public final class GuideTableDiscreteSampler extends Object implements SharedStateDiscreteSampler
n values each with an associated probability. If all unique items
are assigned the same probability it is more efficient to use the DiscreteUniformSampler.
The cumulative probability distribution is searched using a guide table to set an initial start point. This implementation is based on:
Devroye, Luc (1986). Non-Uniform Random Variate Generation. New York: Springer-Verlag. Chapter 3.2.4 "The method of guide tables" p. 96.
The size of the guide table can be controlled using a parameter. A larger guide table will improve performance at the cost of storage space.
Sampling uses UniformRandomProvider.nextDouble().
| Modifier and Type | Method and Description |
|---|---|
static SharedStateDiscreteSampler |
of(UniformRandomProvider rng,
double[] probabilities)
Create a new sampler for an enumerated distribution using the given
probabilities. |
static SharedStateDiscreteSampler |
of(UniformRandomProvider rng,
double[] probabilities,
double alpha)
Create a new sampler for an enumerated distribution using the given
probabilities. |
int |
sample()
Creates an
int sample. |
String |
toString() |
SharedStateDiscreteSampler |
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.
|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitsamples, samplespublic int sample()
int sample.sample in interface DiscreteSamplerpublic SharedStateDiscreteSampler withUniformRandomProvider(UniformRandomProvider rng)
withUniformRandomProvider in interface SharedStateSampler<SharedStateDiscreteSampler>rng - Generator of uniformly distributed random numbers.public static SharedStateDiscreteSampler of(UniformRandomProvider rng, double[] probabilities)
probabilities.
The samples corresponding to each probability are assumed to be a natural sequence
starting at zero.
The size of the guide table is probabilities.length.
rng - Generator of uniformly distributed random numbers.probabilities - The probabilities.IllegalArgumentException - if probabilities is null or empty, a
probability is negative, infinite or NaN, or the sum of all
probabilities is not strictly positive.public static SharedStateDiscreteSampler of(UniformRandomProvider rng, double[] probabilities, double alpha)
probabilities.
The samples corresponding to each probability are assumed to be a natural sequence
starting at zero.
The size of the guide table is alpha * probabilities.length.
rng - Generator of uniformly distributed random numbers.probabilities - The probabilities.alpha - The alpha factor used to set the guide table size.IllegalArgumentException - if probabilities is null or empty, a
probability is negative, infinite or NaN, the sum of all
probabilities is not strictly positive, or alpha is not strictly positive.Copyright © 2016–2022 The Apache Software Foundation. All rights reserved.