#include <Riostream.h>
#include <sstream>
+#include <cstdio>
#define NFITPARAMS 4
}
+using std::endl;
+using std::cout;
+using std::istringstream;
+using std::ostringstream;
/// \cond CLASSIMP
ClassImp(AliMUONGain)
/// \endcond
// compute and store mean DAC values (like pedestals)
flatFile = Form("%s.ped",fPrefixDA.Data());
outputFile=flatFile;
- cout << "\n" << fPrefixDA.Data() << " : Flat file generated : " << flatFile.Data() << "\n";
+ cout << "\n" << fPrefixLDC.Data() << " : Flat file generated : " << flatFile.Data() << "\n";
if (!outputFile.IsNull())
{
ofstream out(outputFile.Data());
if(nInit==1)
stream<<"// "<< nEntries <<" DAC values fit: "<< fnbpf1 << " pts (1st order) " << nbpf2 << " pts (2nd order) DAC=0 excluded" << endl;
stream<<"// * nInit = " << nInit << " * f1nbp = " << fnbpf1 << " * f2nbp = " << nbpf2 << endl;
- stream<<"//" << endl;
stream<<"// RUN DAC " << endl;
stream<<"//-----------------" << endl;
//_______________________________________________________________________________
void AliMUONGain::MakeGainStore(TString shuttleFile)
{
+ Int_t status=0;
/// Store gains in ASCII files
ofstream fileout;
ofstream filcouc;
TString tempstring;
TString filename;
+ char* detail;
Double_t goodA1Min = 0.5;
Double_t goodA1Max = 2.;
// Double_t goodA2Min = -0.5E-03;
// Double_t goodA2Max = 1.E-03;
- Double_t goodA2Min = -0.5E-01; // changed 28/10/2009 (JLC) <=> no condition on a2
+ Double_t goodA2Min = -0.5E-01; // changed 28/10/2009 (JLC) <=> enlarged condition on a2
Double_t goodA2Max = 1.E-01;
// Table for uncalibrated buspatches and manus
THashList* uncalBuspatchManuTable = new THashList(1000,2);
Double_t injChargeErr[11];
for ( Int_t i=0 ; i<11 ; i++) {injCharge[i]=0.;injChargeErr[i]=1.;};
- // some print
- cout<<"\n ******** MUONTRKGAINda for Gain computing (Last Run = " << fRunNumber << ") ********\n" << endl;
- cout<<" * Date : " << fDate->AsString("l") << "\n" << endl;
- cout << " Entries = " << nEntries << " DAC values \n" << endl;
- for (Int_t i = 0; i < nEntries; ++i) {
- cout<< " Run = " << run[i]->GetFirst() << " DAC = " << run[i]->GetSecond() << endl;
- numrun[i] = run[i]->GetFirst();
- injCharge[i] = run[i]->GetSecond();
- injChargeErr[i] = 0.01*injCharge[i];
- if(injChargeErr[i] <= 1.) injChargeErr[i]=1.;
- }
- cout << "" << endl;
-
// print out in .log file
-
+ detail=Form("\n%s : ------ MUONTRKGAINda for Gain computing (Last Run = %d) ------\n",fPrefixLDC.Data(),fRunNumber); printf("%s",detail);
(*fFilcout)<<"\n\n//=================================================" << endl;
(*fFilcout)<<"// MUONTRKGAINda: Gain Computing Run = " << fRunNumber << endl;
(*fFilcout)<<"// RootDataFile = "<< fRootDataFileName.Data() << endl;
(*fFilcout)<<"//=================================================" << endl;
(*fFilcout)<<"//* Date : " << fDate->AsString("l") << "\n" << endl;
+ (*fFilcout) << " Entries = " << nEntries << " DAC values \n" << endl;
