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source: branches/CloningRefactoring/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/SymbolicRegressionProblem.cs @ 4682

Last change on this file since 4682 was 4678, checked in by gkronber, 14 years ago

Refactored cloning in DataAnalysis plugins. #922

File size: 8.8 KB
RevLine 
[3253]1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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.Linq;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Data;
27using HeuristicLab.Optimization;
28using HeuristicLab.Parameters;
29using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
[4068]30using HeuristicLab.Problems.DataAnalysis.Regression.Symbolic.Analyzers;
[3253]31
32namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic {
[4128]33  [Item("Symbolic Regression Problem (single objective)", "Represents a single objective symbolic regression problem.")]
[3253]34  [Creatable("Problems")]
35  [StorableClass]
[4678]36  public sealed class SymbolicRegressionProblem : SymbolicRegressionProblemBase, ISingleObjectiveDataAnalysisProblem {
[3253]37
38    #region Parameter Properties
39    public ValueParameter<BoolValue> MaximizationParameter {
40      get { return (ValueParameter<BoolValue>)Parameters["Maximization"]; }
41    }
42    IParameter ISingleObjectiveProblem.MaximizationParameter {
43      get { return MaximizationParameter; }
44    }
[4036]45    public new ValueParameter<ISymbolicRegressionEvaluator> EvaluatorParameter {
[3253]46      get { return (ValueParameter<ISymbolicRegressionEvaluator>)Parameters["Evaluator"]; }
47    }
48    IParameter IProblem.EvaluatorParameter {
49      get { return EvaluatorParameter; }
50    }
[3452]51    public OptionalValueParameter<DoubleValue> BestKnownQualityParameter {
52      get { return (OptionalValueParameter<DoubleValue>)Parameters["BestKnownQuality"]; }
[3253]53    }
54    IParameter ISingleObjectiveProblem.BestKnownQualityParameter {
55      get { return BestKnownQualityParameter; }
56    }
57    #endregion
58
59    #region Properties
[4036]60    public new ISymbolicRegressionEvaluator Evaluator {
[3253]61      get { return EvaluatorParameter.Value; }
62      set { EvaluatorParameter.Value = value; }
63    }
64    ISingleObjectiveEvaluator ISingleObjectiveProblem.Evaluator {
65      get { return EvaluatorParameter.Value; }
66    }
67    IEvaluator IProblem.Evaluator {
68      get { return EvaluatorParameter.Value; }
69    }
70    public DoubleValue BestKnownQuality {
71      get { return BestKnownQualityParameter.Value; }
72    }
73    #endregion
74
[4098]75    [StorableConstructor]
[4678]76    private SymbolicRegressionProblem(bool deserializing) : base(deserializing) { }
77    private SymbolicRegressionProblem(SymbolicRegressionProblem original, Cloner cloner)
78      : base(original, cloner) {
79      RegisterParameterEvents();
80      RegisterParameterValueEvents();
81    }
82
[3253]83    public SymbolicRegressionProblem()
84      : base() {
[4250]85      var evaluator = new SymbolicRegressionPearsonsRSquaredEvaluator();
86      Parameters.Add(new ValueParameter<BoolValue>("Maximization", "Set to false as the error of the regression model should be minimized.", (BoolValue)new BoolValue(true)));
[3253]87      Parameters.Add(new ValueParameter<ISymbolicRegressionEvaluator>("Evaluator", "The operator which should be used to evaluate symbolic regression solutions.", evaluator));
[3452]88      Parameters.Add(new OptionalValueParameter<DoubleValue>("BestKnownQuality", "The minimal error value that reached by symbolic regression solutions for the problem."));
[3253]89
[4250]90      evaluator.QualityParameter.ActualName = "TrainingPearsonR2";
[3545]91
[4128]92      InitializeOperators();
[3253]93      ParameterizeEvaluator();
94
[4118]95      RegisterParameterEvents();
96      RegisterParameterValueEvents();
[3253]97    }
98
[3452]99    public override IDeepCloneable Clone(Cloner cloner) {
[4678]100      return new SymbolicRegressionProblem(this, cloner);
[3452]101    }
102
[3545]103    private void RegisterParameterValueEvents() {
104      EvaluatorParameter.ValueChanged += new EventHandler(EvaluatorParameter_ValueChanged);
[3269]105    }
106
[4128]107    private void RegisterParameterEvents() { }
[3545]108
109    #region event handling
110    protected override void OnDataAnalysisProblemChanged(EventArgs e) {
111      base.OnDataAnalysisProblemChanged(e);
[3800]112      BestKnownQualityParameter.Value = null;
[3545]113      // paritions could be changed
114      ParameterizeEvaluator();
