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source: branches/DataAnalysis.PopulationDiversityAnalysis/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/SymbolicRegressionProblemBase.cs @ 7461

Last change on this file since 7461 was 4928, checked in by swinkler, 14 years ago

Worked on structural population diversity analysis (#1278):

  • Improved definition of genetic items.
  • Implemented recursive collection of all genetic items of symbolic expression trees.
  • Added FineGrainedStructuralPopulationDiversityAnalyzer to SymbolicRegressionProblemBase.
File size: 18.9 KB
Line 
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.Collections.Generic;
24using System.Linq;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
29using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Analyzers;
30using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Creators;
31using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Interfaces;
32using HeuristicLab.Optimization;
33using HeuristicLab.Parameters;
34using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
35using HeuristicLab.PluginInfrastructure;
36using HeuristicLab.Problems.DataAnalysis.Regression.Symbolic.Analyzers;
37using HeuristicLab.Problems.DataAnalysis.Symbolic;
38
39namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic {
40  [StorableClass]
41  public abstract class SymbolicRegressionProblemBase : DataAnalysisProblem, IProblem {
42
43    #region Parameter Properties
44    public new ValueParameter<SymbolicExpressionTreeCreator> SolutionCreatorParameter {
45      get { return (ValueParameter<SymbolicExpressionTreeCreator>)Parameters["SolutionCreator"]; }
46    }
47    IParameter IProblem.SolutionCreatorParameter {
48      get { return SolutionCreatorParameter; }
49    }
50    public ValueParameter<DoubleValue> LowerEstimationLimitParameter {
51      get { return (ValueParameter<DoubleValue>)Parameters["LowerEstimationLimit"]; }
52    }
53    public ValueParameter<DoubleValue> UpperEstimationLimitParameter {
54      get { return (ValueParameter<DoubleValue>)Parameters["UpperEstimationLimit"]; }
55    }
56    public ValueParameter<ISymbolicExpressionTreeInterpreter> SymbolicExpressionTreeInterpreterParameter {
57      get { return (ValueParameter<ISymbolicExpressionTreeInterpreter>)Parameters["SymbolicExpressionTreeInterpreter"]; }
58    }
59    public ValueParameter<ISymbolicExpressionGrammar> FunctionTreeGrammarParameter {
60      get { return (ValueParameter<ISymbolicExpressionGrammar>)Parameters["FunctionTreeGrammar"]; }
61    }
62    public ValueParameter<IntValue> MaxExpressionLengthParameter {
63      get { return (ValueParameter<IntValue>)Parameters["MaxExpressionLength"]; }
64    }
65    public ValueParameter<IntValue> MaxExpressionDepthParameter {
66      get { return (ValueParameter<IntValue>)Parameters["MaxExpressionDepth"]; }
67    }
68    public ValueParameter<IntValue> MaxFunctionDefiningBranchesParameter {
69      get { return (ValueParameter<IntValue>)Parameters["MaxFunctionDefiningBranches"]; }
70    }
71    public ValueParameter<IntValue> MaxFunctionArgumentsParameter {
72      get { return (ValueParameter<IntValue>)Parameters["MaxFunctionArguments"]; }
73    }
74    #endregion
75
76    #region Properties
77    public IntValue MaxExpressionLength {
78      get { return MaxExpressionLengthParameter.Value; }
79      set { MaxExpressionLengthParameter.Value = value; }
80    }
81    public IntValue MaxExpressionDepth {
82      get { return MaxExpressionDepthParameter.Value; }
83      set { MaxExpressionDepthParameter.Value = value; }
84    }
85    public IntValue MaxFunctionDefiningBranches {
86      get { return MaxFunctionDefiningBranchesParameter.Value; }
87      set { MaxFunctionDefiningBranchesParameter.Value = value; }
88    }
89    public IntValue MaxFunctionArguments {