+ for (Int_t i = 0; i < nEntries; ++i) {
+ (*fFilcout) << " Run = " << run[i]->GetFirst() << " DAC = " << run[i]->GetSecond() << endl;
+ numrun[i] = run[i]->GetFirst();
+ injCharge[i] = run[i]->GetSecond();
+ injChargeErr[i] = 0.01*injCharge[i];
+ if(injChargeErr[i] <= 1.) injChargeErr[i]=1.;
+ }
+ detail=Form("%s : .... Fitting .... \n",fPrefixLDC.Data()); printf("%s",detail);
// why 2 files ? (Ch. F.) => second file contains detailed results
if(fPrintLevel>1)
{
filename=Form("%s.param",fPrefixDA.Data());
- cout << " Second fit parameter file = " << filename.Data() << "\n";
+ detail=Form("%s : Second fit parameter file = %s\n",fPrefixLDC.Data(),filename.Data()); printf("%s",detail);
+ // cout << " Second fit parameter file = " << filename.Data() << "\n";
pfilen = fopen (filename.Data(),"w");
fprintf(pfilen,"//===================================================================\n");
if(fPrintLevel>1)
{
filename=Form("%s.peak",fPrefixDA.Data());
- cout << " File containing Peak mean values = " << filename << "\n";
+ detail=Form("%s : File containing Peak mean values = %s\n",fPrefixLDC.Data(),filename.Data()); printf("%s",detail);
+ // cout << " File containing Peak mean values = " << filename << "\n";
pfilep = fopen (filename,"w");
fprintf(pfilep,"//==============================================================================================================================\n");
// plot out
- TFile* gainFile = 0x0;
TTree* tg = 0x0;
if(fPlotLevel>0)
{
fHistoFileName=Form("%s.root",fPrefixDA.Data());
- gainFile = new TFile(fHistoFileName.Data(),"RECREATE","MUON Tracking gains");
+ new TFile(fHistoFileName.Data(),"RECREATE","MUON Tracking gains");
tg = new TTree("tg","TTree avec class Manu_DiMu");
tg->Branch("bp",&busPatchId, "busPatchId/I");
Double_t xp[11], xpErr[11], yp[11], ypErr[11];
Int_t uncalcountertotal=0 ;
+ Int_t unparabolicfit=0;
while ( ( p = dynamic_cast<AliMUONVCalibParam*>(next() ) ) )
{
ped[0] = p;
+ unparabolicfit=0;
busPatchId = p->ID0();
manuId = p->ID1();
n++;
}
-
// print_peak_mean_values
if(fPrintLevel>1)
{
fprintf(pfilep," sig= %9.3f%9.3f%9.3f%9.3f%9.3f%9.3f%9.3f%9.3f%9.3f%9.3f%9.3f \n",pedSigma[0],pedSigma[1],pedSigma[2],pedSigma[3],pedSigma[4],pedSigma[5],pedSigma[6],pedSigma[7],pedSigma[8],pedSigma[9],pedSigma[10]);
}
- // makegain
-
-
+ // makegain
// Fit Method: Linear fit over gAlinbpf1 points + parabolic fit over nbpf2 points)
// nInit=1 : 1st pt DAC=0 excluded
// 1. - linear fit over gAlinbpf1 points
- Double_t par[4] = {0.,0.5,0.,ADCMax()};
+ Double_t par[4] = {0.,0.5,0.,static_cast<Double_t>(ADCMax())};
Int_t nbs = nEntries - fnInit;
if(nbs < fnbpf1)fnbpf1=nbs;
Int_t fitproceed=1;
Int_t nbpf2Dynamic=nbpf2;
+ Int_t adcLimit=4090; // when RMS < 0.5 (in other cases mean values forced to 4095, see DA_PED)
for (Int_t j = 0; j < nbs; ++j)
{
Int_t k = j + fnInit;
x[j] = pedMean[k];
if(x[j]<=0.){fitproceed=0; break;}
- if(x[j]== ADCMax())
+ // if(x[j]>= ADCMax())
