1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2012 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.Linq;
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25 | using HeuristicLab.Common;
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26 | using HeuristicLab.Core;
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27 | using HeuristicLab.Data;
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28 | using HeuristicLab.Operators;
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29 | using HeuristicLab.Parameters;
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30 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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31 |
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32 | namespace HeuristicLab.Optimization.Operators {
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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.")]
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34 | [StorableClass]
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35 | public class WeightedParentsQualityComparator : SingleSuccessorOperator, ISubScopesQualityComparator {
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36 | public IValueLookupParameter<BoolValue> MaximizationParameter {
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37 | get { return (IValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
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38 | }
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39 | public ILookupParameter<DoubleValue> LeftSideParameter {
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40 | get { return (ILookupParameter<DoubleValue>)Parameters["LeftSide"]; }
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41 | }
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42 | public ILookupParameter<ItemArray<DoubleValue>> RightSideParameter {
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43 | get { return (ILookupParameter<ItemArray<DoubleValue>>)Parameters["RightSide"]; }
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44 | }
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45 | public ILookupParameter<BoolValue> ResultParameter {
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46 | get { return (ILookupParameter<BoolValue>)Parameters["Result"]; }
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47 | }
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48 | public ValueLookupParameter<DoubleValue> ComparisonFactorParameter {
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49 | get { return (ValueLookupParameter<DoubleValue>)Parameters["ComparisonFactor"]; }
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50 | }
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51 |
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52 | [StorableConstructor]
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53 | protected WeightedParentsQualityComparator(bool deserializing) : base(deserializing) { }
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54 | protected WeightedParentsQualityComparator(WeightedParentsQualityComparator original, Cloner cloner) : base(original, cloner) { }
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55 | public WeightedParentsQualityComparator()
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56 | : base() {
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57 | Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, false otherwise"));
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58 | Parameters.Add(new LookupParameter<DoubleValue>("LeftSide", "The quality of the child."));
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59 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("RightSide", "The qualities of the parents."));
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60 | Parameters.Add(new LookupParameter<BoolValue>("Result", "The result of the comparison: True means Quality is better, False means it is worse than parents."));
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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."));
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62 | }
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63 |
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64 | public override IDeepCloneable Clone(Cloner cloner) {
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65 | return new WeightedParentsQualityComparator(this, cloner);
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66 | }
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67 |
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68 | public override IOperation Apply() {
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69 | ItemArray<DoubleValue> rightQualities = RightSideParameter.ActualValue;
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70 | if (rightQualities.Length < 1) throw new InvalidOperationException(Name + ": No subscopes found.");
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71 | double compFact = ComparisonFactorParameter.ActualValue.Value;
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72 | bool maximization = MaximizationParameter.ActualValue.Value;
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73 | double leftQuality = LeftSideParameter.ActualValue.Value;
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74 |
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75 | double threshold = 0;
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76 |
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77 | #region Calculate threshold
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78 | if (rightQualities.Length == 2) { // this case will probably be used most often
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79 | double minQuality = Math.Min(rightQualities[0].Value, rightQualities[1].Value);
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80 | double maxQuality = Math.Max(rightQualities[0].Value, rightQualities[1].Value);
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81 | if (maximization)
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82 | threshold = minQuality + (maxQuality - minQuality) * compFact;
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83 | else
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84 | threshold = maxQuality - (maxQuality - minQuality) * compFact;
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85 | } else if (rightQualities.Length == 1) { // case for just one parent
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86 | threshold = rightQualities[0].Value;
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87 | } else { // general case extended to 3 or more parents
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88 | List<double> sortedQualities = rightQualities.Select(x => x.Value).ToList();
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89 | sortedQualities.Sort();
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90 | double minimumQuality = sortedQualities.First();
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91 |
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92 | double integral = 0;
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93 | for (int i = 0; i < sortedQualities.Count - 1; i++) {
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94 | integral += (sortedQualities[i] + sortedQualities[i + 1]) / 2.0; // sum of the trapezoid
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95 | }
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96 | integral -= minimumQuality * sortedQualities.Count;
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97 | if (integral == 0) threshold = sortedQualities[0]; // all qualities are equal
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98 | else {
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99 | double selectedArea = integral * (maximization ? compFact : (1 - compFact));
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100 | integral = 0;
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101 | for (int i = 0; i < sortedQualities.Count - 1; i++) {
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102 | double currentSliceArea = (sortedQualities[i] + sortedQualities[i + 1]) / 2.0;
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103 | double windowedSliceArea = currentSliceArea - minimumQuality;
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104 | if (windowedSliceArea == 0) continue;
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105 | integral += windowedSliceArea;
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106 | if (integral >= selectedArea) {
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107 | double factor = 1 - ((integral - selectedArea) / (windowedSliceArea));
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108 | threshold = sortedQualities[i] + (sortedQualities[i + 1] - sortedQualities[i]) * factor;
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109 | break;
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110 | }
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111 | }
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112 | }
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113 | }
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114 | #endregion
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115 |
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116 | bool result = maximization && leftQuality > threshold || !maximization && leftQuality < threshold;
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117 | BoolValue resultValue = ResultParameter.ActualValue;
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118 | if (resultValue == null) {
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119 | ResultParameter.ActualValue = new BoolValue(result);
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120 | } else {
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121 | resultValue.Value = result;
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122 | }
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123 |
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124 | return base.Apply();
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125 | }
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126 | }
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127 | }
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