1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2016 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.Linq;
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25 | using HeuristicLab.Common;
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26 | using HeuristicLab.Common.Resources;
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27 | using HeuristicLab.Core;
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28 | using HeuristicLab.Data;
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29 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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30 | using HeuristicLab.Optimization;
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31 | using HeuristicLab.Parameters;
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32 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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33 | using HeuristicLab.PluginInfrastructure;
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34 | using HeuristicLab.Problems.Instances;
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35 |
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36 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
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37 | [StorableClass]
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38 | public abstract class SymbolicDataAnalysisProblem<T, U, V> : HeuristicOptimizationProblem<U, V>, IDataAnalysisProblem<T>, ISymbolicDataAnalysisProblem, IStorableContent,
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39 | IProblemInstanceConsumer<T>, IProblemInstanceExporter<T>
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40 | where T : class, IDataAnalysisProblemData
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41 | where U : class, ISymbolicDataAnalysisEvaluator<T>
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42 | where V : class, ISymbolicDataAnalysisSolutionCreator {
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43 |
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44 | #region parameter names & descriptions
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45 | private const string ProblemDataParameterName = "ProblemData";
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46 | private const string SymbolicExpressionTreeGrammarParameterName = "SymbolicExpressionTreeGrammar";
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47 | private const string SymbolicExpressionTreeInterpreterParameterName = "SymbolicExpressionTreeInterpreter";
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48 | private const string MaximumSymbolicExpressionTreeDepthParameterName = "MaximumSymbolicExpressionTreeDepth";
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49 | private const string MaximumSymbolicExpressionTreeLengthParameterName = "MaximumSymbolicExpressionTreeLength";
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50 | private const string MaximumFunctionDefinitionsParameterName = "MaximumFunctionDefinitions";
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51 | private const string MaximumFunctionArgumentsParameterName = "MaximumFunctionArguments";
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52 | private const string RelativeNumberOfEvaluatedSamplesParameterName = "RelativeNumberOfEvaluatedSamples";
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53 | private const string FitnessCalculationPartitionParameterName = "FitnessCalculationPartition";
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54 | private const string ValidationPartitionParameterName = "ValidationPartition";
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55 | private const string ApplyLinearScalingParameterName = "ApplyLinearScaling";
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56 |
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57 | private const string ProblemDataParameterDescription = "";
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58 | private const string SymbolicExpressionTreeGrammarParameterDescription = "The grammar that should be used for symbolic expression tree.";
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59 | private const string SymoblicExpressionTreeInterpreterParameterDescription = "The interpreter that should be used to evaluate the symbolic expression tree.";
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60 | private const string MaximumSymbolicExpressionTreeDepthParameterDescription = "Maximal depth of the symbolic expression. The minimum depth needed for the algorithm is 3 because two levels are reserved for the ProgramRoot and the Start symbol.";
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61 | private const string MaximumSymbolicExpressionTreeLengthParameterDescription = "Maximal length of the symbolic expression.";
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62 | private const string MaximumFunctionDefinitionsParameterDescription = "Maximal number of automatically defined functions";
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63 | private const string MaximumFunctionArgumentsParameterDescription = "Maximal number of arguments of automatically defined functions.";
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64 | private const string RelativeNumberOfEvaluatedSamplesParameterDescription = "The relative number of samples of the dataset partition, which should be randomly chosen for evaluation.";
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65 | private const string FitnessCalculationPartitionParameterDescription = "The partition of the problem data training partition, that should be used to calculate the fitness of an individual.";
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66 | private const string ValidationPartitionParameterDescription = "The partition of the problem data training partition, that should be used to select the best model from (optional).";
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67 | private const string ApplyLinearScalingParameterDescription = "Flag that indicates if the individual should be linearly scaled before evaluating.";
