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 *
025 * <p>Sampling uses:</p>
026 *
027 * <ul>
028 *   <li>{@link UniformRandomProvider#nextDouble()}
029 *   <li>{@link UniformRandomProvider#nextLong()}
030 * </ul>
031 *
032 * @since 1.0
033 *
034 * @deprecated Since version 1.1. Please use {@link BoxMullerNormalizedGaussianSampler}
035 * and {@link GaussianSampler} instead.
036 */
037@Deprecated
038public class BoxMullerGaussianSampler
039    extends SamplerBase
040    implements ContinuousSampler {
041    /** Next gaussian. */
042    private double nextGaussian = Double.NaN;
043    /** Mean. */
044    private final double mean;
045    /** standardDeviation. */
046    private final double standardDeviation;
047    /** Underlying source of randomness. */
048    private final UniformRandomProvider rng;
049
050    /**
051     * Create an instance.
052     *
053     * @param rng Generator of uniformly distributed random numbers.
054     * @param mean Mean of the Gaussian distribution.
055     * @param standardDeviation Standard deviation of the Gaussian distribution.
056     * @throws IllegalArgumentException if {@code standardDeviation <= 0}
057     */
058    public BoxMullerGaussianSampler(UniformRandomProvider rng,
059                                    double mean,
060                                    double standardDeviation) {
061        this(mean, InternalUtils.requireStrictlyPositiveFinite(standardDeviation, "standardDeviation"), rng);
062    }
063
064    /**
065     * @param rng Generator of uniformly distributed random numbers.
066     * @param mean Mean of the Gaussian distribution.
067     * @param standardDeviation Standard deviation of the Gaussian distribution.
068     */
069    private BoxMullerGaussianSampler(double mean,
070                                     double standardDeviation,
071                                     UniformRandomProvider rng) {
072        super(null);
073        this.rng = rng;
074        this.mean = mean;
075        this.standardDeviation = standardDeviation;
076    }
077
078    /** {@inheritDoc} */
079    @Override
080    public double sample() {
081        final double random;
082        if (Double.isNaN(nextGaussian)) {
083            // Generate a pair of Gaussian numbers.
084
085            // Avoid zero for the uniform deviate y.
086            // The extreme tail of the sample is:
087            // y = 2^-53
088            // r = 8.57167
089            final double x = rng.nextDouble();
090            final double y = InternalUtils.makeNonZeroDouble(rng.nextLong());
091            final double alpha = 2 * Math.PI * x;
092            final double r = Math.sqrt(-2 * Math.log(y));
093
094            // Return the first element of the generated pair.
095            random = r * Math.cos(alpha);
096
097            // Keep second element of the pair for next invocation.
098            nextGaussian = r * Math.sin(alpha);
099        } else {
100            // Use the second element of the pair (generated at the
101            // previous invocation).
102            random = nextGaussian;
103
104            // Both elements of the pair have been used.
105            nextGaussian = Double.NaN;
106        }
107
108        return standardDeviation * random + mean;
109    }
110
111    /** {@inheritDoc} */
112    @Override
113    public String toString() {
114        return "Box-Muller Gaussian deviate [" + rng.toString() + "]";
115    }
116}