1 | #region License Information
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2 |
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3 | /* HeuristicLab
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4 | * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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5 | *
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6 | * This file is part of HeuristicLab.
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7 | *
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8 | * HeuristicLab is free software: you can redistribute it and/or modify
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9 | * it under the terms of the GNU General Public License as published by
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10 | * the Free Software Foundation, either version 3 of the License, or
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11 | * (at your option) any later version.
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12 | *
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13 | * HeuristicLab is distributed in the hope that it will be useful,
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14 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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15 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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16 | * GNU General Public License for more details.
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17 | *
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18 | * You should have received a copy of the GNU General Public License
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19 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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20 | */
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21 |
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22 | #endregion
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23 |
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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.Encodings.SymbolicExpressionTreeEncoding;
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29 | using HeuristicLab.Operators;
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30 | using HeuristicLab.Parameters;
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31 | using HEAL.Attic;
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32 |
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33 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
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34 | [StorableType("DBE27385-2E8C-4314-88B4-F96A5240FC9D")]
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35 | [Item("SymbolicExpressionTreePruningOperator", "An operator that replaces introns with constant values in a symbolic expression tree.")]
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36 | public abstract class SymbolicDataAnalysisExpressionPruningOperator : SingleSuccessorOperator, ISymbolicExpressionTreeOperator {
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37 | #region parameter names
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38 | private const string ProblemDataParameterName = "ProblemData";
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39 | private const string SymbolicDataAnalysisModelParameterName = "SymbolicDataAnalysisModel";
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40 | private const string ImpactValuesCalculatorParameterName = "ImpactValuesCalculator";
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41 | private const string PrunedSubtreesParameterName = "PrunedSubtrees";
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42 | private const string PrunedTreesParameterName = "PrunedTrees";
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43 | private const string PrunedNodesParameterName = "PrunedNodes";
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44 | private const string FitnessCalculationPartitionParameterName = "FitnessCalculationPartition";
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45 | private const string NodeImpactThresholdParameterName = "ImpactThreshold";
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46 | private const string PruneOnlyZeroImpactNodesParameterName = "PruneOnlyZeroImpactNodes";
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47 | private const string SymbolicExpressionTreeParameterName = "SymbolicExpressionTree"; // the tree to be pruned
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48 | private const string QualityParameterName = "Quality"; // the quality
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49 | private const string EstimationLimitsParameterName = "EstimationLimits";
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50 | private const string InterpreterParameterName = "SymbolicExpressionTreeInterpreter";
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51 | private const string ApplyLinearScalingParameterName = "ApplyLinearScaling";
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52 | #endregion
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53 |
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54 | #region parameter properties
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55 | public ILookupParameter<ISymbolicExpressionTree> SymbolicExpressionTreeParameter {
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56 | get { return (ILookupParameter<ISymbolicExpressionTree>)Parameters[SymbolicExpressionTreeParameterName]; }
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57 | }
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58 | public ILookupParameter<DoubleValue> QualityParameter {
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59 | get { return (ILookupParameter<DoubleValue>)Parameters[QualityParameterName]; }
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60 | }
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61 | public ILookupParameter<IDataAnalysisProblemData> ProblemDataParameter {
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62 | get { return (ILookupParameter<IDataAnalysisProblemData>)Parameters[ProblemDataParameterName]; }
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63 | }
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64 | public IValueParameter<ISymbolicDataAnalysisSolutionImpactValuesCalculator> ImpactValuesCalculatorParameter {
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65 | get { return (IValueParameter<ISymbolicDataAnalysisSolutionImpactValuesCalculator>)Parameters[ImpactValuesCalculatorParameterName]; }
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66 | }
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67 | public ILookupParameter<IntRange> FitnessCalculationPartitionParameter {
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68 | get { return (ILookupParameter<IntRange>)Parameters[FitnessCalculationPartitionParameterName]; }
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69 | }
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70 | public ILookupParameter<IntValue> PrunedSubtreesParameter {
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71 | get { return (ILookupParameter<IntValue>)Parameters[PrunedSubtreesParameterName]; }
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72 | }
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73 | public ILookupParameter<IntValue> PrunedTreesParameter {
