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source: stable/HeuristicLab.Optimization.Operators/3.3/WeightedParentsQualityComparator.cs @ 11170

Last change on this file since 11170 was 11170, checked in by ascheibe, 10 years ago

#2115 updated copyright year in stable branch

File size: 6.2 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2014 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.Linq;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Operators;
29using HeuristicLab.Parameters;
30using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
31
32namespace HeuristicLab.Optimization.Operators {
33  [Item("WeightedParentsQualityComparator", "Compares the quality against that of its parents (assumes the parents are subscopes to the child scope). This operator works with any number of subscopes > 0.")]
34  [StorableClass]
35  public class WeightedParentsQualityComparator : SingleSuccessorOperator, ISubScopesQualityComparator {
36    public IValueLookupParameter<BoolValue> MaximizationParameter {
37      get { return (IValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
38    }
39    public ILookupParameter<DoubleValue> LeftSideParameter {
40      get { return (ILookupParameter<DoubleValue>)Parameters["LeftSide"]; }
41    }
42    public ILookupParameter<ItemArray<DoubleValue>> RightSideParameter {
43      get { return (ILookupParameter<ItemArray<DoubleValue>>)Parameters["RightSide"]; }
44    }
45    public ILookupParameter<BoolValue> ResultParameter {
46      get { return (ILookupParameter<BoolValue>)Parameters["Result"]; }
47    }
48    public ValueLookupParameter<DoubleValue> ComparisonFactorParameter {
49      get { return (ValueLookupParameter<DoubleValue>)Parameters["ComparisonFactor"]; }
50    }
51
52    [StorableConstructor]
53    protected WeightedParentsQualityComparator(bool deserializing) : base(deserializing) { }
54    protected WeightedParentsQualityComparator(WeightedParentsQualityComparator original, Cloner cloner) : base(original, cloner) { }
55    public WeightedParentsQualityComparator()
56      : base() {
57      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, false otherwise"));
58      Parameters.Add(new LookupParameter<DoubleValue>("LeftSide", "The quality of the child."));
59      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("RightSide", "The qualities of the parents."));
60      Parameters.Add(new LookupParameter<BoolValue>("Result", "The result of the comparison: True means Quality is better, False means it is worse than parents."));
61      Parameters.Add(new ValueLookupParameter<DoubleValue>("ComparisonFactor", "Determines if the quality should be compared to the better parent (1.0), to the worse (0.0) or to any linearly interpolated value between them."));
62    }
63
64    public override IDeepCloneable Clone(Cloner cloner) {
65      return new WeightedParentsQualityComparator(this, cloner);
66    }
67
68    public override IOperation Apply() {
69      ItemArray<DoubleValue> rightQualities = RightSideParameter.ActualValue;
70      if (rightQualities.Length < 1) throw new InvalidOperationException(Name + ": No subscopes found.");
71      double compFact = ComparisonFactorParameter.ActualValue.Value;
72      bool maximization = MaximizationParameter.ActualValue.Value;
73      double leftQuality = LeftSideParameter.ActualValue.Value;
74
75      double threshold = 0;
76
77      #region Calculate threshold
78      if (rightQualities.Length == 2) { // this case will probably be used most often
79        double minQuality = Math.Min(rightQualities[0].Value, rightQualities[1].Value);
80        double maxQuality = Math.Max(rightQualities[0].Value, rightQualities[1].Value);
81        if (maximization)
82          threshold = minQuality + (maxQuality - minQuality) * compFact;
83        else
84          threshold = maxQuality - (maxQuality - minQuality) * compFact;
85      } else if (rightQualities.Length == 1) { // case for just one parent
86        threshold = rightQualities[0].Value;
87      } else { // general case extended to 3 or more parents
88        List<double> sortedQualities = rightQualities.Select(x => x.Value).ToList();
89        sortedQualities.Sort();
90        double minimumQuality = sortedQualities.First();
91
92        double integral = 0;
93        for (int i = 0; i < sortedQualities.Count - 1; i++) {
94          integral += (sortedQualities[i] + sortedQualities[i + 1]) / 2.0; // sum of the trapezoid
95        }
96        integral -= minimumQuality * sortedQualities.Count;
97        if (integral == 0) threshold = sortedQualities[0]; // all qualities are equal
98        else {
99          double selectedArea = integral * (maximization ? compFact : (1 - compFact));
100          integral = 0;
101          for (int i = 0; i < sortedQualities.Count - 1; i++) {
102            double currentSliceArea = (sortedQualities[i] + sortedQualities[i + 1]) / 2.0;
103            double windowedSliceArea = currentSliceArea - minimumQuality;
104            if (windowedSliceArea == 0) continue;
105            integral += windowedSliceArea;
106            if (integral >= selectedArea) {
107              double factor = 1 - ((integral - selectedArea) / (windowedSliceArea));
108              threshold = sortedQualities[i] + (sortedQualities[i + 1] - sortedQualities[i]) * factor;
109              break;
110            }
111          }
112        }
113      }
114      #endregion
115
116      bool result = maximization && leftQuality > threshold || !maximization && leftQuality < threshold;
117      BoolValue resultValue = ResultParameter.ActualValue;
118      if (resultValue == null) {
119        ResultParameter.ActualValue = new BoolValue(result);
120      } else {
121        resultValue.Value = result;
122      }
123
124      return base.Apply();
125    }
126  }
127}
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