## Class GuideTableDiscreteSampler

• java.lang.Object
• org.apache.commons.rng.sampling.distribution.GuideTableDiscreteSampler
• All Implemented Interfaces:
DiscreteSampler, SharedStateDiscreteSampler, SharedStateSampler<SharedStateDiscreteSampler>

public final class GuideTableDiscreteSampler
extends Object
implements SharedStateDiscreteSampler
Compute a sample from 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().

Since:
1.3
See Also:
Discrete probability distribution (Wikipedia)
• ### Method Summary

All Methods
Modifier and Type Method 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 a 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.
• ### Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
• ### Method Detail

• #### sample

public int sample()
Creates a sample.
Specified by:
sample in interface DiscreteSampler
Returns:
a sample.
• #### toString

public String toString()
Overrides:
toString in class Object
• #### withUniformRandomProvider

public 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.
Specified by:
withUniformRandomProvider in interface SharedStateSampler<SharedStateDiscreteSampler>
Parameters:
rng - Generator of uniformly distributed random numbers.
Returns:
the sampler
• #### of

public static SharedStateDiscreteSampler of​(UniformRandomProvider rng,
double[] probabilities)
Create a new sampler for an enumerated distribution using the given 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.

Parameters:
rng - Generator of uniformly distributed random numbers.
probabilities - The probabilities.
Returns:
the sampler
Throws:
IllegalArgumentException - if probabilities is null or empty, a probability is negative, infinite or NaN, or the sum of all probabilities is not strictly positive.
• #### of

public static SharedStateDiscreteSampler of​(UniformRandomProvider rng,
double[] probabilities,
double alpha)
Create a new sampler for an enumerated distribution using the given 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.

Parameters:
rng - Generator of uniformly distributed random numbers.
probabilities - The probabilities.
alpha - The alpha factor used to set the guide table size.
Returns:
the sampler
Throws:
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.