+ if(x[j]>= adcLimit)
{
if(j < nbs-1){fitproceed=0; break;}
- else nbpf2Dynamic=nbpf2-1;
+ else { nbpf2Dynamic=nbpf2-1; break;}
}
xErr[j] = pedSigma[k];
y[j] = injCharge[k];
a1 = par[1];
// 2. - Translation : new origin (xLim, yLim) + parabolic fit over nbf2 points
-
- if(nbpf2Dynamic > 1)
+ //checking: if(busPatchId ==1841 && manuId==4)nbpf2Dynamic=2;
+ if(nbpf2Dynamic > 2)
{
for (Int_t j = 0; j < nbpf2Dynamic; j++)
{
prChi2P2 = TMath::Prob(chi2P2, nbpf2Dynamic-1);
a2 = par[0];
}
+ else
+ {
+ unparabolicfit++;
+ (*fFilcout) << " Warning : BP = " << busPatchId << " Manu = " << manuId << " Channel = " << channelId <<": parabolic fit not possible (nbpf2=" << nbpf2Dynamic << ") => a2=0 and linear fit OK" << std::endl;
+ if(unparabolicfit==1) std::cout << " Warning : BP = " << busPatchId << " Manu = " << manuId << ": no parabolic fit for some channels (nbpf2=" << nbpf2Dynamic << "), linear fit is OK (see .log for details)" << std::endl;
+ a2=0. ; prChi2P2=0. ;
+ }
par[0] = a0;
par[1] = a1;
char bpmanuname[256];
AliMUONErrorCounter* uncalcounter;
- sprintf(bpmanuname,"bp%dmanu%d",busPatchId,manuId);
+ snprintf(bpmanuname,256,"bp%dmanu%d",busPatchId,manuId);
if (!(uncalcounter = (AliMUONErrorCounter*)uncalBuspatchManuTable->FindObject(bpmanuname)))
{
// New buspatch_manu name
graphErr = new TGraphErrors(nEntries,pedMean,injCharge,pedSigma,injChargeErr);
- sprintf(graphName,"BusPatch_%d_Manu_%d_Ch_%d",busPatchId, manuId,channelId);
+ snprintf(graphName,256,"BusPatch_%d_Manu_%d_Ch_%d",busPatchId, manuId,channelId);
graphErr->SetTitle(graphName);
graphErr->SetMarkerColor(3);
graphErr->SetMarkerStyle(12);
graphErr->Write(graphName);
- sprintf(graphName,"f2_BusPatch_%d_Manu_%d_Ch_%d",busPatchId, manuId,channelId);
+ snprintf(graphName,256,"f2_BusPatch_%d_Manu_%d_Ch_%d",busPatchId, manuId,channelId);
f2Calib->SetTitle(graphName);
f2Calib->SetLineColor(4);
f2Calib->SetParameters(par);
delete f2Calib;
}
}
-
-
tg->Fill();
}
-
-
pfilew << WriteGainData(busPatchId,manuId,channelId,par[1],par[2],threshold,q);
}
nmanu++;
- if(nmanu % 500 == 0)std::cout << " Nb manu = " << nmanu << std::endl;
+ Int_t step=500;
+ if(nmanu % step == 0)printf("%s : Nb manu = %d\n",fPrefixLDC.Data(),nmanu);
}
// print in logfile
(*fFilcout) << " Number of bad calibrated channel = " << uncalcountertotal << endl;
}
+ if(nmanu && nGoodChannel)
+ {
+ Double_t ratio_limit=0.25;
+ Double_t ratio=float (nBadChannel)/float (nmanu*64);
+
+ detail=Form("\n%s : Nb of channels in raw data = %d (%d Manu)",fPrefixLDC.Data(),nmanu*64,nmanu);
+ (*fFilcout) << detail ; printf("%s",detail);
+ detail=Form("\n%s : Nb of calibrated channel = %d (%4.2f <a1< %4.2f and %4.2f <a2< %4.2f)",fPrefixLDC.Data(),nGoodChannel,goodA1Min,goodA1Max, goodA2Min,goodA2Max);
+ (*fFilcout) << detail ; printf("%s",detail);
+ detail=Form("\n%s : Nb of uncalibrated channel = %d [%6.4f] (%d unfitted channels) ",fPrefixLDC.Data(),nBadChannel,ratio,noFitChannel);
