1 | using System;
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2 | using System.Collections.Generic;
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3 | using System.Collections.ObjectModel;
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4 | using System.Diagnostics;
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5 | using System.Linq;
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6 | using System.Threading;
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7 | using HeuristicLab.Algorithms.DataAnalysis.SymRegGrammarEnumeration.GrammarEnumeration;
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8 | using HeuristicLab.Common;
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9 | using HeuristicLab.Core;
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10 | using HeuristicLab.Data;
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11 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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12 | using HeuristicLab.Optimization;
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13 | using HeuristicLab.Parameters;
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14 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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15 | using HeuristicLab.Problems.DataAnalysis;
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16 | using HeuristicLab.Problems.DataAnalysis.Symbolic;
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17 | using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
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18 |
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19 | namespace HeuristicLab.Algorithms.DataAnalysis.SymRegGrammarEnumeration {
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20 | [Item("Grammar Enumeration Symbolic Regression", "Iterates all possible model structures for a fixed grammar.")]
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21 | [StorableClass]
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22 | [Creatable(CreatableAttribute.Categories.DataAnalysisRegression, Priority = 250)]
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23 | public class GrammarEnumerationAlgorithm : FixedDataAnalysisAlgorithm<IRegressionProblem> {
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24 | private readonly string BestTrainingSolution = "Best solution (training)";
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25 | private readonly string BestTrainingSolutionQuality = "Best solution quality (training)";
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26 | private readonly string BestTestSolution = "Best solution (test)";
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27 | private readonly string BestTestSolutionQuality = "Best solution quality (test)";
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28 |
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29 | private readonly string MaxTreeSizeParameterName = "Max. Tree Nodes";
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30 | private readonly string GuiUpdateIntervalParameterName = "GUI Update Interval";
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31 |
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32 |
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33 | #region properties
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34 | public IValueParameter<IntValue> MaxTreeSizeParameter {
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35 | get { return (IValueParameter<IntValue>)Parameters[MaxTreeSizeParameterName]; }
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36 | }
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37 |
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38 | public int MaxTreeSize {
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39 | get { return MaxTreeSizeParameter.Value.Value; }
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40 | }
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41 |
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42 | public IValueParameter<IntValue> GuiUpdateIntervalParameter {
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43 | get { return (IValueParameter<IntValue>)Parameters[MaxTreeSizeParameterName]; }
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44 | }
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45 |
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46 | public int GuiUpdateInterval {
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47 | get { return GuiUpdateIntervalParameter.Value.Value; }
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48 | }
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49 |
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50 | #endregion
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51 |
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52 | private Grammar grammar;
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53 |
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54 |
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55 | #region ctors
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56 | public override IDeepCloneable Clone(Cloner cloner) {
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57 | return new GrammarEnumerationAlgorithm(this, cloner);
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58 | }
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59 |
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60 | public GrammarEnumerationAlgorithm() {
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61 | Problem = new RegressionProblem();
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62 |
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63 | Parameters.Add(new ValueParameter<IntValue>(MaxTreeSizeParameterName, "The number of clusters.", new IntValue(4)));
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64 | Parameters.Add(new ValueParameter<IntValue>(GuiUpdateIntervalParameterName, "Number of generated sentences, until GUI is refreshed.", new IntValue(4000)));
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65 | }
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66 |
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67 | private GrammarEnumerationAlgorithm(GrammarEnumerationAlgorithm original, Cloner cloner) : base(original, cloner) { }
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68 | #endregion
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69 |
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70 |
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71 | protected override void Run(CancellationToken cancellationToken) {
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72 | List<SymbolString> allGenerated = new List<SymbolString>();
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73 | List<SymbolString> distinctGenerated = new List<SymbolString>();
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74 | HashSet<int> evaluatedHashes = new HashSet<int>();
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75 |
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76 | grammar = new Grammar(Problem.ProblemData.AllowedInputVariables.ToArray());
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77 |
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78 | Stack<SymbolString> remainingTrees = new Stack<SymbolString>();
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79 | remainingTrees.Push(new SymbolString(new[] { grammar.StartSymbol }));
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80 |
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81 | while (remainingTrees.Any()) {
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82 | if (cancellationToken.IsCancellationRequested) break;
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83 |
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84 | SymbolString currSymbolString = remainingTrees.Pop();
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85 |
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86 | if (currSymbolString.IsSentence()) {
