,fAccCDB(kFALSE)
,fMinEntries(800)
,fRebin(1)
+ ,fScaleGain(0.02431)
,fNumberFit(0)
,fNumberFitSuccess(0)
,fNumberEnt(0)
,fAccCDB(c.fAccCDB)
,fMinEntries(c.fMinEntries)
,fRebin(c.fRebin)
+,fScaleGain(c.fScaleGain)
,fNumberFit(c.fNumberFit)
,fNumberFitSuccess(c.fNumberFitSuccess)
,fNumberEnt(c.fNumberEnt)
fDebugStreamer = 0x0;
return kTRUE;
}
+//____________Functions fit Online CH2d________________________________________
+Double_t AliTRDCalibraFit::AnalyseCHAllTogether(const TH2I *ch)
+{
+ //
+ // Fit the 1D histos, projections of the 2D ch on the Xaxis, for each
+ // calibration group normalized the resulted coefficients (to 1 normally)
+ //
+ Int_t nbins = ch->GetNbinsX();// charge
+ Int_t nybins = ch->GetNbinsY();// groups number
+ // Take the histo
+ TH1I *projch = (TH1I *) ch->ProjectionX("projch",1,nybins+1,(Option_t *)"e");
+ projch->SetDirectory(0);
+ // Number of entries for this calibration group
+ Double_t nentries = 0.0;
+ Double_t mean = 0.0;
+ for (Int_t k = 0; k < nbins; k++) {
+ nentries += projch->GetBinContent(k+1);
+ mean += projch->GetBinCenter(k+1)*projch->GetBinContent(k+1);
+ projch->SetBinError(k+1,TMath::Sqrt(projch->GetBinContent(k+1)));
+ }
+ projch->SetEntries(nentries);
+ //printf("The number of entries for the group %d is %f\n",idect,nentries);
+ if (nentries > 0) {
+ mean /= nentries;
+ }
+ // This detector has not enough statistics or was off
+ if (nentries <= fMinEntries) {
+ delete projch;
+ AliInfo(Form("There are %d entries for all together, it is not enough (%d)",(Int_t) nentries, fMinEntries));
+ return -100.0;
+ }
+ //Method choosen
+ switch(fMethod)
+ {
+ case 0: FitMeanW((TH1 *) projch, nentries); break;
+ case 1: FitMean((TH1 *) projch, nentries, mean); break;
+ case 2: FitCH((TH1 *) projch, mean); break;
+ case 3: FitBisCH((TH1 *) projch, mean); break;
+ default: return -100.0;
+ }
+ delete fDebugStreamer;
+ fDebugStreamer = 0x0;
+
+ if(fCurrentCoef[0] > 0.0) return fCurrentCoef[0];
+ else return -100.0;
+
+}
//________________functions fit Online PH2d____________________________________
-Bool_t AliTRDCalibraFit::AnalysePH(const TProfile2D *ph)
+Double_t AliTRDCalibraFit::AnalysePHAllTogether(const TProfile2D *ph)
{
//
// Take the 1D profiles (average pulse height), projections of the 2D PH
// A first calibration of T0 is also made using the same method
//
- // Set the calibration mode
- //const char *name = ph->GetTitle();
- TString name = ph->GetTitle();
- if(!SetModeCalibration(name,1)) return kFALSE;
-
- //printf("Mode calibration set\n");
-
// Number of Xbins (detectors or groups of pads)
Int_t nbins = ph->GetNbinsX();// time
Int_t nybins = ph->GetNbinsY();// calibration group
- if (!InitFit(nybins,1)) {
- return kFALSE;
+
+ // Take the histo
+ TH1D *projph = (TH1D *) ph->ProjectionX("projph",1,nybins+1,(Option_t *) "e");
+ projph->SetDirectory(0);
+ // Number of entries for this calibration group
+ Double_t nentries = 0;
+ for(Int_t idect = 0; idect < nybins; idect++){
+ for (Int_t k = 0; k < nbins; k++) {
+ Int_t binnb = (nbins+2)*(idect+1)+(k+1);
+ nentries += ph->GetBinEntries(binnb);
+ }
+ }
+ //printf("AnalysePHAllTogether:: the number of entries is %f\n",nentries);
+ // This detector has not enough statistics or was off
+ if (nentries <= fMinEntries) {
+ AliInfo(Form("There are %d entries for all together, it is not enough (%d)",(Int_t) nentries, fMinEntries));
+ if (fDebugLevel != 1) {
+ delete projph;
+ }
+ return -100.0;
+ }
+ //Method choosen
+ //printf("Method\n");
+ switch(fMethod)
+ {
+ case 0: FitLagrangePoly((TH1 *) projph); break;
+ case 1: FitPente((TH1 *) projph); break;
+ case 2: FitPH((TH1 *) projph,0); break;
+ default: return -100.0;
+ }
+ // Memory!!!
