// @(#)root/roostats:$Id$

/*************************************************************************
 * Project: RooStats                                                     *
 * Package: RooFit/RooStats                                              *
 * Authors:                                                              *
 *   Kyle Cranmer, Lorenzo Moneta, Gregory Schott, Wouter Verkerke       *
 *************************************************************************
 * Copyright (C) 1995-2008, Rene Brun and Fons Rademakers.               *
 * All rights reserved.                                                  *
 *                                                                       *
 * For the licensing terms see $ROOTSYS/LICENSE.                         *
 * For the list of contributors see $ROOTSYS/README/CREDITS.             *
 *************************************************************************/

#ifndef ROOSTATS_HybridResult
#define ROOSTATS_HybridResult

#ifndef ROOSTATS_HypoTestResult
#include "RooStats/HypoTestResult.h"
#endif

namespace RooStats {

   class HybridPlot;

   /*

     Class encapsulating the result of the HybridCalculatorOriginal.
     This class is a fresh rewrite in RooStats of
     RooStatsCms/LimitResults developed by D. Piparo and G. Schott
     New contributions to this class have been written by Matthias Wolf (error estimation)

     The objects of this class store and access with lightweight methods the
     information calculated by LimitResults through a Lent calculation using
     MC toy experiments.
     In some ways can be considered an extended and extensible implementation of the
     TConfidenceLevel class (http://root.cern.ch/root/html/TConfidenceLevel.html).

*/

   class HybridResult : public HypoTestResult {

   public:

      /// Default constructor
      explicit HybridResult(const char *name = 0);

      /// Constructor for HybridResult
      HybridResult(const char *name,
         const std::vector<double>& testStat_sb_vals,
                   const std::vector<double>& testStat_b_vals,
         bool sumLargerValues=true);


      /// Destructor of HybridResult
      virtual ~HybridResult();

      void SetDataTestStatistics(double testStat_data_val);

      void Add(HybridResult* other);

      HybridPlot* GetPlot(const char* name,const char* title, int n_bins);

      void PrintMore(const char* options);

      /// Get test statistics values for the sb model
      std::vector<double> GetTestStat_sb(){return fTestStat_sb;}

      /// Get test statistics values for the b model
      std::vector<double> GetTestStat_b(){return fTestStat_b;}

      /// Get test statistics value for data
      double GetTestStat_data(){ return fTestStat_data;}

      // Return p-value for null hypothesis
      Double_t NullPValue() const;

      // Return p-value for alternate hypothesis
      Double_t AlternatePValue() const;

      /// The error on the "confidence level" of the null hypothesis
      Double_t CLbError() const;

      /// The error on the "confidence level" of the alternative hypothesis
      Double_t CLsplusbError() const;

      /// The error on the ratio \f$CL_{s+b}/CL_{b}\f$
      Double_t CLsError() const;

   private:

      std::vector<double> fTestStat_b; // vector of results for B-only toy-MC
      std::vector<double> fTestStat_sb; // vector of results for S+B toy-MC
      double fTestStat_data; // results (test statistics) evaluated for data

      mutable bool fComputationsNulDoneFlag; // flag if the fNullPValue computation have been already done or not (ie need to be refreshed)
      mutable bool fComputationsAltDoneFlag; // flag if the fAlternatePValue computation have been already done or not (ie need to be refreshed)
      bool fSumLargerValues; // p-value for velues of testStat >= testStat_data (or testStat <= testStat_data)

   protected:

      ClassDef(HybridResult,1)  // Class containing the results of the HybridCalculator
   };
}

#endif