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.Drawing;
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24 | using System.Globalization;
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25 | using System.Linq;
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26 | using System.Text;
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27 | using System.Threading;
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28 | using HeuristicLab.Common;
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29 | using HeuristicLab.Core;
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30 | using HeuristicLab.Data;
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31 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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32 | using HeuristicLab.Operators;
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33 | using HeuristicLab.Optimization;
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34 | using HeuristicLab.Parameters;
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35 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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36 | using HeuristicLab.Problems.DataAnalysis;
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37 | using HeuristicLab.Problems.DataAnalysis.Symbolic;
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38 | // type definitions for ease of use
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39 | using CloneMapType = HeuristicLab.Core.ItemDictionary<HeuristicLab.Core.IItem, HeuristicLab.Core.IItem>;
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40 | using TraceMapType = HeuristicLab.Core.ItemDictionary<HeuristicLab.Core.IItem, HeuristicLab.Core.IItemList<HeuristicLab.Core.IItem>>;
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41 |
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42 | namespace HeuristicLab.EvolutionaryTracking {
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43 | /// <summary>
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44 | /// An operator that tracks the genealogy of every individual
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45 | /// </summary>
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46 | [Item("SymbolicExpressionTreeGenealogyAnalyzer", "An operator that tracks tree lengths of Symbolic Expression Trees")]
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47 | [StorableClass]
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48 | public sealed class SymbolicExpressionTreeGenealogyAnalyzer : SingleSuccessorOperator, IAnalyzer {
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49 | private const string UpdateIntervalParameterName = "UpdateInterval";
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50 | private const string UpdateCounterParameterName = "UpdateCounter";
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51 | private const string ResultsParameterName = "Results";
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52 | private const string ElitesParameterName = "Elites";
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53 | private const string GenerationsParameterName = "Generations";
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54 | private const string MaximumGenerationsParameterName = "MaximumGenerations";
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55 | private const string MaximumSelectionPressureParameterName = "MaximumSelectionPressure";
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56 | private const string SelectionPressureParameterName = "SelectionPressure";
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57 | private const string GlobalTraceMapParameterName = "GlobalTraceMap";
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58 | private const string GlobalCloneMapParameterName = "GlobalCloneMap";
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59 | private const string PopulationGraphResultParameterName = "PopulationGraph";
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60 | private const string PopulationGraphResultParameterDescription = "Individual lineages";
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61 | private const string SymbolicExpressionInterpreterParameterName = "SymbolicExpressionTreeInterpreter";
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62 | private const string SymbolicRegressionProblemDataParameterName = "ProblemData";
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63 | private const string SymbolicDataAnalysisProblemEvaluatorParameterName = "Evaluator";
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64 |
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65 | #region Parameter properties
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66 | public ValueParameter<IntValue> UpdateIntervalParameter {
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67 | get { return (ValueParameter<IntValue>)Parameters[UpdateIntervalParameterName]; }
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68 | }
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69 | public ValueParameter<IntValue> UpdateCounterParameter {
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70 | get { return (ValueParameter<IntValue>)Parameters[UpdateCounterParameterName]; }
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71 | }
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72 | public LookupParameter<ResultCollection> ResultsParameter {
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73 | get { return (LookupParameter<ResultCollection>)Parameters[ResultsParameterName]; }
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74 | }
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75 | public LookupParameter<IntValue> ElitesParameter {
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76 | get { return (LookupParameter<IntValue>)Parameters[ElitesParameterName]; }
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77 | }
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78 | public LookupParameter<IntValue> GenerationsParameter {
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79 | get { return (LookupParameter<IntValue>)Parameters[GenerationsParameterName]; }
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80 | }
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81 | public LookupParameter<IntValue> MaximumGenerationsParameter {
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82 | get { return (LookupParameter<IntValue>)Parameters[MaximumGenerationsParameterName]; }
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83 | }
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84 | public LookupParameter<DoubleValue> SelectionPressureParameter {
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85 | get { return (LookupParameter<DoubleValue>)Parameters[SelectionPressureParameterName]; }
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86 | }
