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source: branches/HeuristicLab.EvolutionTracking/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/SymbolicDataAnalysisProblem.cs @ 15301

Last change on this file since 15301 was 14878, checked in by bburlacu, 8 years ago

#1772: Merge trunk changes.

File size: 23.7 KB
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[5577]1#region License Information
2/* HeuristicLab
[14312]3 * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
[5577]4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using System.Drawing;
[5618]24using System.Linq;
[5577]25using HeuristicLab.Common;
26using HeuristicLab.Common.Resources;
27using HeuristicLab.Core;
28using HeuristicLab.Data;
[5618]29using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
[5577]30using HeuristicLab.Optimization;
31using HeuristicLab.Parameters;
32using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
[5618]33using HeuristicLab.PluginInfrastructure;
[7823]34using HeuristicLab.Problems.Instances;
[5577]35
36namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
37  [StorableClass]
[7823]38  public abstract class SymbolicDataAnalysisProblem<T, U, V> : HeuristicOptimizationProblem<U, V>, IDataAnalysisProblem<T>, ISymbolicDataAnalysisProblem, IStorableContent,
39    IProblemInstanceConsumer<T>, IProblemInstanceExporter<T>
[6978]40    where T : class, IDataAnalysisProblemData
[5580]41    where U : class, ISymbolicDataAnalysisEvaluator<T>
42    where V : class, ISymbolicDataAnalysisSolutionCreator {
[5770]43
[5577]44    #region parameter names & descriptions
45    private const string ProblemDataParameterName = "ProblemData";
46    private const string SymbolicExpressionTreeGrammarParameterName = "SymbolicExpressionTreeGrammar";
47    private const string SymbolicExpressionTreeInterpreterParameterName = "SymbolicExpressionTreeInterpreter";
48    private const string MaximumSymbolicExpressionTreeDepthParameterName = "MaximumSymbolicExpressionTreeDepth";
49    private const string MaximumSymbolicExpressionTreeLengthParameterName = "MaximumSymbolicExpressionTreeLength";
50    private const string MaximumFunctionDefinitionsParameterName = "MaximumFunctionDefinitions";
51    private const string MaximumFunctionArgumentsParameterName = "MaximumFunctionArguments";
[5759]52    private const string RelativeNumberOfEvaluatedSamplesParameterName = "RelativeNumberOfEvaluatedSamples";
[5733]53    private const string FitnessCalculationPartitionParameterName = "FitnessCalculationPartition";
[5775]54    private const string ValidationPartitionParameterName = "ValidationPartition";
[8664]55    private const string ApplyLinearScalingParameterName = "ApplyLinearScaling";
[5577]56
57    private const string ProblemDataParameterDescription = "";
58    private const string SymbolicExpressionTreeGrammarParameterDescription = "The grammar that should be used for symbolic expression tree.";
59    private const string SymoblicExpressionTreeInterpreterParameterDescription = "The interpreter that should be used to evaluate the symbolic expression tree.";
60    private const string MaximumSymbolicExpressionTreeDepthParameterDescription = "Maximal depth of the symbolic expression. The minimum depth needed for the algorithm is 3 because two levels are reserved for the ProgramRoot and the Start symbol.";
61    private const string MaximumSymbolicExpressionTreeLengthParameterDescription = "Maximal length of the symbolic expression.";
62    private const string MaximumFunctionDefinitionsParameterDescription = "Maximal number of automatically defined functions";