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68 | #endregion
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69 |
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70 | #region parameter properties
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71 | IParameter IDataAnalysisProblem.ProblemDataParameter {
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72 | get { return ProblemDataParameter; }
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73 | }
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74 | public IValueParameter<T> ProblemDataParameter {
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75 | get { return (IValueParameter<T>)Parameters[ProblemDataParameterName]; }
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76 | }
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77 | public IValueParameter<ISymbolicDataAnalysisGrammar> SymbolicExpressionTreeGrammarParameter {
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78 | get { return (IValueParameter<ISymbolicDataAnalysisGrammar>)Parameters[SymbolicExpressionTreeGrammarParameterName]; }
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79 | }
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80 | public IValueParameter<ISymbolicDataAnalysisExpressionTreeInterpreter> SymbolicExpressionTreeInterpreterParameter {
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81 | get { return (IValueParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>)Parameters[SymbolicExpressionTreeInterpreterParameterName]; }
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82 | }
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83 | public IFixedValueParameter<IntValue> MaximumSymbolicExpressionTreeDepthParameter {
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84 | get { return (IFixedValueParameter<IntValue>)Parameters[MaximumSymbolicExpressionTreeDepthParameterName]; }
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85 | }
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86 | public IFixedValueParameter<IntValue> MaximumSymbolicExpressionTreeLengthParameter {
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87 | get { return (IFixedValueParameter<IntValue>)Parameters[MaximumSymbolicExpressionTreeLengthParameterName]; }
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88 | }
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89 | public IFixedValueParameter<IntValue> MaximumFunctionDefinitionsParameter {
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90 | get { return (IFixedValueParameter<IntValue>)Parameters[MaximumFunctionDefinitionsParameterName]; }
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91 | }
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92 | public IFixedValueParameter<IntValue> MaximumFunctionArgumentsParameter {
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93 | get { return (IFixedValueParameter<IntValue>)Parameters[MaximumFunctionArgumentsParameterName]; }
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94 | }
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95 | public IFixedValueParameter<PercentValue> RelativeNumberOfEvaluatedSamplesParameter {
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96 | get { return (IFixedValueParameter<PercentValue>)Parameters[RelativeNumberOfEvaluatedSamplesParameterName]; }
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97 | }
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98 | public IFixedValueParameter<IntRange> FitnessCalculationPartitionParameter {
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99 | get { return (IFixedValueParameter<IntRange>)Parameters[FitnessCalculationPartitionParameterName]; }
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100 | }
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101 | public IFixedValueParameter<IntRange> ValidationPartitionParameter {
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102 | get { return (IFixedValueParameter<IntRange>)Parameters[ValidationPartitionParameterName]; }
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103 | }
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104 | public IFixedValueParameter<BoolValue> ApplyLinearScalingParameter {
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105 | get { return (IFixedValueParameter<BoolValue>)Parameters[ApplyLinearScalingParameterName]; }
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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 string Filename { get; set; }
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111 | public static new Image StaticItemImage { get { return VSImageLibrary.Type; } }
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112 |
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113 | IDataAnalysisProblemData IDataAnalysisProblem.ProblemData {
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114 | get { return ProblemData; }
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115 | }
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116 | public T ProblemData {
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117 | get { return ProblemDataParameter.Value; }
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118 | set { ProblemDataParameter.Value = value; }
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119 | }
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120 |
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121 | public ISymbolicDataAnalysisGrammar SymbolicExpressionTreeGrammar {
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122 | get { return SymbolicExpressionTreeGrammarParameter.Value; }
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123 | set { SymbolicExpressionTreeGrammarParameter.Value = value; }
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124 | }
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125 | public ISymbolicDataAnalysisExpressionTreeInterpreter SymbolicExpressionTreeInterpreter {
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126 | get { return SymbolicExpressionTreeInterpreterParameter.Value; }
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127 | set { SymbolicExpressionTreeInterpreterParameter.Value = value; }
