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source: trunk/sources/HeuristicLab.Random/UniformRandomizer.cs @ 1153

Last change on this file since 1153 was 1153, checked in by vdorfer, 15 years ago

Created API documentation for HeuristicLab.Random, HeuristicLab.SGA and HeuristicLab.Selection.OffspringSelection namespace (#331)

File size: 9.3 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2008 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using System.Collections.Generic;
24using System.Text;
25using HeuristicLab.Core;
26using HeuristicLab.Data;
27using HeuristicLab.Constraints;
28
29namespace HeuristicLab.Random {
30  /// <summary>
31  /// Uniformly distributed random number generator.
32  /// </summary>
33  public class UniformRandomizer : OperatorBase {
34    private static int MAX_NUMBER_OF_TRIES = 100;
35    /// <inheritdoc select="summary"/>
36    public override string Description {
37      get { return "Initializes the value of variable 'Value' to a random value uniformly distributed between 'Min' and 'Max' (exclusive)"; }
38    }
39
40    /// <summary>
41    /// Gets or sets the maximum value of the random number generator (exclusive).
42    /// </summary>
43    /// <remarks>Gets or sets the variable with name <c>Max</c> through the
44    /// <see cref="OperatorBase.GetVariable"/> method of class <see cref="OperatorBase"/>.</remarks>
45    public double Max {
46      get { return ((DoubleData)GetVariable("Max").Value).Data; }
47      set { ((DoubleData)GetVariable("Max").Value).Data = value; }
48    }
49    /// <summary>
50    /// Gets or sets the minimum value of the random number generator.
51    /// </summary>
52    /// <remarks>Gets or sets the variable with name <c>Min</c> through the
53    /// <see cref="OperatorBase.GetVariable"/> method of class <see cref="OperatorBase"/>.</remarks>
54    public double Min {
55      get { return ((DoubleData)GetVariable("Min").Value).Data; }
56      set { ((DoubleData)GetVariable("Min").Value).Data = value; }
57    }
58
59    /// <summary>
60    /// Initializes a new instance of <see cref="UniformRandomizer"/> with four variable infos
61    /// (<c>Value</c>, <c>Random</c>, <c>Max</c> and <c>Min</c>), being a random number generator
62    /// between 0.0 and 1.0.
63    /// </summary>
64    public UniformRandomizer() {
65      AddVariableInfo(new VariableInfo("Value", "The value to manipulate (type is one of: IntData, ConstrainedIntData, DoubleData, ConstrainedDoubleData)", typeof(IObjectData), VariableKind.In));
66      AddVariableInfo(new VariableInfo("Random", "The random generator to use", typeof(MersenneTwister), VariableKind.In));
67      AddVariableInfo(new VariableInfo("Min", "Lower bound of the uniform distribution (inclusive)", typeof(DoubleData), VariableKind.None));
68      GetVariableInfo("Min").Local = true;
69      AddVariable(new Variable("Min", new DoubleData(0.0)));
70
71      AddVariableInfo(new VariableInfo("Max", "Upper bound of the uniform distribution (exclusive)", typeof(DoubleData), VariableKind.None));
72      GetVariableInfo("Max").Local = true;
73      AddVariable(new Variable("Max", new DoubleData(1.0)));
74    }
75
76    /// <summary>
77    /// Generates a new uniformly distributed random variable.
78    /// </summary>
79    /// <param name="scope">The scope where to apply the random number generator.</param>
80    /// <returns>null.</returns>
81    public override IOperation Apply(IScope scope) {
82      IObjectData value = GetVariableValue<IObjectData>("Value", scope, false);
83      MersenneTwister mt = GetVariableValue<MersenneTwister>("Random", scope, true);
84      double min = GetVariableValue<DoubleData>("Min", scope, true).Data;
85      double max = GetVariableValue<DoubleData>("Max", scope, true).Data;
86
87      RandomizeUniform(value, mt, min, max);
88      return null;
89    }
90
91    /// <summary>
92    /// Generates a new random number depending on the type of the <paramref name="value"/>.
93    /// </summary>
94    /// <exception cref="ArgumentException">Thrown when an unhandleable type appears.</exception>
95    /// <param name="value">The object whose data should be a new randomly generated number.</param>
96    /// <param name="mt">The MersenneTwister to generate a new random number.</param>
97    /// <param name="min">The left border of the interval in which the next random number has to lie.</param>
98    /// <param name="max">The right border (exclusive) of the interval in which the next random number
99    /// has to lie.</param>
100    private void RandomizeUniform(IObjectData value, MersenneTwister mt, double min, double max) {
101      // Dispatch manually based on dynamic type,