63    private const string MaximumFunctionArgumentsParameterDescription = "Maximal number of arguments of automatically defined functions.";
[5759]64    private const string RelativeNumberOfEvaluatedSamplesParameterDescription = "The relative number of samples of the dataset partition, which should be randomly chosen for evaluation.";
65    private const string FitnessCalculationPartitionParameterDescription = "The partition of the problem data training partition, that should be used to calculate the fitness of an individual.";
[5857]66    private const string ValidationPartitionParameterDescription = "The partition of the problem data training partition, that should be used to select the best model from (optional).";
[8664]67    private const string ApplyLinearScalingParameterDescription = "Flag that indicates if the individual should be linearly scaled before evaluating.";
[5577]68    #endregion
69
70    #region parameter properties
71    IParameter IDataAnalysisProblem.ProblemDataParameter {
72      get { return ProblemDataParameter; }
73    }
74    public IValueParameter<T> ProblemDataParameter {
75      get { return (IValueParameter<T>)Parameters[ProblemDataParameterName]; }
76    }
77    public IValueParameter<ISymbolicDataAnalysisGrammar> SymbolicExpressionTreeGrammarParameter {
78      get { return (IValueParameter<ISymbolicDataAnalysisGrammar>)Parameters[SymbolicExpressionTreeGrammarParameterName]; }
79    }
[5624]80    public IValueParameter<ISymbolicDataAnalysisExpressionTreeInterpreter> SymbolicExpressionTreeInterpreterParameter {
81      get { return (IValueParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>)Parameters[SymbolicExpressionTreeInterpreterParameterName]; }
[5577]82    }
[5618]83    public IFixedValueParameter<IntValue> MaximumSymbolicExpressionTreeDepthParameter {
84      get { return (IFixedValueParameter<IntValue>)Parameters[MaximumSymbolicExpressionTreeDepthParameterName]; }
[5577]85    }
[5618]86    public IFixedValueParameter<IntValue> MaximumSymbolicExpressionTreeLengthParameter {
87      get { return (IFixedValueParameter<IntValue>)Parameters[MaximumSymbolicExpressionTreeLengthParameterName]; }
[5577]88    }
[5618]89    public IFixedValueParameter<IntValue> MaximumFunctionDefinitionsParameter {
90      get { return (IFixedValueParameter<IntValue>)Parameters[MaximumFunctionDefinitionsParameterName]; }
[5577]91    }
[5618]92    public IFixedValueParameter<IntValue> MaximumFunctionArgumentsParameter {
93      get { return (IFixedValueParameter<IntValue>)Parameters[MaximumFunctionArgumentsParameterName]; }
[5577]94    }
[5759]95    public IFixedValueParameter<PercentValue> RelativeNumberOfEvaluatedSamplesParameter {
96      get { return (IFixedValueParameter<PercentValue>)Parameters[RelativeNumberOfEvaluatedSamplesParameterName]; }
97    }
98    public IFixedValueParameter<IntRange> FitnessCalculationPartitionParameter {
99      get { return (IFixedValueParameter<IntRange>)Parameters[FitnessCalculationPartitionParameterName]; }
100    }
[5883]101    public IFixedValueParameter<IntRange> ValidationPartitionParameter {
[5775]102      get { return (IFixedValueParameter<IntRange>)Parameters[ValidationPartitionParameterName]; }
[5759]103    }
[8664]104    public IFixedValueParameter<BoolValue> ApplyLinearScalingParameter {
105      get { return (IFixedValueParameter<BoolValue>)Parameters[ApplyLinearScalingParameterName]; }
106    }
[5577]107    #endregion
108
109    #region properties
110    public string Filename { get; set; }
[7201]111    public static new Image StaticItemImage { get { return VSImageLibrary.Type; } }
[5577]112