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87 | public LookupParameter<DoubleValue> MaximumSelectionPressureParameter {
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88 | get { return (LookupParameter<DoubleValue>)Parameters[MaximumSelectionPressureParameterName]; }
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89 | }
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90 | // problem data, interpreter and evaluator
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91 | public LookupParameter<SymbolicDataAnalysisExpressionTreeInterpreter> SymbolicExpressionInterpreterParameter {
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92 | get { return (LookupParameter<SymbolicDataAnalysisExpressionTreeInterpreter>)Parameters[SymbolicExpressionInterpreterParameterName]; }
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93 | }
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94 | public LookupParameter<RegressionProblemData> SymbolicRegressionProblemDataParameter {
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95 | get { return (LookupParameter<RegressionProblemData>)Parameters[SymbolicRegressionProblemDataParameterName]; }
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96 | }
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97 | public LookupParameter<IEvaluator> SymbolicDataAnalysisProblemEvaluatorParameter {
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98 | get { return (LookupParameter<IEvaluator>)Parameters[SymbolicDataAnalysisProblemEvaluatorParameterName]; }
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99 | }
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100 | // genealogy global parameters
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101 | public LookupParameter<TraceMapType> GlobalTraceMapParameter {
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102 | get { return (LookupParameter<TraceMapType>)Parameters[GlobalTraceMapParameterName]; }
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103 | }
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104 | public LookupParameter<CloneMapType> GlobalCloneMapParameter {
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105 | get { return (LookupParameter<CloneMapType>)Parameters[GlobalCloneMapParameterName]; }
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106 | }
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107 | #endregion
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108 |
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109 | #region Properties
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110 | public bool EnabledByDefault {
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111 | get { return true; }
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112 | }
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113 | public IntValue UpdateInterval {
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114 | get { return UpdateIntervalParameter.Value; }
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115 | }
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116 | public IntValue UpdateCounter {
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117 | get { return UpdateCounterParameter.Value; }
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118 | }
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119 | public ResultCollection Results {
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120 | get { return ResultsParameter.ActualValue; }
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121 | }
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122 | public IntValue Elites {
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123 | get { return ElitesParameter.ActualValue; }
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124 | }
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125 | public IntValue Generations {
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126 | get { return GenerationsParameter.ActualValue; }
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127 | }
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128 | public IntValue MaximumGenerations {
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129 | get { return MaximumGenerationsParameter.ActualValue; }
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130 | }
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131 | public DoubleValue SelectionPressure {
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132 | get { return SelectionPressureParameter.ActualValue; }
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133 | }
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134 | public DoubleValue MaximumSelectionPressure {
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135 | get { return MaximumSelectionPressureParameter.ActualValue; }
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136 | }
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137 | public CloneMapType GlobalCloneMap {
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138 | get { return GlobalCloneMapParameter.ActualValue; }
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139 | }
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140 | public TraceMapType GlobalTraceMap {
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141 | get { return GlobalTraceMapParameter.ActualValue; }
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142 | }
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143 | public SymbolicDataAnalysisExpressionTreeInterpreter SymbolicExpressionInterpreter {
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144 | get { return SymbolicExpressionInterpreterParameter.ActualValue; }
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145 | }
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146 | public RegressionProblemData SymbolicRegressionProblemData {
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147 | get { return SymbolicRegressionProblemDataParameter.ActualValue; }
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148 | }
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149 | public IEvaluator SymbolicDataAnalysisEvaluator {
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150 | get { return SymbolicDataAnalysisProblemEvaluatorParameter.ActualValue; }
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151 | }
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152 | #endregion
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153 |
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154 | [StorableConstructor]
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155 | private SymbolicExpressionTreeGenealogyAnalyzer(bool deserializing)
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156 | : base() {
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157 | }
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158 | private SymbolicExpressionTreeGenealogyAnalyzer(SymbolicExpressionTreeGenealogyAnalyzer original, Cloner cloner)
