1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2014 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.Linq;
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24 | using HeuristicLab.Analysis;
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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.Encodings.PermutationEncoding;
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29 | using HeuristicLab.Operators;
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30 | using HeuristicLab.Optimization;
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31 | using HeuristicLab.Optimization.Operators;
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32 | using HeuristicLab.Parameters;
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33 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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34 | using HeuristicLab.PluginInfrastructure;
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35 |
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36 | namespace HeuristicLab.Algorithms.VOffspringSelectionGeneticAlgorithm {
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37 | [Item("UnwantedMutationsComparator", "Compares the similarity 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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38 | [StorableClass]
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39 | public class UnwantedMutationsComparator : SingleSuccessorOperator, ISubScopesQualityComparatorOperator, ISimilarityBasedOperator {
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40 | [Storable]
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41 | public ISolutionSimilarityCalculator SimilarityCalculator { get; set; }
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42 | public IValueLookupParameter<BoolValue> MaximizationParameter {
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43 | get { return (IValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
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44 | }
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45 | public ILookupParameter<DoubleValue> LeftSideParameter {
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46 | get { return (ILookupParameter<DoubleValue>)Parameters["LeftSide"]; }
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47 | }
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48 | public ILookupParameter<ItemArray<DoubleValue>> RightSideParameter {
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49 | get { return (ILookupParameter<ItemArray<DoubleValue>>)Parameters["RightSide"]; }
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50 | }
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51 | public ILookupParameter<BoolValue> ResultParameter {
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52 | get { return (ILookupParameter<BoolValue>)Parameters["Result"]; }
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53 | }
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54 | public ValueLookupParameter<DoubleValue> ComparisonFactorParameter {
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55 | get { return (ValueLookupParameter<DoubleValue>)Parameters["ComparisonFactor"]; }
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56 | }
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57 | public ValueLookupParameter<DoubleValue> DiversityComparisonFactorParameter {
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58 | get { return (ValueLookupParameter<DoubleValue>)Parameters["DiversityComparisonFactor"]; }
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59 | }
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60 | private ValueLookupParameter<DoubleValue> ComparisonFactorLowerBoundParameter {
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61 | get { return (ValueLookupParameter<DoubleValue>)Parameters["DiversityComparisonFactorLowerBound"]; }
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62 | }
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63 | private ValueLookupParameter<DoubleValue> ComparisonFactorUpperBoundParameter {
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64 | get { return (ValueLookupParameter<DoubleValue>)Parameters["DiversityComparisonFactorUpperBound"]; }
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65 | }
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66 | public IConstrainedValueParameter<IDiscreteDoubleValueModifier> ComparisonFactorModifierParameter {
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67 | get { return (IConstrainedValueParameter<IDiscreteDoubleValueModifier>)Parameters["ComparisonFactorModifier"]; }
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68 | }
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69 | public ValueLookupParameter<ResultCollection> ResultsParameter {
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70 | get { return (ValueLookupParameter<ResultCollection>)Parameters["Results"]; }
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71 | }
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72 | public ILookupParameter<IntValue> GenerationsParameter {
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73 | get { return (LookupParameter<IntValue>)Parameters["Generations"]; }
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74 | }
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75 | public ValueParameter<BoolValue> EnableDivCriteriaParameter {
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76 | get { return (ValueParameter<BoolValue>)Parameters["EnableDivCriteria"]; }
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77 | }
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78 | public ValueParameter<BoolValue> EnableQualityCriteriaParameter {
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79 | get { return (ValueParameter<BoolValue>)Parameters["EnableQualityCriteria"]; }
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80 | }
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81 |
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82 | private const string spDetailsParameterName = "SPDetails";
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83 | private const string divDataRowName = "DiversitySuccessCount";
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84 | private const string qualityDataRowName = "QualitySuccessCount";
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85 | private const string divFailDataRowName = "DiversityFailCount";
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86 | private const string qualityFailDataRowName = "QualityFailCount";
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87 | private const string overallCountDataRowName = "OverallCount";
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88 | private const string successCountDataRowName = "SuccessCount";
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89 | private const string unwantedMutationsDataRowName = "UnwantedMutations";
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90 |
