1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2015 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.Common;
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25 | using HeuristicLab.Core;
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26 | using HeuristicLab.Data;
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27 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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28 | using HeuristicLab.EvolutionTracking;
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29 | using HeuristicLab.Parameters;
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30 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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31 | using HeuristicLab.Random;
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32 |
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33 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Tracking {
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34 | [Item("SchemaEvaluator", "An operator that builds schemas based on the heredity relationship in the genealogy graph.")]
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35 | [StorableClass]
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36 | public class SchemaEvaluator : EvolutionTrackingOperator<ISymbolicExpressionTree> {
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37 | private const string MinimumSchemaFrequencyParameterName = "MinimumSchemaFrequency";
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38 | private const string MinimumPhenotypicSimilarityParameterName = "MinimumPhenotypicSimilarity";
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39 | private const string ReplacementRatioParameterName = "ReplacementRatio";
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40 | private const string SchemaParameterName = "Schema";
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41 | private const string PopulationSizeParameterName = "PopulationSize";
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42 | private const string RandomParameterName = "Random";
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43 | private const string EvaluatorParameterName = "Evaluator";
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44 | private const string ProblemDataParameterName = "ProblemData";
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45 | private const string InterpreterParameterName = "SymbolicExpressionTreeInterpreter";
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46 | private const string EstimationLimitsParameterName = "EstimationLimits";
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47 | private const string ApplyLinearScalingParameterName = "ApplyLinearScaling";
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48 | private const string MutatorParameterName = "Mutator";
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49 | private const string RandomReplacementParameterName = "RandomReplacement";
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50 |
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51 | private readonly SymbolicExpressionTreePhenotypicSimilarityCalculator calculator = new SymbolicExpressionTreePhenotypicSimilarityCalculator();
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52 |
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53 | private readonly ISymbolicExpressionTreeNodeEqualityComparer comp = new SymbolicExpressionTreeNodeEqualityComparer {
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54 | MatchConstantValues = false,
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55 | MatchVariableWeights = false,
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56 | MatchVariableNames = true
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57 | };
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58 |
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59 | private readonly QueryMatch qm;
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60 |
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61 | #region parameters
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62 | public ILookupParameter<ISymbolicDataAnalysisSingleObjectiveEvaluator<IRegressionProblemData>> EvaluatorParameter {
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63 | get { return (ILookupParameter<ISymbolicDataAnalysisSingleObjectiveEvaluator<IRegressionProblemData>>)Parameters[EvaluatorParameterName]; }
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64 | }
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65 | public ILookupParameter<IRegressionProblemData> ProblemDataParameter {
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66 | get { return (ILookupParameter<IRegressionProblemData>)Parameters[ProblemDataParameterName]; }
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67 | }
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68 | public ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter> InterpreterParameter {
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69 | get { return (ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>)Parameters[InterpreterParameterName]; }
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70 | }
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71 | public ILookupParameter<DoubleLimit> EstimationLimitsParameter {
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72 | get { return (ILookupParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
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73 | }
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74 | public ILookupParameter<BoolValue> ApplyLinearScalingParameter {
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75 | get { return (ILookupParameter<BoolValue>)Parameters[ApplyLinearScalingParameterName]; }
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76 | }
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77 | public ILookupParameter<BoolValue> RandomReplacementParameter {
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78 | get { return (ILookupParameter<BoolValue>)Parameters[RandomReplacementParameterName]; }
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79 | }
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80 | public ILookupParameter<ISymbolicExpressionTreeManipulator> MutatorParameter {
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81 | get { return (ILookupParameter<ISymbolicExpressionTreeManipulator>)Parameters[MutatorParameterName]; }
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82 | }
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83 | public ILookupParameter<IRandom> RandomParameter {
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84 | get { return (ILookupParameter<IRandom>)Parameters[RandomParameterName]; }
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85 | }
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86 | public ILookupParameter<IntValue> PopulationSizeParameter {
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87 | get { return (ILookupParameter<IntValue>)Parameters[PopulationSizeParameterName]; }
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88 | }
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89 | public ILookupParameter<ISymbolicExpressionTree> SchemaParameter {
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90 | get { return (ILookupParameter<ISymbolicExpressionTree>)Parameters[SchemaParameterName]; }
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91 | }
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92 | public ILookupParameter<PercentValue> MinimumSchemaFrequencyParameter {
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93 | get { return (ILookupParameter<PercentValue>)Parameters[MinimumSchemaFrequencyParameterName]; }
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94 | }
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95 | public ILookupParameter<PercentValue> ReplacementRatioParameter {
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96 | get { return (ILookupParameter<PercentValue>)Parameters[ReplacementRatioParameterName]; }
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97 | }
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98 | public ILookupParameter<PercentValue> MinimumPhenotypicSimilarityParameter {
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99 | get { return (ILookupParameter<PercentValue>)Parameters[MinimumPhenotypicSimilarityParameterName]; }
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100 | }
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101 | #endregion
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102 |
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103 | #region parameter properties
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104 | public PercentValue MinimumSchemaFrequency {
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105 | get { return MinimumSchemaFrequencyParameter.ActualValue; }
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106 | }
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107 |