+ if (fDebugLevel != 1) {
+ delete projph;
}
+ delete fDebugStreamer;
+ fDebugStreamer = 0x0;
+
+ if(fCurrentCoef[0] > 0.0) return fCurrentCoef[0];
+ else return -100.0;
+
+}
+//____________Functions fit Online PH2d________________________________________
+Bool_t AliTRDCalibraFit::AnalysePH(AliTRDCalibraVector *calvect)
+{
+ //
+ // Reconstruct the average pulse height from the vectorPH for each
+ // calibration group
+ // Reconstruct a drift velocity
+ // A first calibration of T0 is also made using the same method (slope method)
+ //
- //printf("Init fit\n");
+ // Set the calibration mode
+ //const char *name = calvect->GetNamePH();
+ TString name = calvect->GetNamePH();
+ if(!SetModeCalibration(name,1)) return kFALSE;
+ // Number of Xbins (detectors or groups of pads)
+ if (!InitFit((432*calvect->GetDetCha0(1)+108*calvect->GetDetCha2(1)),1)) {
+ return kFALSE;
+ }
if (!InitFitPH()) {
return kFALSE;
}
-
- //printf("Init fit PH\n");
-
fStatisticMean = 0.0;
fNumberFit = 0;
fNumberFitSuccess = 0;
fNumberEnt = 0;
// Init fCountDet and fCount
InitfCountDetAndfCount(1);
- //printf("Init Count Det and fCount %d, %d\n",fDect1,fDect2);
-
// Beginning of the loop
for (Int_t idect = fDect1; idect < fDect2; idect++) {
- //printf("idect = %d\n",idect);
- // Determination of fNnZ, fNnRphi, fNfragZ and fNfragRphi.......
+ // Determination of fNnZ, fNnRphi, fNfragZ and fNfragRphi...........
UpdatefCountDetAndfCount(idect,1);
ReconstructFitRowMinRowMax(idect,1);
// Take the histo
- TH1D *projph = (TH1D *) ph->ProjectionX("projph",idect+1,idect+1,(Option_t *) "e");
- projph->SetDirectory(0);
- // Number of entries for this calibration group
- Double_t nentries = 0;
- for (Int_t k = 0; k < nbins; k++) {
- Int_t binnb = (nbins+2)*(idect+1)+(k+1);
- nentries += ph->GetBinEntries(binnb);
+ fEntriesCurrent = 0;
+ if(!calvect->GetPHEntries(fCountDet)) {
+ NotEnoughStatisticPH(idect,fEntriesCurrent);
+ continue;
}
- if (nentries > 0) {
- fNumberEnt++;
- }
- //printf("The number of entries for the group %d is %f\n",idect,nentries);
+ TString tname("PH");
+ tname += idect;
+ TH1F *projph = calvect->CorrectTheError((TGraphErrors *) (calvect->ConvertVectorPHTGraphErrors(fCountDet,(idect-(fCount-(fCalibraMode->GetNfragZ(1)*fCalibraMode->GetNfragRphi(1)))),(const char *) tname)),fEntriesCurrent);
+ projph->SetDirectory(0);
+ if(fEntriesCurrent > 0) fNumberEnt++;
+ //printf("The number of entries for the group %d is %d\n",idect,fEntriesCurrent);
// This detector has not enough statistics or was off
- if (nentries <= fMinEntries) {
- //printf("Not enough statistic!\n");
- NotEnoughStatisticPH(idect,nentries);
- if (fDebugLevel != 1) {
- delete projph;
- }
+ if (fEntriesCurrent <= fMinEntries) {
+ //printf("Not enough stat!\n");
+ NotEnoughStatisticPH(idect,fEntriesCurrent);
continue;
}
- // Statistics of the histos fitted
+ // Statistic of the histos fitted
fNumberFit++;
- fStatisticMean += nentries;
+ fStatisticMean += fEntriesCurrent;
// Calcul of "real" coef
CalculVdriftCoefMean();
CalculT0CoefMean();
//Method choosen
- //printf("Method\n");
switch(fMethod)
{
case 0: FitLagrangePoly((TH1 *) projph); break;
default: return kFALSE;
}
// Fill the tree if end of a detector or only the pointer to the branch!!!