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128 | }
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129 |
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130 | public IntValue MaximumSymbolicExpressionTreeDepth {
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131 | get { return MaximumSymbolicExpressionTreeDepthParameter.Value; }
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132 | }
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133 | public IntValue MaximumSymbolicExpressionTreeLength {
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134 | get { return MaximumSymbolicExpressionTreeLengthParameter.Value; }
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135 | }
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136 | public IntValue MaximumFunctionDefinitions {
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137 | get { return MaximumFunctionDefinitionsParameter.Value; }
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138 | }
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139 | public IntValue MaximumFunctionArguments {
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140 | get { return MaximumFunctionArgumentsParameter.Value; }
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141 | }
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142 | public PercentValue RelativeNumberOfEvaluatedSamples {
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143 | get { return RelativeNumberOfEvaluatedSamplesParameter.Value; }
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144 | }
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145 |
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146 | public IntRange FitnessCalculationPartition {
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147 | get { return FitnessCalculationPartitionParameter.Value; }
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148 | }
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149 | public IntRange ValidationPartition {
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150 | get { return ValidationPartitionParameter.Value; }
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151 | }
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152 | public BoolValue ApplyLinearScaling {
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153 | get { return ApplyLinearScalingParameter.Value; }
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154 | }
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155 | #endregion
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156 |
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157 | [StorableConstructor]
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158 | protected SymbolicDataAnalysisProblem(bool deserializing) : base(deserializing) { }
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159 | [StorableHook(HookType.AfterDeserialization)]
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160 | private void AfterDeserialization() {
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161 | if (!Parameters.ContainsKey(ApplyLinearScalingParameterName)) {
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162 | Parameters.Add(new FixedValueParameter<BoolValue>(ApplyLinearScalingParameterName, ApplyLinearScalingParameterDescription, new BoolValue(false)));
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163 | ApplyLinearScalingParameter.Hidden = true;
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164 |
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165 | //it is assumed that for all symbolic regression algorithms linear scaling was set to true
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166 | //there is no possibility to determine the previous value of the parameter as it was stored in the evaluator
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167 | if (GetType().Name.Contains("SymbolicRegression"))
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168 | ApplyLinearScaling.Value = true;
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169 | }
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170 |
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171 | RegisterEventHandlers();
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172 | }
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173 | protected SymbolicDataAnalysisProblem(SymbolicDataAnalysisProblem<T, U, V> original, Cloner cloner)
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174 | : base(original, cloner) {
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175 | RegisterEventHandlers();
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176 | }
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177 |
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178 | protected SymbolicDataAnalysisProblem(T problemData, U evaluator, V solutionCreator)
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179 | : base(evaluator, solutionCreator) {
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180 | Parameters.Add(new ValueParameter<T>(ProblemDataParameterName, ProblemDataParameterDescription, problemData));
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181 | Parameters.Add(new ValueParameter<ISymbolicDataAnalysisGrammar>(SymbolicExpressionTreeGrammarParameterName, SymbolicExpressionTreeGrammarParameterDescription));
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182 | Parameters.Add(new ValueParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(SymbolicExpressionTreeInterpreterParameterName, SymoblicExpressionTreeInterpreterParameterDescription));
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183 | Parameters.Add(new FixedValueParameter<IntValue>(MaximumSymbolicExpressionTreeDepthParameterName, MaximumSymbolicExpressionTreeDepthParameterDescription));
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184 | Parameters.Add(new FixedValueParameter<IntValue>(MaximumSymbolicExpressionTreeLengthParameterName, MaximumSymbolicExpressionTreeLengthParameterDescription));
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185 | Parameters.Add(new FixedValueParameter<IntValue>(MaximumFunctionDefinitionsParameterName, MaximumFunctionDefinitionsParameterDescription));
