[10072] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[12009] | 3 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[10072] | 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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[10968] | 19 | *
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| 20 | * Author: Sabine Winkler
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[10072] | 21 | */
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[10968] | 22 |
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[10072] | 23 | #endregion
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| 24 |
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| 25 | using HeuristicLab.Common;
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[10263] | 26 | using HeuristicLab.Core;
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[10290] | 27 | using HeuristicLab.Data;
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[10263] | 28 | using HeuristicLab.Parameters;
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[10072] | 29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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[10073] | 30 | using HeuristicLab.Problems.DataAnalysis;
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| 31 | using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
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| 32 |
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| 33 | namespace HeuristicLab.Problems.GrammaticalEvolution {
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[10072] | 34 | [StorableClass]
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[10263] | 35 | public class GESymbolicRegressionSingleObjectiveEvaluator : GESymbolicDataAnalysisSingleObjectiveEvaluator<IRegressionProblemData>,
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[10276] | 36 | IGESymbolicRegressionSingleObjectiveEvaluator {
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[10263] | 37 |
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| 38 | public const string EvaluatorParameterName = "Evaluator";
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[10280] | 39 | public const string RandomParameterName = "Random";
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[10290] | 40 | public const string BoundsParameterName = "Bounds";
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| 41 | public const string MaximumSymbolicExpressionTreeLengthParameterName = "MaximumSymbolicExpressionTreeLength";
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[10280] | 42 |
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[10263] | 43 | public IValueParameter<ISymbolicRegressionSingleObjectiveEvaluator> EvaluatorParameter {
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| 44 | get { return (IValueParameter<ISymbolicRegressionSingleObjectiveEvaluator>)Parameters[EvaluatorParameterName]; }
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| 45 | }
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[10290] | 46 | public ILookupParameter<IntMatrix> BoundsParameter {
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| 47 | get { return (ILookupParameter<IntMatrix>)Parameters[BoundsParameterName]; }
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| 48 | }
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| 49 | public ILookupParameter<IntValue> MaximumSymbolicExpressionTreeLengthParameter {
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| 50 | get { return (ILookupParameter<IntValue>)Parameters[MaximumSymbolicExpressionTreeLengthParameterName]; }
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| 51 | }
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[10263] | 52 |
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[10974] | 53 | public ISymbolicRegressionSingleObjectiveEvaluator Evaluator {
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[10263] | 54 | get { return EvaluatorParameter.Value; }
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| 55 | }
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| 56 |
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[10280] | 57 |
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[10072] | 58 | [StorableConstructor]
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[10073] | 59 | protected GESymbolicRegressionSingleObjectiveEvaluator(bool deserializing) : base(deserializing) { }
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| 60 | protected GESymbolicRegressionSingleObjectiveEvaluator(GESymbolicRegressionSingleObjectiveEvaluator original, Cloner cloner) : base(original, cloner) { }
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[10263] | 61 | public GESymbolicRegressionSingleObjectiveEvaluator()
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| 62 | : base() {
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| 63 | Parameters.Add(new ValueParameter<ISymbolicRegressionSingleObjectiveEvaluator>(EvaluatorParameterName, "The symbolic regression evaluator that should be used to assess the quality of trees.", new SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator()));
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[10290] | 64 | Parameters.Add(new LookupParameter<IntMatrix>(BoundsParameterName, "The integer number range in which the single genomes of a genotype are created."));
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| 65 | Parameters.Add(new LookupParameter<IntValue>(MaximumSymbolicExpressionTreeLengthParameterName, "Genotype length."));
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[10263] | 66 | }
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| 67 |
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| 68 | public override IDeepCloneable Clone(Cloner cloner) {
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| 69 | return new GESymbolicRegressionSingleObjectiveEvaluator(this, cloner);
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| 70 | }
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| 71 |
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| 72 | public override bool Maximization {
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| 73 | get { return Evaluator.Maximization; }
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| 74 | }
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| 75 |
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| 76 | public override IOperation Apply() {
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| 77 | var genotype = IntegerVectorParameter.ActualValue;
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| 78 |
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| 79 | // translate to phenotype
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| 80 | var tree = GenotypeToPhenotypeMapperParameter.ActualValue.Map(
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[10280] | 81 | RandomParameter.ActualValue,
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[10290] | 82 | BoundsParameter.ActualValue,
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| 83 | MaximumSymbolicExpressionTreeLengthParameter.ActualValue.Value,
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[10263] | 84 | SymbolicExpressionTreeGrammarParameter.ActualValue,
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| 85 | genotype
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| 86 | );
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| 87 | SymbolicExpressionTreeParameter.ActualValue = tree; // write to scope for analyzers
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| 88 |
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| 89 | // create operation for evaluation
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| 90 | var evalOp = ExecutionContext.CreateChildOperation(Evaluator);
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| 91 | var successorOp = base.Apply();
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| 92 |
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| 93 | return new OperationCollection(evalOp, successorOp);
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| 94 | }
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[10072] | 95 | }
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| 96 | }
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