//set cluster parameters
c.SetQ(sumw);
c.SetPad(meani-2.5);
- c.SetTimeBin(meanj-2.5);
+ c.SetTimeBin(meanj-3);
c.SetSigmaY2(mi2);
c.SetSigmaZ2(mj2);
c.SetType(0);
fInput->GetBranch("Segment")->SetAddress(&dummy);
Stat_t nentries = fInput->GetEntries();
- fMaxTime=fParam->GetMaxTBin()+6; // add 3 virtual time bins before and 3 after
+ fMaxTime=fRecoParam->GetLastBin()+6; // add 3 virtual time bins before and 3 after
Int_t nclusters = 0;
Int_t nclusters = 0;
- fMaxTime = fParam->GetMaxTBin() + 6; // add 3 virtual time bins before and 3 after
+ fMaxTime = fRecoParam->GetLastBin() + 6; // add 3 virtual time bins before and 3 after
const Int_t kNIS = fParam->GetNInnerSector();
const Int_t kNOS = fParam->GetNOuterSector();
const Int_t kNS = kNIS + kNOS;
AliTPCCalROC * gainROC = gainTPC->GetCalROC(fSector); // pad gains per given sector
AliTPCCalROC * pedestalROC = pedestalTPC->GetCalROC(fSector); // pedestal per given sector
AliTPCCalROC * noiseROC = noiseTPC->GetCalROC(fSector); // noise per given sector
-
+ //check the presence of the calibration
+ if (!noiseROC ||!pedestalROC ) {
+ AliError(Form("Missing calibration per sector\t%d\n",fSector));
+ continue;
+ }
Int_t nRows = 0;
Int_t nDDLs = 0, indexDDL = 0;
if (fSector < kNIS) {
Float_t gain =1;
Int_t lastPad=-1;
while (input.Next()) {
- digCounter++;
if (input.GetSector() != fSector)
AliFatal(Form("Sector index mismatch ! Expected (%d), but got (%d) !",fSector,input.GetSector()));
Int_t iRow = input.GetRow();
- if (iRow < 0 || iRow >= nRows)
- AliFatal(Form("Pad-row index (%d) outside the range (%d -> %d) !",
+ if (iRow < 0 || iRow >= nRows){
+ AliError(Form("Pad-row index (%d) outside the range (%d -> %d) !",
iRow, 0, nRows -1));
+ continue;
+ }
//pad
Int_t iPad = input.GetPad();
- if (iPad < 0 || iPad >= nPadsMax)
- AliFatal(Form("Pad index (%d) outside the range (%d -> %d) !",
+ if (iPad < 0 || iPad >= nPadsMax) {
+ AliError(Form("Pad index (%d) outside the range (%d -> %d) !",
iPad, 0, nPadsMax-1));
+ continue;
+ }
if (iPad!=lastPad){
gain = gainROC->GetValue(iRow,iPad);
lastPad = iPad;
iPad+=3;
//time
Int_t iTimeBin = input.GetTime();
- if ( iTimeBin < 0 || iTimeBin >= fParam->GetMaxTBin())
+ if ( iTimeBin < fRecoParam->GetFirstBin() || iTimeBin >= fRecoParam->GetLastBin()){
+ continue;
AliFatal(Form("Timebin index (%d) outside the range (%d -> %d) !",
iTimeBin, 0, iTimeBin -1));
+ }
iTimeBin+=3;
+
//signal
Float_t signal = input.GetSignal();
if (!calcPedestal && signal <= zeroSup) continue;
}else{
allBins[iRow][iPad*fMaxTime+iTimeBin] = signal;
}
- allBins[iRow][iPad*fMaxTime+0]=1.; // pad with signal
+ allBins[iRow][iPad*fMaxTime+0]+=1.; // pad with signal
+
+ // Temporary
+ digCounter++;
} // End of the loop over altro data
//
//
+ //
+ //
// Now loop over rows and perform pedestal subtraction