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186 | Parameters.Add(new FixedValueParameter<IntValue>(MaximumFunctionArgumentsParameterName, MaximumFunctionArgumentsParameterDescription));
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187 | Parameters.Add(new FixedValueParameter<IntRange>(FitnessCalculationPartitionParameterName, FitnessCalculationPartitionParameterDescription));
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188 | Parameters.Add(new FixedValueParameter<IntRange>(ValidationPartitionParameterName, ValidationPartitionParameterDescription));
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189 | Parameters.Add(new FixedValueParameter<PercentValue>(RelativeNumberOfEvaluatedSamplesParameterName, RelativeNumberOfEvaluatedSamplesParameterDescription, new PercentValue(1)));
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190 | Parameters.Add(new FixedValueParameter<BoolValue>(ApplyLinearScalingParameterName, ApplyLinearScalingParameterDescription, new BoolValue(false)));
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191 |
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192 | SymbolicExpressionTreeInterpreterParameter.Hidden = true;
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193 | MaximumFunctionArgumentsParameter.Hidden = true;
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194 | MaximumFunctionDefinitionsParameter.Hidden = true;
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195 | ApplyLinearScalingParameter.Hidden = true;
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196 |
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197 | SymbolicExpressionTreeGrammar = new TypeCoherentExpressionGrammar();
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198 | SymbolicExpressionTreeInterpreter = new SymbolicDataAnalysisExpressionTreeLinearInterpreter();
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199 |
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200 | FitnessCalculationPartition.Start = ProblemData.TrainingPartition.Start;
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201 | FitnessCalculationPartition.End = ProblemData.TrainingPartition.End;
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202 |
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203 | InitializeOperators();
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204 |
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205 | UpdateGrammar();
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206 | RegisterEventHandlers();
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207 | }
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208 |
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209 | protected virtual void UpdateGrammar() {
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210 | var problemData = ProblemData;
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211 | var ds = problemData.Dataset;
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212 | var grammar = SymbolicExpressionTreeGrammar;
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213 | grammar.MaximumFunctionArguments = MaximumFunctionArguments.Value;
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214 | grammar.MaximumFunctionDefinitions = MaximumFunctionDefinitions.Value;
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215 | foreach (var varSymbol in grammar.Symbols.OfType<HeuristicLab.Problems.DataAnalysis.Symbolic.VariableBase>()) {
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216 | if (!varSymbol.Fixed) {
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217 | varSymbol.AllVariableNames = problemData.InputVariables.Select(x => x.Value).Where(x => ds.VariableHasType<double>(x));
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218 | varSymbol.VariableNames = problemData.AllowedInputVariables.Where(x => ds.VariableHasType<double>(x));
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219 | }
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220 | }
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221 | foreach (var factorSymbol in grammar.Symbols.OfType<BinaryFactorVariable>()) {
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222 | if (!factorSymbol.Fixed) {
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223 | factorSymbol.AllVariableNames = problemData.InputVariables.Select(x => x.Value).Where(x => ds.VariableHasType<string>(x));
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224 | factorSymbol.VariableNames = problemData.AllowedInputVariables.Where(x => ds.VariableHasType<string>(x));
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225 | factorSymbol.VariableValues = factorSymbol.VariableNames
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226 | .ToDictionary(varName => varName, varName => ds.GetStringValues(varName).Distinct().ToList());
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227 | }
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228 | }
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229 | foreach (var factorSymbol in grammar.Symbols.OfType<FactorVariable>()) {
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230 | if (!factorSymbol.Fixed) {
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231 | factorSymbol.AllVariableNames = problemData.InputVariables.Select(x => x.Value).Where(x => ds.VariableHasType<string>(x));
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232 | factorSymbol.VariableNames = problemData.AllowedInputVariables.Where(x => ds.VariableHasType<string>(x));
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233 | factorSymbol.VariableValues = factorSymbol.VariableNames
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234 | .ToDictionary(varName => varName,
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235 | varName => ds.GetStringValues(varName).Distinct()
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236 | .Select((n, i) => Tuple.Create(n, i))
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237 | .ToDictionary(tup => tup.Item1, tup => tup.Item2));
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238 | }
