| /* |
| * 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 <a href="http://mathworld.wolfram.com/PoissonDistribution.html">Poisson distribution</a>. |
| * |
| * <ul> |
| * <li> |
| * For small means, a Poisson process is simulated using uniform deviates, as |
| * described <a href="http://mathaa.epfl.ch/cours/PMMI2001/interactive/rng7.htm">here</a>. |
| * The Poisson process (and hence, the returned value) is bounded by 1000 * mean. |
| * </li> |
| * <li> |
| * For large means, we use the rejection algorithm described in |
| * <blockquote> |
| * Devroye, Luc. (1981). <i>The Computer Generation of Poisson Random Variables</i><br> |
| * <strong>Computing</strong> vol. 26 pp. 197-207. |
| * </blockquote> |
| * </li> |
| * </ul> |
| * |
| * @since 1.0 |
| */ |
| public class PoissonSampler |
| extends SamplerBase |
| implements DiscreteSampler { |
| |
| /** Value for switching sampling algorithm. */ |
| private static final double PIVOT = 40; |
| /** The internal Poisson sampler. */ |
| private final DiscreteSampler poissonSampler; |
| |
| /** |
| * @param rng Generator of uniformly distributed random numbers. |
| * @param mean Mean. |
| * @throws IllegalArgumentException if {@code mean <= 0}. |
| */ |
| public PoissonSampler(UniformRandomProvider rng, |
| double mean) { |
| super(null); |
| |
| // Delegate all work to specialised samplers. |
| // These should check the input arguments. |
| poissonSampler = mean < PIVOT ? |
| new SmallMeanPoissonSampler(rng, mean) : |
| new LargeMeanPoissonSampler(rng, mean); |
| } |
| |
| /** {@inheritDoc} */ |
| @Override |
| public int sample() { |
| return poissonSampler.sample(); |
| } |
| |
| /** {@inheritDoc} */ |
| @Override |
| public String toString() { |
| return poissonSampler.toString(); |
| } |
| } |