1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2008 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 System.Collections.Generic;
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24 | using System.Text;
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25 | using HeuristicLab.Core;
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26 | using HeuristicLab.Data;
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27 | using HeuristicLab.Constraints;
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28 |
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29 | namespace HeuristicLab.Random {
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30 | /// <summary>
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31 | /// Normally distributed random number generator.
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32 | /// </summary>
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33 | public class NormalRandomizer : OperatorBase {
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34 | private static int MAX_NUMBER_OF_TRIES = 100;
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35 |
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36 | /// <inheritdoc select="summary"/>
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37 | public override string Description {
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38 | get { return "Initializes the value of variable 'Value' to a random value normally distributed with 'Mu' and 'Sigma'."; }
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39 | }
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40 |
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41 | /// <summary>
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42 | /// Gets or sets the value for µ.
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43 | /// </summary>
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44 | /// <remarks>Gets or sets the variable with the name <c>Mu</c> through the method
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45 | /// <see cref="OperatorBase.GetVariable"/> of class <see cref="OperatorBase"/>.</remarks>
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46 | public double Mu {
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47 | get { return ((DoubleData)GetVariable("Mu").Value).Data; }
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48 | set { ((DoubleData)GetVariable("Mu").Value).Data = value; }
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49 | }
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50 | /// <summary>
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51 | /// Gets or sets the value for sigma.
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52 | /// </summary>
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53 | /// <remarks>Gets or sets the variable with the name <c>Sigma</c> through the method
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54 | /// <see cref="OperatorBase.GetVariable"/> of class <see cref="OperatorBase"/>.</remarks>
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55 | public double Sigma {
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56 | get { return ((DoubleData)GetVariable("Sigma").Value).Data; }
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57 | set { ((DoubleData)GetVariable("Sigma").Value).Data = value; }
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58 | }
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59 |
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60 | /// <summary>
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61 | /// Initializes a new instance of <see cref="NormalRandomizer"/> with four variable infos
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62 | /// (<c>Mu</c>, <c>Sigma</c>, <c>Value</c> and <c>Random</c>).
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63 | /// </summary>
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64 | public NormalRandomizer() {
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65 | AddVariableInfo(new VariableInfo("Mu", "Parameter mu of the normal distribution", typeof(DoubleData), VariableKind.None));
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66 | GetVariableInfo("Mu").Local = true;
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67 | AddVariable(new Variable("Mu", new DoubleData(0.0)));
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68 |
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69 | AddVariableInfo(new VariableInfo("Sigma", "Parameter sigma of the normal distribution", typeof(DoubleData), VariableKind.None));
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70 | GetVariableInfo("Sigma").Local = true;
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71 | AddVariable(new Variable("Sigma", new DoubleData(1.0)));
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72 |
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73 | AddVariableInfo(new VariableInfo("Value", "The value to manipulate (actual type is one of: IntData, DoubleData, ConstrainedIntData, ConstrainedDoubleData)", typeof(IObjectData), VariableKind.In));
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74 | AddVariableInfo(new VariableInfo("Random", "The random generator to use", typeof(MersenneTwister), VariableKind.In));
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75 | }
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76 |
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77 | /// <summary>
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78 | /// Generates a new normally distributed random variable and assigns it to the specified variable
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79 | /// in the given <paramref name="scope"/>.
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80 | /// </summary>
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81 | /// <param name="scope">The scope where to assign the new random value to.</param>
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82 | /// <returns>null.</returns>
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83 | public override IOperation Apply(IScope scope) {
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84 | IObjectData value = GetVariableValue<IObjectData>("Value", scope, false);
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85 | MersenneTwister mt = GetVariableValue<MersenneTwister>("Random", scope, true);
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86 | double mu = GetVariableValue<DoubleData>("Mu", scope, true).Data;
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87 | double sigma = GetVariableValue<DoubleData>("Sigma", scope, true).Data;
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88 |
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89 | NormalDistributedRandom n = new NormalDistributedRandom(mt, mu, sigma);
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90 | RandomizeNormal(value, n);
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91 | return null;
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92 | }
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93 |
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94 | private void RandomizeNormal(IObjectData value, NormalDistributedRandom n) {
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95 | // dispatch manually based on dynamic type
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96 | if (value is IntData)
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97 | RandomizeNormal((IntData)value, n);
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98 | else if (value is ConstrainedIntData)
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99 | RandomizeNormal((ConstrainedIntData)value, n);
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100 | else if (value is DoubleData)
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101 | RandomizeNormal((DoubleData)value, n);
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102 | else if (value is ConstrainedDoubleData)
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103 | RandomizeNormal((ConstrainedDoubleData)value, n);
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104 | else throw new InvalidOperationException("Can't handle type " + value.GetType().Name);
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105 | }
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106 |
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107 | /// <summary>
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108 | /// Generates a new double random variable based on a continuous, normally distributed random number generator
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109 | /// <paramref name="normal"/> and checks some contraints.
