org.apache.mahout.math.random.PoissonSampler.java Source code

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Here is the source code for org.apache.mahout.math.random.PoissonSampler.java

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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.mahout.math.random;

import com.google.common.collect.Lists;
import org.apache.commons.math3.distribution.PoissonDistribution;
import org.apache.mahout.common.RandomUtils;
import org.apache.mahout.common.RandomWrapper;

import java.util.List;

/**
 * Samples from a Poisson distribution.  Should probably not be used for lambda > 1000 or so.
 */
public final class PoissonSampler extends AbstractSamplerFunction {

    private double limit;
    private Multinomial<Integer> partial;
    private final RandomWrapper gen;
    private final PoissonDistribution pd;

    public PoissonSampler(double lambda) {
        limit = 1;
        gen = RandomUtils.getRandom();
        pd = new PoissonDistribution(gen.getRandomGenerator(), lambda, PoissonDistribution.DEFAULT_EPSILON,
                PoissonDistribution.DEFAULT_MAX_ITERATIONS);
    }

    @Override
    public Double sample() {
        return sample(gen.nextDouble());
    }

    double sample(double u) {
        if (u < limit) {
            List<WeightedThing<Integer>> steps = Lists.newArrayList();
            limit = 1;
            int i = 0;
            while (u / 20 < limit) {
                double pdf = pd.probability(i);
                limit -= pdf;
                steps.add(new WeightedThing<Integer>(i, pdf));
                i++;
            }
            steps.add(new WeightedThing<Integer>(steps.size(), limit));
            partial = new Multinomial<Integer>(steps);
        }
        return partial.sample(u);
    }
}