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source: branches/HeuristicLab.Hive_Milestone3/sources/HeuristicLab.Selection.OffspringSelection/3.2/OffspringAnalyzer.cs @ 3312

Last change on this file since 3312 was 1530, checked in by gkronber, 16 years ago

Moved source files of plugins Hive ... Visualization.Test into version-specific sub-folders. #576

File size: 7.2 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;
27
28namespace HeuristicLab.Selection.OffspringSelection {
29  /// <summary>
30  /// Analyzes the offspring in a given scope whether it is successful or not.
31  /// </summary>
32  public class OffspringAnalyzer : OperatorBase {
33    /// <inheritdoc select="summary"/>
34    public override string Description {
35      get { return @"TODO\r\nOperator description still missing ..."; }
36    }
37
38    /// <summary>
39    /// Initializes a new instance of <see cref="OffspringAnalyzer"/> with six variable infos
40    /// (<c>Maximization</c>, <c>Quality</c>, <c>ParentQualities</c>, <c>SuccessfulChild</c>,
41    /// <c>ComparisonFactor</c> and <c>ParentsCount</c>).
42    /// </summary>
43    public OffspringAnalyzer() {
44      AddVariableInfo(new VariableInfo("Maximization", "Problem is a maximization problem", typeof(BoolData), VariableKind.In));
45      AddVariableInfo(new VariableInfo("Quality", "Quality value", typeof(DoubleData), VariableKind.In));
46      AddVariableInfo(new VariableInfo("ParentQualities", "Temporarily store parent qualities", typeof(DoubleArrayData), VariableKind.New | VariableKind.Out | VariableKind.In | VariableKind.Deleted));
47      AddVariableInfo(new VariableInfo("SuccessfulChild", "True if the child was successful", typeof(BoolData), VariableKind.New));
48
49      VariableInfo compFactorInfo = new VariableInfo("ComparisonFactor", "Factor for comparing the quality of a child with the qualities of its parents (0 = better than worst parent, 1 = better than best parent)", typeof(DoubleData), VariableKind.In);
50      compFactorInfo.Local = true;
51      AddVariableInfo(compFactorInfo);
52      AddVariable(new Variable("ComparisonFactor", new DoubleData(0.5)));
53      VariableInfo parentCount = new VariableInfo("ParentsCount", "How many parents created the offspring", typeof(IntData), VariableKind.In);
54      parentCount.Local = true;
55      AddVariableInfo(parentCount);
56      AddVariable(new Variable("ParentsCount", new IntData(2)));
57    }
58
59    /// <summary>
60    /// Analyzes the offspring in the given scope whether the children are successful or not.
61    /// </summary>
62    /// <exception cref="InvalidOperationException">Thrown when <c>ParentsCount</c> smaller than 1.</exception>
63    /// <exception cref="InvalidOperationException">Thrown when the number of children is not constant or
64    /// smaller than 1.</exception>
65    /// <param name="scope">The scope whose offspring should be analyzed.</param>
66    /// <returns>The next operation or <c>null</c>.</returns>
67    public override IOperation Apply(IScope scope) {
68      bool maximize = GetVariableValue<BoolData>("Maximization", scope, true).Data;
69      double compFact = GetVariableValue<DoubleData>("ComparisonFactor", scope, true).Data;
70      int parentsCount = GetVariableValue<IntData>("ParentsCount", scope, true).Data;
71      if (parentsCount < 1) throw new InvalidOperationException("OffspringAnalyzer: ParentsCount must be >= 1");
72
73      DoubleArrayData qualities = GetVariableValue<DoubleArrayData>("ParentQualities", scope, false, false);
74      if (qualities == null) {
75        // fetch and store parent qualities
76        IVariableInfo qualityInfo = GetVariableInfo("Quality");
77        double[] qualitiesArray = new double[scope.SubScopes.Count];
78        for (int i = 0; i < qualitiesArray.Length; i++)
79          qualitiesArray[i] = scope.SubScopes[i].GetVariableValue<DoubleData>(qualityInfo.FormalName, false).Data;
80        qualities = new DoubleArrayData(qualitiesArray);
81        IVariableInfo parentQualitiesInfo = GetVariableInfo("ParentQualities");
82        if (parentQualitiesInfo.Local)
83          AddVariable(new Variable(parentQualitiesInfo.ActualName, qualities));
84        else
85          scope.AddVariable(new Variable(scope.TranslateName(parentQualitiesInfo.FormalName), qualities));
86
87        CompositeOperation next = new CompositeOperation();
88        next.AddOperation(new AtomicOperation(SubOperators[0], scope));
89        next.AddOperation(new AtomicOperation(this, scope));
90        return next;
91      } else {
92        int crossoverEvents = qualities.Data.Length / parentsCount;
93        int childrenPerCrossoverEvent = scope.SubScopes.Count / crossoverEvents;
94        if (scope.SubScopes.Count % crossoverEvents != 0 ||
95          childrenPerCrossoverEvent < 1) throw new InvalidOperationException("OffspringAnalyzer: The number of children per crossover event has to be constant and >= 1");
96        // analyze offspring of all crossoverEvents
97        for (int i = 0; i < crossoverEvents; i++) {
98          double worstParent = double.MaxValue; // lowest quality parent
99          double bestParent = double.MinValue; // highest quality parent
100          for (int y = 0; y < parentsCount; y++) {
101            if (qualities.Data[i * parentsCount + y] < worstParent) worstParent = qualities.Data[i * parentsCount + y];
102            if (qualities.Data[i * parentsCount + y] > bestParent) bestParent = qualities.Data[i * parentsCount + y];
103          }
104          for (int j = 0; j < childrenPerCrossoverEvent; j++) {
105            IVariableInfo qualityInfo = GetVariableInfo("Quality");
106            double child = scope.SubScopes[i * childrenPerCrossoverEvent + j].GetVariableValue<DoubleData>(qualityInfo.FormalName, false).Data;
107            double threshold;
108
109            if (!maximize)
110              threshold = bestParent + (worstParent - bestParent) * compFact;
111            else
112              threshold = worstParent + (bestParent - worstParent) * compFact;
113
114            IVariableInfo successfulInfo = GetVariableInfo("SuccessfulChild");
115            BoolData successful;
116            if (((!maximize) && (child < threshold)) ||
117                ((maximize) && (child > threshold)))
118              successful = new BoolData(true);
119            else
120              successful = new BoolData(false);
121            scope.SubScopes[i * childrenPerCrossoverEvent + j].AddVariable(new Variable(scope.TranslateName(successfulInfo.FormalName), successful));
122          }
123        }
124
125        // remove parent qualities again
126        IVariableInfo parentQualitiesInfo = GetVariableInfo("ParentQualities");
127        if (parentQualitiesInfo.Local)
128          RemoveVariable(parentQualitiesInfo.ActualName);
129        else
130          scope.RemoveVariable(scope.TranslateName(parentQualitiesInfo.FormalName));
131
132        return null;
133      }
134    }
135  }
136}
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