Class GuideTableDiscreteSampler
- java.lang.Object
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- org.apache.commons.rng.sampling.distribution.GuideTableDiscreteSampler
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- All Implemented Interfaces:
DiscreteSampler,SharedStateDiscreteSampler,SharedStateSampler<SharedStateDiscreteSampler>
public final class GuideTableDiscreteSampler extends Object implements SharedStateDiscreteSampler
Compute a sample fromnvalues each with an associated probability. If all unique items are assigned the same probability it is more efficient to use theDiscreteUniformSampler.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)
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description static SharedStateDiscreteSamplerof(UniformRandomProvider rng, double[] probabilities)Create a new sampler for an enumerated distribution using the givenprobabilities.static SharedStateDiscreteSamplerof(UniformRandomProvider rng, double[] probabilities, double alpha)Create a new sampler for an enumerated distribution using the givenprobabilities.intsample()Creates anintsample.StringtoString()SharedStateDiscreteSamplerwithUniformRandomProvider(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
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Methods inherited from interface org.apache.commons.rng.sampling.distribution.DiscreteSampler
samples, samples
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Method Detail
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sample
public int sample()
Creates anintsample.- Specified by:
samplein interfaceDiscreteSampler- Returns:
- a sample.
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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:
withUniformRandomProviderin interfaceSharedStateSampler<SharedStateDiscreteSampler>- Parameters:
rng- Generator of uniformly distributed random numbers.- Returns:
- the sampler
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of
public static SharedStateDiscreteSampler of(UniformRandomProvider rng, double[] probabilities)
Create a new sampler for an enumerated distribution using the givenprobabilities. 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- ifprobabilitiesis null or empty, a probability is negative, infinite orNaN, or the sum of all probabilities is not strictly positive.
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of
public static SharedStateDiscreteSampler of(UniformRandomProvider rng, double[] probabilities, double alpha)
Create a new sampler for an enumerated distribution using the givenprobabilities. 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- ifprobabilitiesis null or empty, a probability is negative, infinite orNaN, the sum of all probabilities is not strictly positive, oralphais not strictly positive.
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