1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2018 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.Collections;
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24 | using System.Collections.Generic;
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25 | using System.Linq;
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26 | using HEAL.Attic;
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27 | using HeuristicLab.Common;
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28 | using HeuristicLab.Core;
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29 | using HeuristicLab.Data;
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30 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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31 | using HeuristicLab.EvolutionTracking;
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32 | using HeuristicLab.Parameters;
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33 |
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34 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
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35 | [Item("UpdateQualityOperator", "Put the estimated values of the tree in the scope to be used by the phenotypic similarity calculator")]
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36 | [StorableType("09FFEC05-12F2-4215-8C72-1B3EECF61C00")]
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37 | public class UpdateQualityOperator : EvolutionTrackingOperator<ISymbolicExpressionTree> {
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38 | private const string ProblemDataParameterName = "ProblemData";
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39 | private const string InterpreterParameterName = "SymbolicExpressionTreeInterpreter";
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40 | private const string EstimationLimitsParameterName = "EstimationLimits";
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41 | private const string SymbolicExpressionTreeParameterName = "SymbolicExpressionTree";
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42 | private const string ScaleEstimatedValuesParameterName = "ScaleEstimatedValues";
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43 |
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44 | #region parameters
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45 | public ILookupParameter<IRegressionProblemData> ProblemDataParameter {
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46 | get { return (ILookupParameter<IRegressionProblemData>)Parameters[ProblemDataParameterName]; }
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47 | }
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48 | public ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter> InterpreterParameter {
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49 | get { return (ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>)Parameters[InterpreterParameterName]; }
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50 | }
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51 | public ILookupParameter<DoubleLimit> EstimationLimitsParameter {
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52 | get { return (ILookupParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
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53 | }
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54 | public ILookupParameter<ISymbolicExpressionTree> SymbolicExpressionTreeParameter {
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55 | get { return (ILookupParameter<ISymbolicExpressionTree>)Parameters[SymbolicExpressionTreeParameterName]; }
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56 | }
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57 | public ILookupParameter<BoolValue> ScaleEstimatedValuesParameter {
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58 | get { return (ILookupParameter<BoolValue>)Parameters[ScaleEstimatedValuesParameterName]; }
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59 | }
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60 | #endregion
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61 |
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62 | public UpdateQualityOperator() {
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63 | Parameters.Add(new LookupParameter<IRegressionProblemData>(ProblemDataParameterName));
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64 | Parameters.Add(new LookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(InterpreterParameterName));
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65 | Parameters.Add(new LookupParameter<DoubleLimit>(EstimationLimitsParameterName));
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66 | Parameters.Add(new LookupParameter<ISymbolicExpressionTree>(SymbolicExpressionTreeParameterName));
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67 | Parameters.Add(new LookupParameter<BoolValue>(ScaleEstimatedValuesParameterName));
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68 | }
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69 |
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70 | [StorableConstructor]
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71 | protected UpdateQualityOperator(StorableConstructorFlag _) : base(_) { }
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72 |
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73 | protected UpdateQualityOperator(UpdateQualityOperator original, Cloner cloner) : base(original, cloner) {
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74 | }
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75 |
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76 | public override IDeepCloneable Clone(Cloner cloner) {
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77 | return new UpdateQualityOperator(this, cloner);
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78 | }
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79 |
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80 | public override IOperation Apply() {
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81 | var tree = SymbolicExpressionTreeParameter.ActualValue;
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82 | var problemData = ProblemDataParameter.ActualValue;
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83 | var estimationLimits = EstimationLimitsParameter.ActualValue;
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84 | var interpreter = InterpreterParameter.ActualValue;
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85 |
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86 | var estimatedValues = interpreter.GetSymbolicExpressionTreeValues(tree, problemData.Dataset, problemData.TrainingIndices);
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87 | var targetValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, problemData.TrainingIndices);
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88 |
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89 | var scaleEstimatedValues = ScaleEstimatedValuesParameter.ActualValue.Value;
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90 |
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91 | IEnumerable<double> scaled;
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92 | if (scaleEstimatedValues) {
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93 | var linearScalingCalculator = new OnlineLinearScalingParameterCalculator();
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94 |
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95 | var e1 = estimatedValues.GetEnumerator();
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96 | var e2 = targetValues.GetEnumerator();
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97 |
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98 | int count = 0;
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99 | while (e1.MoveNext() && e2.MoveNext()) {
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100 | var estimated = e1.Current;
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101 | var target = e2.Current;
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102 | if (!double.IsNaN(estimated) && !double.IsInfinity(estimated))
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103 | linearScalingCalculator.Add(estimated, target);
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104 | ++count;
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105 | }
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106 | if (e1.MoveNext() || e2.MoveNext())
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107 | throw new ArgumentException("Number of elements in target and estimated values enumeration do not match.");
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108 |
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109 | double alpha = linearScalingCalculator.Alpha;
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110 | double beta = linearScalingCalculator.Beta;
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111 | if (linearScalingCalculator.ErrorState != OnlineCalculatorError.None) {
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112 | alpha = 0.0;
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113 | beta = 1.0;
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114 | }
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115 | scaled = estimatedValues.Select(x => x * beta + alpha).LimitToRange(estimationLimits.Lower, estimationLimits.Upper);
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116 | } else {
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117 | scaled = estimatedValues.LimitToRange(estimationLimits.Lower, estimationLimits.Upper);
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118 | }
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119 |
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120 | OnlineCalculatorError error;
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121 | var r = OnlinePearsonsRCalculator.Calculate(targetValues, scaled, out error);
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122 | if (error != OnlineCalculatorError.None) r = double.NaN;
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123 |
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124 | var r2 = r * r;
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125 |
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126 | var variables = ExecutionContext.Scope.Variables;
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127 |
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128 | ((DoubleValue)variables["Quality"].Value).Value = r2;
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129 | //GenealogyGraph.GetByContent(tree).Quality = r2;
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130 |
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131 | if (variables.ContainsKey("EstimatedValues")) {
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132 | variables["EstimatedValues"].Value = new DoubleArray(scaled.ToArray());
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133 | } else {
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134 | variables.Add(new Core.Variable("EstimatedValues", new DoubleArray(scaled.ToArray())));
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135 | }
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136 | return base.Apply();
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137 | }
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138 | }
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139 | }
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