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 Gaussian distribution with
024 * mean 0 and standard deviation 1.
025 *
026 * @since 1.1
027 */
028public class BoxMullerNormalizedGaussianSampler
029    implements NormalizedGaussianSampler {
030    /** Next gaussian. */
031    private double nextGaussian = Double.NaN;
032    /** Underlying source of randomness. */
033    private final UniformRandomProvider rng;
034
035    /**
036     * @param rng Generator of uniformly distributed random numbers.
037     */
038    public BoxMullerNormalizedGaussianSampler(UniformRandomProvider rng) {
039        this.rng = rng;
040    }
041
042    /** {@inheritDoc} */
043    @Override
044    public double sample() {
045        final double random;
046        if (Double.isNaN(nextGaussian)) {
047            // Generate a pair of Gaussian numbers.
048
049            final double x = rng.nextDouble();
050            final double y = rng.nextDouble();
051            final double alpha = 2 * Math.PI * x;
052            final double r = Math.sqrt(-2 * Math.log(y));
053
054            // Return the first element of the generated pair.
055            random = r * Math.cos(alpha);
056
057            // Keep second element of the pair for next invocation.
058            nextGaussian = r * Math.sin(alpha);
059        } else {
060            // Use the second element of the pair (generated at the
061            // previous invocation).
062            random = nextGaussian;
063
064            // Both elements of the pair have been used.
065            nextGaussian = Double.NaN;
066        }
067
068        return random;
069    }
070
071    /** {@inheritDoc} */
072    @Override
073    public String toString() {
074        return "Box-Muller normalized Gaussian deviate [" + rng.toString() + "]";
075    }
076}