if (digCounter==0) continue;
- // if (fPedSubtraction) {
- if (calcPedestal) {
+ // if (calcPedestal) {
+ if (kTRUE) {
for (Int_t iRow = 0; iRow < nRows; iRow++) {
Int_t maxPad;
if (fSector < kNIS)
maxPad = fParam->GetNPadsUp(iRow);
for (Int_t iPad = 3; iPad < maxPad + 3; iPad++) {
+ //
+ // Temporary fix for data production - !!!! MARIAN
+ // The noise calibration should take mean and RMS - currently the Gaussian fit used
+ // In case of double peak - the pad should be rejected
+ //
+ // Line mean - if more than given digits over threshold - make a noise calculation
+ // and pedestal substration
+ if (!calcPedestal && allBins[iRow][iPad*fMaxTime+0]<50) continue;
+ //
if (allBins[iRow][iPad*fMaxTime+0] <1 ) continue; // no data
Float_t *p = &allBins[iRow][iPad*fMaxTime+3];
//Float_t pedestal = TMath::Median(fMaxTime, p);
delete [] allSigBins;
delete [] allNSigBins;
- Info("Digits2Clusters", "File %s Event\t%d\tNumber of found clusters : %d\n", fOutput->GetName(),*(rawReader->GetEventId()), nclusters);
+ if (rawReader->GetEventId() && fOutput ){
+ Info("Digits2Clusters", "File %s Event\t%d\tNumber of found clusters : %d\n", fOutput->GetName(),*(rawReader->GetEventId()), nclusters);
+ }
}
if (b[0]<minMaxCutAbs) continue; //threshold for maxima
//
if (b[-1]+b[1]+b[-fMaxTime]+b[fMaxTime]<=0) continue; // cut on isolated clusters
- // if (b[-1]+b[1]<=0) continue; // cut on isolated clusters
- //if (b[-fMaxTime]+b[fMaxTime]<=0) continue; // cut on isolated clusters
+ if (b[-1]+b[1]<=0) continue; // cut on isolated clusters
+ if (b[-fMaxTime]+b[fMaxTime]<=0) continue; // cut on isolated clusters
//
if ((b[0]+b[-1]+b[1])<minUpDownCutAbs) continue; //threshold for up down (TRF)
if ((b[0]+b[-fMaxTime]+b[fMaxTime])<minLeftRightCutAbs) continue; //threshold for left right (PRF)
if (!IsMaximum(*b,fMaxTime,b)) continue;
//
Float_t noise = noiseROC->GetValue(fRow, i/fMaxTime);
+ if (noise>fRecoParam->GetMaxNoise()) continue;
// sigma cuts
if (b[0]<minMaxCutSigma*noise) continue; //threshold form maxima
if ((b[0]+b[-1]+b[1])<minUpDownCutSigma*noise) continue; //threshold for up town TRF
rms +=histo[median+idelta]*(median+idelta)*(median+idelta);
}
}
- mean /=count10;
- mean06/=count06;
- mean09/=count09;
- rms = TMath::Sqrt(TMath::Abs(rms/count10-mean*mean));
- rms06 = TMath::Sqrt(TMath::Abs(rms06/count06-mean06*mean06));
- rms09 = TMath::Sqrt(TMath::Abs(rms09/count09-mean09*mean09));
+ if (count10) {
+ mean /=count10;
+ rms = TMath::Sqrt(TMath::Abs(rms/count10-mean*mean));
+ }
+ if (count06) {
+ mean06/=count06;
+ rms06 = TMath::Sqrt(TMath::Abs(rms06/count06-mean06*mean06));
+ }
+ if (count09) {
+ mean09/=count09;
+ rms09 = TMath::Sqrt(TMath::Abs(rms09/count09-mean09*mean09));
+ }
rmsEvent = rms09;
//
pedestalEvent = median;