//*-- Author: Marco van Leeuwen (LBL)
#include "AliEMCALRawUtils.h"
+#include <stdexcept>
-#include <TF1.h>
-#include <TGraph.h>
+#include "TF1.h"
+#include "TGraph.h"
#include <TRandom.h>
class TSystem;
#include "AliEMCALGeometry.h"
class AliEMCALDigitizer;
#include "AliEMCALDigit.h"
+#include "AliEMCALRawDigit.h"
#include "AliEMCAL.h"
#include "AliCaloCalibPedestal.h"
#include "AliCaloFastAltroFitv0.h"
// some digitization constants
Int_t AliEMCALRawUtils::fgThreshold = 1;
Int_t AliEMCALRawUtils::fgDDLPerSuperModule = 2; // 2 ddls per SuperModule
-Int_t AliEMCALRawUtils::fgPedestalValue = 32; // pedestal value for digits2raw
+Int_t AliEMCALRawUtils::fgPedestalValue = 0; // pedestal value for digits2raw, default generate ZS data
Double_t AliEMCALRawUtils::fgFEENoise = 3.; // 3 ADC channels of noise (sampled)
AliEMCALRawUtils::AliEMCALRawUtils(fitAlgorithm fitAlgo)
: fHighLowGainFactor(0.), fOrder(0), fTau(0.), fNoiseThreshold(0),
fNPedSamples(0), fGeom(0), fOption(""),
- fRemoveBadChannels(kTRUE),fFittingAlgorithm(0),fRawAnalyzer(0)
+ fRemoveBadChannels(kTRUE),fFittingAlgorithm(0),fUseFALTRO(kFALSE),fRawAnalyzer(0)
{
//These are default parameters.
//Can be re-set from without with setter functions
//Already set in the OCDB and passed via setter in the AliEMCALReconstructor
- fHighLowGainFactor = 16. ; // adjusted for a low gain range of 82 GeV (10 bits)
- fOrder = 2; // order of gamma fn
- fTau = 2.35; // in units of timebin, from CERN 2007 testbeam
- fNoiseThreshold = 3; // 3 ADC counts is approx. noise level
- fNPedSamples = 4; // less than this value => likely pedestal samples
- fRemoveBadChannels = kTRUE; //Remove bad channels before fitting
- fFittingAlgorithm = fitAlgo;
-
- if (fitAlgo == kFastFit) {
- fRawAnalyzer = new AliCaloRawAnalyzerFastFit();
- }
- else if (fitAlgo == kNeuralNet) {
- fRawAnalyzer = new AliCaloRawAnalyzerNN();
- }
- else if (fitAlgo == kLMS) {
- fRawAnalyzer = new AliCaloRawAnalyzerLMS();
- }
- else if (fitAlgo == kPeakFinder) {
- fRawAnalyzer = new AliCaloRawAnalyzerPeakFinder();
- }
- else if (fitAlgo == kCrude) {
- fRawAnalyzer = new AliCaloRawAnalyzerCrude();
- }
- else {
- fRawAnalyzer = new AliCaloRawAnalyzer();
- }
+ fHighLowGainFactor = 16. ; // Adjusted for a low gain range of 82 GeV (10 bits)
+ fOrder = 2; // Order of gamma fn
+ fTau = 2.35; // in units of timebin, from CERN 2007 testbeam
+ fNoiseThreshold = 3; // 3 ADC counts is approx. noise level
+ fNPedSamples = 4; // Less than this value => likely pedestal samples
+ fRemoveBadChannels = kFALSE; // Do not remove bad channels before fitting
+ fUseFALTRO = kTRUE; // Get the trigger FALTRO information and pass it to digits.