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91 | [Storable]
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92 | private int currentGeneration;
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93 | [Storable]
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94 | private int divCount;
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95 | [Storable]
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96 | private int qualityCount;
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97 | [Storable]
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98 | private int badQualityCount;
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99 | [Storable]
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100 | private int badDivCount;
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101 | [Storable]
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102 | private int overallCount;
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103 | [Storable]
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104 | private int successCount;
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105 | [Storable]
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106 | private double umRatio;
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107 |
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108 | [StorableConstructor]
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109 | protected UnwantedMutationsComparator(bool deserializing) : base(deserializing) { }
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110 | protected UnwantedMutationsComparator(UnwantedMutationsComparator original, Cloner cloner)
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111 | : base(original, cloner) {
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112 | SimilarityCalculator = cloner.Clone(original.SimilarityCalculator);
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113 | currentGeneration = original.currentGeneration;
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114 | divCount = original.divCount;
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115 | qualityCount = original.qualityCount;
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116 | overallCount = original.overallCount;
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117 | successCount = original.successCount;
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118 | badDivCount = original.badDivCount;
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119 | badQualityCount = original.badQualityCount;
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120 | umRatio = original.umRatio;
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121 | }
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122 | public UnwantedMutationsComparator()
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123 | : base() {
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124 | Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, false otherwise"));
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125 | Parameters.Add(new LookupParameter<DoubleValue>("LeftSide", "The quality of the child."));
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126 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("RightSide", "The qualities of the parents."));
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127 | 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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128 | 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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129 | Parameters.Add(new ValueLookupParameter<DoubleValue>("DiversityComparisonFactor", "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.", new DoubleValue(0.0)));
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130 | Parameters.Add(new ValueLookupParameter<DoubleValue>("DiversityComparisonFactorLowerBound", "The lower bound of the comparison factor (start).", new DoubleValue(0.7)));
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131 | Parameters.Add(new ValueLookupParameter<DoubleValue>("DiversityComparisonFactorUpperBound", "The upper bound of the comparison factor (end).", new DoubleValue(1.0)));
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132 | Parameters.Add(new OptionalConstrainedValueParameter<IDiscreteDoubleValueModifier>("ComparisonFactorModifier", "The operator used to modify the comparison factor.", new ItemSet<IDiscreteDoubleValueModifier>(new IDiscreteDoubleValueModifier[] { new LinearDiscreteDoubleValueModifier() }), new LinearDiscreteDoubleValueModifier()));
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133 | Parameters.Add(new ValueLookupParameter<ResultCollection>("Results", "The result collection where the population diversity analysis results should be stored."));
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134 | Parameters.Add(new LookupParameter<IntValue>("Generations", "The current number of generations."));
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135 | Parameters.Add(new ValueParameter<BoolValue>("EnableDivCriteria", "Use diversity as additional offspring selection criteria.", new BoolValue(true)));
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136 | Parameters.Add(new ValueParameter<BoolValue>("EnableQualityCriteria", "Use quality as additional offspring selection criteria.", new BoolValue(false)));
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137 |
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138 | foreach (IDiscreteDoubleValueModifier modifier in ApplicationManager.Manager.GetInstances<IDiscreteDoubleValueModifier>().OrderBy(x => x.Name))
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139 | ComparisonFactorModifierParameter.ValidValues.Add(modifier);
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140 | IDiscreteDoubleValueModifier linearModifier = ComparisonFactorModifierParameter.ValidValues.FirstOrDefault(x => x.GetType().Name.Equals("LinearDiscreteDoubleValueModifier"));
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141 | if (linearModifier != null) ComparisonFactorModifierParameter.Value = linearModifier;
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142 | ParameterizeComparisonFactorModifiers();
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143 | }
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144 |
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145 | public override IDeepCloneable Clone(Cloner cloner) {
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146 | return new UnwantedMutationsComparator(this, cloner);
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147 | }
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148 |
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149 | private void ParameterizeComparisonFactorModifiers() {
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150 | //TODO: does not work if Generations parameter names are changed
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151 | foreach (IDiscreteDoubleValueModifier modifier in ComparisonFactorModifierParameter.ValidValues) {