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239 | }
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240 | }
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241 |
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242 | private void InitializeOperators() {
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243 | Operators.AddRange(ApplicationManager.Manager.GetInstances<ISymbolicExpressionTreeOperator>());
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244 | Operators.AddRange(ApplicationManager.Manager.GetInstances<ISymbolicDataAnalysisExpressionCrossover<T>>());
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245 | Operators.Add(new SymbolicExpressionSymbolFrequencyAnalyzer());
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246 | Operators.Add(new SymbolicDataAnalysisVariableFrequencyAnalyzer());
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247 | Operators.Add(new MinAverageMaxSymbolicExpressionTreeLengthAnalyzer());
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248 | Operators.Add(new SymbolicExpressionTreeLengthAnalyzer());
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249 | Operators.Add(new SymbolicExpressionTreeBottomUpSimilarityCalculator());
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250 | Operators.Add(new SymbolicDataAnalysisBottomUpDiversityAnalyzer(Operators.OfType<SymbolicExpressionTreeBottomUpSimilarityCalculator>().First()));
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251 | Operators.Add(new SymbolicDataAnalysisGenealogyAnalyzer());
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252 | ParameterizeOperators();
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253 | }
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254 |
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255 | #region events
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256 | private void RegisterEventHandlers() {
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257 | ProblemDataParameter.ValueChanged += new EventHandler(ProblemDataParameter_ValueChanged);
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258 | ProblemDataParameter.Value.Changed += (object sender, EventArgs e) => OnProblemDataChanged();
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259 |
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260 | SymbolicExpressionTreeGrammarParameter.ValueChanged += new EventHandler(SymbolicExpressionTreeGrammarParameter_ValueChanged);
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261 |
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262 | MaximumFunctionArguments.ValueChanged += new EventHandler(ArchitectureParameterValue_ValueChanged);
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263 | MaximumFunctionDefinitions.ValueChanged += new EventHandler(ArchitectureParameterValue_ValueChanged);
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264 | MaximumSymbolicExpressionTreeDepth.ValueChanged += new EventHandler(MaximumSymbolicExpressionTreeDepth_ValueChanged);
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265 | }
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266 |
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267 | private void ProblemDataParameter_ValueChanged(object sender, EventArgs e) {
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268 | ValidationPartition.Start = 0;
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269 | ValidationPartition.End = 0;
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270 | ProblemDataParameter.Value.Changed += (object s, EventArgs args) => OnProblemDataChanged();
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271 | OnProblemDataChanged();
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272 | }
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273 |
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274 | private void SymbolicExpressionTreeGrammarParameter_ValueChanged(object sender, EventArgs e) {
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275 | UpdateGrammar();
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276 | }
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277 |
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278 | private void ArchitectureParameterValue_ValueChanged(object sender, EventArgs e) {
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279 | UpdateGrammar();
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280 | }
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281 |
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282 | private void MaximumSymbolicExpressionTreeDepth_ValueChanged(object sender, EventArgs e) {
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283 | if (MaximumSymbolicExpressionTreeDepth != null && MaximumSymbolicExpressionTreeDepth.Value < 3)
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284 | MaximumSymbolicExpressionTreeDepth.Value = 3;
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285 | }
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286 |
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287 | protected override void OnSolutionCreatorChanged() {
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288 | base.OnSolutionCreatorChanged();
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289 | SolutionCreator.SymbolicExpressionTreeParameter.ActualNameChanged += new EventHandler(SolutionCreator_SymbolicExpressionTreeParameter_ActualNameChanged);
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290 | ParameterizeOperators();
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291 | }
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292 |
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293 | private void SolutionCreator_SymbolicExpressionTreeParameter_ActualNameChanged(object sender, EventArgs e) {
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294 | ParameterizeOperators();
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295 | }
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296 |
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297 | protected override void OnEvaluatorChanged() {
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298 | base.OnEvaluatorChanged();
