[u/mrichter/AliRoot.git] / EMCAL / AliCaloRawAnalyzerKStandard.cxx

/**************************************************************************
 * This file is property of and copyright by                              *
 * the Relativistic 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.                  *
 **************************************************************************/


// Extraction of amplitude and peak position
// FRom CALO raw data using
// least square fit for the
// Moment assuming identical and 
// independent errors (equivalent with chi square)
// 

#include "AliCaloRawAnalyzerKStandard.h"
#include "AliCaloBunchInfo.h"
#include "AliCaloFitResults.h"
#include "AliLog.h"
#include "TMath.h"
#include <stdexcept>
#include <iostream>
#include "TF1.h"
#include "TGraph.h"
#include "TRandom.h"


using namespace std;


#define BAD 4  //CRAP PTH
 
ClassImp( AliCaloRawAnalyzerKStandard )


AliCaloRawAnalyzerKStandard::AliCaloRawAnalyzerKStandard() : AliCaloRawAnalyzerFitter("Chi Square ( kStandard )", "KStandard")
//						 fkEulerSquared(7.389056098930650227),
//						 fTf1(0)
//		 fTau(2.35),
//						 fFixTau(kTRUE)
{
  
  fAlgo = Algo::kStandard;
  //comment
 
  /*
  for(int i=0; i < ALTROMAXSAMPLES; i++)
    {
      fXaxis[i] = i;
    }
  */  

  //  fTf1 = new TF1( "myformula", "[0]*((x - [1])/[2])^2*exp(-2*(x -[1])/[2])",  0, 30 ); 

  //  InitFormula(fTf1);

  /*
  if (fFixTau) 
    {
      fTf1->FixParameter(2, fTau);
    }
  else 
    {
      fTf1->ReleaseParameter(2); // allow par. to vary
      fTf1->SetParameter(2, fTau);
    }
  */
}


AliCaloRawAnalyzerKStandard::~AliCaloRawAnalyzerKStandard()
{
  delete fTf1;
}


/*
void 
AliCaloRawAnalyzerKStandard::InitFormula( TF1* f)
{
  f = new TF1( "myformula", "[0]*((x - [1])/[2])^2*exp(-2*(x -[1])/[2])",  0, 30 ); 
}
*/

AliCaloFitResults
AliCaloRawAnalyzerKStandard::Evaluate( const vector<AliCaloBunchInfo>  &bunchlist, const UInt_t altrocfg1,  const UInt_t altrocfg2 )
{
  
  Float_t pedEstimate  = 0;
  short maxADC = 0;
  Int_t first = 0;
  Int_t last = 0;
  Int_t bunchIndex = 0;
  Float_t ampEstimate = 0;
  short timeEstimate  = 0;
  Float_t time = 0;
  Float_t amp=0;
  Float_t chi2 = 0;
  Int_t ndf = 0;
  Bool_t fitDone = kFALSE;

  
  int nsamples = PreFitEvaluateSamples( bunchlist, altrocfg1, altrocfg2, bunchIndex, ampEstimate, 
					maxADC, timeEstimate, pedEstimate, first, last,   fAmpCut ); 
  
  
  if (ampEstimate >= fAmpCut  ) 
    { 
      time = timeEstimate; 
      Int_t timebinOffset = bunchlist.at(bunchIndex).GetStartBin() - (bunchlist.at(bunchIndex).GetLength()-1); 
      amp = ampEstimate; 
      
      if ( nsamples > 1 && maxADC< OVERFLOWCUT ) 
	{ 
	  FitRaw(first, last, amp, time, chi2, fitDone);
	  time += timebinOffset;
	  timeEstimate += timebinOffset;
	  ndf = nsamples - 2;
	}
    } 
  if ( fitDone ) 
    { 
      Float_t ampAsymm = (amp - ampEstimate)/(amp + ampEstimate);
      Float_t timeDiff = time - timeEstimate;
      
      if ( (TMath::Abs(ampAsymm) > 0.1) || (TMath::Abs(timeDiff) > 2) ) 
	{
	  amp     = ampEstimate;
	  time    = timeEstimate; 
	  fitDone = kFALSE;
	} 
    }  
  if (amp >= fAmpCut ) 
    { 
      if ( ! fitDone) 
	{ 
	  amp += (0.5 - gRandom->Rndm()); 
	}
      //Int_t id = fGeom->GetAbsCellIdFromCellIndexes(in.GetModule(), in.GetRow(), in.GetColumn()) ;
      // lowGain  = in.IsLowGain();
     
      time = time * TIMEBINWITH; 
      