+ SetFittingAlgorithm(fitAlgo);
//Get Mapping RCU files from the AliEMCALRecParam
const TObjArray* maps = AliEMCALRecParam::GetMappings();
//To make sure we match with the geometry in a simulation file,
//let's try to get it first. If not, take the default geometry
AliRunLoader *rl = AliRunLoader::Instance();
- if(!rl) AliError("Cannot find RunLoader!");
- if (rl->GetAliRun() && rl->GetAliRun()->GetDetector("EMCAL")) {
+ if (rl && rl->GetAliRun() && rl->GetAliRun()->GetDetector("EMCAL")) {
fGeom = dynamic_cast<AliEMCAL*>(rl->GetAliRun()->GetDetector("EMCAL"))->GetGeometry();
} else {
AliInfo(Form("Using default geometry in raw reco"));
AliEMCALRawUtils::AliEMCALRawUtils(AliEMCALGeometry *pGeometry, fitAlgorithm fitAlgo)
: fHighLowGainFactor(0.), fOrder(0), fTau(0.), fNoiseThreshold(0),
fNPedSamples(0), fGeom(pGeometry), fOption(""),
- fRemoveBadChannels(kTRUE),fFittingAlgorithm(0),fRawAnalyzer()
+ fRemoveBadChannels(kTRUE),fFittingAlgorithm(0),fUseFALTRO(kFALSE),fRawAnalyzer()
{
//
// Initialize with the given geometry - constructor required by HLT
//These are default parameters.
//Can be re-set from without with setter functions
//Already set in the OCDB and passed via setter in the AliEMCALReconstructor
- fHighLowGainFactor = 16. ; // adjusted for a low gain range of 82 GeV (10 bits)
- fOrder = 2; // order of gamma fn
- fTau = 2.35; // in units of timebin, from CERN 2007 testbeam
- fNoiseThreshold = 3; // 3 ADC counts is approx. noise level
- fNPedSamples = 4; // less than this value => likely pedestal samples
- fRemoveBadChannels = kTRUE; //Remove bad channels before fitting
- fFittingAlgorithm = fitAlgo;
-
- if (fitAlgo == kFastFit) {
- fRawAnalyzer = new AliCaloRawAnalyzerFastFit();
- }
- else if (fitAlgo == kNeuralNet) {
- fRawAnalyzer = new AliCaloRawAnalyzerNN();
- }
- else if (fitAlgo == kLMS) {
- fRawAnalyzer = new AliCaloRawAnalyzerLMS();
- }
- else if (fitAlgo == kPeakFinder) {
- fRawAnalyzer = new AliCaloRawAnalyzerPeakFinder();
- }
- else if (fitAlgo == kCrude) {
- fRawAnalyzer = new AliCaloRawAnalyzerCrude();
- }
- else {
- fRawAnalyzer = new AliCaloRawAnalyzer();
- }
+ fHighLowGainFactor = 16. ; // adjusted for a low gain range of 82 GeV (10 bits)
+ fOrder = 2; // order of gamma fn
+ fTau = 2.35; // in units of timebin, from CERN 2007 testbeam
+ fNoiseThreshold = 3; // 3 ADC counts is approx. noise level
+ fNPedSamples = 4; // Less than this value => likely pedestal samples
+ fRemoveBadChannels = kFALSE; // Do not remove bad channels before fitting
+ fUseFALTRO = kTRUE; // Get the trigger FALTRO information and pass it to digits.