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159 | : base(original, cloner) {
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160 | }
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161 | public override IDeepCloneable Clone(Cloner cloner) {
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162 | return new SymbolicExpressionTreeGenealogyAnalyzer(this, cloner);
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163 | }
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164 | public SymbolicExpressionTreeGenealogyAnalyzer()
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165 | : base() {
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166 | Parameters.Add(new LookupParameter<IntValue>(ElitesParameterName, "The number of elites."));
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167 | Parameters.Add(new LookupParameter<IntValue>(GenerationsParameterName, "The number of generations so far."));
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168 | Parameters.Add(new LookupParameter<IntValue>(MaximumGenerationsParameterName, "The maximum number of generations"));
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169 | Parameters.Add(new LookupParameter<DoubleValue>(SelectionPressureParameterName, "The current selection (ony for OSGA)"));
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170 | Parameters.Add(new LookupParameter<DoubleValue>(MaximumSelectionPressureParameterName, "Maximum allowed value of selection pressure."));
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171 | Parameters.Add(new ValueParameter<IntValue>(UpdateIntervalParameterName, "The interval in which the tree length analysis should be applied.", new IntValue(1)));
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172 | Parameters.Add(new ValueParameter<IntValue>(UpdateCounterParameterName, "The value which counts how many times the operator was called since the last update", new IntValue(0)));
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173 | Parameters.Add(new LookupParameter<TraceMapType>(GlobalTraceMapParameterName, "A global cache containing the whole genealogy."));
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174 | Parameters.Add(new LookupParameter<CloneMapType>(GlobalCloneMapParameterName, "A global map keeping track of trees and their clones (made during selection)."));
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175 | Parameters.Add(new ValueLookupParameter<ResultCollection>(ResultsParameterName, "The results collection where the analysis values should be stored."));
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176 | Parameters.Add(new LookupParameter<SymbolicDataAnalysisExpressionTreeInterpreter>(SymbolicExpressionInterpreterParameterName, "Interpreter for symbolic expression trees"));
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177 | Parameters.Add(new LookupParameter<RegressionProblemData>(SymbolicRegressionProblemDataParameterName, "The symbolic data analysis problem."));
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178 | Parameters.Add(new LookupParameter<IEvaluator>(SymbolicDataAnalysisProblemEvaluatorParameterName, "The fitness evaluator"));
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179 |
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180 | UpdateCounterParameter.Hidden = true;
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181 | UpdateIntervalParameter.Hidden = true;
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182 | }
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183 |
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184 | [StorableHook(HookType.AfterDeserialization)]
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185 | private void AfterDeserialization() {
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186 | // check if all the parameters are present and accounted for
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187 | if (!Parameters.ContainsKey(UpdateIntervalParameterName)) {
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188 | Parameters.Add(new ValueParameter<IntValue>(UpdateIntervalParameterName, "The interval in which the tree length analysis should be applied.", new IntValue(1)));
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189 | }
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190 | if (Parameters.ContainsKey(UpdateCounterParameterName)) return;
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191 | Parameters.Add(new ValueParameter<IntValue>(UpdateCounterParameterName, "The value which counts how many times the operator was called since the last update", new IntValue(0)));
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192 | UpdateCounterParameter.Hidden = true;
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193 | }
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194 |
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195 | #region IStatefulItem members
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196 | public override void InitializeState() {
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197 | base.InitializeState();
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198 | UpdateCounter.Value = 0;
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199 | }
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200 |
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201 | public override void ClearState() {
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202 | base.ClearState();
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203 | UpdateCounter.Value = 0;
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204 | }
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205 | #endregion
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206 |
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207 | public override IOperation Apply() {
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208 | UpdateCounter.Value++;
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209 | // the analyzer runs periodically, every 'updateInterval' times
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210 | if (UpdateCounter.Value == UpdateInterval.Value) {
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211 | UpdateCounter.Value = 0; // reset counter
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212 |
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213 | var gScope = ExecutionContext.Scope;
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214 | while (gScope.Parent != null) gScope = gScope.Parent;
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215 | SymbolicExpressionTreeGenealogyGraph graph;
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216 | if (!Results.ContainsKey(PopulationGraphResultParameterName)) {
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217 | graph = new SymbolicExpressionTreeGenealogyGraph();