      /////////////!!!!!!!!!time -= in.GetL1Phase();

      time -= fL1Phase;

      //    AliDebug(2,Form("id %d lowGain %d amp %g", id, lowGain, amp));
      //  AddDigit(digitsArr, id, lowGain, amp, time, chi2, ndf); 
      

      return AliCaloFitResults( -99, -99, fAlgo , amp, time,
				time, chi2, ndf, Ret::kDummy );
      
      
      //	AliCaloFitSubarray(index, maxrev, first, last));
    
    }
  
  
  return AliCaloFitResults( Ret::kInvalid, Ret::kInvalid );
}


/*
void 
AliCaloRawAnalyzerKStandard::PrintFitResult(const TF1 *f) const
{
  //comment
  cout << endl;
  cout << __FILE__ << __LINE__ << "Using this samplerange we get" << endl;
  cout << __FILE__ << __LINE__ << "AMPLITUDE = " << f->GetParameter(0)/fkEulerSquared << ",.. !!!!" << endl;
  cout << __FILE__ << __LINE__ << "TOF = " << f->GetParameter(1) << ",.. !!!!" << endl;
  cout << __FILE__ << __LINE__ << "NDF = " << f->GetNDF() << ",.. !!!!" << endl;
  //  cout << __FILE__ << __LINE__ << "STATUS = " << f->GetStatus()  << ",.. !!!!" << endl << endl;
  cout << endl << endl;
}
*/


//____________________________________________________________________________ 
void
 AliCaloRawAnalyzerKStandard::FitRaw(const Int_t firstTimeBin, const Int_t lastTimeBin, Float_t & amp, Float_t & time, Float_t & chi2, Bool_t & fitDone) const 
{ // Fits the raw signal time distribution
  
  //--------------------------------------------------
  //Do the fit, different fitting algorithms available
  //--------------------------------------------------
  
  // fprintf(fp, "%s:%d:%s\n", __FILE__, __LINE__, __FUNCTION__ );

  int nsamples = lastTimeBin - firstTimeBin + 1;
  fitDone = kFALSE;
  
  // switch(fFittingAlgorithm) 
  //   {
  //  case Algo::kStandard:
  //    {
  if (nsamples < 3) { return; } // nothing much to fit
  //printf("Standard fitter \n");

  // Create Graph to hold data we will fit 
  
  TGraph *gSig =  new TGraph( nsamples); 
 
  for (int i=0; i<nsamples; i++) 
    {
      Int_t timebin = firstTimeBin + i;    
      gSig->SetPoint(i, timebin, GetReversed(timebin)); 
    }
      
  TF1 * signalF = new TF1("signal", RawResponseFunction, 0, TIMEBINS , 5);
  signalF->SetParameters(10.,5., TAU  ,ORDER,0.); //set all defaults once, just to be safe
  signalF->SetParNames("amp","t0","tau","N","ped");
  signalF->FixParameter(2,TAU); // tau in units of time bin
  signalF->FixParameter(3,ORDER); // order
  signalF->FixParameter(4, 0); // pedestal should be subtracted when we get here 
  signalF->SetParameter(1, time);
  signalF->SetParameter(0, amp);
  // set rather loose parameter limits
  signalF->SetParLimits(0, 0.5*amp, 2*amp );
  signalF->SetParLimits(1, time - 4, time + 4); 
      
  try {			
    gSig->Fit(signalF, "QROW"); // Note option 'W': equal errors on all points
    // assign fit results
    amp  = signalF->GetParameter(0); 
    time = signalF->GetParameter(1);
    chi2 = signalF->GetChisquare();
    fitDone = kTRUE;
  }
  catch (const std::exception & e) {
    AliError( Form("TGraph Fit exception %s", e.what()) ); 
    // stay with default amp and time in case of exception, i.e. no special action required
    fitDone = kFALSE;
  }
  delete signalF;
      