- FillInfosFitPH(idect,nentries);
- // Memory!!!
- if (fDebugLevel != 1) {
- delete projph;
- }
+ FillInfosFitPH(idect,fEntriesCurrent);
} // Boucle object
+
// Mean Statistic
if (fNumberFit > 0) {
AliInfo(Form("There are %d with at least one entries. %d fits have been proceeded (sucessfully or not...). There is a mean statistic of: %d over these fitted histograms and %d successfulled fits",fNumberEnt, fNumberFit, (Int_t) fStatisticMean/fNumberFit,fNumberFitSuccess));
fDebugStreamer = 0x0;
return kTRUE;
}
-//____________Functions fit Online PH2d________________________________________
-Bool_t AliTRDCalibraFit::AnalysePH(AliTRDCalibraVector *calvect)
+//________________functions fit Online PH2d____________________________________
+Bool_t AliTRDCalibraFit::AnalysePH(const TProfile2D *ph)
{
//
- // Reconstruct the average pulse height from the vectorPH for each
- // calibration group
+ // Take the 1D profiles (average pulse height), projections of the 2D PH
+ // on the Xaxis, for each calibration group
// Reconstruct a drift velocity
- // A first calibration of T0 is also made using the same method (slope method)
+ // A first calibration of T0 is also made using the same method
//
// Set the calibration mode
- //const char *name = calvect->GetNamePH();
- TString name = calvect->GetNamePH();
+ //const char *name = ph->GetTitle();
+ TString name = ph->GetTitle();
if(!SetModeCalibration(name,1)) return kFALSE;
+
+ //printf("Mode calibration set\n");
// Number of Xbins (detectors or groups of pads)
- if (!InitFit((432*calvect->GetDetCha0(1)+108*calvect->GetDetCha2(1)),1)) {
+ Int_t nbins = ph->GetNbinsX();// time
+ Int_t nybins = ph->GetNbinsY();// calibration group
+ if (!InitFit(nybins,1)) {
return kFALSE;
}
+
+ //printf("Init fit\n");
+
if (!InitFitPH()) {
return kFALSE;
}
+
+ //printf("Init fit PH\n");
+
fStatisticMean = 0.0;
fNumberFit = 0;
fNumberFitSuccess = 0;
fNumberEnt = 0;
// Init fCountDet and fCount
InitfCountDetAndfCount(1);
+ //printf("Init Count Det and fCount %d, %d\n",fDect1,fDect2);
+
// Beginning of the loop
for (Int_t idect = fDect1; idect < fDect2; idect++) {
- // Determination of fNnZ, fNnRphi, fNfragZ and fNfragRphi...........
+ //printf("idect = %d\n",idect);
+ // Determination of fNnZ, fNnRphi, fNfragZ and fNfragRphi.......
