////////////////////////////////////////////////////////////////////////
/// \class RAT::Classifiers::AlphaBetaClassifier
///
/// \brief  Calculates the likelihood ratio for an event to be BiPo event
///
/// \author name Eric Marzec <marzece@sas.upenn.edu>
///
/// REVISION HISTORY:\n
///   - 01/14/2014 : Eric Marzec - New file
///   - 2015/04/15 : M Mottram: optimised method (assumes equal binning
///                  in time and energy).
///   - 2020/07/29 : Meng Luo - added nhit cut feature
///
/// \details Calculates a log likelihood that an event is either a BiPo event
/// 	  or a two beta event and returns the ratio of those likelihoods.
///
///
////////////////////////////////////////////////////////////////////////

#ifndef __RAT_Classifiers_AlphaBetaClassifier_
#define __RAT_Classifiers_AlphaBetaClassifier_
#include <RAT/OptimisedClassifier.hh>
#include <RAT/SeededClassifier.hh>
#include <RAT/DU/TimeResidualCalculator.hh>

namespace RAT
{
namespace DS
{
  class FitResult;
}

namespace Classifiers
{

  class AlphaBetaClassifier : public OptimisedClassifier, public SeededClassifier
{
public:

  AlphaBetaClassifier() : fNHitCut(0) { }

  virtual std::string
  GetName() const  { return AlphaBetaClassifier::Name(); }

  static std::string
  Name() { return std::string( "AlphaBetaClassifier" ); }

  void Initialise( const std::string& param );

  void BeginOfRun( DS::Run& run );

  void EndOfRun( DS::Run& ) { }

  void DefaultSeed();

  void SetI( const std::string& name, const int value );

  void SetSeed(const DS::FitResult& seed);

  virtual std::vector<double> GetParams() const;

  virtual std::vector<double> GetPositiveErrors() const;

  virtual std::vector<double> GetNegativeErrors() const;

  virtual double operator() (const std::vector<double>& params);

  virtual void SetParams( const std::vector<double>& params);

  virtual void SetPositiveErrors( const std::vector<double>& errors);

  virtual void SetNegativeErrors( const std::vector<double>& errors);

  virtual DS::ClassifierResult
  GetClassification();
private:
  std::vector<double> fTimeResiduals;
  std::vector<double> fTimes,fEnergies,fEnergyProb,fBetaProbability,fAlphaProbability,fTwoBetaProbability;
  std::vector<double> fSummedBetaProbability, fSummedAlphaProbability, fSummedTwoBetaProbability;
  std::vector<double> fParams;
  std::vector<double> fPositiveErrors,fNegativeErrors;
  double fEnergyStep, fTimeStep;
  double fMinValue;
  std::string fIndex; ///< Optional index override
  bool fFitHypothesis;///< This acts as a switch for fitting under a two beta hypothesis or a BiPo one.
  TVector3 fEventPos;
  double fEventTime;
  DU::TimeResidualCalculator fTRCalc;
  std::vector<double>
  MakePDF(std::vector<double>);
  void MattMethod(const std::vector<double>&, double);

protected:
  size_t fNHitCut;
};

} //::Classifier

} //::RAT

#endif