// variables for RTS analysis
vector<TH1FO*> compareHistogramVectorRTSSeed, compareHistogramVectorRTSSum;
+ vector<HistogramType*> compareHistogramClassVectorRTS;
// variables for cluster multiplicity
vector<TH1FO*> compareHistogramVectorClusterMultiplicity;
if (!isBatch)
gROOT->SetBatch(kFALSE);
+ // ****************************************************************
+ //
+ // ADD own anaylsis below
+ //
+ // *****************************************************************
// use only lower case when matching anaylsis types
+ // ****************************************************************
+
+ // default histogram type to be used in the anaylsis below
+ HistogramType* HistogramTypeDefaultPt = runs[runi]->histogram;
+ if (analysisType.Contains("rts")) {
+ HistogramTypeDefaultPt = runs[runi]->histogramwoRTS;
+ }
+
+ // ###################################
if (analysisType.Contains("clas")) { // classic analysis
compareHistogramClassVectorClassic.push_back(runs[runi]->histogram->normalized);
if (runi+1 == numberRuns)
compareHistogramClassVectorVector.push_back(compareHistogramClassVectorClassic);
- }
+ }
if (analysisType.Contains("clusthresh")) { // cluster charge > 2 * noise in cluster
compareHistogramClassVectorClusterThreshold.push_back(runs[runi]->histogramthreshold->normalized);
}
if (analysisType.Contains("cali")) { // calibrated analysis
- compareHistogramClassVectorCalibrated.push_back(runs[runi]->histogram->normalized->calibrated);
+ runs[runi]->plot1DHistogram( HistogramTypeDefaultPt->Veto, "GaussTail", true, false, false, HistogramTypeDefaultPt->noisethresholdborder);
+ compareHistogramClassVectorCalibrated.push_back(HistogramTypeDefaultPt->normalized->calibrated);
if (runi+1 == numberRuns)
compareHistogramClassVectorVector.push_back(compareHistogramClassVectorCalibrated);
}
TNtupleO *numpixelincl;
numpixelincl =new TNtupleO("Average charge collected", "data", "x:y:xerr:yerr");
- numpixelincl->itsHistogramType = runs[runi]->histogram;
+ numpixelincl->itsHistogramType = HistogramTypeDefaultPt;
numpixelincl->xaxisTitle = "Number of pixel in cluster";
numpixelincl->yaxisTitle = "Average charge collected [e]";
for (UInt_t sumi = 0; sumi < (*runs[runi]->histogramdynamicalthreshold->a_Sum).size(); sumi++) {
if (!(sumi%2))
- compareHistogramVectorDepletionSum.push_back((*runs[runi]->histogram->normalized->a_Sum)[sumi]);
+ compareHistogramVectorDepletionSum.push_back((*HistogramTypeDefaultPt->normalized->a_Sum)[sumi]);
numpixelincl->Fill(sumi+1,AverageCharge[sumi],0,0);
}
ntupleVectorDepltetion3.push_back(numpixelincl);
}
}
- if (analysisType.Contains("rts")) { // rts studies
+ if (analysisType.Contains("rts")) { // rts studies
+ compareHistogramClassVectorRTS.push_back(runs[runi]->histogramwoRTS->normalized);
+ if (runi+1 == numberRuns)
+ compareHistogramClassVectorVector.push_back(compareHistogramClassVectorRTS);
+
vector<HistogramType*> compareHistogramClassVectorRTS;
compareHistogramClassVectorRTS.push_back(runs[runi]->histogramwoRTS);
compareHistogramClassVectorRTS.push_back(runs[runi]->histogram);
compareHistogramVectorRTSSeed.push_back(runs[runi]->histogramwoRTS->normalized->Seed);
compareHistogramVectorRTSSum.push_back(*(runs[runi]->histogramwoRTS->normalized->Sum));
- runs[runi]->plot1DHistogram(runs[runi]->histogramwoRTS->pixeltimefiredDistrib);
+ runs[runi]->plot1DHistogram(runs[runi]->histogramwoRTS->pixeltimefiredDistrib, "gaus", false, true);
runs[runi]->plot1DHistogram(runs[runi]->histogramwoRTS->LeakageCurrentInPixelSorted);
if (runi+1 == numberRuns) {
}
if (analysisType.Contains("seedf")) { // seedfit: seed integral anaylsis
- runs[runi]->plot1DHistogram( runs[runi]->histogram->normalized->Seed, "gaus", true, false, false, runs[runi]->histogram->fixedThresholdValue);
- runs[runi]->plot1DHistogram( runs[runi]->histogramdynamicalthreshold->normalized->Seed, "gaus", true, false, false, runs[runi]->histogram->fixedThresholdValue);
+ runs[runi]->plot1DHistogram( HistogramTypeDefaultPt->normalized->Seed, "gaus", true, false, false, HistogramTypeDefaultPt->fixedThresholdValue);