90      get { return MaxFunctionArgumentsParameter.Value; }
91      set { MaxFunctionArgumentsParameter.Value = value; }
92    }
93    public new SymbolicExpressionTreeCreator SolutionCreator {
94      get { return SolutionCreatorParameter.Value; }
95      set { SolutionCreatorParameter.Value = value; }
96    }
97    ISolutionCreator IProblem.SolutionCreator {
98      get { return SolutionCreatorParameter.Value; }
99    }
100    public ISymbolicExpressionTreeInterpreter SymbolicExpressionTreeInterpreter {
101      get { return SymbolicExpressionTreeInterpreterParameter.Value; }
102      set { SymbolicExpressionTreeInterpreterParameter.Value = value; }
103    }
104    public DoubleValue LowerEstimationLimit {
105      get { return LowerEstimationLimitParameter.Value; }
106      set { LowerEstimationLimitParameter.Value = value; }
107    }
108    public DoubleValue UpperEstimationLimit {
109      get { return UpperEstimationLimitParameter.Value; }
110      set { UpperEstimationLimitParameter.Value = value; }
111    }
112
113    public ISymbolicExpressionGrammar FunctionTreeGrammar {
114      get { return (ISymbolicExpressionGrammar)FunctionTreeGrammarParameter.Value; }
115      private set { FunctionTreeGrammarParameter.Value = value; }
116    }
117    public override IEnumerable<IOperator> Operators {
118      get { return operators; }
119    }
120    public IEnumerable<ISymbolicRegressionAnalyzer> Analyzers {
121      get { return operators.OfType<ISymbolicRegressionAnalyzer>(); }
122    }
123    public DoubleValue PunishmentFactor {
124      get { return new DoubleValue(10.0); }
125    }
126    public IntValue TrainingSamplesStart {
127      get { return new IntValue(DataAnalysisProblemData.TrainingIndizes.First()); }
128    }
129    public IntValue TrainingSamplesEnd {
130      get {
131        int endIndex = (int)(DataAnalysisProblemData.TrainingIndizes.Count() * (1.0 - DataAnalysisProblemData.ValidationPercentage.Value) - 1);
132        if (endIndex < 0) endIndex = 0;
133        return new IntValue(DataAnalysisProblemData.TrainingIndizes.ElementAt(endIndex));
134      }
135    }
136    public IntValue ValidationSamplesStart {
137      get { return TrainingSamplesEnd; }
138    }
139    public IntValue ValidationSamplesEnd {
140      get { return new IntValue(DataAnalysisProblemData.TrainingIndizes.Last() + 1); }
141    }
142    public IntValue TestSamplesStart {
143      get { return DataAnalysisProblemData.TestSamplesStart; }
144    }
145    public IntValue TestSamplesEnd {
146      get { return DataAnalysisProblemData.TestSamplesEnd; }
147    }
148
149    #endregion
150
151    [Storable]
152    private List<IOperator> operators;
153
154    [StorableConstructor]
155    protected SymbolicRegressionProblemBase(bool deserializing) : base(deserializing) { }
156    protected SymbolicRegressionProblemBase(SymbolicRegressionProblemBase original, Cloner cloner)
157      : base(original, cloner) {
158      operators = original.operators.Select(x => (IOperator)cloner.Clone(x)).ToList();
159      RegisterParameterEvents();
160      RegisterParameterValueEvents();
161    }
162    public SymbolicRegressionProblemBase()
163      : base() {
164      SymbolicExpressionTreeCreator creator = new ProbabilisticTreeCreator();
165      var grammar = new FullFunctionalExpressionGrammar();
166      var globalGrammar = new GlobalSymbolicExpressionGrammar(grammar);
167      var interpreter = new SimpleArithmeticExpressionInterpreter();
168      Parameters.Add(new ValueParameter<SymbolicExpressionTreeCreator>("SolutionCreator", "The operator which should be used to create new symbolic regression solutions.", creator));
169      Parameters.Add(new ValueParameter<ISymbolicExpressionTreeInterpreter>("SymbolicExpressionTreeInterpreter", "The interpreter that should be used to evaluate the symbolic expression tree.", interpreter));