UpdatefCountDetAndfCount(idect,1);
ReconstructFitRowMinRowMax(idect,1);
// Take the histo
- fEntriesCurrent = 0;
- if(!calvect->GetPHEntries(fCountDet)) {
- NotEnoughStatisticPH(idect,fEntriesCurrent);
- continue;
+ TH1D *projph = (TH1D *) ph->ProjectionX("projph",idect+1,idect+1,(Option_t *) "e");
+ projph->SetDirectory(0);
+ // Number of entries for this calibration group
+ Double_t nentries = 0;
+ for (Int_t k = 0; k < nbins; k++) {
+ Int_t binnb = (nbins+2)*(idect+1)+(k+1);
+ nentries += ph->GetBinEntries(binnb);
}
- TString tname("PH");
- tname += idect;
- TH1F *projph = calvect->CorrectTheError((TGraphErrors *) (calvect->ConvertVectorPHTGraphErrors(fCountDet,(idect-(fCount-(fCalibraMode->GetNfragZ(1)*fCalibraMode->GetNfragRphi(1)))),(const char *) tname)),fEntriesCurrent);
- projph->SetDirectory(0);
- if(fEntriesCurrent > 0) fNumberEnt++;
- //printf("The number of entries for the group %d is %d\n",idect,fEntriesCurrent);
+ if (nentries > 0) {
+ fNumberEnt++;
+ }
+ //printf("The number of entries for the group %d is %f\n",idect,nentries);
// This detector has not enough statistics or was off
- if (fEntriesCurrent <= fMinEntries) {
- //printf("Not enough stat!\n");
- NotEnoughStatisticPH(idect,fEntriesCurrent);
+ if (nentries <= fMinEntries) {
+ //printf("Not enough statistic!\n");
+ NotEnoughStatisticPH(idect,nentries);
+ if (fDebugLevel != 1) {
+ delete projph;
+ }
continue;
}
- // Statistic of the histos fitted
+ // Statistics of the histos fitted
fNumberFit++;
- fStatisticMean += fEntriesCurrent;
+ fStatisticMean += nentries;
// Calcul of "real" coef
CalculVdriftCoefMean();
CalculT0CoefMean();
//Method choosen
+ //printf("Method\n");
switch(fMethod)
{
case 0: FitLagrangePoly((TH1 *) projph); break;
default: return kFALSE;
}
// Fill the tree if end of a detector or only the pointer to the branch!!!
- FillInfosFitPH(idect,fEntriesCurrent);
+ FillInfosFitPH(idect,nentries);
+ // Memory!!!
+ if (fDebugLevel != 1) {
+ delete projph;
+ }
} // Boucle object
-
// Mean Statistic
if (fNumberFit > 0) {
AliInfo(Form("There are %d with at least one entries. %d fits have been proceeded (sucessfully or not...). There is a mean statistic of: %d over these fitted histograms and %d successfulled fits",fNumberEnt, fNumberFit, (Int_t) fStatisticMean/fNumberFit,fNumberFitSuccess));
fDebugStreamer = 0x0;
return kTRUE;
+}
+//____________Functions fit Online CH2d________________________________________
+Double_t AliTRDCalibraFit::AnalyseLinearFittersAllTogether(AliTRDCalibraVdriftLinearFit *calivdli)
+{
+ //
+ // The linear method
+ //
+
+ // Add histos
+
+ TH2S *linearfitterhisto = 0x0;
+
+ for(Int_t idet = 0; idet < 540; idet++){
+
+ TH2S * u = calivdli->GetLinearFitterHistoForce(idet);
+ if(idet == 0) linearfitterhisto = u;
+ else linearfitterhisto->Add(u);
+
+ }
+
+ // Fit
+
+ Int_t entries = 0;
+ TAxis *xaxis = linearfitterhisto->GetXaxis();
+ TAxis *yaxis = linearfitterhisto->GetYaxis();
+ TLinearFitter linearfitter = TLinearFitter(2,"pol1");
+ //printf("test\n");
+ Double_t integral = linearfitterhisto->Integral();
+ //printf("Integral is %f\n",integral);
+ Bool_t securitybreaking = kFALSE;
+ if(TMath::Abs(integral-1199) < 0.00001) securitybreaking = kTRUE;
+ for(Int_t ibinx = 0; ibinx < linearfitterhisto->GetNbinsX(); ibinx++){
+ for(Int_t ibiny = 0; ibiny < linearfitterhisto->GetNbinsY(); ibiny++){
+ if(linearfitterhisto->GetBinContent(ibinx+1,ibiny+1)>0){
+ Double_t x = xaxis->GetBinCenter(ibinx+1);
+ Double_t y = yaxis->GetBinCenter(ibiny+1);
+
+ for(Int_t k = 0; k < (Int_t)linearfitterhisto->GetBinContent(ibinx+1,ibiny+1); k++){
+ if(!securitybreaking){
+ linearfitter.AddPoint(&x,y);
+ entries++;
+ }
+ else {
+ if(entries< 1198){
+ linearfitter.AddPoint(&x,y);
+ entries++;
+ }
+ }
+ }
+
+ }
+ }
+ }
+
+ //printf("AnalyseLinearFittersAllTogether::Find %d entries\n",entries);
+ //printf("Minstats %d\n",fMinEntries);
+
+ // Eval the linear fitter
+ if(entries > fMinEntries){
+ TVectorD par = TVectorD(2);
+ //printf("Fit\n");
+ if((linearfitter.EvalRobust(0.8)==0)) {
+ //printf("Take the param\n");
+ linearfitter.GetParameters(par);
+ //printf("Done\n");
+ par.Print();
+ //printf("Finish\n");
+ // Put the fCurrentCoef
+ fCurrentCoef[0] = -par[1];
+ // here the database must be the one of the reconstruction for the lorentz angle....
