1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2010 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.Linq;
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23 | using HeuristicLab.Analysis;
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24 | using HeuristicLab.Common;
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25 | using HeuristicLab.Core;
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26 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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27 | using HeuristicLab.Operators;
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28 | using HeuristicLab.Optimization;
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29 | using HeuristicLab.Parameters;
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30 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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31 | using HeuristicLab.Problems.DataAnalysis.Symbolic;
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32 |
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33 | namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic.Analyzers {
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34 | [Item("SymbolicRegressionVariableFrequencyAnalyzer", "An operator for analyzing the variable frequencies of symbolic regression solutions given in symbolic expression tree encoding.")]
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35 | [StorableClass]
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36 | public sealed class SymbolicRegressionVariableFrequencyAnalyzer : SingleSuccessorOperator, ISymbolicRegressionAnalyzer {
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37 | private const string SymbolicExpressionTreeParameterName = "SymbolicExpressionTree";
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38 | private const string ProblemDataParameterName = "ProblemData";
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39 | private const string VariableFrequenciesParameterName = "VariableFrequencies";
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40 | private const string ResultsParameterName = "Results";
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41 |
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42 | #region parameter properties
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43 | public ScopeTreeLookupParameter<SymbolicExpressionTree> SymbolicExpressionTreeParameter {
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44 | get { return (ScopeTreeLookupParameter<SymbolicExpressionTree>)Parameters[SymbolicExpressionTreeParameterName]; }
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45 | }
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46 | public ILookupParameter<DataTable> VariableFrequenciesParameter {
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47 | get { return (ILookupParameter<DataTable>)Parameters[VariableFrequenciesParameterName]; }
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48 | }
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49 | public ILookupParameter<DataAnalysisProblemData> ProblemDataParameter {
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50 | get { return (ILookupParameter<DataAnalysisProblemData>)Parameters[ProblemDataParameterName]; }
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51 | }
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52 | public ILookupParameter<ResultCollection> ResultsParameter {
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53 | get { return (ILookupParameter<ResultCollection>)Parameters[ResultsParameterName]; }
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54 | }
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55 | #endregion
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56 | #region properties
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57 | public DataTable VariableFrequencies {
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58 | get { return VariableFrequenciesParameter.ActualValue; }
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59 | set { VariableFrequenciesParameter.ActualValue = value; }
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60 | }
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61 | #endregion
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62 |
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63 | [StorableConstructor]
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64 | private SymbolicRegressionVariableFrequencyAnalyzer(bool deserializing) : base(deserializing) { }
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65 | private SymbolicRegressionVariableFrequencyAnalyzer(SymbolicRegressionVariableFrequencyAnalyzer original, Cloner cloner) : base(original, cloner) { }
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66 | public SymbolicRegressionVariableFrequencyAnalyzer()
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67 | : base() {
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68 | Parameters.Add(new ScopeTreeLookupParameter<SymbolicExpressionTree>(SymbolicExpressionTreeParameterName, "The symbolic expression trees to analyze."));
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69 | Parameters.Add(new LookupParameter<DataAnalysisProblemData>(ProblemDataParameterName, "The problem data containing the input varaibles for the symbolic regression problem."));
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70 | Parameters.Add(new ValueLookupParameter<DataTable>(VariableFrequenciesParameterName, "The data table to store the variable frequencies."));
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71 | Parameters.Add(new LookupParameter<ResultCollection>(ResultsParameterName, "The result collection where the best symbolic regression solution should be stored."));
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72 | }
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73 |
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74 | public override IDeepCloneable Clone(Cloner cloner) {
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75 | return new SymbolicRegressionVariableFrequencyAnalyzer(this, cloner);
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76 | }
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77 |
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78 | public override IOperation Apply(IExecutionContext context) {
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79 | ItemArray<SymbolicExpressionTree> expressions = SymbolicExpressionTreeParameter.ActualValue;
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80 | DataAnalysisProblemData problemData = ProblemDataParameter.ActualValue;
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81 | var inputVariables = problemData.InputVariables.CheckedItems.Select(x => x.Value.Value);
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82 | ResultCollection results = ResultsParameter.ActualValue;
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83 |
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84 | if (VariableFrequencies == null) {
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85 | VariableFrequencies = new DataTable("Variable frequencies", "Relative frequency of variable references aggregated over the whole population.");
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86 | VariableFrequencies.VisualProperties.XAxisTitle = "Generation";
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87 | VariableFrequencies.VisualProperties.YAxisTitle = "Relative Variable Frequency";
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88 | // add a data row for each input variable
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89 | foreach (var inputVariable in inputVariables) {
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90 | DataRow row = new DataRow(inputVariable);
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91 | row.VisualProperties.StartIndexZero = true;
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92 | VariableFrequencies.Rows.Add(row);
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93 | }
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94 | results.Add(new Result("Variable frequencies", VariableFrequencies));
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95 | }
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96 | foreach (var pair in VariableFrequencyAnalyser.CalculateVariableFrequencies(expressions, inputVariables)) {
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97 | VariableFrequencies.Rows[pair.Key].Values.Add(pair.Value);
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98 | results["Variable frequencies"].Value = VariableFrequencies;
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99 | }
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100 |
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101 | return base.Apply(context);
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102 | }
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103 | }
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104 | }
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