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110 | /// </summary>
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111 | /// <exception cref="InvalidOperationException">Thrown when with the given settings no valid value in
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112 | /// 100 tries could be found.
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113 | /// </exception>
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114 | /// <param name="data">The double object where to assign the new number to and whose constraints
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115 | /// must be fulfilled.</param>
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116 | /// <param name="normal">The continuous, normally distributed random variable.</param>
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117 | public void RandomizeNormal(ConstrainedDoubleData data, NormalDistributedRandom normal) {
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118 | for (int tries = MAX_NUMBER_OF_TRIES; tries >= 0; tries--) {
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119 | double r = normal.NextDouble();
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120 | if (IsIntegerConstrained(data)) {
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121 | r = Math.Round(r);
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122 | }
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123 | if (data.TrySetData(r)) {
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124 | return;
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125 | }
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126 | }
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127 | throw new InvalidOperationException("Couldn't find a valid value in 100 tries with mu=" + normal.Mu + " sigma=" + normal.Sigma);
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128 | }
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129 |
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130 | /// <summary>
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131 | /// Generates a new int random variable based on a continuous, normally distributed random number
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132 | /// generator <paramref name="normal"/> and checks some constraints.
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133 | /// </summary>
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134 | /// <exception cref="InvalidOperationException">Thrown when with the given settings no valid
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135 | /// value could be found.</exception>
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136 | /// <param name="data">The int object where to assign the new value to and whose constraints must
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137 | /// be fulfilled.</param>
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138 | /// <param name="normal">The continuous, normally distributed random variable.</param>
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139 | public void RandomizeNormal(ConstrainedIntData data, NormalDistributedRandom normal) {
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140 | for (int tries = MAX_NUMBER_OF_TRIES; tries >= 0; tries--) {
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141 | double r = normal.NextDouble();
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142 | if (data.TrySetData((int)Math.Round(r))) // since r is a continuous, normally distributed random variable rounding should be OK
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143 | return;
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144 | }
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145 | throw new InvalidOperationException("Couldn't find a valid value");
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146 | }
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147 |
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148 | /// <summary>
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149 | /// Generates a new double random number based on a continuous, normally distributed random number
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150 | /// generator <paramref name="normal"/>.
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151 | /// </summary>
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152 | /// <param name="data">The double object where to assign the new value to.</param>
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153 | /// <param name="normal">The continuous, normally distributed random variable.</param>
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154 | public void RandomizeNormal(DoubleData data, NormalDistributedRandom normal) {
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155 | data.Data = normal.NextDouble();
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156 | }
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157 |
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158 | /// <summary>
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159 | /// Generates a new int random number based on a continuous, normally distributed random number
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160 | /// generator <paramref name="normal"/>.
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161 | /// </summary>
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162 | /// <param name="data">The int object where to assign the new value to.</param>
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163 | /// <param name="normal">The continuous, normally distributed random variable.</param>
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164 | public void RandomizeNormal(IntData data, NormalDistributedRandom normal) {
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165 | data.Data = (int)Math.Round(normal.NextDouble());
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166 | }
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167 |
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168 |
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169 | private bool IsIntegerConstrained(ConstrainedDoubleData data) {
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170 | foreach (IConstraint constraint in data.Constraints) {
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171 | if (constraint is IsIntegerConstraint) {
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172 | return true;
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173 | }
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174 | }
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175 | return false;
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176 | }
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177 | }
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178 | }
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