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218 | Results.Add(new Result(PopulationGraphResultParameterName, PopulationGraphResultParameterDescription, graph));
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219 | } else {
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220 | graph = (SymbolicExpressionTreeGenealogyGraph)(Results[PopulationGraphResultParameterName].Value);
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221 | }
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222 | // get tree quality values (Key => Individual, Value => Quality)
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223 | var qualities = (from s in gScope.SubScopes
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224 | let individual = s.Variables.First().Value
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225 | let quality = (DoubleValue)s.Variables["Quality"].Value
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226 | orderby quality.Value descending
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227 | select new Tuple<ISymbolicExpressionTree, double>((ISymbolicExpressionTree)individual, quality.Value)).ToDictionary(t => t.Item1, t => t.Item2);
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228 |
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229 | // add all individuals to the evolutionary graph
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230 | int generation = Generations.Value;
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231 | string label;
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232 | if (generation == 0) {
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233 | // at generation 0 no trace map is present (since no reproduction has taken place yet),
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234 | // so we only add the initial individuals as nodes in the genealogy graph
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235 | for (int i = 0; i != qualities.Count; ++i) {
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236 | var tree = qualities.ElementAt(i).Key;
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237 | label = (i + 1).ToString(CultureInfo.InvariantCulture);
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238 | graph.AddNode(tree, qualities[tree], label, generation, i < Elites.Value);
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239 | }
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240 | return base.Apply();
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241 | }
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242 |
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243 | // add nodes to genealogy graph
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244 | for (int i = 0; i != qualities.Count; ++i) {
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245 | var child = qualities.ElementAt(i).Key;
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246 | label = (generation * qualities.Count + i + 1).ToString(CultureInfo.InvariantCulture);
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247 | if (!graph.HasNode(child))
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248 | graph.AddNode(child, qualities[child], label, generation, i < Elites.Value);
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249 | if (!GlobalTraceMap.ContainsKey(child)) continue;
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250 | var parents = GlobalTraceMap[child];
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251 |
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252 | foreach (var parent in parents) {
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253 | if (GlobalTraceMap.ContainsKey(parent)) {
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254 | double quality = Evaluate((ISymbolicExpressionTree)parent);
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255 | graph.AddNode((ISymbolicExpressionTree)parent, quality, "", generation - 0.5);
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256 | var pp = GlobalTraceMap[parent];
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257 | foreach (var p in pp) {
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258 | graph.AddArc((ISymbolicExpressionTree)p, (ISymbolicExpressionTree)parent);
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259 | }
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260 | }
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261 | graph.AddArc((ISymbolicExpressionTree)parent, child);
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262 | }
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263 | }
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264 |
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265 | // clear trace and clone maps in preparation for the next generation
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266 | if (this.Successor == null || !(this.Successor is SymbolicExpressionTreeFragmentsAnalyzer)) {
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267 | GlobalTraceMap.Clear();
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268 | GlobalCloneMap.Clear();
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269 | }
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270 |
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271 | #region end of the run (code for writing results to dot files)
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272 | //bool maxGenerationsReached = (Generations.Value == MaximumGenerations.Value);
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273 | //bool isOsga = (SelectionPressure != null && MaximumSelectionPressure != null);
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274 | //bool maxSelectionPressureReached = isOsga && (SelectionPressure.Value >= MaximumSelectionPressure.Value);
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275 | //if (maxGenerationsReached || maxSelectionPressureReached) {
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276 | // var path = Environment.GetFolderPath(Environment.SpecialFolder.UserProfile);
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277 |
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278 | // // write whole graph to a dot file
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279 | // WriteDot(path + @"\lineage.dot", graph);
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280 |
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281 | // // get genealogy of the best solution
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282 | // var bestSolution = (ISymbolicExpressionTree)qualities.First().Key;
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283 | // var genealogy = graph.GetNode(bestSolution).Ancestors();
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284 | // //WriteDot(path + @"\bestlineage.dot", genealogy);
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285 |
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286 | // // write the direct root lineage of the best solution (is it useful?)