170      Parameters.Add(new ValueParameter<DoubleValue>("LowerEstimationLimit", "The lower limit for the estimated value that can be returned by the symbolic regression model.", new DoubleValue(double.NegativeInfinity)));
171      Parameters.Add(new ValueParameter<DoubleValue>("UpperEstimationLimit", "The upper limit for the estimated value that can be returned by the symbolic regression model.", new DoubleValue(double.PositiveInfinity)));
172      Parameters.Add(new ValueParameter<ISymbolicExpressionGrammar>("FunctionTreeGrammar", "The grammar that should be used for symbolic regression models.", globalGrammar));
173      Parameters.Add(new ValueParameter<IntValue>("MaxExpressionLength", "Maximal length of the symbolic expression.", new IntValue(100)));
174      Parameters.Add(new ValueParameter<IntValue>("MaxExpressionDepth", "Maximal depth of the symbolic expression.", new IntValue(10)));
175      Parameters.Add(new ValueParameter<IntValue>("MaxFunctionDefiningBranches", "Maximal number of automatically defined functions.", (IntValue)new IntValue(0).AsReadOnly()));
176      Parameters.Add(new ValueParameter<IntValue>("MaxFunctionArguments", "Maximal number of arguments of automatically defined functions.", (IntValue)new IntValue(0).AsReadOnly()));
177
178      creator.SymbolicExpressionTreeParameter.ActualName = "SymbolicRegressionModel";
179
180      ParameterizeSolutionCreator();
181
182      UpdateGrammar();
183      UpdateEstimationLimits();
184      InitializeOperators();
185      RegisterParameterEvents();
186      RegisterParameterValueEvents();
187    }
188
189    private void RegisterParameterValueEvents() {
190      MaxFunctionArgumentsParameter.ValueChanged += new EventHandler(ArchitectureParameter_ValueChanged);
191      MaxFunctionDefiningBranchesParameter.ValueChanged += new EventHandler(ArchitectureParameter_ValueChanged);
192      SolutionCreatorParameter.ValueChanged += new EventHandler(SolutionCreatorParameter_ValueChanged);
193      FunctionTreeGrammarParameter.ValueChanged += new EventHandler(FunctionTreeGrammarParameter_ValueChanged);
194    }
195
196    private void RegisterParameterEvents() {
197      MaxFunctionArgumentsParameter.Value.ValueChanged += new EventHandler(ArchitectureParameterValue_ValueChanged);
198      MaxFunctionDefiningBranchesParameter.Value.ValueChanged += new EventHandler(ArchitectureParameterValue_ValueChanged);
199      SolutionCreator.SymbolicExpressionTreeParameter.ActualNameChanged += new EventHandler(SolutionCreator_SymbolicExpressionTreeParameter_ActualNameChanged);
200    }
201
202    #region event handling
203    protected override void OnDataAnalysisProblemChanged(EventArgs e) {
204      base.OnDataAnalysisProblemChanged(e);
205      // paritions could be changed
206      ParameterizeAnalyzers();
207      // input variables could have been changed
208      UpdateGrammar();
209      // estimation limits have to be recalculated
210      UpdateEstimationLimits();
211    }
212    protected virtual void OnArchitectureParameterChanged(EventArgs e) {
213      UpdateGrammar();
214    }
215    protected virtual void OnGrammarChanged() { UpdateGrammar(); }
216    protected virtual void OnOperatorsChanged(EventArgs e) { RaiseOperatorsChanged(e); }
217    protected virtual void OnSolutionCreatorChanged(EventArgs e) {
218      SolutionCreator.SymbolicExpressionTreeParameter.ActualNameChanged += new EventHandler(SolutionCreator_SymbolicExpressionTreeParameter_ActualNameChanged);
219      ParameterizeSolutionCreator();
220      OnSolutionParameterNameChanged(e);
221      RaiseSolutionCreatorChanged(e);
222    }
223
224    protected virtual void OnSolutionParameterNameChanged(EventArgs e) {
225      ParameterizeAnalyzers();
226      ParameterizeOperators();
227    }
228
229    protected virtual void OnEvaluatorChanged(EventArgs e) {
230      RaiseEvaluatorChanged(e);
