source: branches/GrammaticalEvolution/HeuristicLab.Problems.GrammaticalEvolution/Symbolic/GESymbolicRegressionSingleObjectiveEvaluator.cs @ 10280

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2013 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
 *
 * This file is part of HeuristicLab.
 *
 * HeuristicLab is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * HeuristicLab is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
 */
#endregion

using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Problems.DataAnalysis;
using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;

namespace HeuristicLab.Problems.GrammaticalEvolution {
  [StorableClass]
  public class GESymbolicRegressionSingleObjectiveEvaluator : GESymbolicDataAnalysisSingleObjectiveEvaluator<IRegressionProblemData>,
                                                              IGESymbolicRegressionSingleObjectiveEvaluator {

    public const string EvaluatorParameterName = "Evaluator";
    public const string RandomParameterName = "Random";

    public IValueParameter<ISymbolicRegressionSingleObjectiveEvaluator> EvaluatorParameter {
      get { return (IValueParameter<ISymbolicRegressionSingleObjectiveEvaluator>)Parameters[EvaluatorParameterName]; }
    }
    public ILookupParameter<IRandom> RandomParameter {
      get { return (ILookupParameter<IRandom>)Parameters[RandomParameterName]; }
    }

    private ISymbolicRegressionSingleObjectiveEvaluator Evaluator {
      get { return EvaluatorParameter.Value; }
    }


    [StorableConstructor]
    protected GESymbolicRegressionSingleObjectiveEvaluator(bool deserializing) : base(deserializing) { }
    protected GESymbolicRegressionSingleObjectiveEvaluator(GESymbolicRegressionSingleObjectiveEvaluator original, Cloner cloner) : base(original, cloner) { }
    public GESymbolicRegressionSingleObjectiveEvaluator()
      : base() {
      Parameters.Add(new ValueParameter<ISymbolicRegressionSingleObjectiveEvaluator>(EvaluatorParameterName, "The symbolic regression evaluator that should be used to assess the quality of trees.", new SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator()));
    }

    public override IDeepCloneable Clone(Cloner cloner) {
      return new GESymbolicRegressionSingleObjectiveEvaluator(this, cloner);
    }

    public override bool Maximization {
      get { return Evaluator.Maximization; }
    }

    public override IOperation Apply() {
      var genotype = IntegerVectorParameter.ActualValue;

      // translate to phenotype
      var tree = GenotypeToPhenotypeMapperParameter.ActualValue.Map(
        RandomParameter.ActualValue,
        SymbolicExpressionTreeGrammarParameter.ActualValue,
        genotype
      );
      SymbolicExpressionTreeParameter.ActualValue = tree; // write to scope for analyzers

      // create operation for evaluation
      var evalOp = ExecutionContext.CreateChildOperation(Evaluator);
      var successorOp = base.Apply();

      return new OperationCollection(evalOp, successorOp);
    }
  }
}