+ SetFittingAlgorithm(fitAlgo);
//Get Mapping RCU files from the AliEMCALRecParam
const TObjArray* maps = AliEMCALRecParam::GetMappings();
fOption(rawU.fOption),
fRemoveBadChannels(rawU.fRemoveBadChannels),
fFittingAlgorithm(rawU.fFittingAlgorithm),
+ fUseFALTRO(rawU.fUseFALTRO),
fRawAnalyzer(rawU.fRawAnalyzer)
{
//copy ctor
if(this != &rawU) {
fHighLowGainFactor = rawU.fHighLowGainFactor;
- fOrder = rawU.fOrder;
- fTau = rawU.fTau;
- fNoiseThreshold = rawU.fNoiseThreshold;
- fNPedSamples = rawU.fNPedSamples;
- fGeom = rawU.fGeom;
- fOption = rawU.fOption;
+ fOrder = rawU.fOrder;
+ fTau = rawU.fTau;
+ fNoiseThreshold = rawU.fNoiseThreshold;
+ fNPedSamples = rawU.fNPedSamples;
+ fGeom = rawU.fGeom;
+ fOption = rawU.fOption;
fRemoveBadChannels = rawU.fRemoveBadChannels;
fFittingAlgorithm = rawU.fFittingAlgorithm;
- fRawAnalyzer = rawU.fRawAnalyzer;
- fMapping[0] = rawU.fMapping[0];
- fMapping[1] = rawU.fMapping[1];
- fMapping[2] = rawU.fMapping[2];
- fMapping[3] = rawU.fMapping[3];
+ fUseFALTRO = rawU.fUseFALTRO;
+ fRawAnalyzer = rawU.fRawAnalyzer;
+ fMapping[0] = rawU.fMapping[0];
+ fMapping[1] = rawU.fMapping[1];
+ fMapping[2] = rawU.fMapping[2];
+ fMapping[3] = rawU.fMapping[3];
}
return *this;
}
//____________________________________________________________________________
-void AliEMCALRawUtils::Raw2Digits(AliRawReader* reader,TClonesArray *digitsArr, const AliCaloCalibPedestal* pedbadmap)
+void AliEMCALRawUtils::Raw2Digits(AliRawReader* reader,TClonesArray *digitsArr, const AliCaloCalibPedestal* pedbadmap, TClonesArray *digitsTRG)
{
// convert raw data of the current event to digits
reader->Select("EMCAL",0,43); // 43 = AliEMCALGeoParams::fgkLastAltroDDL
// fRawAnalyzer setup
+ fRawAnalyzer->SetNsampleCut(5); // requirement for fits to be done
fRawAnalyzer->SetAmpCut(fNoiseThreshold);
fRawAnalyzer->SetFitArrayCut(fNoiseThreshold);
fRawAnalyzer->SetIsZeroSuppressed(true); // TMP - should use stream->IsZeroSuppressed(), or altro cfg registers later
// start loop over input stream
while (in.NextDDL()) {
+
+// if ( in.GetDDLNumber() != 0 && in.GetDDLNumber() != 2 ) continue;
+
while (in.NextChannel()) {
+/*
+ Int_t hhwAdd = in.GetHWAddress();
+ UShort_t iiBranch = ( hhwAdd >> 11 ) & 0x1; // 0/1
+ UShort_t iiFEC = ( hhwAdd >> 7 ) & 0xF;
+ UShort_t iiChip = ( hhwAdd >> 4 ) & 0x7;
+ UShort_t iiChannel = hhwAdd & 0xF;
+
+ if ( !( iiBranch == 0 && iiFEC == 1 && iiChip == 3 && ( iiChannel >= 8 && iiChannel <= 15 ) ) && !( iiBranch == 1 && iiFEC == 0 && in.GetColumn() == 0 ) ) continue;
+*/
+
//Check if the signal is high or low gain and then do the fit,
//if it is from TRU or LEDMon do not fit
caloFlag = in.GetCaloFlag();
- if (caloFlag != 0 && caloFlag != 1) continue;
-
- //Do not fit bad channels
- if(fRemoveBadChannels && pedbadmap->IsBadChannel(in.GetModule(),in.GetColumn(),in.GetRow())) {
+// if (caloFlag != 0 && caloFlag != 1) continue;
+ if (caloFlag > 2) continue; // Work with ALTRO and FALTRO
+
+ //Do not fit bad channels of ALTRO
+ if(caloFlag < 2 && fRemoveBadChannels && pedbadmap->IsBadChannel(in.GetModule(),in.GetColumn(),in.GetRow())) {
//printf("Tower from SM %d, column %d, row %d is BAD!!! Skip \n", in.GetModule(),in.GetColumn(),in.GetRow());
continue;
}
bunchlist.push_back( AliCaloBunchInfo(in.GetStartTimeBin(), in.GetBunchLength(), in.GetSignals() ) );
} // loop over bunches
- Float_t time = 0;
- Float_t amp = 0;
-
+
+ if ( caloFlag < 2 ){ // ALTRO
+
+ Float_t time = 0;
+ Float_t amp = 0;
+ short timeEstimate = 0;
+ Float_t ampEstimate = 0;
+ Bool_t fitDone = kFALSE;
+
if ( fFittingAlgorithm == kFastFit || fFittingAlgorithm == kNeuralNet || fFittingAlgorithm == kLMS || fFittingAlgorithm == kPeakFinder || fFittingAlgorithm == kCrude) {
// all functionality to determine amp and time etc is encapsulated inside the Evaluate call for these methods
AliCaloFitResults fitResults = fRawAnalyzer->Evaluate( bunchlist, in.GetAltroCFG1(), in.GetAltroCFG2());
amp = fitResults.GetAmp();
- time = fitResults.GetTof();
+ time = fitResults.GetTime();
+ timeEstimate = fitResults.GetMaxTimebin();
+ ampEstimate = fitResults.GetMaxSig();
+ if (fitResults.GetStatus() == AliCaloFitResults::kFitPar) {
+ fitDone = kTRUE;
+ }
}
else { // for the other methods we for now use the functionality of
// AliCaloRawAnalyzer as well, to select samples and prepare for fits,
// if it looks like there is something to fit
// parameters init.