231    }
232    #endregion
233
234    #region event handlers
235    private void FunctionTreeGrammarParameter_ValueChanged(object sender, EventArgs e) {
236      if (!(FunctionTreeGrammar is GlobalSymbolicExpressionGrammar))
237        FunctionTreeGrammar = new GlobalSymbolicExpressionGrammar(FunctionTreeGrammar);
238      OnGrammarChanged();
239    }
240
241    private void SolutionCreatorParameter_ValueChanged(object sender, EventArgs e) {
242      OnSolutionCreatorChanged(e);
243    }
244    private void SolutionCreator_SymbolicExpressionTreeParameter_ActualNameChanged(object sender, EventArgs e) {
245      OnSolutionParameterNameChanged(e);
246    }
247    private void ArchitectureParameter_ValueChanged(object sender, EventArgs e) {
248      MaxFunctionArgumentsParameter.Value.ValueChanged += new EventHandler(ArchitectureParameterValue_ValueChanged);
249      MaxFunctionDefiningBranchesParameter.Value.ValueChanged += new EventHandler(ArchitectureParameterValue_ValueChanged);
250      OnArchitectureParameterChanged(e);
251    }
252    private void ArchitectureParameterValue_ValueChanged(object sender, EventArgs e) {
253      OnArchitectureParameterChanged(e);
254    }
255    #endregion
256
257    #region Helpers
258    [StorableHook(HookType.AfterDeserialization)]
259    private void AfterDeserializationHook() {
260      // BackwardsCompatibility3.3
261      #region Backwards compatible code (remove with 3.4)
262      if (operators == null) InitializeOperators();
263      #endregion
264      RegisterParameterEvents();
265      RegisterParameterValueEvents();
266    }
267
268    protected void AddOperator(IOperator op) {
269      operators.Add(op);
270    }
271
272    private void UpdateGrammar() {
273      foreach (var varSymbol in FunctionTreeGrammar.Symbols.OfType<HeuristicLab.Problems.DataAnalysis.Symbolic.Symbols.Variable>()) {
274        varSymbol.VariableNames = DataAnalysisProblemData.InputVariables.CheckedItems.Select(x => x.Value.Value);
275      }
276      var globalGrammar = FunctionTreeGrammar as GlobalSymbolicExpressionGrammar;
277      if (globalGrammar != null) {
278        globalGrammar.MaxFunctionArguments = MaxFunctionArguments.Value;
279        globalGrammar.MaxFunctionDefinitions = MaxFunctionDefiningBranches.Value;
280      }
281    }
282
283    private void UpdateEstimationLimits() {
284      if (TrainingSamplesStart.Value < TrainingSamplesEnd.Value &&
285        DataAnalysisProblemData.Dataset.VariableNames.Contains(DataAnalysisProblemData.TargetVariable.Value)) {
286        var targetValues = DataAnalysisProblemData.Dataset.GetVariableValues(DataAnalysisProblemData.TargetVariable.Value, TrainingSamplesStart.Value, TrainingSamplesEnd.Value);
287        var mean = targetValues.Average();
288        var range = targetValues.Max() - targetValues.Min();
289        UpperEstimationLimit = new DoubleValue(mean + PunishmentFactor.Value * range);
290        LowerEstimationLimit = new DoubleValue(mean - PunishmentFactor.Value * range);
291      }
292    }
293
294    private void InitializeOperators() {
295      operators = new List<IOperator>();
296      operators.AddRange(ApplicationManager.Manager.GetInstances<ISymbolicExpressionTreeOperator>().OfType<IOperator>());
297      operators.Add(new SymbolicRegressionVariableFrequencyAnalyzer());
298      operators.Add(new MinAverageMaxSymbolicExpressionTreeSizeAnalyzer());
299      operators.Add(new SymbolicRegressionModelQualityAnalyzer());
300      operators.Add(new VariablesUsagePopulationDiversityAnalyzer());
301      operators.Add(new FineGrainedStructuralPopulationDiversityAnalyzer());
302      ParameterizeOperators();
303      ParameterizeAnalyzers();
304    }
305
306    private void ParameterizeSolutionCreator() {
307      SolutionCreator.SymbolicExpressionGrammarParameter.ActualName = FunctionTreeGrammarParameter.Name;