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299 | ParameterizeOperators();
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300 | }
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301 |
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302 | public event EventHandler ProblemDataChanged;
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303 | protected virtual void OnProblemDataChanged() {
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304 | FitnessCalculationPartition.Start = ProblemData.TrainingPartition.Start;
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305 | FitnessCalculationPartition.End = ProblemData.TrainingPartition.End;
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306 |
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307 | UpdateGrammar();
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308 | ParameterizeOperators();
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309 |
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310 | var handler = ProblemDataChanged;
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311 | if (handler != null) handler(this, EventArgs.Empty);
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312 |
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313 | OnReset();
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314 | }
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315 | #endregion
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316 |
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317 | protected virtual void ParameterizeOperators() {
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318 | var operators =
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319 | Parameters.OfType<IValueParameter>().Select(p => p.Value).OfType<IOperator>().Union(Operators).ToList();
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320 |
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321 | foreach (var op in operators.OfType<ISymbolicExpressionTreeGrammarBasedOperator>()) {
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322 | op.SymbolicExpressionTreeGrammarParameter.ActualName = SymbolicExpressionTreeGrammarParameter.Name;
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323 | }
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324 | foreach (var op in operators.OfType<ISymbolicExpressionTreeSizeConstraintOperator>()) {
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325 | op.MaximumSymbolicExpressionTreeDepthParameter.ActualName = MaximumSymbolicExpressionTreeDepthParameter.Name;
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326 | op.MaximumSymbolicExpressionTreeLengthParameter.ActualName = MaximumSymbolicExpressionTreeLengthParameter.Name;
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327 | }
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328 | foreach (var op in operators.OfType<ISymbolicExpressionTreeArchitectureAlteringOperator>()) {
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329 | op.MaximumFunctionArgumentsParameter.ActualName = MaximumFunctionArgumentsParameter.Name;
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330 | op.MaximumFunctionDefinitionsParameter.ActualName = MaximumFunctionDefinitionsParameter.Name;
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331 | }
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332 | foreach (var op in operators.OfType<ISymbolicDataAnalysisEvaluator<T>>()) {
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333 | op.ProblemDataParameter.ActualName = ProblemDataParameterName;
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334 | op.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
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335 | op.EvaluationPartitionParameter.ActualName = FitnessCalculationPartitionParameter.Name;
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336 | op.RelativeNumberOfEvaluatedSamplesParameter.ActualName = RelativeNumberOfEvaluatedSamplesParameter.Name;
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337 | op.ApplyLinearScalingParameter.ActualName = ApplyLinearScalingParameter.Name;
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338 | }
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339 | foreach (var op in operators.OfType<ISymbolicExpressionTreeCrossover>()) {
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340 | op.ParentsParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
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341 | op.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
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342 | }
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343 | foreach (var op in operators.OfType<ISymbolicExpressionTreeManipulator>()) {
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344 | op.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
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345 | }
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346 | foreach (var op in operators.OfType<ISymbolicExpressionTreeAnalyzer>()) {
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347 | op.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
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348 | }
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349 | foreach (var op in operators.OfType<ISymbolicDataAnalysisSingleObjectiveAnalyzer>()) {
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350 | op.ApplyLinearScalingParameter.ActualName = ApplyLinearScalingParameter.Name;
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351 | }
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352 | foreach (var op in operators.OfType<ISymbolicDataAnalysisMultiObjectiveAnalyzer>()) {
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353 | op.ApplyLinearScalingParameter.ActualName = ApplyLinearScalingParameter.Name;
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354 | }
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355 | foreach (var op in operators.OfType<ISymbolicDataAnalysisAnalyzer>()) {
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356 | op.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