- Float_t ampEstimate = 0;
+ Float_t pedEstimate = 0;
short maxADC = 0;
- short timeEstimate = 0;
- Float_t pedEstimate = 0;
Int_t first = 0;
Int_t last = 0;
Int_t bunchIndex = 0;
if (ampEstimate > fNoiseThreshold) { // something worth looking at
- time = timeEstimate;
+ time = timeEstimate; // maxrev in AliCaloRawAnalyzer speak; comes with an offset w.r.t. real timebin
+ Int_t timebinOffset = bunchlist.at(bunchIndex).GetStartBin() - (bunchlist.at(bunchIndex).GetLength()-1);
amp = ampEstimate;
if ( nsamples > 1 ) { // possibly something to fit
- FitRaw(first, last, amp, time);
+ FitRaw(first, last, amp, time, fitDone);
+ time += timebinOffset;
+ timeEstimate += timebinOffset;
}
- if ( amp>0 && time>0 ) { // brief sanity check of fit results
-
- // check fit results: should be consistent with initial estimates
- // more magic numbers, but very loose cuts, for now..
- // We have checked that amp and ampEstimate values are positive so division for assymmetry
- // calculation should be OK/safe
- Float_t ampAsymm = (amp - ampEstimate)/(amp + ampEstimate);
- if ( (TMath::Abs(ampAsymm) > 0.1) ) {
- AliDebug(2,Form("Fit results amp %f time %f not consistent with expectations ped %f max-ped %f time %d",
- amp, time, pedEstimate, ampEstimate, timeEstimate));
-
- // what should do we do then? skip this channel or assign the simple estimate?
- // for now just overwrite the fit results with the simple estimate
- amp = ampEstimate;
- time = timeEstimate;
- } // asymm check
- } // amp & time check
} // ampEstimate check
} // method selection
+
+ if ( fitDone ) { // brief sanity check of fit results
+ Float_t ampAsymm = (amp - ampEstimate)/(amp + ampEstimate);
+ Float_t timeDiff = time - timeEstimate;
+ if ( (TMath::Abs(ampAsymm) > 0.1) || (TMath::Abs(timeDiff) > 2) ) {
+ // AliDebug(2,Form("Fit results amp %f time %f not consistent with expectations amp %f time %d", amp, time, ampEstimate, timeEstimate));
+
+ // for now just overwrite the fit results with the simple/initial estimate
+ amp = ampEstimate;
+ time = timeEstimate;
+ fitDone = kFALSE;
+ }
+ } // fitDone
- if (amp > fNoiseThreshold) { // something to be stored
+ if (amp > fNoiseThreshold && amp<fgkRawSignalOverflow) { // something to be stored
+ if ( ! fitDone) { // smear ADC with +- 0.5 uniform (avoid discrete effects)
+ amp += (0.5 - gRandom->Rndm()); // Rndm generates a number in ]0,1]
+ }
+
Int_t id = fGeom->GetAbsCellIdFromCellIndexes(in.GetModule(), in.GetRow(), in.GetColumn()) ;
lowGain = in.IsLowGain();
AddDigit(digitsArr, id, lowGain, TMath::Nint(amp), time);
}
+ }//ALTRO
+ else if(fUseFALTRO)
+ {// Fake ALTRO
+ // if (maxTimeBin && gSig->GetN() > maxTimeBin + 10) gSig->Set(maxTimeBin + 10); // set actual max size of TGraph
+ Int_t hwAdd = in.GetHWAddress();
+ UShort_t iRCU = in.GetDDLNumber() % 2; // 0/1
+ UShort_t iBranch = ( hwAdd >> 11 ) & 0x1; // 0/1
+
+ // Now find TRU number
+ Int_t itru = 3 * in.GetModule() + ( (iRCU << 1) | iBranch ) - 1;
+
+ AliDebug(1,Form("Found TRG digit in TRU: %2d ADC: %2d",itru,in.GetColumn()));
+
