001/*
002 * Licensed to the Apache Software Foundation (ASF) under one or more
003 * contributor license agreements.  See the NOTICE file distributed with
004 * this work for additional information regarding copyright ownership.
005 * The ASF licenses this file to You under the Apache License, Version 2.0
006 * (the "License"); you may not use this file except in compliance with
007 * the License.  You may obtain a copy of the License at
008 *
009 *      http://www.apache.org/licenses/LICENSE-2.0
010 *
011 * Unless required by applicable law or agreed to in writing, software
012 * distributed under the License is distributed on an "AS IS" BASIS,
013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
014 * See the License for the specific language governing permissions and
015 * limitations under the License.
016 */
017package org.apache.commons.rng.sampling.distribution;
018
019import org.apache.commons.rng.UniformRandomProvider;
020
021/**
022 * <a href="https://en.wikipedia.org/wiki/Box%E2%80%93Muller_transform">
023 * Box-Muller algorithm</a> for sampling from a Gaussian distribution.
024 */
025public class BoxMullerGaussianSampler
026    extends SamplerBase
027    implements ContinuousSampler {
028    /** Next gaussian. */
029    private double nextGaussian = Double.NaN;
030    /** Mean. */
031    private final double mean;
032    /** standardDeviation. */
033    private final double standardDeviation;
034
035    /**
036     * @param rng Generator of uniformly distributed random numbers.
037     * @param mean Mean of the Gaussian distribution.
038     * @param standardDeviation Standard deviation of the Gaussian distribution.
039     */
040    public BoxMullerGaussianSampler(UniformRandomProvider rng,
041                                    double mean,
042                                    double standardDeviation) {
043        super(rng);
044        this.mean = mean;
045        this.standardDeviation = standardDeviation;
046    }
047
048    /** {@inheritDoc} */
049    @Override
050    public double sample() {
051        final double random;
052        if (Double.isNaN(nextGaussian)) {
053            // Generate a pair of Gaussian numbers.
054
055            final double x = nextDouble();
056            final double y = nextDouble();
057            final double alpha = 2 * Math.PI * x;
058            final double r = Math.sqrt(-2 * Math.log(y));
059
060            // Return the first element of the generated pair.
061            random = r * Math.cos(alpha);
062
063            // Keep second element of the pair for next invocation.
064            nextGaussian = r * Math.sin(alpha);
065        } else {
066            // Use the second element of the pair (generated at the
067            // previous invocation).
068            random = nextGaussian;
069
070            // Both elements of the pair have been used.
071            nextGaussian = Double.NaN;
072        }
073
074        return standardDeviation * random + mean;
075    }
076
077    /** {@inheritDoc} */
078    @Override
079    public String toString() {
080        return "Box-Muller Gaussian deviate [" + super.toString() + "]";
081    }
082}