  //printf("Std   : Amp %f, time %g\n",amp, time);
  delete gSig; // delete TGraph
      
  //	break;
  //    }//kStandard Fitter
  //----------------------------
 
  /*
    case Algo::kLogFit:
    {
    if (nsamples < 3) { return; } // nothing much to fit
    //printf("LogFit \n");
      
    // Create Graph to hold data we will fit 
    TGraph *gSigLog =  new TGraph( nsamples); 
    for (int i=0; i<nsamples; i++) {
    Int_t timebin = firstTimeBin + i;    
    gSigLog->SetPoint(timebin, timebin, TMath::Log(fRawAnalyzer->GetReversed(timebin) ) ); 
    }
      
    TF1 * signalFLog = new TF1("signalLog", RawResponseFunctionLog, 0,  TIMEBINS , 5);
    signalFLog->SetParameters(2.3, 5.,TAU,ORDER,0.); //set all defaults once, just to be safe
    signalFLog->SetParNames("amplog","t0","tau","N","ped");
    signalFLog->FixParameter(2,TAU); // tau in units of time bin
    signalFLog->FixParameter(3, ORDER); // order
    signalFLog->FixParameter(4, 0); // pedestal should be subtracted when we get here 
    signalFLog->SetParameter(1, time);
    if (amp>=1) {
    signalFLog->SetParameter(0, TMath::Log(amp));
    }
      
    gSigLog->Fit(signalFLog, "QROW"); // Note option 'W': equal errors on all points
      
    // assign fit results
    Double_t amplog = signalFLog->GetParameter(0); //Not Amp, but Log of Amp
    amp = TMath::Exp(amplog);
    time = signalFLog->GetParameter(1);
    fitDone = kTRUE;
      
    delete signalFLog;
    //printf("LogFit: Amp %f, time %g\n",amp, time);
    delete gSigLog; 
    break;
    } //kLogFit 
      //----------------------------	
      //----------------------------
      }//switch fitting algorithms
  */
  return;
}


//__________________________________________________________________
void 
AliCaloRawAnalyzerKStandard::FitParabola(const TGraph *gSig, Float_t & amp) const 
{
  //BEG YS alternative methods to calculate the amplitude
  Double_t * ymx = gSig->GetX() ; 
  Double_t * ymy = gSig->GetY() ; 
  const Int_t kN = 3 ; 
  Double_t ymMaxX[kN] = {0., 0., 0.} ; 
  Double_t ymMaxY[kN] = {0., 0., 0.} ; 
  Double_t ymax = 0. ; 
  // find the maximum amplitude
  Int_t ymiMax = 0 ;  
  for (Int_t ymi = 0; ymi < gSig->GetN(); ymi++) {
    if (ymy[ymi] > ymMaxY[0] ) {
      ymMaxY[0] = ymy[ymi] ; //<========== This is the maximum amplitude
      ymMaxX[0] = ymx[ymi] ;
      ymiMax = ymi ; 
    }
  }
  // find the maximum by fitting a parabola through the max and the two adjacent samples
  if ( ymiMax < gSig->GetN()-1 && ymiMax > 0) {
    ymMaxY[1] = ymy[ymiMax+1] ;
    ymMaxY[2] = ymy[ymiMax-1] ; 
    ymMaxX[1] = ymx[ymiMax+1] ;
    ymMaxX[2] = ymx[ymiMax-1] ; 
    if (ymMaxY[0]*ymMaxY[1]*ymMaxY[2] > 0) {
      //fit a parabola through the 3 points y= a+bx+x*x*x
      Double_t sy = 0 ; 
      Double_t sx = 0 ; 
      Double_t sx2 = 0 ; 
      Double_t sx3 = 0 ; 
      Double_t sx4 = 0 ; 
      Double_t sxy = 0 ; 
      Double_t sx2y = 0 ; 
      for (Int_t i = 0; i < kN ; i++) {
        sy += ymMaxY[i] ; 
        sx += ymMaxX[i] ; 		
        sx2 += ymMaxX[i]*ymMaxX[i] ; 
        sx3 += ymMaxX[i]*ymMaxX[i]*ymMaxX[i] ; 
        sx4 += ymMaxX[i]*ymMaxX[i]*ymMaxX[i]*ymMaxX[i] ; 
        sxy += ymMaxX[i]*ymMaxY[i] ; 
        sx2y += ymMaxX[i]*ymMaxX[i]*ymMaxY[i] ; 
      }
      Double_t cN = (sx2y*kN-sy*sx2)*(sx3*sx-sx2*sx2)-(sx2y*sx-sxy*sx2)*(sx3*kN-sx*sx2); 
      Double_t cD = (sx4*kN-sx2*sx2)*(sx3*sx-sx2*sx2)-(sx4*sx-sx3*sx2)*(sx3*kN-sx*sx2) ;
      Double_t c  = cN / cD ; 
      Double_t b  = ((sx2y*kN-sy*sx2)-c*(sx4*kN-sx2*sx2))/(sx3*kN-sx*sx2) ;
      Double_t a  = (sy-b*sx-c*sx2)/kN  ;
      Double_t xmax = -b/(2*c) ; 
      ymax = a + b*xmax + c*xmax*xmax ;//<========== This is the maximum amplitude
      amp = ymax;
    }
  }
  