+ Int_t idtrg;
+
+ Bool_t isOK = fGeom->GetAbsFastORIndexFromTRU(itru, in.GetColumn(), idtrg);
+
+ Int_t timeSamples[256]; for (Int_t j=0;j<256;j++) timeSamples[j] = 0;
+ Int_t nSamples = 0;
+
+ for (std::vector<AliCaloBunchInfo>::iterator itVectorData = bunchlist.begin(); itVectorData != bunchlist.end(); itVectorData++)
+ {
+ AliCaloBunchInfo bunch = *(itVectorData);
+
+ const UShort_t* sig = bunch.GetData();
+ Int_t startBin = bunch.GetStartBin();
+
+ for (Int_t iS = 0; iS < bunch.GetLength(); iS++)
+ {
+ Int_t time = startBin--;
+ Int_t amp = sig[iS];
+
+ if ( amp ) timeSamples[nSamples++] = ( ( time << 12 ) & 0xFF000 ) | ( amp & 0xFFF );
+ }
+ }
+
+ if (nSamples && isOK) AddDigit(digitsTRG, idtrg, timeSamples, nSamples);
+ }//Fake ALTRO
} // end while over channel
} //end while over DDL's, of input stream
return ;
}
+//____________________________________________________________________________
+void AliEMCALRawUtils::AddDigit(TClonesArray *digitsArr, Int_t id, Int_t timeSamples[], Int_t nSamples)
+{
+ new((*digitsArr)[digitsArr->GetEntriesFast()]) AliEMCALRawDigit(id, timeSamples, nSamples);
+
+ // Int_t idx = digitsArr->GetEntriesFast()-1;
+ // AliEMCALRawDigit* d = (AliEMCALRawDigit*)digitsArr->At(idx);
+}
+
//____________________________________________________________________________
void AliEMCALRawUtils::AddDigit(TClonesArray *digitsArr, Int_t id, Int_t lowGain, Int_t amp, Float_t time) {
//
}
//____________________________________________________________________________
-void AliEMCALRawUtils::FitRaw(const Int_t firstTimeBin, const Int_t lastTimeBin, Float_t & amp, Float_t & time) const
+void AliEMCALRawUtils::FitRaw(const Int_t firstTimeBin, const Int_t lastTimeBin, Float_t & amp, Float_t & time, Bool_t & fitDone) const
{ // Fits the raw signal time distribution
//--------------------------------------------------
//Do the fit, different fitting algorithms available
//--------------------------------------------------
int nsamples = lastTimeBin - firstTimeBin + 1;
+ fitDone = kFALSE;
switch(fFittingAlgorithm) {
case kStandard:
TGraph *gSig = new TGraph( nsamples);
for (int i=0; i<nsamples; i++) {
Int_t timebin = firstTimeBin + i;
- gSig->SetPoint(timebin, timebin, fRawAnalyzer->GetReversed(timebin));
+ gSig->SetPoint(i, timebin, fRawAnalyzer->GetReversed(timebin));
}
TF1 * signalF = new TF1("signal", RawResponseFunction, 0, GetRawFormatTimeBins(), 5);
signalF->FixParameter(4, 0); // pedestal should be subtracted when we get here
signalF->SetParameter(1, time);
signalF->SetParameter(0, amp);
-
- gSig->Fit(signalF, "QROW"); // Note option 'W': equal errors on all points
-
- // assign fit results
- amp = signalF->GetParameter(0);
- time = signalF->GetParameter(1);
-
+ // 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);
+
+ // cross-check with ParabolaFit to see if the results make sense
+ FitParabola(gSig, amp); // amp is possibly updated
+ 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;
- // cross-check with ParabolaFit to see if the results make sense
