Package org.apache.commons.rng.sampling

Interface SharedStateSampler<R>

Type Parameters:

R - Type of the sampler.

All Known Subinterfaces:

SharedStateContinuousSampler, SharedStateDiscreteSampler, SharedStateLongSampler, SharedStateObjectSampler<T>

All Known Implementing Classes:

AhrensDieterExponentialSampler, AhrensDieterMarsagliaTsangGammaSampler, AliasMethodDiscreteSampler, BoxMullerNormalizedGaussianSampler, BoxSampler, ChengBetaSampler, CollectionSampler, CombinationSampler, ContinuousUniformSampler, DirichletSampler, DiscreteProbabilityCollectionSampler, DiscreteUniformSampler, FastLoadedDiceRollerDiscreteSampler, GaussianSampler, GuideTableDiscreteSampler, InverseTransformContinuousSampler, InverseTransformDiscreteSampler, InverseTransformParetoSampler, KempSmallMeanPoissonSampler, LargeMeanPoissonSampler, LevySampler, LineSampler, LogNormalSampler, MarsagliaNormalizedGaussianSampler, PermutationSampler, PoissonSampler, RejectionInversionZipfSampler, SmallMeanPoissonSampler, StableSampler, TetrahedronSampler, TriangleSampler, TSampler, UniformLongSampler, UnitBallSampler, UnitSphereSampler, ZigguratNormalizedGaussianSampler, ZigguratSampler, ZigguratSampler.Exponential, ZigguratSampler.NormalizedGaussian

Functional Interface:

This is a functional interface and can therefore be used as the assignment target for a lambda expression or method reference.

@FunctionalInterface
public interface SharedStateSampler<R>

Applies to samplers that can share state between instances. Samplers can be created with a new source of randomness that sample from the same state.

Since:

1.3

Method Summary

Modifier and Type	Method	Description
R	withUniformRandomProvider(org.apache.commons.rng.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.

Method Detail

withUniformRandomProvider

R withUniformRandomProvider(org.apache.commons.rng.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.

Parameters:

rng - Generator of uniformly distributed random numbers.

Returns:

the sampler