// @(#)root/roostats:$Id$
// Author: 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_HypoTestInverter
#define ROOSTATS_HypoTestInverter


#include "RooStats/IntervalCalculator.h"


#include "RooStats/HypoTestInverterResult.h"

class RooRealVar;
class TGraphErrors;

#include <memory>


namespace RooStats {

   //class HypoTestCalculator;
   class HybridCalculator;
   class FrequentistCalculator;
   class AsymptoticCalculator;
   class HypoTestCalculatorGeneric;
   class TestStatistic;


class HypoTestInverter : public IntervalCalculator {

public:

   enum ECalculatorType { kUndefined = 0, kHybrid = 1, kFrequentist = 2, kAsymptotic = 3};

   // default constructor (used only for I/O)
   HypoTestInverter();

   // constructor from generic hypotest calculator
   HypoTestInverter( HypoTestCalculatorGeneric & hc,
                     RooRealVar* scannedVariable =0,
                     double size = 0.05) ;


   // constructor from hybrid calculator
   HypoTestInverter( HybridCalculator & hc,
                     RooRealVar* scannedVariable = 0,
                     double size = 0.05) ;

   // constructor from frequentist calculator
   HypoTestInverter( FrequentistCalculator & hc,
                     RooRealVar* scannedVariable,
                     double size = 0.05) ;

   // constructor from asymptotic calculator
   HypoTestInverter( AsymptoticCalculator & hc,
                     RooRealVar* scannedVariable,
                     double size = 0.05) ;

   // constructor from two ModelConfigs (first sb (the null model) then b (the alt model)
   // creating a calculator inside
   HypoTestInverter( RooAbsData& data, ModelConfig &sb, ModelConfig &b,
           RooRealVar * scannedVariable = 0,  ECalculatorType type = kFrequentist,
           double size = 0.05) ;


   virtual HypoTestInverterResult* GetInterval() const;

   void Clear();

   /// Set up to perform a fixed scan.
   /// \param[in] nBins Number of points to scan.
   /// \param[in] xMin Lower limit of range to be scanned.
   /// \param[in] xMax Upper limit of range to be scanned.
   /// \param[in] scanLog Run in logarithmic steps along x.
   void SetFixedScan(int nBins, double xMin = 1, double xMax = -1, bool scanLog = false ) {
      fNBins = nBins;
      fXmin = xMin; fXmax = xMax;
      fScanLog = scanLog;
   }

   /// Use automatic scanning, i.e. adaptive
   void SetAutoScan() { SetFixedScan(0); }

   /// Run a fixed scan.
   /// \param[in] nBins Number of points to scan.
   /// \param[in] xMin Lower limit of range to be scanned.
   /// \param[in] xMax Upper limit of range to be scanned.
   /// \param[in] scanLog Run in logarithmic steps along x.
   bool RunFixedScan( int nBins, double xMin, double xMax, bool scanLog = false ) const;

   bool RunOnePoint( double thisX, bool adaptive = false, double clTarget = -1 ) const;

   //bool RunAutoScan( double xMin, double xMax, double target, double epsilon=0.005, unsigned int numAlgorithm=0 );

   bool RunLimit(double &limit, double &limitErr, double absTol = 0, double relTol = 0, const double *hint=0) const;

   void UseCLs( bool on = true) { fUseCLs = on; if (fResults) fResults->UseCLs(on);   }

   virtual void  SetData(RooAbsData &);

   virtual void SetModel(const ModelConfig &) { } // not needed

   // set the size of the test (rate of Type I error) ( Eg. 0.05 for a 95% Confidence Interval)
   virtual void SetTestSize(Double_t size) {fSize = size; if (fResults) fResults->SetTestSize(size); }
   // set the confidence level for the interval (eg. 0.95 for a 95% Confidence Interval)
   virtual void SetConfidenceLevel(Double_t cl) {fSize = 1.-cl;  if (fResults) fResults->SetConfidenceLevel(cl); }
   // Get the size of the test (eg. rate of Type I error)
   virtual Double_t Size() const {return fSize;}
   // Get the Confidence level for the test
   virtual Double_t ConfidenceLevel()  const {return 1.-fSize;}

   // destructor
   virtual ~HypoTestInverter() ;

   // retrieved a reference to the internally used HypoTestCalculator
   // it might be invalid when the class is deleted
   HypoTestCalculatorGeneric * GetHypoTestCalculator() const { return fCalculator0; }

   // get the upper/lower limit distribution
   SamplingDistribution * GetLowerLimitDistribution(bool rebuild=false, int nToys = 100);
   SamplingDistribution * GetUpperLimitDistribution(bool rebuild=false, int nToys = 100);

   // function to rebuild the distributions
   SamplingDistribution * RebuildDistributions(bool isUpper=true, int nToys = 100,
                                               TList * clsDist = 0, TList *clsbDist= 0, TList * clbDist = 0, const char *  outputfile = "HypoTestInverterRebuiltDist.root");

   // get the test statistic
   TestStatistic * GetTestStatistic() const;

   // set the test statistic
   bool SetTestStatistic(TestStatistic& stat);

   // set verbose level (0,1,2)
   void SetVerbose(int level=1) { fVerbose = level; }

   // set maximum number of toys
   void SetMaximumToys(int ntoys) { fMaxToys = ntoys;}

   // set numerical error in test statistic evaluation (default is zero)
   void SetNumErr(double err) { fNumErr = err; }

   // set flag to close proof for every new run
   static void SetCloseProof(Bool_t flag);


protected:

   // copy c-tor
   HypoTestInverter(const HypoTestInverter & rhs);

   // assignment
   HypoTestInverter & operator=(const HypoTestInverter & rhs);

   void CreateResults() const;

   // run the hybrid at a single point
   HypoTestResult * Eval( HypoTestCalculatorGeneric &hc, bool adaptive , double clsTarget) const;

   // helper functions
   static RooRealVar * GetVariableToScan(const HypoTestCalculatorGeneric &hc);
   static void CheckInputModels(const HypoTestCalculatorGeneric &hc, const RooRealVar & scanVar);

private:


   static unsigned int fgNToys;
   static double fgCLAccuracy;
   static double fgAbsAccuracy;
   static double fgRelAccuracy;
   static bool fgCloseProof;
   static std::string fgAlgo;

   // graph, used to compute the limit, not just for plotting!
   mutable std::unique_ptr<TGraphErrors> fLimitPlot;  //! plot of limits


   // performance counter: remember how many toys have been thrown
   mutable int fTotalToysRun;
   int fMaxToys;  // maximum number of toys to run

   HypoTestCalculatorGeneric* fCalculator0;   // pointer to the calculator passed in the constructor
   std::unique_ptr<HypoTestCalculatorGeneric> fHC;  //! pointer to the generic hypotest calculator used
   RooRealVar* fScannedVariable;     // pointer to the constrained variable
   mutable HypoTestInverterResult* fResults; // pointer to the result

   bool fUseCLs;
   bool fScanLog;
   double fSize;
   int fVerbose;
   ECalculatorType fCalcType;
   int fNBins;
   double fXmin;
   double fXmax;
   double fNumErr;

protected:

   ClassDef(HypoTestInverter,4)  // HypoTestInverter class

};

}

#endif