[3651]115      ParameterizeAnalyzers();
[3480]116    }
[3532]117
[4128]118    protected override void OnSolutionParameterNameChanged(EventArgs e) {
119      base.OnSolutionParameterNameChanged(e);
[3545]120      ParameterizeEvaluator();
[3651]121      ParameterizeAnalyzers();
[3294]122    }
123
[4128]124    protected override void OnEvaluatorChanged(EventArgs e) {
125      base.OnEvaluatorChanged(e);
[3545]126      ParameterizeEvaluator();
[3651]127      ParameterizeAnalyzers();
[3545]128      RaiseEvaluatorChanged(e);
129    }
130    #endregion
[3513]131
[3545]132    #region event handlers
133    private void EvaluatorParameter_ValueChanged(object sender, EventArgs e) {
134      OnEvaluatorChanged(e);
135    }
136    #endregion
[3253]137
[3545]138    #region Helpers
[4098]139    [StorableHook(HookType.AfterDeserialization)]
[4118]140    private void AfterDeserializationHook() {
141      // BackwardsCompatibility3.3
142      #region Backwards compatible code (remove with 3.4)
[4128]143      if (Operators == null || Operators.Count() == 0) InitializeOperators();
[4118]144      #endregion
[3545]145      RegisterParameterEvents();
146      RegisterParameterValueEvents();
[3253]147    }
148
149    private void InitializeOperators() {
[4128]150      AddOperator(new FixedValidationBestScaledSymbolicRegressionSolutionAnalyzer());
[3651]151      ParameterizeAnalyzers();
[3253]152    }
153
154    private void ParameterizeEvaluator() {
[3452]155      Evaluator.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
[3373]156      Evaluator.RegressionProblemDataParameter.ActualName = DataAnalysisProblemDataParameter.Name;
[3545]157      Evaluator.SamplesStartParameter.Value = TrainingSamplesStart;
158      Evaluator.SamplesEndParameter.Value = TrainingSamplesEnd;
[3253]159    }
[3545]160
[3651]161    private void ParameterizeAnalyzers() {
162      foreach (var analyzer in Analyzers) {
163        analyzer.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
[3996]164        var fixedBestValidationSolutionAnalyzer = analyzer as FixedValidationBestScaledSymbolicRegressionSolutionAnalyzer;
165        if (fixedBestValidationSolutionAnalyzer != null) {
166          fixedBestValidationSolutionAnalyzer.ProblemDataParameter.ActualName = DataAnalysisProblemDataParameter.Name;
167          fixedBestValidationSolutionAnalyzer.UpperEstimationLimitParameter.ActualName = UpperEstimationLimitParameter.Name;
168          fixedBestValidationSolutionAnalyzer.LowerEstimationLimitParameter.ActualName = LowerEstimationLimitParameter.Name;
169          fixedBestValidationSolutionAnalyzer.SymbolicExpressionTreeInterpreterParameter.ActualName = SymbolicExpressionTreeInterpreterParameter.Name;
170          fixedBestValidationSolutionAnalyzer.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
171          fixedBestValidationSolutionAnalyzer.ValidationSamplesStartParameter.Value = ValidationSamplesStart;
172          fixedBestValidationSolutionAnalyzer.ValidationSamplesEndParameter.Value = ValidationSamplesEnd;
173          fixedBestValidationSolutionAnalyzer.BestKnownQualityParameter.ActualName = BestKnownQualityParameter.Name;
174        }
[4468]175
[4127]176        var bestValidationSolutionAnalyzer = analyzer as ValidationBestScaledSymbolicRegressionSolutionAnalyzer;
[3651]177        if (bestValidationSolutionAnalyzer != null) {
178          bestValidationSolutionAnalyzer.ProblemDataParameter.ActualName = DataAnalysisProblemDataParameter.Name;
179          bestValidationSolutionAnalyzer.UpperEstimationLimitParameter.ActualName = UpperEstimationLimitParameter.Name;
180          bestValidationSolutionAnalyzer.LowerEstimationLimitParameter.ActualName = LowerEstimationLimitParameter.Name;
181          bestValidationSolutionAnalyzer.SymbolicExpressionTreeInterpreterParameter.ActualName = SymbolicExpressionTreeInterpreterParameter.Name;
182          bestValidationSolutionAnalyzer.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
[3806]183          bestValidationSolutionAnalyzer.ValidationSamplesStartParameter.Value = ValidationSamplesStart;
184          bestValidationSolutionAnalyzer.ValidationSamplesEndParameter.Value = ValidationSamplesEnd;
[3791]185          bestValidationSolutionAnalyzer.BestKnownQualityParameter.ActualName = BestKnownQualityParameter.Name;
[3800]186          bestValidationSolutionAnalyzer.QualityParameter.ActualName = Evaluator.QualityParameter.ActualName;
[3651]187        }
188      }
[3253]189    }
190    #endregion
191  }
192}
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