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, ISymbolicDataAnalysisBoundedOperator { private const string EstimationLimitsParameterName = "EstimationLimits"; private const string ApplyLinearScalingParameterName = "ApplyLinearScaling"; #region parameter properties public IValueLookupParameter EstimationLimitsParameter { get { return (IValueLookupParameter)Parameters[EstimationLimitsParameterName]; } } public IValueParameter ApplyLinearScalingParameter { get { return (IValueParameter)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(EstimationLimitsParameterName, "The lower and upper limit for the estimated values produced by the symbolic regression model.")); Parameters.Add(new ValueParameter(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()); } } }