  Double_t diff = TMath::Abs(1-ymMaxY[0]/amp) ; 
  if (diff > 0.1) 
    amp = ymMaxY[0] ; 
  //printf("Yves   : Amp %f, time %g\n",amp, time);
  //END YS
  return;
}


//__________________________________________________________________
Double_t 
AliCaloRawAnalyzerKStandard::RawResponseFunction(Double_t *x, Double_t *par)
{
  // Matches version used in 2007 beam test
  //
  // Shape of the electronics raw reponse:
  // It is a semi-gaussian, 2nd order Gamma function of the general form
  //
  // xx = (t - t0 + tau) / tau  [xx is just a convenient help variable]
  // F = A * (xx**N * exp( N * ( 1 - xx) )   for xx >= 0
  // F = 0                                   for xx < 0 
  //
  // parameters:
  // A:   par[0]   // Amplitude = peak value
  // t0:  par[1]
  // tau: par[2]
  // N:   par[3]
  // ped: par[4]
  //
  Double_t signal = 0.;
  Double_t tau    = par[2];
  Double_t n      = par[3];
  Double_t ped    = par[4];
  Double_t xx     = ( x[0] - par[1] + tau ) / tau ;

  if (xx <= 0) 
    signal = ped ;  
  else {  
    signal = ped + par[0] * TMath::Power(xx , n) * TMath::Exp(n * (1 - xx )) ; 
  }
  return signal ;  
}
Commit	Line	Data
92d9f317	1	/**************************************************************************
	2	* This file is property of and copyright by *
	3	* the Relativistic Heavy Ion Group (RHIG), Yale University, US, 2009 *
	4	* *
	5	* Primary Author: Per Thomas Hille <p.t.hille@fys.uio.no> *
	6	* *
	7	* Contributors are mentioned in the code where appropriate. *
	8	* Please report bugs to p.t.hille@fys.uio.no *
	9	* *
	10	* Permission to use, copy, modify and distribute this software and its *
	11	* documentation strictly for non-commercial purposes is hereby granted *
	12	* without fee, provided that the above copyright notice appears in all *
	13	* copies and that both the copyright notice and this permission notice *
	14	* appear in the supporting documentation. The authors make no claims *
	15	* about the suitability of this software for any purpose. It is *
	16	* provided "as is" without express or implied warranty. *
	17	**************************************************************************/
	18
	19
	20	// Extraction of amplitude and peak position
	21	// FRom CALO raw data using
	22	// least square fit for the
	23	// Moment assuming identical and
	24	// independent errors (equivalent with chi square)
	25	//
	26
	27	#include "AliCaloRawAnalyzerKStandard.h"
	28	#include "AliCaloBunchInfo.h"
	29	#include "AliCaloFitResults.h"
	30	#include "AliLog.h"
	31	#include "TMath.h"
	32	#include <stdexcept>
	33	#include <iostream>
	34	#include "TF1.h"
	35	#include "TGraph.h"
	36	#include "TRandom.h"
	37
	38
	39	using namespace std;
	40
	41
	42	#define BAD 4 //CRAP PTH
	43