113    IDataAnalysisProblemData IDataAnalysisProblem.ProblemData {
114      get { return ProblemData; }
115    }
116    public T ProblemData {
117      get { return ProblemDataParameter.Value; }
[5618]118      set { ProblemDataParameter.Value = value; }
[5577]119    }
120
121    public ISymbolicDataAnalysisGrammar SymbolicExpressionTreeGrammar {
122      get { return SymbolicExpressionTreeGrammarParameter.Value; }
[5618]123      set { SymbolicExpressionTreeGrammarParameter.Value = value; }
[5577]124    }
[5624]125    public ISymbolicDataAnalysisExpressionTreeInterpreter SymbolicExpressionTreeInterpreter {
[5577]126      get { return SymbolicExpressionTreeInterpreterParameter.Value; }
[5618]127      set { SymbolicExpressionTreeInterpreterParameter.Value = value; }
[5577]128    }
129
130    public IntValue MaximumSymbolicExpressionTreeDepth {
131      get { return MaximumSymbolicExpressionTreeDepthParameter.Value; }
132    }
133    public IntValue MaximumSymbolicExpressionTreeLength {
134      get { return MaximumSymbolicExpressionTreeLengthParameter.Value; }
135    }
136    public IntValue MaximumFunctionDefinitions {
137      get { return MaximumFunctionDefinitionsParameter.Value; }
138    }
139    public IntValue MaximumFunctionArguments {
[5618]140      get { return MaximumFunctionArgumentsParameter.Value; }
[5577]141    }
[5759]142    public PercentValue RelativeNumberOfEvaluatedSamples {
143      get { return RelativeNumberOfEvaluatedSamplesParameter.Value; }
144    }
145
146    public IntRange FitnessCalculationPartition {
147      get { return FitnessCalculationPartitionParameter.Value; }
148    }
[5775]149    public IntRange ValidationPartition {
[5883]150      get { return ValidationPartitionParameter.Value; }
[5759]151    }
[8664]152    public BoolValue ApplyLinearScaling {
153      get { return ApplyLinearScalingParameter.Value; }
154    }
[5577]155    #endregion
156
157    [StorableConstructor]
158    protected SymbolicDataAnalysisProblem(bool deserializing) : base(deserializing) { }
[5618]159    [StorableHook(HookType.AfterDeserialization)]
160    private void AfterDeserialization() {
[8664]161      if (!Parameters.ContainsKey(ApplyLinearScalingParameterName)) {
162        Parameters.Add(new FixedValueParameter<BoolValue>(ApplyLinearScalingParameterName, ApplyLinearScalingParameterDescription, new BoolValue(false)));
163        ApplyLinearScalingParameter.Hidden = true;
[8666]164
165        //it is assumed that for all symbolic regression algorithms linear scaling was set to true
166        //there is no possibility to determine the previous value of the parameter as it was stored in the evaluator
167        if (GetType().Name.Contains("SymbolicRegression"))
168          ApplyLinearScaling.Value = true;
[8664]169      }
170
[5618]171      RegisterEventHandlers();
172    }
173    protected SymbolicDataAnalysisProblem(SymbolicDataAnalysisProblem<T, U, V> original, Cloner cloner)
174      : base(original, cloner) {
175      RegisterEventHandlers();
176    }
[5577]177
[5618]178    protected SymbolicDataAnalysisProblem(T problemData, U evaluator, V solutionCreator)
179      : base(evaluator, solutionCreator) {
180      Parameters.Add(new ValueParameter<T>(ProblemDataParameterName, ProblemDataParameterDescription, problemData));
[5577]181      Parameters.Add(new ValueParameter<ISymbolicDataAnalysisGrammar>(SymbolicExpressionTreeGrammarParameterName, SymbolicExpressionTreeGrammarParameterDescription));
[5624]182      Parameters.Add(new ValueParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(SymbolicExpressionTreeInterpreterParameterName, SymoblicExpressionTreeInterpreterParameterDescription));