- FitParabola(gSig, amp); // amp is possibly updated
-
//printf("Std : Amp %f, time %g\n",amp, time);
delete gSig; // delete TGraph
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);
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;
}
}
}
//__________________________________________________________________
-Bool_t AliEMCALRawUtils::RawSampledResponse(const Double_t dtime, const Double_t damp,
-Int_t * adcH, Int_t * adcL, const Int_t keyErr) const
+Bool_t AliEMCALRawUtils::RawSampledResponse(const Double_t dtime, const Double_t damp, Int_t * adcH, Int_t * adcL, const Int_t keyErr) const
{
// for a start time dtime and an amplitude damp given by digit,
// calculates the raw sampled response AliEMCAL::RawResponseFunction
signalF.SetParameter(2, fTau) ;
signalF.SetParameter(3, fOrder);
signalF.SetParameter(4, fgPedestalValue);
-
+
Double_t signal=0.0, noise=0.0;
for (Int_t iTime = 0; iTime < GetRawFormatTimeBins(); iTime++) {
- signal = signalF.Eval(iTime) ;
-
+ signal = signalF.Eval(iTime) ;
+
// Next lines commeted for the moment but in principle it is not necessary to add
// extra noise since noise already added at the digits level.
//signal = sqrt(signal*signal + noise*noise);
// March 17,09 for fast fit simulations by Alexei Pavlinov.
- // Get from PHOS analysis. In some sense it is open question.
- if(keyErr>0) {
- noise = gRandom->Gaus(0.,fgFEENoise);
- signal += noise;
- }
-
+ // Get from PHOS analysis. In some sense it is open questions.
+ if(keyErr>0) {
+ noise = gRandom->Gaus(0.,fgFEENoise);
+ signal += noise;
+ }
+
adcH[iTime] = static_cast<Int_t>(signal + 0.5) ;
if ( adcH[iTime] > fgkRawSignalOverflow ){ // larger than 10 bits
adcH[iTime] = fgkRawSignalOverflow ;
}
return lowGain ;
}
+
+//__________________________________________________________________
+void AliEMCALRawUtils::SetFittingAlgorithm(Int_t fitAlgo)
+{
+ //Set fitting algorithm and initialize it if this same algorithm was not set before.
+ //printf("**** Set Algorithm , number %d ****\n",fitAlgo);
+
+ if(fitAlgo == fFittingAlgorithm && fRawAnalyzer) {
+ //Do nothing, this same algorithm already set before.
+ //printf("**** Algorithm already set before, number %d, %s ****\n",fitAlgo, fRawAnalyzer->GetName());
+ return;
+ }
+ //Initialize the requested algorithm
+ if(fitAlgo != fFittingAlgorithm || !fRawAnalyzer) {
+ //printf("**** Init Algorithm , number %d ****\n",fitAlgo);
+
+ fFittingAlgorithm = fitAlgo;
+ if (fRawAnalyzer) delete fRawAnalyzer; // delete prev. analyzer if existed.
+
+ if (fitAlgo == kFastFit) {
+ fRawAnalyzer = new AliCaloRawAnalyzerFastFit();
+ }
+ else if (fitAlgo == kNeuralNet) {
+ fRawAnalyzer = new AliCaloRawAnalyzerNN();
+ }
+ else if (fitAlgo == kLMS) {
+ fRawAnalyzer = new AliCaloRawAnalyzerLMS();
+ }
+ else if (fitAlgo == kPeakFinder) {
+ fRawAnalyzer = new AliCaloRawAnalyzerPeakFinder();
+ }
+ else if (fitAlgo == kCrude) {
+ fRawAnalyzer = new AliCaloRawAnalyzerCrude();
+ }
+ else {
+ fRawAnalyzer = new AliCaloRawAnalyzer();
+ }
+ }
+
+}
+
+
git://git.uio.no / u / mrichter / AliRoot.git / blobdiff