1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2015 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.Collections.Generic;
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23 | using System.Linq;
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24 | using HeuristicLab.Analysis;
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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.Optimization;
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30 | using HeuristicLab.Parameters;
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31 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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32 |
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33 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
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34 | [Item("SymbolicRegressionPhenotypicDiversityAnalyzer", "An analyzer which calculates diversity based on the phenotypic distance between trees")]
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35 | [StorableClass]
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36 | public class SymbolicRegressionPhenotypicDiversityAnalyzer : PopulationSimilarityAnalyzer,
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37 | ISymbolicDataAnalysisBoundedOperator, ISymbolicDataAnalysisInterpreterOperator, ISymbolicExpressionTreeOperator {
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38 | #region parameter names
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39 | private const string SymbolicExpressionTreeParameterName = "SymbolicExpressionTree";
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40 | private const string EvaluatedValuesParameterName = "EstimatedValues";
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41 | private const string SymbolicDataAnalysisTreeInterpreterParameterName = "SymbolicExpressionTreeInterpreter";
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42 | private const string ProblemDataParameterName = "ProblemData";
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43 | private const string EstimationLimitsParameterName = "EstimationLimits";
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44 | #endregion
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45 |
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46 | #region parameter properties
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47 | public IScopeTreeLookupParameter<ISymbolicExpressionTree> SymbolicExpressionTreeParameter {
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48 | get { return (IScopeTreeLookupParameter<ISymbolicExpressionTree>)Parameters[SymbolicExpressionTreeParameterName]; }
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49 | }
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50 | private IScopeTreeLookupParameter<DoubleArray> EvaluatedValuesParameter {
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51 | get { return (IScopeTreeLookupParameter<DoubleArray>)Parameters[EvaluatedValuesParameterName]; }
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52 | }
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53 | public ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter> SymbolicDataAnalysisTreeInterpreterParameter {
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54 | get { return (ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>)Parameters[SymbolicDataAnalysisTreeInterpreterParameterName]; }
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55 | }
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56 | public IValueLookupParameter<IRegressionProblemData> ProblemDataParameter {
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57 | get { return (IValueLookupParameter<IRegressionProblemData>)Parameters[ProblemDataParameterName]; }
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58 | }
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59 | public IValueLookupParameter<DoubleLimit> EstimationLimitsParameter {
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60 | get { return (IValueLookupParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
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61 | }
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62 | #endregion
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63 |
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64 | public SymbolicRegressionPhenotypicDiversityAnalyzer(IEnumerable<ISolutionSimilarityCalculator> validSimilarityCalculators)
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65 | : base(validSimilarityCalculators) {
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66 | #region add parameters
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67 | Parameters.Add(new ScopeTreeLookupParameter<ISymbolicExpressionTree>(SymbolicExpressionTreeParameterName, "The symbolic expression trees."));
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68 | Parameters.Add(new ScopeTreeLookupParameter<DoubleArray>(EvaluatedValuesParameterName, "Intermediate estimated values to be saved in the scopes."));
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69 | Parameters.Add(new LookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(SymbolicDataAnalysisTreeInterpreterParameterName, "The interpreter that should be used to calculate the output values of the symbolic data analysis tree."));
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70 | Parameters.Add(new ValueLookupParameter<IRegressionProblemData>(ProblemDataParameterName, "The problem data on which the symbolic data analysis solution should be evaluated."));
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71 | Parameters.Add(new ValueLookupParameter<DoubleLimit>(EstimationLimitsParameterName, "The upper and lower limit that should be used as cut off value for the output values of symbolic data analysis trees."));
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72 | #endregion
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73 |
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74 | UpdateCounterParameter.ActualName = "PhenotypicDiversityAnalyzerUpdateCounter";
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75 | DiversityResultName = "Phenotypic Diversity";
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76 | }
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77 |
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78 | [StorableConstructor]
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79 | protected SymbolicRegressionPhenotypicDiversityAnalyzer(bool deserializing)
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80 | : base(deserializing) {
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81 | }
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82 |
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83 | public override IDeepCloneable Clone(Cloner cloner) {
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84 | return new SymbolicRegressionPhenotypicDiversityAnalyzer(this, cloner);
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85 | }
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86 |
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87 | protected SymbolicRegressionPhenotypicDiversityAnalyzer(SymbolicRegressionPhenotypicDiversityAnalyzer original, Cloner cloner)
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88 | : base(original, cloner) {
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89 | }
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90 |
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91 | public override IOperation Apply() {
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92 | int updateInterval = UpdateIntervalParameter.Value.Value;
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93 | IntValue updateCounter = UpdateCounterParameter.ActualValue;
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94 |
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95 | if (updateCounter == null) {
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96 | updateCounter = new IntValue(updateInterval);
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97 | UpdateCounterParameter.ActualValue = updateCounter;
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98 | }
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99 |
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100 | if (updateCounter.Value == updateInterval) {
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101 | var trees = SymbolicExpressionTreeParameter.ActualValue;
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102 | var interpreter = SymbolicDataAnalysisTreeInterpreterParameter.ActualValue;
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103 | var ds = ProblemDataParameter.ActualValue.Dataset;
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104 | var rows = ProblemDataParameter.ActualValue.TrainingIndices;
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105 |
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106 | var evaluatedValues = new ItemArray<DoubleArray>(trees.Select(t => new DoubleArray(interpreter.GetSymbolicExpressionTreeValues(t, ds, rows).ToArray())));
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107 | EvaluatedValuesParameter.ActualValue = evaluatedValues;
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108 | }
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109 | return base.Apply();
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110 | }
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111 | }
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112 | }
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