[12029] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[16453] | 3 | * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[12029] | 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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[12075] | 22 | using System.Collections.Generic;
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[12977] | 23 | using System.Linq;
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[12029] | 24 | using HeuristicLab.Analysis;
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| 25 | using HeuristicLab.Common;
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| 26 | using HeuristicLab.Core;
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[12977] | 27 | using HeuristicLab.Data;
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| 28 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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[12075] | 29 | using HeuristicLab.Optimization;
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[12977] | 30 | using HeuristicLab.Parameters;
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[16559] | 31 | using HEAL.Attic;
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[12029] | 32 |
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[12049] | 33 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
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[12030] | 34 | [Item("SymbolicRegressionPhenotypicDiversityAnalyzer", "An analyzer which calculates diversity based on the phenotypic distance between trees")]
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[16462] | 35 | [StorableType("A72624D2-6628-45E6-8EBF-4AAD88CC01F5")]
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[12977] | 36 | public class SymbolicRegressionPhenotypicDiversityAnalyzer : PopulationSimilarityAnalyzer,
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| 37 | ISymbolicDataAnalysisBoundedOperator, ISymbolicDataAnalysisInterpreterOperator, ISymbolicExpressionTreeAnalyzer {
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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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[12086] | 64 | public SymbolicRegressionPhenotypicDiversityAnalyzer(IEnumerable<ISolutionSimilarityCalculator> validSimilarityCalculators)
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[12075] | 65 | : base(validSimilarityCalculators) {
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[12977] | 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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[12075] | 73 |
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| 74 | UpdateCounterParameter.ActualName = "PhenotypicDiversityAnalyzerUpdateCounter";
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[12103] | 75 | DiversityResultName = "Phenotypic Diversity";
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[12029] | 76 | }
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| 77 |
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| 78 | [StorableConstructor]
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[16462] | 79 | protected SymbolicRegressionPhenotypicDiversityAnalyzer(StorableConstructorFlag _) : base(_) {
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[12029] | 80 | }
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| 81 |
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| 82 | public override IDeepCloneable Clone(Cloner cloner) {
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| 83 | return new SymbolicRegressionPhenotypicDiversityAnalyzer(this, cloner);
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| 84 | }
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| 85 |
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[12103] | 86 | protected SymbolicRegressionPhenotypicDiversityAnalyzer(SymbolicRegressionPhenotypicDiversityAnalyzer original, Cloner cloner)
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[12029] | 87 | : base(original, cloner) {
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| 88 | }
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[12977] | 89 |
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| 90 | public override IOperation Apply() {
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| 91 | int updateInterval = UpdateIntervalParameter.Value.Value;
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| 92 | IntValue updateCounter = UpdateCounterParameter.ActualValue;
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| 93 |
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| 94 | if (updateCounter == null) {
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| 95 | updateCounter = new IntValue(updateInterval);
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| 96 | UpdateCounterParameter.ActualValue = updateCounter;
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| 97 | }
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| 98 |
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[14354] | 99 | if (updateCounter.Value == updateInterval) {
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| 100 | var trees = SymbolicExpressionTreeParameter.ActualValue;
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[12977] | 101 | var interpreter = SymbolicDataAnalysisTreeInterpreterParameter.ActualValue;
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| 102 | var ds = ProblemDataParameter.ActualValue.Dataset;
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| 103 | var rows = ProblemDataParameter.ActualValue.TrainingIndices;
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| 104 |
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[14354] | 105 | var evaluatedValues = new ItemArray<DoubleArray>(trees.Select(t => new DoubleArray(interpreter.GetSymbolicExpressionTreeValues(t, ds, rows).ToArray())));
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| 106 | EvaluatedValuesParameter.ActualValue = evaluatedValues;
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[12977] | 107 | }
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| 108 | return base.Apply();
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| 109 | }
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[12029] | 110 | }
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| 111 | }
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