1 /* 2 * Licensed to the Apache Software Foundation (ASF) under one or more 3 * contributor license agreements. See the NOTICE file distributed with 4 * this work for additional information regarding copyright ownership. 5 * The ASF licenses this file to You under the Apache License, Version 2.0 6 * (the "License"); you may not use this file except in compliance with 7 * the License. You may obtain a copy of the License at 8 * 9 * http://www.apache.org/licenses/LICENSE-2.0 10 * 11 * Unless required by applicable law or agreed to in writing, software 12 * distributed under the License is distributed on an "AS IS" BASIS, 13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 * See the License for the specific language governing permissions and 15 * limitations under the License. 16 */ 17 package org.apache.commons.rng.sampling.distribution; 18 19 import org.apache.commons.rng.UniformRandomProvider; 20 21 /** 22 * <a href="https://en.wikipedia.org/wiki/Marsaglia_polar_method"> 23 * Marsaglia polar method</a> for sampling from a Gaussian distribution 24 * with mean 0 and standard deviation 1. 25 * This is a variation of the algorithm implemented in 26 * {@link BoxMullerNormalizedGaussianSampler}. 27 * 28 * @since 1.1 29 */ 30 public class MarsagliaNormalizedGaussianSampler 31 implements NormalizedGaussianSampler { 32 /** Next gaussian. */ 33 private double nextGaussian = Double.NaN; 34 /** Underlying source of randomness. */ 35 private final UniformRandomProvider rng; 36 37 /** 38 * @param rng Generator of uniformly distributed random numbers. 39 */ 40 public MarsagliaNormalizedGaussianSampler(UniformRandomProvider rng) { 41 this.rng = rng; 42 } 43 44 /** {@inheritDoc} */ 45 @Override 46 public double sample() { 47 if (Double.isNaN(nextGaussian)) { 48 // Rejection scheme for selecting a pair that lies within the unit circle. 49 while (true) { 50 // Generate a pair of numbers within [-1 , 1). 51 final double x = 2 * rng.nextDouble() - 1; 52 final double y = 2 * rng.nextDouble() - 1; 53 final double r2 = x * x + y * y; 54 55 if (r2 < 1 && r2 > 0) { 56 // Pair (x, y) is within unit circle. 57 final double alpha = Math.sqrt(-2 * Math.log(r2) / r2); 58 59 // Keep second element of the pair for next invocation. 60 nextGaussian = alpha * y; 61 62 // Return the first element of the generated pair. 63 return alpha * x; 64 } 65 66 // Pair is not within the unit circle: Generate another one. 67 } 68 } else { 69 // Use the second element of the pair (generated at the 70 // previous invocation). 71 final double r = nextGaussian; 72 73 // Both elements of the pair have been used. 74 nextGaussian = Double.NaN; 75 76 return r; 77 } 78 } 79 80 /** {@inheritDoc} */ 81 @Override 82 public String toString() { 83 return "Box-Muller (with rejection) normalized Gaussian deviate [" + rng.toString() + "]"; 84 } 85 }