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source: branches/GrammaticalEvolution/HeuristicLab.Problems.GrammaticalEvolution/Symbolic/GESymbolicRegressionSingleObjectiveEvaluator.cs @ 10263

Last change on this file since 10263 was 10263, checked in by gkronber, 10 years ago

#2109 implemented a wrapper for evaluators that transforms genotypes to phenotypes for symbolic regression (deleted obsolete evaluators)

File size: 3.4 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2013 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.Collections.Generic;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Encodings.IntegerVectorEncoding;
26using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
27using HeuristicLab.Parameters;
28using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
29using HeuristicLab.Problems.DataAnalysis;
30using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
31
32namespace HeuristicLab.Problems.GrammaticalEvolution {
33  [StorableClass]
34  public class GESymbolicRegressionSingleObjectiveEvaluator : GESymbolicDataAnalysisSingleObjectiveEvaluator<IRegressionProblemData>,
35                                                                       IGESymbolicRegressionSingleObjectiveEvaluator {
36
37    public const string EvaluatorParameterName = "Evaluator";
38    public IValueParameter<ISymbolicRegressionSingleObjectiveEvaluator> EvaluatorParameter {
39      get { return (IValueParameter<ISymbolicRegressionSingleObjectiveEvaluator>)Parameters[EvaluatorParameterName]; }
40    }
41
42    private ISymbolicRegressionSingleObjectiveEvaluator Evaluator {
43      get { return EvaluatorParameter.Value; }
44    }
45
46    [StorableConstructor]
47    protected GESymbolicRegressionSingleObjectiveEvaluator(bool deserializing) : base(deserializing) { }
48    protected GESymbolicRegressionSingleObjectiveEvaluator(GESymbolicRegressionSingleObjectiveEvaluator original, Cloner cloner) : base(original, cloner) { }
49    public GESymbolicRegressionSingleObjectiveEvaluator()
50      : base() {
51      Parameters.Add(new ValueParameter<ISymbolicRegressionSingleObjectiveEvaluator>(EvaluatorParameterName, "The symbolic regression evaluator that should be used to assess the quality of trees.", new SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator()));
52    }
53
54    public override IDeepCloneable Clone(Cloner cloner) {
55      return new GESymbolicRegressionSingleObjectiveEvaluator(this, cloner);
56    }
57
58    public override bool Maximization {
59      get { return Evaluator.Maximization; }
60    }
61
62    public override IOperation Apply() {
63      var genotype = IntegerVectorParameter.ActualValue;
64
65      // translate to phenotype
66      var tree = GenotypeToPhenotypeMapperParameter.ActualValue.Map(
67        SymbolicExpressionTreeGrammarParameter.ActualValue,
68        genotype
69      );
70      SymbolicExpressionTreeParameter.ActualValue = tree; // write to scope for analyzers
71
72      // create operation for evaluation
73      var evalOp = ExecutionContext.CreateChildOperation(Evaluator);
74      var successorOp = base.Apply();
75
76      return new OperationCollection(evalOp, successorOp);
77    }
78  }
79}
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