	44	ClassImp( AliCaloRawAnalyzerKStandard )
	45
	46
396baaf6	47	AliCaloRawAnalyzerKStandard::AliCaloRawAnalyzerKStandard() : AliCaloRawAnalyzerFitter("Chi Square ( kStandard )", "KStandard")
	48	// fkEulerSquared(7.389056098930650227),
	49	// fTf1(0)
	50	// fTau(2.35),
	51	// fFixTau(kTRUE)
92d9f317	52	{
	53
	54	fAlgo = Algo::kStandard;
	55	//comment
396baaf6	56
396baaf6	57	/*
92d9f317	58	for(int i=0; i < ALTROMAXSAMPLES; i++)
	59	{
	60	fXaxis[i] = i;
	61	}
396baaf6	62	*/
	63
	64	// fTf1 = new TF1( "myformula", "[0]((x - [1])/[2])^2exp(-2*(x -[1])/[2])", 0, 30 );
	65
	66	// InitFormula(fTf1);
	67
	68	/*
92d9f317	69	if (fFixTau)
92d9f317	70	{
396baaf6	71	fTf1->FixParameter(2, fTau);
92d9f317	72	}
	73	else
	74	{
	75	fTf1->ReleaseParameter(2); // allow par. to vary
	76	fTf1->SetParameter(2, fTau);
	77	}
396baaf6	78	*/
92d9f317	79	}
	80
	81
	82	AliCaloRawAnalyzerKStandard::~AliCaloRawAnalyzerKStandard()
	83	{
	84	delete fTf1;
	85	}
	86
	87
396baaf6	88	/*
	89	void
	90	AliCaloRawAnalyzerKStandard::InitFormula( TF1* f)
	91	{
	92	f = new TF1( "myformula", "[0]((x - [1])/[2])^2exp(-2*(x -[1])/[2])", 0, 30 );
	93	}
	94	*/
92d9f317	95
	96	AliCaloFitResults
	97	AliCaloRawAnalyzerKStandard::Evaluate( const vector<AliCaloBunchInfo> &bunchlist, const UInt_t altrocfg1, const UInt_t altrocfg2 )
	98	{
	99
	100	Float_t pedEstimate = 0;
	101	short maxADC = 0;
	102	Int_t first = 0;
	103	Int_t last = 0;
	104	Int_t bunchIndex = 0;
	105	Float_t ampEstimate = 0;
	106	short timeEstimate = 0;
	107	Float_t time = 0;
	108	Float_t amp=0;
	109	Float_t chi2 = 0;
	110	Int_t ndf = 0;
	111	Bool_t fitDone = kFALSE;
	112
	113
	114	int nsamples = PreFitEvaluateSamples( bunchlist, altrocfg1, altrocfg2, bunchIndex, ampEstimate,
	115	maxADC, timeEstimate, pedEstimate, first, last, fAmpCut );
	116
	117
	118	if (ampEstimate >= fAmpCut )
	119	{
	120	time = timeEstimate;
	121	Int_t timebinOffset = bunchlist.at(bunchIndex).GetStartBin() - (bunchlist.at(bunchIndex).GetLength()-1);
	122	amp = ampEstimate;
	123
	124	if ( nsamples > 1 && maxADC< OVERFLOWCUT )
	125	{
	126	FitRaw(first, last, amp, time, chi2, fitDone);
	127	time += timebinOffset;
	128	timeEstimate += timebinOffset;
	129	ndf = nsamples - 2;
	130	}
	131	}
	132	if ( fitDone )
	133	{
	134	Float_t ampAsymm = (amp - ampEstimate)/(amp + ampEstimate);
	135	Float_t timeDiff = time - timeEstimate;
	136
	137	if ( (TMath::Abs(ampAsymm) > 0.1) \|\| (TMath::Abs(timeDiff) > 2) )
	138	{
	139	amp = ampEstimate;
	140	time = timeEstimate;
	141	fitDone = kFALSE;
	142	}
	143	}
	144	if (amp >= fAmpCut )
	145	{
	146	if ( ! fitDone)
	147	{
	148	amp += (0.5 - gRandom->Rndm());
	149	}
	150	//Int_t id = fGeom->GetAbsCellIdFromCellIndexes(in.GetModule(), in.GetRow(), in.GetColumn()) ;
	151	// lowGain = in.IsLowGain();