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152 | modifier.IndexParameter.ActualName = "Generations";
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153 | modifier.EndIndexParameter.ActualName = "MaximumGenerations";
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154 | modifier.EndValueParameter.ActualName = ComparisonFactorUpperBoundParameter.Name;
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155 | modifier.StartIndexParameter.Value = new IntValue(0);
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156 | modifier.StartValueParameter.ActualName = ComparisonFactorLowerBoundParameter.Name;
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157 | modifier.ValueParameter.ActualName = "DiversityComparisonFactor";
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158 | }
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159 | }
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160 |
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161 | public override IOperation Apply() {
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162 | ItemArray<DoubleValue> rightQualities = RightSideParameter.ActualValue;
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163 | if (rightQualities.Length < 1) throw new InvalidOperationException(Name + ": No subscopes found.");
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164 | double compFact = ComparisonFactorParameter.ActualValue.Value;
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165 | double diversityComFact = DiversityComparisonFactorParameter.ActualValue.Value;
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166 | bool maximization = MaximizationParameter.ActualValue.Value;
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167 | double leftQuality = LeftSideParameter.ActualValue.Value;
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168 | double threshold = 0;
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169 |
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170 | DataTable spDetailsTable;
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171 | if (ResultsParameter.ActualValue.ContainsKey(spDetailsParameterName)) {
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172 | spDetailsTable = (DataTable)ResultsParameter.ActualValue[spDetailsParameterName].Value;
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173 | } else {
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174 | spDetailsTable = new DataTable(spDetailsParameterName);
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175 | spDetailsTable.Rows.Add(new DataRow(divDataRowName));
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176 | spDetailsTable.Rows.Add(new DataRow(qualityDataRowName));
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177 | spDetailsTable.Rows.Add(new DataRow(overallCountDataRowName));
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178 | spDetailsTable.Rows.Add(new DataRow(successCountDataRowName));
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179 | spDetailsTable.Rows.Add(new DataRow(divFailDataRowName));
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180 | spDetailsTable.Rows.Add(new DataRow(qualityFailDataRowName));
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181 | spDetailsTable.Rows.Add(new DataRow(unwantedMutationsDataRowName));
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182 | ResultsParameter.ActualValue.Add(new Result(spDetailsParameterName, spDetailsTable));
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183 | }
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184 |
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185 | if (GenerationsParameter.ActualValue.Value != currentGeneration) {
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186 | spDetailsTable.Rows[divDataRowName].Values.Add(divCount);
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187 | divCount = 0;
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188 | spDetailsTable.Rows[qualityDataRowName].Values.Add(qualityCount);
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189 | qualityCount = 0;
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190 | spDetailsTable.Rows[overallCountDataRowName].Values.Add(overallCount);
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191 | spDetailsTable.Rows[successCountDataRowName].Values.Add(successCount);
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192 | successCount = 0;
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193 | spDetailsTable.Rows[qualityFailDataRowName].Values.Add(badQualityCount);
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194 | badQualityCount = 0;
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195 | spDetailsTable.Rows[divFailDataRowName].Values.Add(badDivCount);
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196 | badDivCount = 0;
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197 | if (overallCount != 0) {
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198 | spDetailsTable.Rows[unwantedMutationsDataRowName].Values.Add(umRatio / (double)overallCount);
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199 | }
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200 | umRatio = 0.0;
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201 | overallCount = 0;
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202 | currentGeneration = GenerationsParameter.ActualValue.Value;
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203 | }
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204 |
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205 | string solutionVariableName = ((ISingleObjectiveSolutionSimilarityCalculator)SimilarityCalculator).SolutionVariableName;
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206 | double resultVal = AnalyzeUnwantedMutations(ExecutionContext.Scope.SubScopes[0],
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207 | ExecutionContext.Scope.SubScopes[1], ExecutionContext.Scope, solutionVariableName);
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208 |
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209 | bool resultDiversity = resultVal < diversityComFact;
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210 | umRatio += resultVal;
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211 |
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212 | double minQuality = Math.Min(rightQualities[0].Value, rightQualities[1].Value);
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213 | double maxQuality = Math.Max(rightQualities[0].Value, rightQualities[1].Value);
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214 | if (maximization)
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215 | threshold = minQuality + (maxQuality - minQuality) * compFact;
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216 | else
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217 | threshold = maxQuality - (maxQuality - minQuality) * compFact;
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218 |