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108 | public PercentValue ReplacementRatio {
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109 | get { return ReplacementRatioParameter.ActualValue; }
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110 | }
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111 |
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112 | public PercentValue MinimumPhenotypicSimilarity {
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113 | get { return MinimumPhenotypicSimilarityParameter.ActualValue; }
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114 | }
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115 |
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116 | public BoolValue RandomReplacement {
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117 | get { return RandomReplacementParameter.ActualValue; }
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118 | }
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119 | #endregion
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120 |
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121 | public SchemaEvaluator() {
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122 | qm = new QueryMatch(comp) { MatchParents = true };
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123 |
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124 | Parameters.Add(new LookupParameter<ISymbolicExpressionTree>(SchemaParameterName, "The current schema to be evaluated"));
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125 | Parameters.Add(new LookupParameter<PercentValue>(MinimumSchemaFrequencyParameterName));
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126 | Parameters.Add(new LookupParameter<PercentValue>(ReplacementRatioParameterName));
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127 | Parameters.Add(new LookupParameter<PercentValue>(MinimumPhenotypicSimilarityParameterName));
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128 | Parameters.Add(new LookupParameter<ISymbolicExpressionTree>(PopulationSizeParameterName));
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129 | Parameters.Add(new LookupParameter<IRandom>(RandomParameterName));
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130 | Parameters.Add(new LookupParameter<ISymbolicDataAnalysisSingleObjectiveEvaluator<IRegressionProblemData>>(EvaluatorParameterName));
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131 | Parameters.Add(new LookupParameter<IRegressionProblemData>(ProblemDataParameterName));
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132 | Parameters.Add(new LookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(InterpreterParameterName));
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133 | Parameters.Add(new LookupParameter<DoubleLimit>(EstimationLimitsParameterName));
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134 | Parameters.Add(new LookupParameter<BoolValue>(ApplyLinearScalingParameterName));
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135 | Parameters.Add(new LookupParameter<ISymbolicExpressionTreeManipulator>(MutatorParameterName));
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136 | Parameters.Add(new LookupParameter<BoolValue>(RandomReplacementParameterName));
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137 | }
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138 |
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139 | protected SchemaEvaluator(SchemaEvaluator original, Cloner cloner) : base(original, cloner) {
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140 | this.comp = original.comp;
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141 | this.qm = original.qm;
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142 | }
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143 |
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144 | public override IDeepCloneable Clone(Cloner cloner) {
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145 | return new SchemaEvaluator(this, cloner);
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146 | }
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147 |
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148 | private static double CalculatePhenotypicSimilarity(ScopeList individuals, SymbolicExpressionTreePhenotypicSimilarityCalculator calculator) {
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149 | double similarity = 0;
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150 | int count = individuals.Count;
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151 | for (int i = 0; i < count - 1; ++i) {
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152 | for (int j = i + 1; j < count; ++j) {
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153 | similarity += calculator.CalculateSolutionSimilarity(individuals[i], individuals[j]);
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154 | }
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155 | }
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156 | return similarity / (count * (count - 1) / 2.0);
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157 | }
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158 |
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159 | public override IOperation Apply() {
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160 | var individuals = ExecutionContext.Scope.SubScopes; // the scopes represent the individuals
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161 |
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162 | var random = RandomParameter.ActualValue;
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163 | var mutator = MutatorParameter.ActualValue;
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164 | var evaluator = EvaluatorParameter.ActualValue;
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165 | var updateEstimatedValuesOperator = new UpdateEstimatedValuesOperator();
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166 |
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167 | var s = SchemaParameter.ActualValue;
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168 | var matchingIndividuals = new ScopeList(from ind in individuals
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169 | let t = (ISymbolicExpressionTree)ind.Variables["SymbolicExpressionTree"].Value
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170 | where qm.Match(t, s)
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171 | select ind);
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172 |
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173 | if (matchingIndividuals.Count < MinimumSchemaFrequency.Value * individuals.Count)
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174 | return base.Apply();
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175 |
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176 | var similarity = CalculatePhenotypicSimilarity(matchingIndividuals, calculator);
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177 | if (similarity < MinimumPhenotypicSimilarity.Value)
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178 | return base.Apply();
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179 |
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180 | var oc = new OperationCollection();
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181 |
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182 | int n = (int)Math.Round(matchingIndividuals.Count * ReplacementRatio.Value);
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183 | var individualsToReplace = RandomReplacement.Value ? matchingIndividuals.SampleRandomWithoutRepetition(random, n)
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184 | : matchingIndividuals.OrderBy(x => (DoubleValue)x.Variables["Quality"].Value).Take(n);
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185 | foreach (var ind in individualsToReplace) {
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186 | var mutatorOp = ExecutionContext.CreateChildOperation(mutator, ind);
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187 | var evaluatorOp = ExecutionContext.CreateChildOperation(evaluator, ind);
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188 | var updateEstimatedValuesOp = ExecutionContext.CreateChildOperation(updateEstimatedValuesOperator, ind);
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189 | oc.Add(mutatorOp);
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190 | oc.Add(evaluatorOp);
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191 | oc.Add(updateEstimatedValuesOp);
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192 | }
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193 |
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194 | return new OperationCollection(oc, base.Apply());
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195 | }
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196 | }
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197 | }
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