+ runs[runi]->plot1DHistogram( runs[runi]->histogramdynamicalthreshold->normalized->Seed, "gaus", true, false, false, HistogramTypeDefaultPt->fixedThresholdValue);
vector<TH1FO*> compareHistogramVectorSeedFit;
- compareHistogramVectorSeedFit.push_back(runs[runi]->histogram->Seed);
+ compareHistogramVectorSeedFit.push_back(HistogramTypeDefaultPt->Seed);
compareHistogramVectorSeedFit.push_back(runs[runi]->histogramdynamicalthreshold->Seed);
CompareHistograms(&compareHistogramVectorSeedFit);
compareHistogramVectorSeedFit.clear();
- datainputIntSeed->itsHistogramType = runs[runi]->histogram->normalized;
+ datainputIntSeed->itsHistogramType = HistogramTypeDefaultPt->normalized;
datainputIntSeed->xaxisTitle = "Voltage";
datainputIntSeed->yaxisTitle = "Integral of Seed";
- datainputIntSeed->Fill(runs[runi]->labbook.depletionV,runs[runi]->histogram->integralSeed,0,runs[runi]->histogram->integralSeedErr);
+ datainputIntSeed->Fill(runs[runi]->labbook.depletionV,HistogramTypeDefaultPt->integralSeed,0,HistogramTypeDefaultPt->integralSeedErr);
if (runi+1 == numberRuns) {
ntupleVectorSeed.push_back(datainputIntSeed);
ntupleVectorVector.push_back(ntupleVectorSeed);
}
if (analysisType.Contains("sumf")) { // seedfit: seed integral anaylsis
- runs[runi]->plot1DHistogram(*(runs[runi]->histogram->normalized->Sum), "gaus", true, false, false, runs[runi]->histogram->fixedThresholdValue);
- runs[runi]->plot1DHistogram(*(runs[runi]->histogramdynamicalthreshold->normalized->Sum), "gaus", true, false, false, runs[runi]->histogram->fixedThresholdValue);
+ runs[runi]->plot1DHistogram(*(HistogramTypeDefaultPt->normalized->Sum), "gaus", true, false, false, HistogramTypeDefaultPt->fixedThresholdValue);
+ runs[runi]->plot1DHistogram(*(runs[runi]->histogramdynamicalthreshold->normalized->Sum), "gaus", true, false, false, HistogramTypeDefaultPt->fixedThresholdValue);
vector<TH1FO*> compareHistogramVectorSumFit;
- compareHistogramVectorSumFit.push_back(*(runs[runi]->histogram->Sum));
+ compareHistogramVectorSumFit.push_back(*(HistogramTypeDefaultPt->Sum));
compareHistogramVectorSumFit.push_back(*(runs[runi]->histogramdynamicalthreshold->Sum));
CompareHistograms(&compareHistogramVectorSumFit);
compareHistogramVectorSumFit.clear();
- datainputIntSum->itsHistogramType = runs[runi]->histogram->normalized;
+ datainputIntSum->itsHistogramType = HistogramTypeDefaultPt->normalized;
datainputIntSum->xaxisTitle = "Voltage";
datainputIntSum->yaxisTitle = "Integral of Sum";
- datainputIntSum->Fill(runs[runi]->labbook.depletionV,runs[runi]->histogram->integralSum,0,runs[runi]->histogram->integralSumErr);
+ datainputIntSum->Fill(runs[runi]->labbook.depletionV,HistogramTypeDefaultPt->integralSum,0,HistogramTypeDefaultPt->integralSumErr);
if (runi+1 == numberRuns) {
ntupleVectorSum.push_back(datainputIntSum);
ntupleVectorVector.push_back(ntupleVectorSeed);
if (analysisType.Contains("cluster")) { // analyze cluster formation
// show cluster multiplicity
- compareHistogramVectorClusterMultiplicity.push_back(runs[runi]->histogram->normalized->clustermultiplicity);
+ compareHistogramVectorClusterMultiplicity.push_back(HistogramTypeDefaultPt->normalized->clustermultiplicity);
// runs[runi]->plot1DHistogram( runs[runi]->histogram->clustermultiplicity);
vector<TH1FO*> compareHistogramVectorCluster;
- compareHistogramVectorCluster.push_back(runs[runi]->histogram->Sum9);
- compareHistogramVectorCluster.push_back(runs[runi]->histogram->Sum25);
+ compareHistogramVectorCluster.push_back(HistogramTypeDefaultPt->Sum9);
+ compareHistogramVectorCluster.push_back(HistogramTypeDefaultPt->Sum25);
CompareHistograms(&compareHistogramVectorCluster);
compareHistogramVectorCluster.clear();
vector<TH1FO*> compareHistogramVectorCluster2;
- compareHistogramVectorCluster2.push_back(runs[runi]->histogram->Seed);
- compareHistogramVectorCluster2.push_back(runs[runi]->histogram->a_Sum9[1]);
- compareHistogramVectorCluster2.push_back(runs[runi]->histogram->Sum9);
- compareHistogramVectorCluster2.push_back(runs[runi]->histogram->a_Sum25[1]);