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357 | }
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358 | foreach (var op in operators.OfType<ISymbolicDataAnalysisValidationAnalyzer<U, T>>()) {
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359 | op.RelativeNumberOfEvaluatedSamplesParameter.ActualName = RelativeNumberOfEvaluatedSamplesParameter.Name;
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360 | op.ValidationPartitionParameter.ActualName = ValidationPartitionParameter.Name;
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361 | }
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362 | foreach (var op in operators.OfType<ISymbolicDataAnalysisInterpreterOperator>()) {
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363 | op.SymbolicDataAnalysisTreeInterpreterParameter.ActualName = SymbolicExpressionTreeInterpreterParameter.Name;
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364 | }
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365 | foreach (var op in operators.OfType<ISymbolicDataAnalysisExpressionCrossover<T>>()) {
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366 | op.EvaluationPartitionParameter.ActualName = FitnessCalculationPartitionParameter.Name;
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367 | op.ProblemDataParameter.ActualName = ProblemDataParameter.Name;
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368 | op.EvaluationPartitionParameter.ActualName = FitnessCalculationPartitionParameter.Name;
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369 | op.RelativeNumberOfEvaluatedSamplesParameter.ActualName = RelativeNumberOfEvaluatedSamplesParameter.Name;
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370 | op.EvaluatorParameter.ActualName = EvaluatorParameter.Name;
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371 | }
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372 | // add tracking analyzer
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373 | foreach (var op in operators.OfType<SymbolicDataAnalysisGenealogyAnalyzer>()) {
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374 | op.BeforeCrossoverOperatorParameter.ActualValue = new SymbolicDataAnalysisExpressionBeforeCrossoverOperator();
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375 | op.AfterCrossoverOperatorParameter.ActualValue = new SymbolicDataAnalysisExpressionAfterCrossoverOperator();
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376 | op.BeforeManipulatorOperatorParameter.ActualValue =
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377 | new SymbolicDataAnalysisExpressionBeforeManipulatorOperator();
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378 | op.AfterManipulatorOperatorParameter.ActualValue = new SymbolicDataAnalysisExpressionAfterManipulatorOperator();
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379 | // get crossover parameter names
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380 | var crossover = operators.OfType<ISymbolicExpressionTreeCrossover>().FirstOrDefault();
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381 | if (crossover != null) {
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382 | op.BeforeCrossoverOperator.ParentsParameter.ActualName = crossover.ParentsParameter.Name;
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383 | op.AfterCrossoverOperator.ParentsParameter.ActualName = crossover.ParentsParameter.Name;
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384 | op.BeforeCrossoverOperator.ChildParameter.ActualName = crossover.SymbolicExpressionTreeParameter.Name;
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385 | op.AfterCrossoverOperator.ChildParameter.ActualName = crossover.SymbolicExpressionTreeParameter.Name;
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386 | // get manipulator parameter names
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387 | var manipulator = operators.OfType<ISymbolicExpressionTreeManipulator>().FirstOrDefault();
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388 | if (manipulator != null) {
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389 | op.BeforeManipulatorOperator.ChildParameter.ActualName = manipulator.SymbolicExpressionTreeParameter.Name;
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390 | op.AfterManipulatorOperator.ChildParameter.ActualName = manipulator.SymbolicExpressionTreeParameter.Name;
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391 | }
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392 | var creator = operators.OfType<ISymbolicExpressionTreeCreator>().FirstOrDefault();
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393 | if (creator != null) {
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394 | op.PopulationParameter.ActualName = creator.SymbolicExpressionTreeParameter.ActualName;
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395 | }
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396 | }
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397 | }
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398 | }
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399 |
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400 | #region Import & Export
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401 | public virtual void Load(T data) {
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402 | Name = data.Name;
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403 | Description = data.Description;
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404 | ProblemData = data;
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405 | }
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406 |
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407 | public virtual T Export() {
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408 | return ProblemData;
|
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409 | }
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410 | #endregion
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411 | }
|
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412 | }
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