
(package private)
Beta0WeronStableSampler
(UniformRandomProvider rng, double alpha) (package private)
BoxMullerGaussianSampler
(UniformRandomProvider rng, double mean, double standardDeviation) Deprecated.BoxMullerLogNormalSampler
(UniformRandomProvider rng, double mu, double sigma) Deprecated.(package private)
CauchyStableSampler
(UniformRandomProvider rng, double gamma, double delta) (package private)
(package private)
ChengBBBetaSampler
(UniformRandomProvider rng, boolean aIsAlphaShape, double a, double b) private
(package private)
ChengBCBetaSampler
(UniformRandomProvider rng, boolean aIsAlphaShape, double a, double b) private
ChengBetaSampler
(UniformRandomProvider rng, double alpha, double beta) Creates a sampler instance.(package private)
CMSStableSampler
(UniformRandomProvider rng, double alpha, double beta) (package private)
ContinuousUniformSampler
(UniformRandomProvider rng, double lo, double hi) private
DiscreteUniformSampler
(UniformRandomProvider rng, int lower, int upper) This instance delegates sampling.private
(package private)
ExponentialMean
(UniformRandomProvider rng, double mean) (package private)
FLDRSampler
(UniformRandomProvider rng, int n, int k, int[] h, int[] lH) Creates a sampler.private
Creates a copy with a new source of randomness.private
GaussianSampler
(UniformRandomProvider rng, GaussianSampler source) (package private)
GaussianStableSampler
(UniformRandomProvider rng, double gamma, double delta) (package private)
(package private)
GeneralDirichletSampler
(UniformRandomProvider rng, SharedStateContinuousSampler[] samplers) (package private)
GeometricExponentialSampler
(UniformRandomProvider rng, double probabilityOfSuccess) (package private)
GeometricExponentialSampler
(UniformRandomProvider rng, GeometricSampler.GeometricExponentialSampler source) private
GuideTableDiscreteSampler
(UniformRandomProvider rng, double[] cumulativeProbabilities, int[] guideTable) InverseTransformContinuousSampler
(UniformRandomProvider rng, ContinuousInverseCumulativeProbabilityFunction function) InverseTransformDiscreteSampler
(UniformRandomProvider rng, DiscreteInverseCumulativeProbabilityFunction function) InverseTransformParetoSampler
(UniformRandomProvider rng, double scale, double shape) private
private
KempSmallMeanPoissonSampler
(UniformRandomProvider rng, double p0, double mean) LargeMeanPoissonSampler
(UniformRandomProvider rng, double mean) private
(package private)
LargeMeanPoissonSampler
(UniformRandomProvider rng, LargeMeanPoissonSampler.LargeMeanPoissonSamplerState state, double lambdaFractional) Instantiates a sampler using a precomputed state.(package private)
LargeRangeDiscreteUniformSampler
(UniformRandomProvider rng, int lower, int upper) (package private)
LargeRangeUniformLongSampler
(UniformRandomProvider rng, long lower, long upper) private
LevySampler
(UniformRandomProvider rng, double location, double scale) private
LevySampler
(UniformRandomProvider rng, LevySampler source) (package private)
LevyStableSampler
(UniformRandomProvider rng, double gamma, double delta) (package private)
private
LogNormalSampler
(UniformRandomProvider rng, LogNormalSampler source) (package private)
MarsagliaTsangGammaSampler
(UniformRandomProvider rng, double alpha, double theta) (package private)
MarsagliaTsangGammaSampler
(UniformRandomProvider rng, AhrensDieterMarsagliaTsangGammaSampler.MarsagliaTsangGammaSampler source) (package private)
MarsagliaTsangWangBase64Int16DiscreteSampler
(UniformRandomProvider rng, String distributionName, int[] prob, int offset) private
MarsagliaTsangWangBase64Int16DiscreteSampler
(UniformRandomProvider rng, MarsagliaTsangWangDiscreteSampler.MarsagliaTsangWangBase64Int16DiscreteSampler source) (package private)
MarsagliaTsangWangBase64Int32DiscreteSampler
(UniformRandomProvider rng, String distributionName, int[] prob, int offset) private