[5847]183      Parameters.Add(new FixedValueParameter<IntValue>(MaximumSymbolicExpressionTreeDepthParameterName, MaximumSymbolicExpressionTreeDepthParameterDescription));
184      Parameters.Add(new FixedValueParameter<IntValue>(MaximumSymbolicExpressionTreeLengthParameterName, MaximumSymbolicExpressionTreeLengthParameterDescription));
185      Parameters.Add(new FixedValueParameter<IntValue>(MaximumFunctionDefinitionsParameterName, MaximumFunctionDefinitionsParameterDescription));
186      Parameters.Add(new FixedValueParameter<IntValue>(MaximumFunctionArgumentsParameterName, MaximumFunctionArgumentsParameterDescription));
187      Parameters.Add(new FixedValueParameter<IntRange>(FitnessCalculationPartitionParameterName, FitnessCalculationPartitionParameterDescription));
188      Parameters.Add(new FixedValueParameter<IntRange>(ValidationPartitionParameterName, ValidationPartitionParameterDescription));
[5759]189      Parameters.Add(new FixedValueParameter<PercentValue>(RelativeNumberOfEvaluatedSamplesParameterName, RelativeNumberOfEvaluatedSamplesParameterDescription, new PercentValue(1)));
[8664]190      Parameters.Add(new FixedValueParameter<BoolValue>(ApplyLinearScalingParameterName, ApplyLinearScalingParameterDescription, new BoolValue(false)));
[5618]191
[5854]192      SymbolicExpressionTreeInterpreterParameter.Hidden = true;
193      MaximumFunctionArgumentsParameter.Hidden = true;
194      MaximumFunctionDefinitionsParameter.Hidden = true;
[8664]195      ApplyLinearScalingParameter.Hidden = true;
[5854]196
[5618]197      SymbolicExpressionTreeGrammar = new TypeCoherentExpressionGrammar();
[9830]198      SymbolicExpressionTreeInterpreter = new SymbolicDataAnalysisExpressionTreeLinearInterpreter();
[5618]199
[5770]200      FitnessCalculationPartition.Start = ProblemData.TrainingPartition.Start;
201      FitnessCalculationPartition.End = ProblemData.TrainingPartition.End;
202
[5722]203      InitializeOperators();
204
[5618]205      UpdateGrammar();
206      RegisterEventHandlers();
[5577]207    }
208
[5685]209    protected virtual void UpdateGrammar() {
[14878]210      var problemData = ProblemData;
211      var ds = problemData.Dataset;
212      var grammar = SymbolicExpressionTreeGrammar;
213      grammar.MaximumFunctionArguments = MaximumFunctionArguments.Value;
214      grammar.MaximumFunctionDefinitions = MaximumFunctionDefinitions.Value;
215      foreach (var varSymbol in grammar.Symbols.OfType<HeuristicLab.Problems.DataAnalysis.Symbolic.VariableBase>()) {
[8936]216        if (!varSymbol.Fixed) {
[14878]217          varSymbol.AllVariableNames = problemData.InputVariables.Select(x => x.Value).Where(x => ds.VariableHasType<double>(x));
218          varSymbol.VariableNames = problemData.AllowedInputVariables.Where(x => ds.VariableHasType<double>(x));
[8936]219        }
[5685]220      }
[14878]221      foreach (var factorSymbol in grammar.Symbols.OfType<BinaryFactorVariable>()) {
222        if (!factorSymbol.Fixed) {
223          factorSymbol.AllVariableNames = problemData.InputVariables.Select(x => x.Value).Where(x => ds.VariableHasType<string>(x));
224          factorSymbol.VariableNames = problemData.AllowedInputVariables.Where(x => ds.VariableHasType<string>(x));
225          factorSymbol.VariableValues = factorSymbol.VariableNames
226            .ToDictionary(varName => varName, varName => ds.GetStringValues(varName).Distinct().ToList());
[8936]227        }
[5685]228      }
[14878]229      foreach (var factorSymbol in grammar.Symbols.OfType<FactorVariable>()) {
230        if (!factorSymbol.Fixed) {