	152
	153	time = time * TIMEBINWITH;
	154
	155	/////////////!!!!!!!!!time -= in.GetL1Phase();
	156
	157	time -= fL1Phase;
	158
159	// AliDebug(2,Form("id %d lowGain %d amp %g", id, lowGain, amp));
160	// AddDigit(digitsArr, id, lowGain, amp, time, chi2, ndf);
161
162
163	return AliCaloFitResults( -99, -99, fAlgo , amp, time,
164	time, chi2, ndf, Ret::kDummy );
165
166
167	// AliCaloFitSubarray(index, maxrev, first, last));
168
169	}
170
171
172	return AliCaloFitResults( Ret::kInvalid, Ret::kInvalid );
173	}
174
175
92d9f317	176	/*
92d9f317	177	void
	178	AliCaloRawAnalyzerKStandard::PrintFitResult(const TF1 *f) const
	179	{
	180	//comment
	181	cout << endl;
	182	cout << __FILE__ << __LINE__ << "Using this samplerange we get" << endl;
	183	cout << __FILE__ << __LINE__ << "AMPLITUDE = " << f->GetParameter(0)/fkEulerSquared << ",.. !!!!" << endl;
	184	cout << __FILE__ << __LINE__ << "TOF = " << f->GetParameter(1) << ",.. !!!!" << endl;
	185	cout << __FILE__ << __LINE__ << "NDF = " << f->GetNDF() << ",.. !!!!" << endl;
	186	// cout << __FILE__ << __LINE__ << "STATUS = " << f->GetStatus() << ",.. !!!!" << endl << endl;
	187	cout << endl << endl;
	188	}
396baaf6	189	*/
92d9f317	190
	191
	192
	193
	194	//____________________________________________________________________________
	195	void
	196	AliCaloRawAnalyzerKStandard::FitRaw(const Int_t firstTimeBin, const Int_t lastTimeBin, Float_t & amp, Float_t & time, Float_t & chi2, Bool_t & fitDone) const
	197	{ // Fits the raw signal time distribution
	198
	199	//--------------------------------------------------
	200	//Do the fit, different fitting algorithms available
	201	//--------------------------------------------------
	202
	203	// fprintf(fp, "%s:%d:%s\n", __FILE__, __LINE__, __FUNCTION__ );
	204
	205	int nsamples = lastTimeBin - firstTimeBin + 1;
	206	fitDone = kFALSE;
	207
	208	// switch(fFittingAlgorithm)
	209	// {
	210	// case Algo::kStandard:
	211	// {
	212	if (nsamples < 3) { return; } // nothing much to fit
	213	//printf("Standard fitter \n");
	214
	215	// Create Graph to hold data we will fit
	216
	217	TGraph *gSig = new TGraph( nsamples);
	218
	219	for (int i=0; i<nsamples; i++)
	220	{
	221	Int_t timebin = firstTimeBin + i;
	222	gSig->SetPoint(i, timebin, GetReversed(timebin));
	223	}
	224
	225	TF1 * signalF = new TF1("signal", RawResponseFunction, 0, TIMEBINS , 5);
	226	signalF->SetParameters(10.,5., TAU ,ORDER,0.); //set all defaults once, just to be safe
	227	signalF->SetParNames("amp","t0","tau","N","ped");
	228	signalF->FixParameter(2,TAU); // tau in units of time bin
	229	signalF->FixParameter(3,ORDER); // order
	230	signalF->FixParameter(4, 0); // pedestal should be subtracted when we get here
	231	signalF->SetParameter(1, time);