MarsagliaTsangWangBase64Int32DiscreteSampler
(UniformRandomProvider rng, MarsagliaTsangWangDiscreteSampler.MarsagliaTsangWangBase64Int32DiscreteSampler source) (package private)
MarsagliaTsangWangBase64Int8DiscreteSampler
(UniformRandomProvider rng, String distributionName, int[] prob, int offset) private
MarsagliaTsangWangBase64Int8DiscreteSampler
(UniformRandomProvider rng, MarsagliaTsangWangDiscreteSampler.MarsagliaTsangWangBase64Int8DiscreteSampler source) private
(package private)
(package private)
OpenIntervalContinuousUniformSampler
(UniformRandomProvider rng, double lo, double hi) PoissonSampler
(UniformRandomProvider rng, double mean) This instance delegates sampling.(package private)
PowerOf2RangeDiscreteUniformSampler
(UniformRandomProvider rng, int range) (package private)
PowerOf2RangeDiscreteUniformSampler
(UniformRandomProvider rng, DiscreteUniformSampler.PowerOf2RangeDiscreteUniformSampler source) (package private)
PowerOf2RangeUniformLongSampler
(UniformRandomProvider rng, long range) (package private)
PowerOf2RangeUniformLongSampler
(UniformRandomProvider rng, UniformLongSampler.PowerOf2RangeUniformLongSampler source) RejectionInversionZipfSampler
(UniformRandomProvider rng, int numberOfElements, double exponent) This instance delegates sampling.(package private)
RejectionInversionZipfSamplerImpl
(UniformRandomProvider rng, int numberOfElements, double exponent) private
RejectionInversionZipfSamplerImpl
(UniformRandomProvider rng, RejectionInversionZipfSampler.RejectionInversionZipfSamplerImpl source) protected
Deprecated.SmallMeanPoissonSampler
(UniformRandomProvider rng, double mean) private
(package private)
SmallRangeDiscreteUniformSampler
(UniformRandomProvider rng, int range) (package private)
SmallRangeDiscreteUniformSampler
(UniformRandomProvider rng, DiscreteUniformSampler.SmallRangeDiscreteUniformSampler source) (package private)
SmallRangeUniformLongSampler
(UniformRandomProvider rng, long range) (package private)
SmallRangeUniformLongSampler
(UniformRandomProvider rng, UniformLongSampler.SmallRangeUniformLongSampler source) (package private)
SmallTableAliasMethodDiscreteSampler
(UniformRandomProvider rng, long[] probability, int[] alias) Create a new instance.(package private)
(package private)
StudentsTSampler
(UniformRandomProvider rng, double v) private
(package private)
SymmetricDirichletSampler
(UniformRandomProvider rng, int k, SharedStateContinuousSampler sampler) (package private)
(package private)
(package private)
WeronStableSampler
(UniformRandomProvider rng, double alpha, double beta) (package private)
(package private)
-
Uses of UniformRandomProvider in org.apache.commons.rng.sampling.shape
Fields in org.apache.commons.rng.sampling.shape declared as UniformRandomProviderModifier and TypeFieldDescriptionprivate final UniformRandomProvider
BoxSampler.rng
The source of randomness.private final UniformRandomProvider
LineSampler.rng
The source of randomness.private final UniformRandomProvider
TetrahedronSampler.rng
The source of randomness.private final UniformRandomProvider
TriangleSampler.rng
The source of randomness.private final UniformRandomProvider
UnitBallSampler.UnitBallSampler1D.rng
The source of randomness.private final UniformRandomProvider
UnitBallSampler.UnitBallSampler2D.rng
The source of randomness.Methods in org.apache.commons.rng.sampling.shape with parameters of type UniformRandomProviderModifier and TypeMethodDescriptionstatic BoxSampler
BoxSampler.of
(UniformRandomProvider rng, double[] a, double[] b) Create a box sampler with boundsa
andb
.static LineSampler
LineSampler.of
(UniformRandomProvider rng, double[] a, double[] b) Create a line sampler with verticesa
andb
.static TetrahedronSampler
TetrahedronSampler.of
