// -*- mode: c++ -*-
#ifndef ALICALORAWANALYZER_H
#define ALICALORAWANALYZER_H
/**************************************************************************
 * This file is property of and copyright by                              *
 * the Relatvistic Heavy Ion Group (RHIG), Yale University, US, 2009      *
 *                                                                        *
 * Primary Author: Per Thomas Hille <p.t.hille@fys.uio.no>                *
 *                                                                        *
 * Contributors are mentioned in the code where appropriate.              *
 * Please report bugs to p.t.hille@fys.uio.no                             *
 *                                                                        *
 * Permission to use, copy, modify and distribute this software and its   *
 * documentation strictly for non-commercial purposes is hereby granted   *
 * without fee, provided that the above copyright notice appears in all   *
 * copies and that both the copyright notice and this permission notice   *
 * appear in the supporting documentation. The authors make no claims     *
 * about the suitability of this software for any purpose. It is          *
 * provided "as is" without express or implied warranty.                  *
 **************************************************************************/


//Base class for extraction 
//of signal amplitude and peak position
//From CALO Calorimeter RAW data

#include "Rtypes.h"
#include "TObject.h"
#define MAXSAMPLES 1008 //CRAP PTH
#include <vector>
#include "AliCaloConstants.h"

//using  namespace CaloConstants::FitAlgorithm;
//using  CaloConstants::ReturnCodes;

class AliCaloBunchInfo;
class AliCaloFitResults;

class  AliCaloRawAnalyzer : public TObject
{
 public:
  AliCaloRawAnalyzer(const char *name="AliCaloRawAnalyzer", const char *nameshort="RawAna");
  virtual ~AliCaloRawAnalyzer();
  virtual AliCaloFitResults Evaluate( const std::vector<AliCaloBunchInfo> &bunchvector, 
				      const UInt_t altrocfg1,  const UInt_t altrocfg2 ) = 0;
  //enum fitAlgorithm {kCrude, kPeakFinder, kLMS, kFastFit, kNeuralNet, kNONE};
  void PrintBunches( const std::vector<AliCaloBunchInfo> &bunchvector ) const;
  void PrintBunch( const AliCaloBunchInfo &bunch ) const ;
  
  virtual int PreFitEvaluateSamples( const std::vector<AliCaloBunchInfo>  &bunchvector, 
				     const UInt_t altrocfg1,  const UInt_t altrocfg2, Int_t & index, 
				     Float_t & maxf, short & maxamp, short & maxampindex, Float_t & ped, int & first, int & last);
  void SetTimeConstraint(const int min, const int max );
  void SetVerbose(bool verbose = true){ fVerbose = verbose; };
  void SetIsZeroSuppressed(const bool iszs = true) { fIsZerosupressed = iszs; } ;
  void SetAmpCut(const Float_t cut) { fAmpCut = cut ; } ;
  void SetFitArrayCut(const Int_t cut) { fFitArrayCut = cut ; } ;
  void SetNsampleCut(const Int_t cut) { fNsampleCut = cut ; } ;
  void SetOverflowCut(const Int_t cut) { fOverflowCut = cut ; } ;
  void SetNsamplePed(const Int_t i) { fNsamplePed = i ; } ;

  bool GetIsZeroSuppressed() const { return fIsZerosupressed;} ;
  Float_t GetAmpCut() const { return fAmpCut; } ;
  Int_t GetFitArrayCut() const { return fFitArrayCut; } ;
  Int_t GetNsampleCut() const { return fNsampleCut; } ;
  Int_t GetOverflowCut() const { return fOverflowCut; } ;
  Int_t GetNsamplePed() const { return fNsamplePed; } ;

  // access to array info
  Double_t GetReversed(const int i) const { return fReversed[i]; }
  const char * GetAlgoName() const { return fName;  };
  const char * GetAlgoAbbr() const { return fNameShort;  };
  Algo::fitAlgorithm GetAlgo() const { return fAlgo; };

  Double_t CalculateChi2(const Double_t amp, const Double_t time,
			 const Int_t first, const Int_t last,
			 const Double_t adcErr=1, 
			 const Double_t tau=2.35);

  void CalculateMeanAndRMS(const Int_t first, const Int_t last,
			   Double_t & mean, Double_t & rms);

 protected:
public: // PAI
  short Max( const AliCaloBunchInfo *const bunch, int *const maxindex) const;
  UShort_t Max(const UShort_t *data, const int length ) const;
  bool CheckBunchEdgesForMax( const AliCaloBunchInfo *const bunch) const;
  bool IsInTimeRange( const int maxindex ) const;
  Float_t  ReverseAndSubtractPed( const AliCaloBunchInfo *bunch, const UInt_t altrocfg1,  const UInt_t altrocfg2, double *outarray ) const;
  int  SelectBunch( const std::vector<AliCaloBunchInfo> &bunchvector, short *const maxampbin, short *const maxamplitude ) const;
  virtual void SelectSubarray( const Double_t *fData, const int length, const short maxindex, int *const  first, int *const last ) const;
  Float_t EvaluatePedestal(const UShort_t * const data, const int length ) const;
  
  Double_t fReversed[MAXSAMPLES]; //Reversed sequence of samples (pedestalsubtracted)

  // private:
  int fMinTimeIndex; //The timebin of the max signal value must be between fMinTimeIndex and fMaxTimeIndex
  int fMaxTimeIndex; //The timebin of the max signal value must be between fMinTimeIndex and fMaxTimeIndex
  int fFitArrayCut;  //Cut on ADC value (after ped. subtraction) for signals used for fit
  Float_t fAmpCut;   //Max ADC - pedestal must be higher than this befor attemting to extract the amplitude 
  int fNsampleCut;   //Minimum number of sample require before attemting to extract signal parameters 
  int fOverflowCut; // value when ADC starts to saturate
  int fNsamplePed;   //Number of samples used for pedestal calculation (first in bunch) 
  bool fIsZerosupressed; //Wether or not the data is zeros supressed, by default its assumed that the baseline is also subtracted if set to true
  bool fVerbose;     //Print debug information to std out if set to true

  char fName[256]; // Name of the algorithm
  char fNameShort[256]; // Abbrevation for the name
 

  //  CaloConstants  fAlgo;
  Algo::fitAlgorithm fAlgo;
  
  ClassDef(AliCaloRawAnalyzer, 2)  

};

#endif