231          factorSymbol.AllVariableNames = problemData.InputVariables.Select(x => x.Value).Where(x => ds.VariableHasType<string>(x));
232          factorSymbol.VariableNames = problemData.AllowedInputVariables.Where(x => ds.VariableHasType<string>(x));
233          factorSymbol.VariableValues = factorSymbol.VariableNames
234            .ToDictionary(varName => varName,
235            varName => ds.GetStringValues(varName).Distinct()
236            .Select((n, i) => Tuple.Create(n, i))
237            .ToDictionary(tup => tup.Item1, tup => tup.Item2));
238        }
239      }
[5685]240    }
241
[5618]242    private void InitializeOperators() {
243      Operators.AddRange(ApplicationManager.Manager.GetInstances<ISymbolicExpressionTreeOperator>());
[7506]244      Operators.AddRange(ApplicationManager.Manager.GetInstances<ISymbolicDataAnalysisExpressionCrossover<T>>());
[5618]245      Operators.Add(new SymbolicExpressionSymbolFrequencyAnalyzer());
[5685]246      Operators.Add(new SymbolicDataAnalysisVariableFrequencyAnalyzer());
[5618]247      Operators.Add(new MinAverageMaxSymbolicExpressionTreeLengthAnalyzer());
[6978]248      Operators.Add(new SymbolicExpressionTreeLengthAnalyzer());
[12155]249      Operators.Add(new SymbolicExpressionTreeBottomUpSimilarityCalculator());
250      Operators.Add(new SymbolicDataAnalysisBottomUpDiversityAnalyzer(Operators.OfType<SymbolicExpressionTreeBottomUpSimilarityCalculator>().First()));
[11928]251      Operators.Add(new SymbolicDataAnalysisGenealogyAnalyzer());
[5618]252      ParameterizeOperators();
253    }
254
[5685]255    #region events
[5618]256    private void RegisterEventHandlers() {
257      ProblemDataParameter.ValueChanged += new EventHandler(ProblemDataParameter_ValueChanged);
258      ProblemDataParameter.Value.Changed += (object sender, EventArgs e) => OnProblemDataChanged();
259
[5841]260      SymbolicExpressionTreeGrammarParameter.ValueChanged += new EventHandler(SymbolicExpressionTreeGrammarParameter_ValueChanged);
261
[5618]262      MaximumFunctionArguments.ValueChanged += new EventHandler(ArchitectureParameterValue_ValueChanged);
263      MaximumFunctionDefinitions.ValueChanged += new EventHandler(ArchitectureParameterValue_ValueChanged);
264      MaximumSymbolicExpressionTreeDepth.ValueChanged += new EventHandler(MaximumSymbolicExpressionTreeDepth_ValueChanged);
265    }
266
[5685]267    private void ProblemDataParameter_ValueChanged(object sender, EventArgs e) {
[5887]268      ValidationPartition.Start = 0;
269      ValidationPartition.End = 0;
[5685]270      ProblemDataParameter.Value.Changed += (object s, EventArgs args) => OnProblemDataChanged();
271      OnProblemDataChanged();
272    }
273
[5841]274    private void SymbolicExpressionTreeGrammarParameter_ValueChanged(object sender, EventArgs e) {
275      UpdateGrammar();
276    }
277
[5618]278    private void ArchitectureParameterValue_ValueChanged(object sender, EventArgs e) {
279      UpdateGrammar();
280    }
281
282    private void MaximumSymbolicExpressionTreeDepth_ValueChanged(object sender, EventArgs e) {
283      if (MaximumSymbolicExpressionTreeDepth != null && MaximumSymbolicExpressionTreeDepth.Value < 3)
284        MaximumSymbolicExpressionTreeDepth.Value = 3;
285    }
286
287    protected override void OnSolutionCreatorChanged() {
288      base.OnSolutionCreatorChanged();
289      SolutionCreator.SymbolicExpressionTreeParameter.ActualNameChanged += new EventHandler(SolutionCreator_SymbolicExpressionTreeParameter_ActualNameChanged);
290      ParameterizeOperators();
291    }
[5685]292