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74 | get { return (ILookupParameter<IntValue>)Parameters[PrunedTreesParameterName]; }
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75 | }
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76 | public ILookupParameter<IntValue> PrunedNodesParameter {
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77 | get { return (ILookupParameter<IntValue>)Parameters[PrunedNodesParameterName]; }
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78 | }
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79 | public IFixedValueParameter<DoubleValue> NodeImpactThresholdParameter {
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80 | get { return (IFixedValueParameter<DoubleValue>)Parameters[NodeImpactThresholdParameterName]; }
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81 | }
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82 | public IFixedValueParameter<BoolValue> PruneOnlyZeroImpactNodesParameter {
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83 | get { return (IFixedValueParameter<BoolValue>)Parameters[PruneOnlyZeroImpactNodesParameterName]; }
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84 | }
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85 | public ILookupParameter<DoubleLimit> EstimationLimitsParameter {
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86 | get { return (ILookupParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
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87 | }
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88 | public ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter> InterpreterParameter {
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89 | get { return (ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>)Parameters[InterpreterParameterName]; }
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90 | }
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91 | public ILookupParameter<BoolValue> ApplyLinearScalingParameter {
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92 | get { return (ILookupParameter<BoolValue>)Parameters[ApplyLinearScalingParameterName]; }
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93 | }
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94 | #endregion
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95 |
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96 | #region properties
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97 | public ISymbolicDataAnalysisSolutionImpactValuesCalculator ImpactValuesCalculator {
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98 | get { return ImpactValuesCalculatorParameter.Value; }
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99 | set { ImpactValuesCalculatorParameter.Value = value; }
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100 | }
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101 | public bool PruneOnlyZeroImpactNodes {
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102 | get { return PruneOnlyZeroImpactNodesParameter.Value.Value; }
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103 | set { PruneOnlyZeroImpactNodesParameter.Value.Value = value; }
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104 | }
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105 | public double NodeImpactThreshold {
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106 | get { return NodeImpactThresholdParameter.Value.Value; }
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107 | set { NodeImpactThresholdParameter.Value.Value = value; }
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108 | }
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109 | #endregion
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110 |
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111 | [StorableConstructor]
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112 | protected SymbolicDataAnalysisExpressionPruningOperator(StorableConstructorFlag _) : base(_) { }
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113 | protected SymbolicDataAnalysisExpressionPruningOperator(SymbolicDataAnalysisExpressionPruningOperator original, Cloner cloner)
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114 | : base(original, cloner) { }
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115 |
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116 | protected SymbolicDataAnalysisExpressionPruningOperator(ISymbolicDataAnalysisSolutionImpactValuesCalculator impactValuesCalculator) {
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117 | #region add parameters
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118 | Parameters.Add(new LookupParameter<IDataAnalysisProblemData>(ProblemDataParameterName));
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119 | Parameters.Add(new LookupParameter<ISymbolicDataAnalysisModel>(SymbolicDataAnalysisModelParameterName));
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120 | Parameters.Add(new LookupParameter<IntRange>(FitnessCalculationPartitionParameterName));
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121 | Parameters.Add(new LookupParameter<IntValue>(PrunedNodesParameterName, "A counter of how many nodes were pruned."));
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122 | Parameters.Add(new LookupParameter<IntValue>(PrunedSubtreesParameterName, "A counter of how many subtrees were replaced."));
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123 | Parameters.Add(new LookupParameter<IntValue>(PrunedTreesParameterName, "A counter of how many trees were pruned."));
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124 | Parameters.Add(new FixedValueParameter<BoolValue>(PruneOnlyZeroImpactNodesParameterName, "Specify whether or not only zero impact nodes should be pruned."));
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125 | Parameters.Add(new FixedValueParameter<DoubleValue>(NodeImpactThresholdParameterName, "Specifies an impact value threshold below which nodes should be pruned."));
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126 | Parameters.Add(new LookupParameter<DoubleLimit>(EstimationLimitsParameterName));
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127 | Parameters.Add(new LookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(InterpreterParameterName));
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128 | Parameters.Add(new LookupParameter<ISymbolicExpressionTree>(SymbolicExpressionTreeParameterName));
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129 | Parameters.Add(new LookupParameter<DoubleValue>(QualityParameterName));
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130 | Parameters.Add(new LookupParameter<BoolValue>(ApplyLinearScalingParameterName));
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131 | Parameters.Add(new ValueParameter<ISymbolicDataAnalysisSolutionImpactValuesCalculator>(ImpactValuesCalculatorParameterName, impactValuesCalculator));
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132 | #endregion
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133 | }
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134 |
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135 | [StorableHook(HookType.AfterDeserialization)]
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136 | private void AfterDeserialization() {
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137 | // BackwardsCompatibility3.3
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138 | #region Backwards compatible code, remove with 3.4