102      // a bit awkward but necessary until we create a better type hierarchy for numeric types (gkronber 15.11.2008).
103      if (value is DoubleData)
104        RandomizeUniform((DoubleData)value, mt, min, max);
105      else if (value is ConstrainedDoubleData)
106        RandomizeUniform((ConstrainedDoubleData)value, mt, min, max);
107      else if (value is IntData)
108        RandomizeUniform((IntData)value, mt, min, max);
109      else if (value is ConstrainedIntData)
110        RandomizeUniform((ConstrainedIntData)value, mt, min, max);
111      else throw new ArgumentException("Can't handle type " + value.GetType().Name);
112    }
113
114      /// <summary>
115      /// Generates a new double random number.
116      /// </summary>
117      /// <param name="data">The double object which the new value is assigned to.</param>
118      /// <param name="mt">The random number generator.</param>
119      /// <param name="min">The left border of the interval in which the next random number has to lie.</param>
120      /// <param name="max">The right border (exclusive) of the interval in which the next random number
121      /// has to lie.</param>
122      public void RandomizeUniform(DoubleData data, MersenneTwister mt, double min, double max) {
123        data.Data = mt.NextDouble() * (max - min) + min;
124      }
125
126      /// <summary>
127      /// Generates a new int random number.
128      /// </summary>
129      /// <param name="data">The int object which the new value is assigned to.</param>
130      /// <param name="mt">The random number generator.</param>
131      /// <param name="min">The left border of the interval in which the next random number has to lie.</param>
132      /// <param name="max">The right border (exclusive) of the interval in which the next random number
133      /// has to lie.</param>
134      public void RandomizeUniform(IntData data, MersenneTwister mt, double min, double max) {
135        data.Data = (int)Math.Floor(mt.NextDouble() * (max - min) + min);
136      }
137
138      /// <summary>
139      /// Generates a new double random number, being restricted to some constraints.
140      /// </summary>
141      /// <exception cref="InvalidOperationException">Thrown when no valid value could be found.</exception>
142      /// <param name="data">The double object which the new value is assigned to and whose constraints
143      /// must be fulfilled.</param>
144      /// <param name="mt">The random number generator.</param>
145      /// <param name="min">The left border of the interval in which the next random number has to lie.</param>
146      /// <param name="max">The right border (exclusive) of the interval in which the next random number
147      /// has to lie.</param>
148      public void RandomizeUniform(ConstrainedDoubleData data, MersenneTwister mt, double min, double max) {
149        for(int tries = MAX_NUMBER_OF_TRIES; tries >= 0; tries--) {
150          double r = mt.NextDouble() * (max - min) + min;
151          if(IsIntegerConstrained(data)) {
152            r = Math.Floor(r);
153          }
154          if(data.TrySetData(r)) {
155            return;
156          }
157        }
158        throw new InvalidOperationException("Couldn't find a valid value");
159      }
160      /// <summary>
161      /// Generates a new int random number, being restricted to some constraints.
162      /// </summary>
163      /// <exception cref="InvalidOperationException">Thrown when no valid value could be found.</exception>
164      /// <param name="data">The int object which the new value is assigned to and whose constraints
165      /// must be fulfilled.</param>
166      /// <param name="mt">The random number generator.</param>
167      /// <param name="min">The left border of the interval in which the next random number has to lie.</param>
168      /// <param name="max">The right border (exclusive) of the interval in which the next random number
169      /// has to lie.</param>
170      public void RandomizeUniform(ConstrainedIntData data, MersenneTwister mt, double min, double max) {
171        for(int tries = MAX_NUMBER_OF_TRIES; tries >= 0; tries--) {
172          int r = (int)Math.Floor(mt.NextDouble() * (max - min) + min);
173          if(data.TrySetData(r)) {
174            return;
175          }
176        }
177        throw new InvalidOperationException("Couldn't find a valid value");
178      }
179
180      private bool IsIntegerConstrained(ConstrainedDoubleData data) {
181        foreach(IConstraint constraint in data.Constraints) {
182          if(constraint is IsIntegerConstraint) {
183            return true;
184          }
185        }
186        return false;
187      }
188    }
189}
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