[5618]293    private void SolutionCreator_SymbolicExpressionTreeParameter_ActualNameChanged(object sender, EventArgs e) {
294      ParameterizeOperators();
295    }
296
297    protected override void OnEvaluatorChanged() {
298      base.OnEvaluatorChanged();
[5685]299      ParameterizeOperators();
[5618]300    }
301
[5577]302    public event EventHandler ProblemDataChanged;
303    protected virtual void OnProblemDataChanged() {
[5770]304      FitnessCalculationPartition.Start = ProblemData.TrainingPartition.Start;
305      FitnessCalculationPartition.End = ProblemData.TrainingPartition.End;
306
[5618]307      UpdateGrammar();
[5685]308      ParameterizeOperators();
309
[5577]310      var handler = ProblemDataChanged;
311      if (handler != null) handler(this, EventArgs.Empty);
[5618]312
313      OnReset();
[5577]314    }
[5685]315    #endregion
[5618]316
[5685]317    protected virtual void ParameterizeOperators() {
[12891]318      var operators =
319        Parameters.OfType<IValueParameter>().Select(p => p.Value).OfType<IOperator>().Union(Operators).ToList();
[5618]320
321      foreach (var op in operators.OfType<ISymbolicExpressionTreeGrammarBasedOperator>()) {
[8664]322        op.SymbolicExpressionTreeGrammarParameter.ActualName = SymbolicExpressionTreeGrammarParameter.Name;
[5618]323      }
324      foreach (var op in operators.OfType<ISymbolicExpressionTreeSizeConstraintOperator>()) {
[8664]325        op.MaximumSymbolicExpressionTreeDepthParameter.ActualName = MaximumSymbolicExpressionTreeDepthParameter.Name;
326        op.MaximumSymbolicExpressionTreeLengthParameter.ActualName = MaximumSymbolicExpressionTreeLengthParameter.Name;
[5618]327      }
328      foreach (var op in operators.OfType<ISymbolicExpressionTreeArchitectureAlteringOperator>()) {
[8664]329        op.MaximumFunctionArgumentsParameter.ActualName = MaximumFunctionArgumentsParameter.Name;
330        op.MaximumFunctionDefinitionsParameter.ActualName = MaximumFunctionDefinitionsParameter.Name;
[5618]331      }
332      foreach (var op in operators.OfType<ISymbolicDataAnalysisEvaluator<T>>()) {
[5685]333        op.ProblemDataParameter.ActualName = ProblemDataParameterName;
[5618]334        op.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
[5759]335        op.EvaluationPartitionParameter.ActualName = FitnessCalculationPartitionParameter.Name;
336        op.RelativeNumberOfEvaluatedSamplesParameter.ActualName = RelativeNumberOfEvaluatedSamplesParameter.Name;
[8664]337        op.ApplyLinearScalingParameter.ActualName = ApplyLinearScalingParameter.Name;
[5618]338      }
339      foreach (var op in operators.OfType<ISymbolicExpressionTreeCrossover>()) {
340        op.ParentsParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
[12891]341        op.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
[5618]342      }
343      foreach (var op in operators.OfType<ISymbolicExpressionTreeManipulator>()) {
344        op.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
345      }
346      foreach (var op in operators.OfType<ISymbolicExpressionTreeAnalyzer>()) {
347        op.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
348      }
[8664]349      foreach (var op in operators.OfType<ISymbolicDataAnalysisSingleObjectiveAnalyzer>()) {
350        op.ApplyLinearScalingParameter.ActualName = ApplyLinearScalingParameter.Name;
351      }
352      foreach (var op in operators.OfType<ISymbolicDataAnalysisMultiObjectiveAnalyzer>()) {
353        op.ApplyLinearScalingParameter.ActualName = ApplyLinearScalingParameter.Name;
354      }
[6135]355      foreach (var op in operators.OfType<ISymbolicDataAnalysisAnalyzer>()) {