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219 | bool result = maximization && leftQuality > threshold || !maximization && leftQuality < threshold;
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220 |
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221 | //collect statistics
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222 | if (result) {
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223 | qualityCount++;
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224 | } else {
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225 | badQualityCount++;
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226 | }
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227 | if (resultDiversity) {
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228 | divCount++;
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229 | } else {
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230 | badDivCount++;
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231 | }
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232 | if (result && resultDiversity) {
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233 | successCount++;
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234 | }
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235 | overallCount++;
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236 |
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237 | if (EnableDivCriteriaParameter.Value.Value && !EnableQualityCriteriaParameter.Value.Value) {
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238 | result = resultDiversity;
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239 | }
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240 | //use diveristiy criteria or not
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241 | if (EnableDivCriteriaParameter.Value.Value && EnableQualityCriteriaParameter.Value.Value) {
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242 | result = result && resultDiversity;
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243 | }
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244 |
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245 | BoolValue resultValue = ResultParameter.ActualValue;
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246 | if (resultValue == null) {
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247 | ResultParameter.ActualValue = new BoolValue(result);
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248 | } else {
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249 | resultValue.Value = result;
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250 | }
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251 |
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252 | //like the placeholder, though we create child operations
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253 | OperationCollection next = new OperationCollection(base.Apply());
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254 | IOperator op = ComparisonFactorModifierParameter.Value;
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255 | if (op != null)
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256 | next.Insert(0, ExecutionContext.CreateChildOperation(op));
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257 | return next;
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258 | }
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259 |
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260 | public double AnalyzeUnwantedMutations(IScope parent1, IScope parent2, IScope child, string solutionVariableName) {
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261 | Permutation p1 = parent1.Variables[solutionVariableName].Value as Permutation;
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262 | Permutation p2 = parent2.Variables[solutionVariableName].Value as Permutation;
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263 | Permutation c = child.Variables[solutionVariableName].Value as Permutation;
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264 |
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265 | return AnalyzeUnwantedMutations(p1, p2, c);
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266 | }
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267 |
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268 | private double AnalyzeUnwantedMutations(Permutation parent1, Permutation parent2, Permutation child) {
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269 | int cnt = 0;
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270 | int[] edgesP1 = CalculateEdgesVector(parent1);
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271 | int[] edgesP2 = CalculateEdgesVector(parent2);
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272 | int[] edgesC = CalculateEdgesVector(child);
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273 |
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274 | for (int i = 0; i < edgesP1.Length; i++) {
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275 | if (edgesC[i] != edgesP1[i] &&
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276 | edgesC[i] != edgesP2[i] &&
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277 | edgesP1[edgesC[i]] != i &&
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278 | edgesP2[edgesC[i]] != i) {
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279 | cnt += 1;
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280 | }
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281 | }
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282 |
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283 | //reverse so that it matches the other diversity charts
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284 | return 1.0 - (((double)cnt) / parent1.Length);
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285 | }
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286 |
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287 | //copied from PermutationEqualityComparer
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288 | private int[] CalculateEdgesVector(Permutation permutation) {
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289 | // transform path representation into adjacency representation
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290 | int[] edgesVector = new int[permutation.Length];
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291 | for (int i = 0; i < permutation.Length - 1; i++)
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292 | edgesVector[permutation[i]] = permutation[i + 1];
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293 | edgesVector[permutation[permutation.Length - 1]] = permutation[0];
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294 | return edgesVector;
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295 | }
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296 | }
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297 | }
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