using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;

using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
using HeuristicLab.Problems.DataAnalysis.Symbolic;
using HeuristicLab.Problems.DataAnalysis;
using HeuristicLab.Problems.TradeRules.Evaluator;

namespace HeuristicLab.Problems.TradeRules
{
    [Item("Trade Rules Evaluator", "Calculates the profit")]
    [StorableClass]
    public class EvaluatorTradeRules : TradeRulesSingleObjectiveEvaluator
    {
        private static int initialTraining;
        private static int initialTest;
        public override bool Maximization { get { return true; } }

        [StorableConstructor]
        protected EvaluatorTradeRules(bool deserializing) : base(deserializing) { }
        protected EvaluatorTradeRules(EvaluatorTradeRules original, Cloner cloner)
            : base(original, cloner)
        {
        }
        public override IDeepCloneable Clone(Cloner cloner)
        {
            return new EvaluatorTradeRules(this, cloner);
        }

        public EvaluatorTradeRules() : base() { }

        public override IOperation Apply()
        {
            var solution = SymbolicExpressionTreeParameter.ActualValue;
            IEnumerable<int> rows = GenerateRowsToEvaluate();
            initialTraining = initialTrainingValue();
            initialTest = initialTestValue();
            double quality = Calculate((ITradeRulesExpresionTree) SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, solution, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, ProblemDataParameter.ActualValue, rows);
            QualityParameter.ActualValue = new DoubleValue(quality);
            return base.Apply();
        }

        public static double Calculate(ITradeRulesExpresionTree interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, IRegressionProblemData problemData, IEnumerable<int> rows)
        {
            interpreter.setInitialTraining(initialTraining);
            interpreter.setInitialTest(rows.ToArray()[0]);
            IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
            interpreter.clearVariables();
            double tradingCash = OnlineTradeRulesCalculator.Calculate(estimatedValues, problemData, rows);
            

            return tradingCash;
        }

        public override double Evaluate(IExecutionContext context, ISymbolicExpressionTree tree, IRegressionProblemData problemData, IEnumerable<int> rows)
        {
            SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = context;
            EstimationLimitsParameter.ExecutionContext = context;

            double r2 = Calculate((ITradeRulesExpresionTree) SymbolicDataAnalysisTreeInterpreterParameter.ActualValue, tree, EstimationLimitsParameter.ActualValue.Lower, EstimationLimitsParameter.ActualValue.Upper, problemData, rows);
            SymbolicDataAnalysisTreeInterpreterParameter.ExecutionContext = null;
            EstimationLimitsParameter.ExecutionContext = null;
         
            return r2;
        }
    }
}