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/Box%E2%80%93Muller_transform"> 23 * Box-Muller algorithm</a> for sampling from Gaussian distribution with 24 * mean 0 and standard deviation 1. 25 * 26 * @since 1.1 27 */ 28 public class BoxMullerNormalizedGaussianSampler 29 implements NormalizedGaussianSampler { 30 /** Next gaussian. */ 31 private double nextGaussian = Double.NaN; 32 /** Underlying source of randomness. */ 33 private final UniformRandomProvider rng; 34 35 /** 36 * @param rng Generator of uniformly distributed random numbers. 37 */ 38 public BoxMullerNormalizedGaussianSampler(UniformRandomProvider rng) { 39 this.rng = rng; 40 } 41 42 /** {@inheritDoc} */ 43 @Override 44 public double sample() { 45 final double random; 46 if (Double.isNaN(nextGaussian)) { 47 // Generate a pair of Gaussian numbers. 48 49 final double x = rng.nextDouble(); 50 final double y = rng.nextDouble(); 51 final double alpha = 2 * Math.PI * x; 52 final double r = Math.sqrt(-2 * Math.log(y)); 53 54 // Return the first element of the generated pair. 55 random = r * Math.cos(alpha); 56 57 // Keep second element of the pair for next invocation. 58 nextGaussian = r * Math.sin(alpha); 59 } else { 60 // Use the second element of the pair (generated at the 61 // previous invocation). 62 random = nextGaussian; 63 64 // Both elements of the pair have been used. 65 nextGaussian = Double.NaN; 66 } 67 68 return random; 69 } 70 71 /** {@inheritDoc} */ 72 @Override 73 public String toString() { 74 return "Box-Muller normalized Gaussian deviate [" + rng.toString() + "]"; 75 } 76 }