308      SolutionCreator.MaxTreeHeightParameter.ActualName = MaxExpressionDepthParameter.Name;
309      SolutionCreator.MaxTreeSizeParameter.ActualName = MaxExpressionLengthParameter.Name;
310      SolutionCreator.MaxFunctionArgumentsParameter.ActualName = MaxFunctionArgumentsParameter.Name;
311      SolutionCreator.MaxFunctionDefinitionsParameter.ActualName = MaxFunctionDefiningBranchesParameter.Name;
312    }
313
314    private void ParameterizeAnalyzers() {
315      foreach (var analyzer in Analyzers) {
316        analyzer.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
317        var symbolicRegressionModelQualityAnalyzer = analyzer as SymbolicRegressionModelQualityAnalyzer;
318        if (symbolicRegressionModelQualityAnalyzer != null) {
319          symbolicRegressionModelQualityAnalyzer.ProblemDataParameter.ActualName = DataAnalysisProblemDataParameter.Name;
320          symbolicRegressionModelQualityAnalyzer.UpperEstimationLimitParameter.ActualName = UpperEstimationLimitParameter.Name;
321          symbolicRegressionModelQualityAnalyzer.LowerEstimationLimitParameter.ActualName = LowerEstimationLimitParameter.Name;
322          symbolicRegressionModelQualityAnalyzer.SymbolicExpressionTreeInterpreterParameter.ActualName = SymbolicExpressionTreeInterpreterParameter.Name;
323          symbolicRegressionModelQualityAnalyzer.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
324        }
325        var varFreqAnalyzer = analyzer as SymbolicRegressionVariableFrequencyAnalyzer;
326        if (varFreqAnalyzer != null) {
327          varFreqAnalyzer.ProblemDataParameter.ActualName = DataAnalysisProblemDataParameter.Name;
328        }
329        var populationDiversityAnalyzer = analyzer as SymbolicRegressionPopulationDiversityAnalyzer;
330        if (populationDiversityAnalyzer != null) {
331          populationDiversityAnalyzer.ProblemDataParameter.ActualName = DataAnalysisProblemDataParameter.Name;
332          // ??? populationDiversityAnalyzer.MaximizationParameter.ActualName =
333          populationDiversityAnalyzer.SolutionParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
334          // ??? populationDiversityAnalyzer.QualityParameter.ActualName
335          populationDiversityAnalyzer.ResultsParameter.ActualName = "Results";
336        }
337      }
338      foreach (ISymbolicExpressionTreeAnalyzer analyzer in Operators.OfType<ISymbolicExpressionTreeAnalyzer>()) {
339        analyzer.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
340      }
341    }
342
343    private void ParameterizeOperators() {
344      foreach (ISymbolicExpressionTreeOperator op in Operators.OfType<ISymbolicExpressionTreeOperator>()) {
345        op.MaxTreeHeightParameter.ActualName = MaxExpressionDepthParameter.Name;
346        op.MaxTreeSizeParameter.ActualName = MaxExpressionLengthParameter.Name;
347        op.SymbolicExpressionGrammarParameter.ActualName = FunctionTreeGrammarParameter.Name;
348      }
349      foreach (ISymbolicExpressionTreeCrossover op in Operators.OfType<ISymbolicExpressionTreeCrossover>()) {
350        op.ParentsParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
351        op.ChildParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
352      }
353      foreach (ISymbolicExpressionTreeManipulator op in Operators.OfType<ISymbolicExpressionTreeManipulator>()) {
354        op.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
355      }
356      foreach (ISymbolicExpressionTreeArchitectureManipulator op in Operators.OfType<ISymbolicExpressionTreeArchitectureManipulator>()) {
357        op.MaxFunctionArgumentsParameter.ActualName = MaxFunctionArgumentsParameter.Name;
358        op.MaxFunctionDefinitionsParameter.ActualName = MaxFunctionDefiningBranchesParameter.Name;
359      }
360    }
361    #endregion
362  }
363}
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