[17244] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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| 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using System;
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| 23 | using HeuristicLab.Common;
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| 24 | using HeuristicLab.Core;
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| 25 | using HEAL.Attic;
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| 26 |
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| 27 | namespace HeuristicLab.Random {
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| 28 |
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| 29 | /// <summary>
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| 30 | /// Normally distributed random variable.
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| 31 | /// Uses Marsaglia's polar method
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| 32 | /// </summary>
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| 33 | [Item("NormalDistributedRandomPolar", "A pseudo random number generator which uses Marsaglia's polar method to create normally distributed random numbers.")]
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| 34 | public sealed class NormalDistributedRandomPolar : Item, IRandom {
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| 35 | [Storable]
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| 36 | private double mu;
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| 37 | /// <summary>
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| 38 | /// Gets or sets the value for µ.
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| 39 | /// </summary>
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| 40 | public double Mu {
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| 41 | get { return mu; }
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| 42 | set { mu = value; }
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| 43 | }
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| 44 |
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| 45 | [Storable]
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| 46 | private double sigma;
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| 47 | /// <summary>
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| 48 | /// Gets or sets the value for sigma.
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| 49 | /// </summary>
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| 50 | public double Sigma {
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| 51 | get { return sigma; }
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| 52 | set { sigma = value; }
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| 53 | }
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| 54 |
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| 55 | [Storable]
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| 56 | private IRandom uniform;
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| 57 |
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| 58 |
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| 59 | [StorableConstructor]
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| 60 | private NormalDistributedRandomPolar(StorableConstructorFlag _) : base(_) { }
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| 61 |
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| 62 | private NormalDistributedRandomPolar(NormalDistributedRandomPolar original, Cloner cloner)
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| 63 | : base(original, cloner) {
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| 64 | uniform = cloner.Clone(original.uniform);
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| 65 | mu = original.mu;
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| 66 | sigma = original.sigma;
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| 67 | }
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| 68 |
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| 69 | /// <summary>
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| 70 | /// Initializes a new instance of <see cref="NormalDistributedRandomPolar"/> with µ = 0 and sigma = 1
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| 71 | /// and a new random number generator.
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| 72 | /// </summary>
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| 73 | public NormalDistributedRandomPolar() {
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| 74 | this.mu = 0.0;
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| 75 | this.sigma = 1.0;
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| 76 | this.uniform = new MersenneTwister();
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| 77 | }
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| 78 |
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| 79 | /// <summary>
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| 80 | /// Initializes a new instance of <see cref="NormalDistributedRandomPolar"/> with the given parameters.
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| 81 | /// <note type="caution"> The random number generator is not copied!</note>
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| 82 | /// </summary>
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| 83 | /// <param name="uniformRandom">The random number generator.</param>
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| 84 | /// <param name="mu">The value for µ.</param>
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| 85 | /// <param name="sigma">The value for sigma.</param>
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| 86 | public NormalDistributedRandomPolar(IRandom uniformRandom, double mu, double sigma) {
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| 87 | this.mu = mu;
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| 88 | this.sigma = sigma;
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| 89 | this.uniform = uniformRandom;
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| 90 | }
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| 91 |
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| 92 | #region IRandom Members
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| 93 |
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| 94 | /// <inheritdoc cref="IRandom.Reset()"/>
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| 95 | public void Reset() {
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| 96 | uniform.Reset();
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| 97 | }
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| 98 |
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| 99 | /// <inheritdoc cref="IRandom.Reset(int)"/>
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| 100 | public void Reset(int seed) {
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| 101 | uniform.Reset(seed);
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| 102 | }
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| 103 |
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| 104 | /// <summary>
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| 105 | /// This method is not implemented.
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| 106 | /// </summary>
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| 107 | public int Next() {
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| 108 | throw new NotImplementedException();
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| 109 | }
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| 110 |
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| 111 | /// <summary>
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| 112 | /// This method is not implemented.
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| 113 | /// </summary>
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| 114 | public int Next(int maxVal) {
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| 115 | throw new NotImplementedException();
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| 116 | }
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| 117 |
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| 118 | /// <summary>
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| 119 | /// This method is not implemented.
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| 120 | /// </summary>
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| 121 | public int Next(int minVal, int maxVal) {
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| 122 | throw new NotImplementedException();
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| 123 | }
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| 124 |
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| 125 | /// <summary>
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| 126 | /// Generates a new double random number.
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| 127 | /// </summary>
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| 128 | /// <returns>A double random number.</returns>
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| 129 | public double NextDouble() {
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| 130 | return NormalDistributedRandomPolar.NextDouble(uniform, mu, sigma);
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| 131 | }
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| 132 |
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| 133 | #endregion
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| 134 |
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| 135 | /// <summary>
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| 136 | /// Clones the current instance (deep clone).
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| 137 | /// </summary>
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| 138 | /// <returns>The cloned object as <see cref="NormalDistributedRandomPolar"/>.</returns>
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| 139 | public override IDeepCloneable Clone(Cloner cloner) {
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| 140 | return new NormalDistributedRandomPolar(this, cloner);
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| 141 | }
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| 142 |
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| 143 |
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| 144 | /**
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| 145 | * Polar method due to Marsaglia.
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| 146 | *
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| 147 | * Devroye, L. Non-Uniform Random Variates Generation. Springer-Verlag,
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| 148 | * New York, 1986, Ch. V, Sect. 4.4.
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| 149 | */
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| 150 | public static double NextDouble(IRandom uniformRandom, double mu, double sigma) {
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| 151 | // we don't use spare numbers (efficency loss but easier for multi-threaded code)
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| 152 | double u, v, s;
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| 153 | do {
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| 154 | u = uniformRandom.NextDouble() * 2 - 1;
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| 155 | v = uniformRandom.NextDouble() * 2 - 1;
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| 156 | s = u * u + v * v;
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[17245] | 157 | } while (s > 1 || s == 0);
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[17244] | 158 | s = Math.Sqrt(-2.0 * Math.Log(s) / s);
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| 159 | return mu + sigma * u * s;
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| 160 | }
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| 161 | }
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| 162 | }
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