source: branches/sluengo/HeuristicLab.Problems.TradeRules/Solution/TradeRulesSolutionBase.cs @ 9386

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using HeuristicLab.Problems.DataAnalysis;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Data;
using HeuristicLab.Common;
using HeuristicLab.Optimization;
using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;

namespace HeuristicLab.Problems.TradeRules
{
      [StorableClass]
    public abstract class TradeRulesSolutionBase : DataAnalysisSolution, IRegressionSolution
    {
        private const string TrainingCashResultName = "Cash after the operation (training)";
        private const string TestCashResultName = "Cash after the operation (test)";
        private const string TrainingMeanSquaredErrorResultName = "Mean squared error (training)";
        private const string TestMeanSquaredErrorResultName = "Mean squared error (test)";
        private const string TrainingMeanAbsoluteErrorResultName = "Mean absolute error (training)";
        private const string TestMeanAbsoluteErrorResultName = "Mean absolute error (test)";
        private const string TrainingSquaredCorrelationResultName = "Pearson's R² (training)";
        private const string TestSquaredCorrelationResultName = "Pearson's R² (test)";
        private const string TrainingRelativeErrorResultName = "Average relative error (training)";
        private const string TestRelativeErrorResultName = "Average relative error (test)";
        private const string TrainingNormalizedMeanSquaredErrorResultName = "Normalized mean squared error (training)";
        private const string TestNormalizedMeanSquaredErrorResultName = "Normalized mean squared error (test)";
        private const string TrainingMeanErrorResultName = "Mean error (training)";
        private const string TestMeanErrorResultName = "Mean error (test)";
        private const string TestTradeDaysResultName = "Trade days";
        private const string TestNumberTradesResultName = "Number of trades";
        private const string TestTotalTradesResultName = "Total trades";


        public new IRegressionModel Model
        {
            get { return (IRegressionModel)base.Model; }
            protected set { base.Model = value; }
        }

        public new IRegressionProblemData ProblemData
        {
            get { return (IRegressionProblemData)base.ProblemData; }
            set { base.ProblemData = value; }
        }

        public abstract IEnumerable<double> EstimatedValues { get; }
        public abstract IEnumerable<double> EstimatedTrainingValues { get; }
        public abstract IEnumerable<double> EstimatedTestValues { get; }
        public abstract IEnumerable<double> GetEstimatedValues(IEnumerable<int> rows);


        #region Results
        public double TrainingCash
        {
            get { return ((DoubleValue)this[TrainingCashResultName].Value).Value; }
            private set { ((DoubleValue)this[TrainingCashResultName].Value).Value = value; }
        }
        public double TestCash
        {
            get { return ((DoubleValue)this[TestCashResultName].Value).Value; }
            private set { ((DoubleValue)this[TestCashResultName].Value).Value = value; }
        }
        public double TradeDays
        {
            get { return ((DoubleValue)this[TestTradeDaysResultName].Value).Value; }
            private set { ((DoubleValue)this[TestTradeDaysResultName].Value).Value = value; }
        }
        public double NumberTrades
        {
            get { return ((DoubleValue)this[TestNumberTradesResultName].Value).Value; }
            private set { ((DoubleValue)this[TestNumberTradesResultName].Value).Value = value; }
        }
        public double TotalTrades
        {
            get { return ((DoubleValue)this[TestTotalTradesResultName].Value).Value; }
            private set { ((DoubleValue)this[TestTotalTradesResultName].Value).Value = value; }
        }
        public double TrainingMeanSquaredError
        {
            get { return ((DoubleValue)this[TrainingMeanSquaredErrorResultName].Value).Value; }
            private set { ((DoubleValue)this[TrainingMeanSquaredErrorResultName].Value).Value = value; }
        }
        public double TestMeanSquaredError
        {
            get { return ((DoubleValue)this[TestMeanSquaredErrorResultName].Value).Value; }
            private set { ((DoubleValue)this[TestMeanSquaredErrorResultName].Value).Value = value; }
        }
        public double TrainingMeanAbsoluteError
        {
            get { return ((DoubleValue)this[TrainingMeanAbsoluteErrorResultName].Value).Value; }
            private set { ((DoubleValue)this[TrainingMeanAbsoluteErrorResultName].Value).Value = value; }
        }
        public double TestMeanAbsoluteError
        {
            get { return ((DoubleValue)this[TestMeanAbsoluteErrorResultName].Value).Value; }
            private set { ((DoubleValue)this[TestMeanAbsoluteErrorResultName].Value).Value = value; }
        }
        public double TrainingRSquared
        {
            get { return ((DoubleValue)this[TrainingSquaredCorrelationResultName].Value).Value; }
            private set { ((DoubleValue)this[TrainingSquaredCorrelationResultName].Value).Value = value; }
        }
        public double TestRSquared
        {
            get { return ((DoubleValue)this[TestSquaredCorrelationResultName].Value).Value; }
            private set { ((DoubleValue)this[TestSquaredCorrelationResultName].Value).Value = value; }
        }
        public double TrainingRelativeError
        {
            get { return ((DoubleValue)this[TrainingRelativeErrorResultName].Value).Value; }
            private set { ((DoubleValue)this[TrainingRelativeErrorResultName].Value).Value = value; }
        }
        public double TestRelativeError
        {
            get { return ((DoubleValue)this[TestRelativeErrorResultName].Value).Value; }
            private set { ((DoubleValue)this[TestRelativeErrorResultName].Value).Value = value; }
        }
        public double TrainingNormalizedMeanSquaredError
        {
            get { return ((DoubleValue)this[TrainingNormalizedMeanSquaredErrorResultName].Value).Value; }
            private set { ((DoubleValue)this[TrainingNormalizedMeanSquaredErrorResultName].Value).Value = value; }
        }
        public double TestNormalizedMeanSquaredError
        {
            get { return ((DoubleValue)this[TestNormalizedMeanSquaredErrorResultName].Value).Value; }
            private set { ((DoubleValue)this[TestNormalizedMeanSquaredErrorResultName].Value).Value = value; }
        }
        public double TrainingMeanError
        {
            get { return ((DoubleValue)this[TrainingMeanErrorResultName].Value).Value; }
            private set { ((DoubleValue)this[TrainingMeanErrorResultName].Value).Value = value; }
        }
        public double TestMeanError
        {
            get { return ((DoubleValue)this[TestMeanErrorResultName].Value).Value; }
            private set { ((DoubleValue)this[TestMeanErrorResultName].Value).Value = value; }
        }
        #endregion