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287 |
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288 | // // calculate impact values of nodes in the best solution, attempt to trace those with high impact to their origins
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289 | // var calculator = new SymbolicRegressionSolutionValuesCalculator();
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290 | // var impactValues = calculator.CalculateImpactValues(bestSolution, SymbolicExpressionInterpreter, SymbolicRegressionProblemData, 0, 0);
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291 | // foreach (var pair in impactValues.Where(pair => !(pair.Key is ConstantTreeNode || pair.Key is VariableTreeNode)).OrderByDescending(pair => pair.Value).Take(2)) {
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292 | // var node = pair.Key;
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293 | // }
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294 | // //WriteDot(path + @"\impactancestry.dot", genealogy);
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295 |
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296 | // // trim the graph
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297 | // // exclude the individuals of the last generation
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298 | // var individuals = graph.Keys.Except(qualities.Select(x => x.Key)).ToList();
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299 | // bool done = false;
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300 | // while (!done) {
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301 | // done = true;
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302 | // foreach (var ind in individuals) {
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303 | // // if node has no outgoing connections (absence of offspring), remove it from the graph
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304 | // var node = graph.GetNode(ind);
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305 | // if (node == null) continue;
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306 | // if (node.OutEdges == null) {
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307 | // done = false; // we still have "dead" nodes
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308 | // graph.RemoveNode(ind);
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309 | // }
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310 | // }
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311 | // }
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312 | // WriteDot(path + @"\trimmedlineage.dot", graph);
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313 | //}
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314 | #endregion
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315 | }
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316 | return base.Apply();
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317 | }
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318 |
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319 |
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320 |
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321 | private double Evaluate(ISymbolicExpressionTree tree) {
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322 | // we perform evaluation by adding a temporary subscope with the tree in it, and calling evaluator.Apply()
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323 | var subScope = new Scope();
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324 | // inject expected variables into the subscope
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325 | subScope.Variables.Add(new Core.Variable("SymbolicExpressionTree", tree));
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326 | ExecutionContext.Scope.SubScopes.Add(subScope);
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327 | var context = new Core.ExecutionContext(ExecutionContext, SymbolicDataAnalysisEvaluator, subScope);
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328 | SymbolicDataAnalysisEvaluator.Execute(context, new CancellationToken());
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329 | // get the quality
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330 | double quality = ((DoubleValue)subScope.Variables["Quality"].Value).Value;
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331 | // remove the subscope
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332 | ExecutionContext.Scope.SubScopes.Remove(subScope);
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333 | return quality;
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334 | }
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335 |
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336 | #region Export to dot file
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337 | private static void WriteDot(string path, SymbolicExpressionTreeGenealogyGraph graph) {
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338 | using (var file = new System.IO.StreamWriter(path)) {
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339 | string nl = Environment.NewLine;
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340 | file.WriteLine("digraph \"lineage " + graph.AverageDegree.ToString(CultureInfo.InvariantCulture) + "\" {" + nl + "ratio=auto;" + nl + "mincross=2.0");
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341 | file.WriteLine("\tnode [shape=circle,label=\"\",style=filled]");
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342 |
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343 | foreach (var node in graph.Values) {
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344 | var color = Color.FromArgb((int)((1 - node.Quality) * 255), (int)(node.Quality * 255), 0);
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345 | string fillColor = String.Format("#{0:x2}{1:x2}{2:x2}", color.R, color.G, color.B);
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346 | string shape = "circle";
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347 | if (node.IsElite)
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348 | shape = "doublecircle";
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349 | file.WriteLine("\t\"" + node.Id + "\" [shape=" + shape + ",fillcolor=\"" + fillColor + "\",label=\"" + node.Label + "\"];");
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350 | if (node.InEdges == null)
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351 | continue;
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352 | foreach (var edge in node.InEdges) {
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353 | //var edgeStyle = node.InEdges.Count == 1 ? "dashed" : String.Empty;
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354 | var edgeStyle = String.Empty;
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355 | file.WriteLine("\t\"" + edge.Target.Id + "\" -> \"" + node.Id + "\" [arrowsize=.5, color=\"" + fillColor + "\", style=\"" + edgeStyle + "\"];");
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356 | }
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357 | }
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358 | foreach (var g in graph.Values.GroupBy(x => x.Rank)) {
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359 | var sb = new StringBuilder();
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360 | sb.Append("\t{rank=same;");
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361 | foreach (var node in g)
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362 | sb.Append("\"" + node.Id + "\" ");
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363 | sb.Append("}\n");
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364 | file.Write(sb.ToString());
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365 | }
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366 | file.WriteLine("}");
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367 | }
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368 | }
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369 | #endregion
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370 | }
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371 | }
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