blob: 170a85bf1f1c9eaf19b0c7ceac7cd7358f78d7f9 [file] [log] [blame]
/*
* 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>
* </ul>
*
* @since 1.1
*
* This sampler is suitable for {@code mean < 40}.
*/
public class SmallMeanPoissonSampler
implements DiscreteSampler {
/**
* Pre-compute {@code Math.exp(-mean)}.
* Note: This is the probability of the Poisson sample {@code P(n=0)}.
*/
private final double p0;
/** Pre-compute {@code 1000 * mean} as the upper limit of the sample. */
private final int limit;
/** Underlying source of randomness. */
private final UniformRandomProvider rng;
/**
* @param rng Generator of uniformly distributed random numbers.
* @param mean Mean.
* @throws IllegalArgumentException if {@code mean <= 0}.
*/
public SmallMeanPoissonSampler(UniformRandomProvider rng,
double mean) {
this.rng = rng;
if (mean <= 0) {
throw new IllegalArgumentException(mean + " <= " + 0);
}
p0 = Math.exp(-mean);
// The returned sample is bounded by 1000 * mean or Integer.MAX_VALUE
limit = (int) Math.ceil(Math.min(1000 * mean, Integer.MAX_VALUE));
}
/** {@inheritDoc} */
@Override
public int sample() {
int n = 0;
double r = 1;
while (n < limit) {
r *= rng.nextDouble();
if (r >= p0) {
n++;
} else {
break;
}
}
return n;
}
/** {@inheritDoc} */
@Override
public String toString() {
return "Small Mean Poisson deviate [" + rng.toString() + "]";
}
}