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87 | allGenerated.Add(currSymbolString);
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88 |
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89 | if (evaluatedHashes.Add(grammar.CalcHashCode(currSymbolString))) {
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90 | EvaluateSentence(currSymbolString);
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91 | distinctGenerated.Add(currSymbolString);
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92 | }
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93 |
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94 | UpdateView(allGenerated, distinctGenerated);
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95 |
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96 | } else {
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97 | // expand next nonterminal symbols
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98 | int nonterminalSymbolIndex = currSymbolString.FindIndex(s => s is NonterminalSymbol);
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99 | NonterminalSymbol expandedSymbol = currSymbolString[nonterminalSymbolIndex] as NonterminalSymbol;
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100 |
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101 | foreach (Production productionAlternative in expandedSymbol.Alternatives) {
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102 | SymbolString newSentence = new SymbolString(currSymbolString);
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103 | newSentence.RemoveAt(nonterminalSymbolIndex);
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104 | newSentence.InsertRange(nonterminalSymbolIndex, productionAlternative);
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105 |
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106 | if (newSentence.Count <= MaxTreeSize) {
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107 | remainingTrees.Push(newSentence);
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108 | }
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109 | }
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110 | }
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111 | }
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112 |
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113 | StringArray sentences = new StringArray(allGenerated.Select(r => r.ToString()).ToArray());
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114 | Results.Add(new Result("All generated sentences", sentences));
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115 | StringArray distinctSentences = new StringArray(distinctGenerated.Select(r => r.ToString()).ToArray());
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116 | Results.Add(new Result("Distinct generated sentences", distinctSentences));
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117 | }
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118 |
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119 |
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120 | private void UpdateView(List<SymbolString> allGenerated, List<SymbolString> distinctGenerated) {
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121 | int generatedSolutions = allGenerated.Count;
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122 | int distinctSolutions = distinctGenerated.Count;
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123 |
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124 | if (generatedSolutions % GuiUpdateInterval == 0) {
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125 | Results.AddOrUpdateResult("Generated Solutions", new IntValue(generatedSolutions));
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126 | Results.Add(new Result("Distinct Solutions", new IntValue(distinctSolutions)));
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127 |
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128 | DoubleValue averageTreeLength = new DoubleValue(allGenerated.Select(r => r.Count).Average());
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129 | Results.Add(new Result("Average Tree Length of Solutions", averageTreeLength));
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130 | }
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131 | }
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132 |
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133 | private void EvaluateSentence(SymbolString symbolString) {
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134 | SymbolicExpressionTree tree = grammar.ParseSymbolicExpressionTree(symbolString);
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135 | SymbolicRegressionModel model = new SymbolicRegressionModel(
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136 | Problem.ProblemData.TargetVariable,
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137 | tree,
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138 | new SymbolicDataAnalysisExpressionTreeLinearInterpreter());
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139 |
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140 | IRegressionSolution newSolution = model.CreateRegressionSolution(Problem.ProblemData);
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141 |
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142 | IResult currBestTrainingSolutionResult;
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143 | IResult currBestTestSolutionResult;
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144 | if (!Results.TryGetValue(BestTrainingSolution, out currBestTrainingSolutionResult)
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145 | || !Results.TryGetValue(BestTestSolution, out currBestTestSolutionResult)) {
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146 |
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147 | Results.Add(new Result(BestTrainingSolution, newSolution));
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148 | Results.Add(new Result(BestTrainingSolutionQuality, new DoubleValue(newSolution.TrainingRSquared).AsReadOnly()));
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149 | Results.Add(new Result(BestTestSolution, newSolution));
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150 | Results.Add(new Result(BestTestSolutionQuality, new DoubleValue(newSolution.TestRSquared).AsReadOnly()));
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151 |
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152 | } else {
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153 | IRegressionSolution currBestTrainingSolution = (IRegressionSolution)currBestTrainingSolutionResult.Value;
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154 | if (currBestTrainingSolution.TrainingRSquared < newSolution.TrainingRSquared) {
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155 | currBestTrainingSolutionResult.Value = newSolution;
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156 | Results.AddOrUpdateResult(BestTrainingSolutionQuality, new DoubleValue(newSolution.TrainingRSquared).AsReadOnly());
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157 | }
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158 |
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159 | IRegressionSolution currBestTestSolution = (IRegressionSolution)currBestTestSolutionResult.Value;
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160 | if (currBestTestSolution.TestRSquared < newSolution.TestRSquared) {
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161 | currBestTestSolutionResult.Value = newSolution;
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162 | Results.AddOrUpdateResult(BestTestSolutionQuality, new DoubleValue(newSolution.TestRSquared).AsReadOnly());
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163 | }
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164 | }
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165 | }
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166 | }
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167 | } |
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