source: branches/sluengo/HeuristicLab.Problems.TradeRules/TradeRulesSingleObjectiveValidationBestSolutionAnalyzer.cs @ 9456

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using HeuristicLab.Core;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Problems.DataAnalysis.Symbolic;
using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
using HeuristicLab.Problems.DataAnalysis;
using HeuristicLab.Common;
using HeuristicLab.Data;
using HeuristicLab.Parameters;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;

namespace HeuristicLab.Problems.TradeRules
{
    [Item("TradeRulesSingleObjectiveValidationBestSolutionAnalyzer", "An operator that analyzes the validation best symbolic regression solution for single objective symbolic regression problems.")]
    [StorableClass]
    public sealed class TradeRulesSingleObjectiveValidationBestSolutionAnalyzer : SymbolicDataAnalysisSingleObjectiveValidationBestSolutionAnalyzer<ISymbolicRegressionSolution, ISymbolicRegressionSingleObjectiveEvaluator, IRegressionProblemData>,
    ISymbolicDataAnalysisBoundedOperator
    {
         private const string EstimationLimitsParameterName = "EstimationLimits";
    private const string ApplyLinearScalingParameterName = "ApplyLinearScaling";

    #region parameter properties
    public IValueLookupParameter<DoubleLimit> EstimationLimitsParameter {
      get { return (IValueLookupParameter<DoubleLimit>)Parameters[EstimationLimitsParameterName]; }
    }
    public IValueParameter<BoolValue> ApplyLinearScalingParameter {
      get { return (IValueParameter<BoolValue>)Parameters[ApplyLinearScalingParameterName]; }
    }
    #endregion

    #region properties
    public BoolValue ApplyLinearScaling {
      get { return ApplyLinearScalingParameter.Value; }
    }
    #endregion

    [StorableConstructor]
    private TradeRulesSingleObjectiveValidationBestSolutionAnalyzer(bool deserializing) : base(deserializing) { }
    private TradeRulesSingleObjectiveValidationBestSolutionAnalyzer(TradeRulesSingleObjectiveValidationBestSolutionAnalyzer original, Cloner cloner) : base(original, cloner) { }
    public TradeRulesSingleObjectiveValidationBestSolutionAnalyzer()
      : base() {
      Parameters.Add(new ValueLookupParameter<DoubleLimit>(EstimationLimitsParameterName, "The lower and upper limit for the estimated values produced by the symbolic regression model."));
      Parameters.Add(new ValueParameter<BoolValue>(ApplyLinearScalingParameterName, "Flag that indicates if the produced symbolic regression solution should be linearly scaled.", new BoolValue(false)));
    }

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

    protected override ISymbolicRegressionSolution CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality) {
      var model = new SymbolicRegressionModel((ISymbolicExpressionTree)bestTree.Clone(), SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper);
      if (ApplyLinearScaling.Value)
        SymbolicRegressionModel.Scale(model, ProblemDataParameter.ActualValue);
      return new TradingRulesSolution(model, (IRegressionProblemData)ProblemDataParameter.ActualValue.Clone());
    }

    }
}