+ (*fFilcout) << detail ; printf("%s",detail);
+
+ if(ratio > ratio_limit) { status=-1;
+ detail=Form("\n%s : !!!!! WARNING : Nb of uncalibrated channels very large : %6.4f > %6.4f (status= %d) ",fPrefixLDC.Data(),ratio,ratio_limit,status);
+ (*fFilcout) << detail ; printf("%s",detail);
+ }
-
- (*fFilcout) << "\n Nb of channels in raw data = " << nmanu*64 << " (" << nmanu << " Manu)" << endl;
- (*fFilcout) << " Nb of calibrated channel = " << nGoodChannel << " (" << goodA1Min << "<a1<" << goodA1Max
- << " and " << goodA2Min << "<a2<" << goodA2Max << ") " << endl;
- (*fFilcout) << " Nb of uncalibrated channel = " << nBadChannel << " (" << noFitChannel << " unfitted)" << endl;
-
- cout << "\n Nb of channels in raw data = " << nmanu*64 << " (" << nmanu << " Manu)" << endl;
- cout << " Nb of calibrated channel = " << nGoodChannel << " (" << goodA1Min << "<a1<" << goodA1Max
- << " and " << goodA2Min << "<a2<" << goodA2Max << ") " << endl;
- cout << " Nb of uncalibrated channel = " << nBadChannel << " (" << noFitChannel << " unfitted)" << endl;
-
- Double_t meanA1 = sumA1/(nGoodChannel);
- Double_t meanProbChi2 = sumProbChi2/(nGoodChannel);
- Double_t meanA2 = sumA2/(nGoodChannel);
- Double_t meanProbChi2P2 = sumProbChi2P2/(nGoodChannel);
-
- Double_t capaManu = 0.2; // pF
- (*fFilcout) << "\n linear fit : <a1> = " << meanA1 << "\t <gain> = " << 1./(meanA1*capaManu)
- << " mV/fC (capa= " << capaManu << " pF)" << endl;
- (*fFilcout) << " Prob(chi2)> = " << meanProbChi2 << endl;
- (*fFilcout) << "\n parabolic fit: <a2> = " << meanA2 << endl;
- (*fFilcout) << " Prob(chi2)> = " << meanProbChi2P2 << "\n" << endl;
-
- cout << "\n <gain> = " << 1./(meanA1*capaManu)
- << " mV/fC (capa= " << capaManu << " pF)"
- << " Prob(chi2)> = " << meanProbChi2 << endl;
-
+ Double_t meanA1 = sumA1/(nGoodChannel);
+ Double_t meanProbChi2 = sumProbChi2/(nGoodChannel);
+ Double_t meanA2 = sumA2/(nGoodChannel);
+ Double_t meanProbChi2P2 = sumProbChi2P2/(nGoodChannel);
+ Double_t capaManu = 0.2; // pF
+ (*fFilcout) << "\n linear fit : <a1> = " << meanA1 << " Prob(chi2)> = " << meanProbChi2 << " <gain> = " << 1./(meanA1*capaManu)
+ << " mV/fC (capa= " << capaManu << " pF)" << endl;
+ (*fFilcout) <<" parabolic fit: <a2> = " << meanA2 << " Prob(chi2)> = " << meanProbChi2P2 << "\n" << endl;
+
+ detail=Form("\n%s : <gain> = %7.5f mV/fC (capa= %3.1f pF) Prob(chi2) = %5.3f\n" ,fPrefixLDC.Data(),1./(meanA1*capaManu),capaManu,meanProbChi2);
+ printf("%s",detail);
+ }
+ else
+ { status=-1;
+ detail=Form("\n%s : !!!!! ERROR : Nb of Manu = %d or Nb calibrated channel = %d !!!!! (status= %d)\n",fPrefixLDC.Data(),nmanu,nGoodChannel,status);
+ (*fFilcout) << detail ; printf("%s",detail);
+ }
pfilew.close();
if(fPlotLevel>0){tg->Write();histoFile->Close();}
if(fPrintLevel>1){fclose(pfilep); fclose(pfilen);}
+ SetStatusDA(status);
}
git://git.uio.no / u / mrichter / AliRoot.git / blobdiff