(UniformRandomProvider rng, double[] a, double[] b, double[] c, double[] d) Create a tetrahedron sampler with verticesa
,b
,c
andd
.static TriangleSampler
TriangleSampler.of
(UniformRandomProvider rng, double[] a, double[] b, double[] c) Create a triangle sampler with verticesa
,b
andc
.static UnitBallSampler
UnitBallSampler.of
(UniformRandomProvider rng, int dimension) Create a unit n-ball sampler for the given dimension.BoxSampler.BoxSampler2D.withUniformRandomProvider
(UniformRandomProvider rng) BoxSampler.BoxSampler3D.withUniformRandomProvider
(UniformRandomProvider rng) BoxSampler.BoxSamplerND.withUniformRandomProvider
(UniformRandomProvider rng) 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.LineSampler.LineSampler1D.withUniformRandomProvider
(UniformRandomProvider rng) LineSampler.LineSampler2D.withUniformRandomProvider
(UniformRandomProvider rng) LineSampler.LineSampler3D.withUniformRandomProvider
(UniformRandomProvider rng) LineSampler.LineSamplerND.withUniformRandomProvider
(UniformRandomProvider rng) 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.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.TriangleSampler.TriangleSampler2D.withUniformRandomProvider
(UniformRandomProvider rng) TriangleSampler.TriangleSampler3D.withUniformRandomProvider
(UniformRandomProvider rng) TriangleSampler.TriangleSamplerND.withUniformRandomProvider
(UniformRandomProvider rng) 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.UnitBallSampler.UnitBallSampler1D.withUniformRandomProvider
(UniformRandomProvider rng) UnitBallSampler.UnitBallSampler2D.withUniformRandomProvider
(UniformRandomProvider rng) UnitBallSampler.UnitBallSampler3D.withUniformRandomProvider
(UniformRandomProvider rng) UnitBallSampler.UnitBallSamplerND.withUniformRandomProvider
(UniformRandomProvider rng) 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.Constructors in org.apache.commons.rng.sampling.shape with parameters of type UniformRandomProviderModifierConstructorDescription(package private)
(package private)
BoxSampler2D
(UniformRandomProvider rng, double[] a, double[] b) (package private)
BoxSampler2D
(UniformRandomProvider rng, BoxSampler.BoxSampler2D source) (package private)
BoxSampler3D
(UniformRandomProvider rng, double[] a, double[] b) (package private)
BoxSampler3D
(UniformRandomProvider rng, BoxSampler.BoxSampler3D source) (package private)
BoxSamplerND
(UniformRandomProvider rng, double[] a, double[] b) (package private)
BoxSamplerND
(UniformRandomProvider rng, BoxSampler.BoxSamplerND source) (package private)
(package private)
LineSampler1D
(UniformRandomProvider rng, double[] a, double[] b) (package private)
LineSampler1D
(UniformRandomProvider rng, LineSampler.LineSampler1D source) (package private)
LineSampler2D
(UniformRandomProvider rng, double[] a, double[] b) (package private)
LineSampler2D
(UniformRandomProvider rng, LineSampler.LineSampler2D source) (package private)
LineSampler3D
(UniformRandomProvider rng, double[] a, double[] b) (package private)
LineSampler3D
(UniformRandomProvider rng, LineSampler.LineSampler3D source) (package private)
LineSamplerND
(UniformRandomProvider rng, double[] a, double[] b) (package private)
LineSamplerND
(UniformRandomProvider rng, LineSampler.LineSamplerND source) (package private)
TetrahedronSampler
(UniformRandomProvider rng, double[] a, double[] b, double[] c, double[] d) (package private)
TetrahedronSampler
(UniformRandomProvider rng, TetrahedronSampler source) (package private)
(package private)
TriangleSampler2D
(UniformRandomProvider rng, double[] a, double[] b, double[] c) (package private)
(package private)
TriangleSampler3D
(UniformRandomProvider rng, double[] a, double[] b, double[] c) (package private)
(package private)
TriangleSamplerND
(UniformRandomProvider rng, double[] a, double[] b, double[] c) (package private)
(package private)
(package private)