	232	signalF->SetParameter(0, amp);
	233	// set rather loose parameter limits
	234	signalF->SetParLimits(0, 0.5amp, 2amp );
	235	signalF->SetParLimits(1, time - 4, time + 4);
	236
	237	try {
	238	gSig->Fit(signalF, "QROW"); // Note option 'W': equal errors on all points
	239	// assign fit results
	240	amp = signalF->GetParameter(0);
	241	time = signalF->GetParameter(1);
	242	chi2 = signalF->GetChisquare();
	243	fitDone = kTRUE;
	244	}
	245	catch (const std::exception & e) {
	246	AliError( Form("TGraph Fit exception %s", e.what()) );
	247	// stay with default amp and time in case of exception, i.e. no special action required
	248	fitDone = kFALSE;
	249	}
	250	delete signalF;
	251
	252	//printf("Std : Amp %f, time %g\n",amp, time);
	253	delete gSig; // delete TGraph
254
255	// break;
256	// }//kStandard Fitter
257	//----------------------------
258
259	/*
260	case Algo::kLogFit:
261	{
262	if (nsamples < 3) { return; } // nothing much to fit
263	//printf("LogFit \n");
264
265	// Create Graph to hold data we will fit
266	TGraph *gSigLog = new TGraph( nsamples);
267	for (int i=0; i<nsamples; i++) {
268	Int_t timebin = firstTimeBin + i;
269	gSigLog->SetPoint(timebin, timebin, TMath::Log(fRawAnalyzer->GetReversed(timebin) ) );
270	}
271
272	TF1 * signalFLog = new TF1("signalLog", RawResponseFunctionLog, 0, TIMEBINS , 5);
273	signalFLog->SetParameters(2.3, 5.,TAU,ORDER,0.); //set all defaults once, just to be safe
274	signalFLog->SetParNames("amplog","t0","tau","N","ped");
275	signalFLog->FixParameter(2,TAU); // tau in units of time bin
276	signalFLog->FixParameter(3, ORDER); // order
277	signalFLog->FixParameter(4, 0); // pedestal should be subtracted when we get here
278	signalFLog->SetParameter(1, time);
279	if (amp>=1) {
280	signalFLog->SetParameter(0, TMath::Log(amp));
281	}
282
283	gSigLog->Fit(signalFLog, "QROW"); // Note option 'W': equal errors on all points
284
285	// assign fit results
286	Double_t amplog = signalFLog->GetParameter(0); //Not Amp, but Log of Amp
287	amp = TMath::Exp(amplog);
288	time = signalFLog->GetParameter(1);
289	fitDone = kTRUE;
290
291	delete signalFLog;
292	//printf("LogFit: Amp %f, time %g\n",amp, time);
293	delete gSigLog;
294	break;
295	} //kLogFit
296	//----------------------------
297	//----------------------------
298	}//switch fitting algorithms
299	*/
300	return;
301	}
302
303
304	//__________________________________________________________________
305	void
306	AliCaloRawAnalyzerKStandard::FitParabola(const TGraph *gSig, Float_t & amp) const
307	{
308	//BEG YS alternative methods to calculate the amplitude
309	Double_t * ymx = gSig->GetX() ;
310	Double_t * ymy = gSig->GetY() ;
311	const Int_t kN = 3 ;
312	Double_t ymMaxX[kN] = {0., 0., 0.} ;
