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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.commons.rng.sampling.distribution;
import org.apache.commons.rng.UniformRandomProvider;
/**
* Sampler for the Poisson distribution.
*
*
* -
* For small means, a Poisson process is simulated using uniform deviates, as
* described here.
* The Poisson process (and hence, the returned value) is bounded by 1000 * mean.
*
* -
* For large means, we use the rejection algorithm described in
*
* Devroye, Luc. (1981). The Computer Generation of Poisson Random Variables
* Computing vol. 26 pp. 197-207.
*
*
*
*
* Sampling uses:
*
*
* - {@link UniformRandomProvider#nextDouble()}
*
- {@link UniformRandomProvider#nextLong()} (large means only)
*
*
* @since 1.0
*/
public class PoissonSampler
extends SamplerBase
implements DiscreteSampler {
/**
* Value for switching sampling algorithm.
*
* Package scope for the {@link PoissonSamplerCache}.
*/
static final double PIVOT = 40;
/** The internal Poisson sampler. */
private final DiscreteSampler poissonSamplerDelegate;
/**
* @param rng Generator of uniformly distributed random numbers.
* @param mean Mean.
* @throws IllegalArgumentException if {@code mean <= 0} or
* {@code mean >} {@link Integer#MAX_VALUE}.
*/
public PoissonSampler(UniformRandomProvider rng,
double mean) {
super(null);
// Delegate all work to specialised samplers.
// These should check the input arguments.
poissonSamplerDelegate = mean < PIVOT ?
new SmallMeanPoissonSampler(rng, mean) :
new LargeMeanPoissonSampler(rng, mean);
}
/** {@inheritDoc} */
@Override
public int sample() {
return poissonSamplerDelegate.sample();
}
/** {@inheritDoc} */
@Override
public String toString() {
return poissonSamplerDelegate.toString();
}
}