356        op.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
357      }
[5759]358      foreach (var op in operators.OfType<ISymbolicDataAnalysisValidationAnalyzer<U, T>>()) {
359        op.RelativeNumberOfEvaluatedSamplesParameter.ActualName = RelativeNumberOfEvaluatedSamplesParameter.Name;
[5883]360        op.ValidationPartitionParameter.ActualName = ValidationPartitionParameter.Name;
[5759]361      }
[5685]362      foreach (var op in operators.OfType<ISymbolicDataAnalysisInterpreterOperator>()) {
[8664]363        op.SymbolicDataAnalysisTreeInterpreterParameter.ActualName = SymbolicExpressionTreeInterpreterParameter.Name;
[5685]364      }
[7506]365      foreach (var op in operators.OfType<ISymbolicDataAnalysisExpressionCrossover<T>>()) {
[8664]366        op.EvaluationPartitionParameter.ActualName = FitnessCalculationPartitionParameter.Name;
[7506]367        op.ProblemDataParameter.ActualName = ProblemDataParameter.Name;
368        op.EvaluationPartitionParameter.ActualName = FitnessCalculationPartitionParameter.Name;
369        op.RelativeNumberOfEvaluatedSamplesParameter.ActualName = RelativeNumberOfEvaluatedSamplesParameter.Name;
370        op.EvaluatorParameter.ActualName = EvaluatorParameter.Name;
371      }
[11928]372      // add tracking analyzer
373      foreach (var op in operators.OfType<SymbolicDataAnalysisGenealogyAnalyzer>()) {
374        op.BeforeCrossoverOperatorParameter.ActualValue = new SymbolicDataAnalysisExpressionBeforeCrossoverOperator();
375        op.AfterCrossoverOperatorParameter.ActualValue = new SymbolicDataAnalysisExpressionAfterCrossoverOperator();
[12891]376        op.BeforeManipulatorOperatorParameter.ActualValue =
377          new SymbolicDataAnalysisExpressionBeforeManipulatorOperator();
[11928]378        op.AfterManipulatorOperatorParameter.ActualValue = new SymbolicDataAnalysisExpressionAfterManipulatorOperator();
379        // get crossover parameter names
380        var crossover = operators.OfType<ISymbolicExpressionTreeCrossover>().FirstOrDefault();
381        if (crossover != null) {
382          op.BeforeCrossoverOperator.ParentsParameter.ActualName = crossover.ParentsParameter.Name;
383          op.AfterCrossoverOperator.ParentsParameter.ActualName = crossover.ParentsParameter.Name;
[12891]384          op.BeforeCrossoverOperator.ChildParameter.ActualName = crossover.SymbolicExpressionTreeParameter.Name;
385          op.AfterCrossoverOperator.ChildParameter.ActualName = crossover.SymbolicExpressionTreeParameter.Name;
386          // get manipulator parameter names
387          var manipulator = operators.OfType<ISymbolicExpressionTreeManipulator>().FirstOrDefault();
388          if (manipulator != null) {
389            op.BeforeManipulatorOperator.ChildParameter.ActualName = manipulator.SymbolicExpressionTreeParameter.Name;
390            op.AfterManipulatorOperator.ChildParameter.ActualName = manipulator.SymbolicExpressionTreeParameter.Name;
391          }
392          var creator = operators.OfType<ISymbolicExpressionTreeCreator>().FirstOrDefault();
393          if (creator != null) {
394            op.PopulationParameter.ActualName = creator.SymbolicExpressionTreeParameter.ActualName;
395          }
[11928]396        }
397      }
[5618]398    }
[5623]399
[7823]400    #region Import & Export
[9452]401    public virtual void Load(T data) {
[7823]402      Name = data.Name;
403      Description = data.Description;
404      ProblemData = data;
405    }
406
[9452]407    public virtual T Export() {
[7823]408      return ProblemData;
409    }
410    #endregion
[5577]411  }
412}
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