(package private)
(package private)
UnitBallSamplerND
(UniformRandomProvider rng, int dimension) -
Uses of UniformRandomProvider in org.apache.commons.rng.simple
Classes in org.apache.commons.rng.simple that implement UniformRandomProviderModifier and TypeClassDescriptionfinal class
Wraps aRandom
instance to implementUniformRandomProvider
.Fields in org.apache.commons.rng.simple with type parameters of type UniformRandomProviderModifier and TypeFieldDescriptionprivate static final EnumMap
<RandomSource, ThreadLocal<UniformRandomProvider>> ThreadLocalRandomSource.SOURCES
A map containing theThreadLocal
instance for eachRandomSource
.Methods in org.apache.commons.rng.simple that return UniformRandomProviderModifier and TypeMethodDescriptionstatic UniformRandomProvider
ThreadLocalRandomSource.current
(RandomSource source) Returns the current thread's copy of the givensource
.protected UniformRandomProvider
ThreadLocalRandomSource.ThreadLocalRng.initialValue()
static UniformRandomProvider
RandomSource.unrestorable
(UniformRandomProvider delegate) Wraps the givendelegate
generator in a new instance that only provides access to theUniformRandomProvider
methods.Methods in org.apache.commons.rng.simple with parameters of type UniformRandomProviderModifier and TypeMethodDescriptionbyte[]
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 givendelegate
generator in a new instance that only provides access to theUniformRandomProvider
methods. -
Uses of UniformRandomProvider in org.apache.commons.rng.simple.internal
Fields in org.apache.commons.rng.simple.internal declared as UniformRandomProviderModifier and TypeFieldDescriptionprivate final UniformRandomProvider
SeedUtils.UnsignedByteProvider.rng
Source of randomness.private static final UniformRandomProvider
SeedFactory.SEED_GENERATOR
Generator with a long period.Fields in org.apache.commons.rng.simple.internal with type parameters of type UniformRandomProviderModifier and TypeFieldDescriptionprivate final Class
<? extends UniformRandomProvider> ProviderBuilder.RandomSourceInternal.rng
Source type.Methods in org.apache.commons.rng.simple.internal with parameters of type UniformRandomProviderModifier and TypeMethodDescription(package private) static byte[]
SeedFactory.createByteArray
(UniformRandomProvider source, int n, int from, int to) Creates an array ofbyte
numbers for use as a seed using the supplied source of randomness.protected byte[]
ProviderBuilder.RandomSourceInternal.createByteArraySeed
(UniformRandomProvider source) Creates abyte[]
seed using the provided source of randomness.(package private) static int
SeedUtils.createIntHexPermutation
(UniformRandomProvider rng) Creates anint
containing a permutation of 8 hex digits chosen from 16.(package private) static long
SeedUtils.createLongHexPermutation
(UniformRandomProvider rng) Creates along
containing a permutation of 8 hex digits chosen from 16 in the upper and lower 32-bits.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.(package private) static void
SeedFactory.ensureNonZero
(byte[] seed, int from, int to, UniformRandomProvider source) Ensure the seed is not all-zero within the specified sub-range.Constructors in org.apache.commons.rng.simple.internal with parameters of type UniformRandomProviderConstructor parameters in org.apache.commons.rng.simple.internal with type arguments of type UniformRandomProviderModifierConstructorDescriptionprivate
RandomSourceInternal
(Class<? extends UniformRandomProvider> rng, int nativeSeedSize, int notAllZeroFrom, int notAllZeroTo, NativeSeedType nativeSeedType, Class<?>... args) Create a new instance.private
RandomSourceInternal
(Class<? extends UniformRandomProvider> rng, int nativeSeedSize, NativeSeedType nativeSeedType, Class<?>... args) Create a new instance.
UnitSphereSampler.of(UniformRandomProvider, int)
.