+ fCurrentCoef2[0] = (par[0]+fCurrentCoef[1]*fCurrentCoef2[1])/fCurrentCoef[0];
+
+ return fCurrentCoef[0];
+ }
+ else return -100.0;
+
+
+ }
+ else {
+ return -100.0;
+ }
+
+ delete linearfitterhisto;
+ delete fDebugStreamer;
+ fDebugStreamer = 0x0;
+
}
//____________Functions for seeing if the pad is really okey___________________
//_____________________________________________________________________________
for (Int_t row = 0; row < rowMax; row++) {
for (Int_t col = 0; col < colMax; col++) {
value = coef[(Int_t)(col*rowMax+row)];
- if((value < 70.0) && (rmsAll > 0.0) && (TMath::Abs(value-meanAll) > (2.5*rmsAll))) coef[(Int_t)(col*rowMax+row)] = 100.0;
+ if((value < 70.0) && (rmsAll > 0.0) && (TMath::Abs(value-meanAll) > (2.5*rmsAll))) {
+ //printf("value outlier %f\n",value);
+ coef[(Int_t)(col*rowMax+row)] = 100.0;
+ }
} // Col
} // Row
}
// Create the DetObject
AliTRDCalDet *object = new AliTRDCalDet("ChamberGainFactor","GainFactor (detector value)");
+ fScaleGain = scaleFitFactor;
Int_t loop = (Int_t) vectorFit->GetEntriesFast();
if(loop != 540) AliInfo("The Vector Fit is not complete!");
Float_t min = 100.0;
if(perdetector){
value = ((AliTRDFitInfo *) vectorFit->At(k))->GetCoef()[0];
+ //printf("Create det object %f for %d\n",value,k);
// check successful
if(value > 70.0) value = value-100.0;
//
if (fPhdt0 >= 0.0) {
fCurrentCoef2[0] = (fPhdt0 - t0Shift) / widbins;
- if (fCurrentCoef2[0] < -1.0) {
+ if (fCurrentCoef2[0] < -3.0) {
fCurrentCoef2[0] = fCurrentCoef2[1] + 100.0;
}
}
else fNumberFitSuccess++;
if (fPhdt0 >= 0.0) {
fCurrentCoef2[0] = (fPhdt0 - t0Shift) / widbins;
- if (fCurrentCoef2[0] < -1.0) {
+ //printf("Value of timeoffset %f\n",fCurrentCoef2[0]);
+ if (fCurrentCoef2[0] < -3.0) {
fCurrentCoef2[0] = fCurrentCoef2[1] + 100.0;
}
}
}
}
else {
- //printf("Put default %f\n",-TMath::Abs(fCurrentCoef[1]));
+ ////printf("Put default %f\n",-TMath::Abs(fCurrentCoef[1]));
fCurrentCoef[0] = -TMath::Abs(fCurrentCoef[1]);
if((fPhd[1] > fPhd[0]) &&
(put)) {
if (fPhdt0 >= 0.0) {
fCurrentCoef2[0] = (fPhdt0 - t0Shift) / widbins;
- if (fCurrentCoef2[0] < -1.0) {
+ if (fCurrentCoef2[0] < -3.0) {
fCurrentCoef2[0] = fCurrentCoef2[1] + 100.0;
}
}
//Provisoire
//if(fCurrentCoef[0] > 1.7) fCurrentCoef[0] = -TMath::Abs(fCurrentCoef[1]);
//if((fCurrentCoef2[0] > 2.6) || (fCurrentCoef2[0] < 2.1)) fCurrentCoef2[0] = fCurrentCoef2[1] + 100.0;
-
+ //printf("Value of timeoffset final %f\n",fCurrentCoef2[0]);
projPH->SetDirectory(0);
}
git://git.uio.no / u / mrichter / AliRoot.git / blobdiff