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139 | if (!Parameters.ContainsKey(PrunedNodesParameterName)) {
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140 | Parameters.Add(new LookupParameter<IntValue>(PrunedNodesParameterName, "A counter of how many nodes were pruned."));
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141 | }
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142 | if (!Parameters.ContainsKey(ApplyLinearScalingParameterName)) {
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143 | Parameters.Add(new LookupParameter<BoolValue>(ApplyLinearScalingParameterName));
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144 | }
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145 | if (!Parameters.ContainsKey(ImpactValuesCalculatorParameterName)) {
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146 | // value must be set by derived operators (regression/classification)
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147 | Parameters.Add(new ValueParameter<ISymbolicDataAnalysisSolutionImpactValuesCalculator>(ImpactValuesCalculatorParameterName));
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148 | }
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149 | #endregion
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150 | }
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151 |
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152 | protected abstract ISymbolicDataAnalysisModel CreateModel(ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, IDataAnalysisProblemData problemData, DoubleLimit estimationLimits);
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153 |
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154 | protected abstract double Evaluate(IDataAnalysisModel model);
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155 |
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156 | public override IOperation Apply() {
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157 | var tree = SymbolicExpressionTreeParameter.ActualValue;
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158 | var problemData = ProblemDataParameter.ActualValue;
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159 | var fitnessCalculationPartition = FitnessCalculationPartitionParameter.ActualValue;
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160 | var estimationLimits = EstimationLimitsParameter.ActualValue;
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161 | var interpreter = InterpreterParameter.ActualValue;
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162 |
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163 | var model = CreateModel(tree, interpreter, problemData, estimationLimits);
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164 | var nodes = tree.Root.GetSubtree(0).GetSubtree(0).IterateNodesPrefix().ToList();
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165 | var rows = Enumerable.Range(fitnessCalculationPartition.Start, fitnessCalculationPartition.Size).ToList();
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166 | var prunedSubtrees = 0;
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167 | var prunedTrees = 0;
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168 | var prunedNodes = 0;
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169 |
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170 | double qualityForImpactsCalculation = double.NaN;
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171 |
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172 | for (int i = 0; i < nodes.Count; ++i) {
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173 | var node = nodes[i];
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174 | if (node is ConstantTreeNode) continue;
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175 |
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176 | double impactValue, replacementValue;
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177 | double newQualityForImpacts;
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178 | ImpactValuesCalculator.CalculateImpactAndReplacementValues(model, node, problemData, rows, out impactValue, out replacementValue, out newQualityForImpacts, qualityForImpactsCalculation);
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179 |
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180 | if (PruneOnlyZeroImpactNodes && !impactValue.IsAlmost(0.0)) continue;
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181 | if (!PruneOnlyZeroImpactNodes && impactValue > NodeImpactThreshold) continue;
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182 |
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183 | var constantNode = (ConstantTreeNode)node.Grammar.GetSymbol("Constant").CreateTreeNode();
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184 | constantNode.Value = replacementValue;
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185 |
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186 | var length = node.GetLength();
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187 | ReplaceWithConstant(node, constantNode);
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188 | i += length - 1; // skip subtrees under the node that was folded
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189 |
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190 | prunedSubtrees++;
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191 | prunedNodes += length;
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192 |
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193 | qualityForImpactsCalculation = newQualityForImpacts;
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194 | }
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195 |
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196 | if (prunedSubtrees > 0) prunedTrees = 1;
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197 | PrunedSubtreesParameter.ActualValue = new IntValue(prunedSubtrees);
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198 | PrunedTreesParameter.ActualValue = new IntValue(prunedTrees);
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199 | PrunedNodesParameter.ActualValue = new IntValue(prunedNodes);
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200 |
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201 | if (prunedSubtrees > 0) // if nothing was pruned then there's no need to re-evaluate the tree
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202 | QualityParameter.ActualValue.Value = Evaluate(model);
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203 |
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204 | return base.Apply();
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205 | }
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206 |
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207 | protected static void ReplaceWithConstant(ISymbolicExpressionTreeNode original, ISymbolicExpressionTreeNode replacement) {
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208 | var parent = original.Parent;
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209 | var i = parent.IndexOfSubtree(original);
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210 | parent.RemoveSubtree(i);
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211 | parent.InsertSubtree(i, replacement);
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212 | }
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213 | }
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214 | }
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