          [StorableConstructor]
    protected TradeRulesSolutionBase(bool deserializing) : base(deserializing) { }
    protected TradeRulesSolutionBase(TradeRulesSolutionBase original, Cloner cloner)
      : base(original, cloner) {
    }
    protected TradeRulesSolutionBase(IRegressionModel model, IRegressionProblemData problemData)
      : base(model, problemData) {
      Add(new Result(TrainingCashResultName, "Cash obtained after training period in the stock market", new DoubleValue()));
      Add(new Result(TestCashResultName, "Cash obtained after test period in the stock market", new DoubleValue()));
      Add(new Result(TestTradeDaysResultName, "Number of trading days", new DoubleValue()));
      Add(new Result(TestNumberTradesResultName, "Number of trades", new DoubleValue()));
      Add(new Result(TestTotalTradesResultName, "Total trades", new DoubleValue()));
     }

    [StorableHook(HookType.AfterDeserialization)]
    private void AfterDeserialization()
    {
        // BackwardsCompatibility3.4

        #region Backwards compatible code, remove with 3.5

        if (!ContainsKey(TrainingMeanAbsoluteErrorResultName))
        {
            OnlineCalculatorError errorState;
            Add(new Result(TrainingMeanAbsoluteErrorResultName, "Mean of absolute errors of the model on the training partition", new DoubleValue()));
            double trainingMAE = OnlineMeanAbsoluteErrorCalculator.Calculate(EstimatedTrainingValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices), out errorState);
            TrainingMeanAbsoluteError = errorState == OnlineCalculatorError.None ? trainingMAE : double.NaN;
        }

        if (!ContainsKey(TestMeanAbsoluteErrorResultName))
        {
            OnlineCalculatorError errorState;
            Add(new Result(TestMeanAbsoluteErrorResultName, "Mean of absolute errors of the model on the test partition", new DoubleValue()));
            double testMAE = OnlineMeanAbsoluteErrorCalculator.Calculate(EstimatedTestValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndices), out errorState);
            TestMeanAbsoluteError = errorState == OnlineCalculatorError.None ? testMAE : double.NaN;
        }

        if (!ContainsKey(TrainingMeanErrorResultName))
        {
            OnlineCalculatorError errorState;
            Add(new Result(TrainingMeanErrorResultName, "Mean of errors of the model on the training partition", new DoubleValue()));
            double trainingME = OnlineMeanErrorCalculator.Calculate(EstimatedTrainingValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices), out errorState);
            TrainingMeanError = errorState == OnlineCalculatorError.None ? trainingME : double.NaN;
        }
        if (!ContainsKey(TestMeanErrorResultName))
        {
            OnlineCalculatorError errorState;
            Add(new Result(TestMeanErrorResultName, "Mean of errors of the model on the test partition", new DoubleValue()));
            double testME = OnlineMeanErrorCalculator.Calculate(EstimatedTestValues, ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndices), out errorState);
            TestMeanError = errorState == OnlineCalculatorError.None ? testME : double.NaN;
        }
        #endregion
    }


    protected void CalculateResults()
    {
        IEnumerable<double> estimatedValues = EstimatedValues;
        IEnumerable<double> estimatedTrainingValues = EstimatedTrainingValues; // cache values
        IEnumerable<double> originalTrainingValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices);
        IEnumerable<double> estimatedTestValues = EstimatedTestValues; // cache values
        IEnumerable<double> originalTestValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TestIndices);

        double trainingCTR = OnlineTradeRulesCalculator.Calculate(estimatedTrainingValues, ProblemData, ProblemData.TrainingIndices);
        TrainingCash = trainingCTR;
        double testCTR = OnlineTradeRulesCalculator.Calculate(estimatedTestValues, ProblemData, ProblemData.TestIndices);
        TestCash = testCTR;
        double testTradeDays = OnlineTradeRulesCalculator.getTradeDays();
        TradeDays = testTradeDays;
        double testNumberTrades = OnlineTradeRulesCalculator.getNumberTrades();
        NumberTrades = testNumberTrades;
        double testTotalTradeDays = OnlineTradeRulesCalculator.getTotalTradesDays();
        TotalTrades = testTotalTradeDays;

    }


   }
}