313	Double_t ymMaxY[kN] = {0., 0., 0.} ;
314	Double_t ymax = 0. ;
315	// find the maximum amplitude
316	Int_t ymiMax = 0 ;
317	for (Int_t ymi = 0; ymi < gSig->GetN(); ymi++) {
318	if (ymy[ymi] > ymMaxY[0] ) {
319	ymMaxY[0] = ymy[ymi] ; //<========== This is the maximum amplitude
320	ymMaxX[0] = ymx[ymi] ;
321	ymiMax = ymi ;
322	}
323	}
324	// find the maximum by fitting a parabola through the max and the two adjacent samples
325	if ( ymiMax < gSig->GetN()-1 && ymiMax > 0) {
326	ymMaxY[1] = ymy[ymiMax+1] ;
327	ymMaxY[2] = ymy[ymiMax-1] ;
328	ymMaxX[1] = ymx[ymiMax+1] ;
329	ymMaxX[2] = ymx[ymiMax-1] ;
330	if (ymMaxY[0]ymMaxY[1]ymMaxY[2] > 0) {
331	//fit a parabola through the 3 points y= a+bx+xxx
332	Double_t sy = 0 ;
333	Double_t sx = 0 ;
334	Double_t sx2 = 0 ;
335	Double_t sx3 = 0 ;
336	Double_t sx4 = 0 ;
337	Double_t sxy = 0 ;
338	Double_t sx2y = 0 ;
339	for (Int_t i = 0; i < kN ; i++) {
340	sy += ymMaxY[i] ;
341	sx += ymMaxX[i] ;
342	sx2 += ymMaxX[i]*ymMaxX[i] ;
343	sx3 += ymMaxX[i]ymMaxX[i]ymMaxX[i] ;
344	sx4 += ymMaxX[i]ymMaxX[i]ymMaxX[i]*ymMaxX[i] ;
345	sxy += ymMaxX[i]*ymMaxY[i] ;
346	sx2y += ymMaxX[i]ymMaxX[i]ymMaxY[i] ;
347	}
348	Double_t cN = (sx2ykN-sysx2)(sx3sx-sx2sx2)-(sx2ysx-sxysx2)(sx3kN-sxsx2);
349	Double_t cD = (sx4kN-sx2sx2)(sx3sx-sx2sx2)-(sx4sx-sx3sx2)(sx3kN-sxsx2) ;
350	Double_t c = cN / cD ;
351	Double_t b = ((sx2ykN-sysx2)-c(sx4kN-sx2sx2))/(sx3kN-sx*sx2) ;
352	Double_t a = (sy-bsx-csx2)/kN ;
353	Double_t xmax = -b/(2*c) ;
354	ymax = a + bxmax + cxmax*xmax ;//<========== This is the maximum amplitude
355	amp = ymax;
356	}
357	}
358
359	Double_t diff = TMath::Abs(1-ymMaxY[0]/amp) ;
360	if (diff > 0.1)
361	amp = ymMaxY[0] ;
362	//printf("Yves : Amp %f, time %g\n",amp, time);
363	//END YS
364	return;
365	}
366
367
368
369	//__________________________________________________________________
370	Double_t
371	AliCaloRawAnalyzerKStandard::RawResponseFunction(Double_t x, Double_t par)
372	{
373	// Matches version used in 2007 beam test
374	//
375	// Shape of the electronics raw reponse:
376	// It is a semi-gaussian, 2nd order Gamma function of the general form
377	//
378	// xx = (t - t0 + tau) / tau [xx is just a convenient help variable]
379	// F = A * (xx*N exp( N * ( 1 - xx) ) for xx >= 0
380	// F = 0 for xx < 0
381	//
382	// parameters:
383	// A: par[0] // Amplitude = peak value
384	// t0: par[1]
385	// tau: par[2]
386	// N: par[3]
387	// ped: par[4]
388	//
389	Double_t signal = 0.;
390	Double_t tau = par[2];
391	Double_t n = par[3];
392	Double_t ped = par[4];
393	Double_t xx = ( x[0] - par[1] + tau ) / tau ;
394
395	if (xx <= 0)
396	signal = ped ;
397	else {
398	signal = ped + par[0] * TMath::Power(xx , n) * TMath::Exp(n * (1 - xx )) ;
399	}
400	return signal ;
401	}
402