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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  }