| /* |
| * Licensed to the Apache Software Foundation (ASF) under one or more |
| * contributor license agreements. See the NOTICE file distributed with |
| * this work for additional information regarding copyright ownership. |
| * The ASF licenses this file to You under the Apache License, Version 2.0 |
| * (the "License"); you may not use this file except in compliance with |
| * the License. You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, software |
| * distributed under the License is distributed on an "AS IS" BASIS, |
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| * See the License for the specific language governing permissions and |
| * limitations under the License. |
| */ |
| package org.apache.commons.rng.sampling.distribution; |
| |
| import org.apache.commons.rng.UniformRandomProvider; |
| |
| /** |
| * <a href="https://en.wikipedia.org/wiki/Box%E2%80%93Muller_transform"> |
| * Box-Muller algorithm</a> for sampling from a Gaussian distribution. |
| * |
| * @since 1.0 |
| * |
| * @deprecated Since v1.1. Please use {@link BoxMullerNormalizedGaussianSampler} |
| * and {@link GaussianSampler} instead. |
| */ |
| @Deprecated |
| public class BoxMullerGaussianSampler |
| extends SamplerBase |
| implements ContinuousSampler { |
| /** Next gaussian. */ |
| private double nextGaussian = Double.NaN; |
| /** Mean. */ |
| private final double mean; |
| /** standardDeviation. */ |
| private final double standardDeviation; |
| /** Underlying source of randomness. */ |
| private final UniformRandomProvider rng; |
| |
| /** |
| * @param rng Generator of uniformly distributed random numbers. |
| * @param mean Mean of the Gaussian distribution. |
| * @param standardDeviation Standard deviation of the Gaussian distribution. |
| */ |
| public BoxMullerGaussianSampler(UniformRandomProvider rng, |
| double mean, |
| double standardDeviation) { |
| super(null); |
| this.rng = rng; |
| this.mean = mean; |
| this.standardDeviation = standardDeviation; |
| } |
| |
| /** {@inheritDoc} */ |
| @Override |
| public double sample() { |
| final double random; |
| if (Double.isNaN(nextGaussian)) { |
| // Generate a pair of Gaussian numbers. |
| |
| final double x = rng.nextDouble(); |
| final double y = rng.nextDouble(); |
| final double alpha = 2 * Math.PI * x; |
| final double r = Math.sqrt(-2 * Math.log(y)); |
| |
| // Return the first element of the generated pair. |
| random = r * Math.cos(alpha); |
| |
| // Keep second element of the pair for next invocation. |
| nextGaussian = r * Math.sin(alpha); |
| } else { |
| // Use the second element of the pair (generated at the |
| // previous invocation). |
| random = nextGaussian; |
| |
| // Both elements of the pair have been used. |
| nextGaussian = Double.NaN; |
| } |
| |
| return standardDeviation * random + mean; |
| } |
| |
| /** {@inheritDoc} */ |
| @Override |
| public String toString() { |
| return "Box-Muller Gaussian deviate [" + rng.toString() + "]"; |
| } |
| } |