- compareHistogramVectorCluster2.push_back(runs[runi]->histogram->Sum25);
+ compareHistogramVectorCluster2.push_back(HistogramTypeDefaultPt->Seed);
+ compareHistogramVectorCluster2.push_back(HistogramTypeDefaultPt->a_Sum9[1]);
+ compareHistogramVectorCluster2.push_back(HistogramTypeDefaultPt->Sum9);
+ compareHistogramVectorCluster2.push_back(HistogramTypeDefaultPt->a_Sum25[1]);
+ compareHistogramVectorCluster2.push_back(HistogramTypeDefaultPt->Sum25);
CompareHistograms(&compareHistogramVectorCluster2);
compareHistogramVectorCluster2.clear();
TNtupleO *numpixelincl2;
numpixelincl2 =new TNtupleO("Average charge collected", "data", "x:y:xerr:yerr");
- numpixelincl2->itsHistogramType = runs[runi]->histogram;
+ numpixelincl2->itsHistogramType = HistogramTypeDefaultPt;
numpixelincl2->Title = "5x5 cluster";
numpixelincl2->xaxisTitle = "Number of pixel in cluster";
numpixelincl2->yaxisTitle = "Average charge collected [ADU]";
TNtupleO *numpixelincl;
numpixelincl =new TNtupleO("Average charge collected", "data", "x:y:xerr:yerr");
- numpixelincl->itsHistogramType = runs[runi]->histogram;
+ numpixelincl->itsHistogramType = HistogramTypeDefaultPt;
numpixelincl->Title = "3x3 cluster";
numpixelincl->xaxisTitle = "Number of pixel in cluster";
numpixelincl->yaxisTitle = "Average charge collected [ADU]";
if (analysisType.Contains("leak")) { // analyze cluster formation
// Plot leakage current
- compareHistogramLeakageCurrent.push_back(runs[runi]->histogramwoRTS->LeakageCurrentDistrib);
+ compareHistogramLeakageCurrent.push_back(HistogramTypeDefaultPt->LeakageCurrentDistrib);
if (runi+1 == numberRuns) {
compareHistogramVectorVector.push_back(compareHistogramLeakageCurrent);
}
runs[runi]->plot1DHistogram(runs[runi]->histogramdynamicalthreshold->Veto, "GaussTail", true);
- runs[runi]->plot1DHistogram(runs[runi]->histogramwoRTS->LeakageCurrentInPixelSorted, "", false, true);
+ runs[runi]->plot1DHistogram(HistogramTypeDefaultPt->LeakageCurrentInPixelSorted, "", false, true);
}
runs[runi]->writeAllHistogramsToFile();
}
+
+ // DEBUGGING
+ // runs[runi]->histogramwoRTS->FindNoisethresholdborder(runs[runi]->histogramwoRTS->Veto, false, true);
+ // runs[runi]->plot1DHistogram( runs[runi]->histogramwoRTS->Veto, "GaussTail", true, false, false, runs[runi]->histogramwoRTS->noisethresholdborder);
+// runs[runi]->plot1DHistogram( runs[runi]->histogramwoRTS->a_Sum25[22], "gaus", true, false, false, runs[runi]->histogramwoRTS->noisethresholdborder);
+
//cout << runs[runi]->histogram
}
}
void Init()
{
-// FindGoodTitle();
+ // FindGoodTitle();
TTimeStamp timestamp = TTimeStamp();
savepathresults = Form("./results/%d%06d %s", (int)timestamp.GetDate(kFALSE), (int)timestamp.GetTime(kFALSE), analysisType.Data());
if (runnumber.Contains(";")) {
*analysisis = runnumber(runnumber.First(";")+1,runnumber.Length());
analysisis->ToLower();
-// cout << colorcyan << "*analysisis: " << *analysisis << endlr;
+ // cout << colorcyan << "*analysisis: " << *analysisis << endlr;
}
}
else
leg1->SetTextFont(132);
leg1->SetFillColor(0);
leg1->SetBorderSize(0);
-
+
TString canvastitle = Form("%s", ntuplepointer->GetName());
TTimeStamp* time = new TTimeStamp();
TString canvasname = Form("%s_%d",ntuplepointer->GetName(),(int)time->GetNanoSec()/100000);
owntitle->Draw("SAME");
}
canvas->Update();
- // canvas -> SaveAs( savepathresults + "/" + runcode + " " + onehistogram->GetName() + ".eps");
+ // canvas -> SaveAs( savepathresults + "/" + runcode + " " + onehistogram->GetName() + ".eps");
TImageDump *img = new TImageDump(savepathresults + folderadd + "/" + ntuplepointer->GetName() + ".png");
canvas->Paint();
img->Close();
-
+
writeNTupleVectorToFile(ntuplepvectorpointer);
return canvas;
}
fout->close();
-// for (vector<TH1FO*>::iterator curHistogram = ptCompareHistogramVector->begin(); curHistogram != ptCompareHistogramVector->end(); curHistogram++) {
-// writeHistogramToFile(curHistogram);
-// }
+ // for (vector<TH1FO*>::iterator curHistogram = ptCompareHistogramVector->begin(); curHistogram != ptCompareHistogramVector->end(); curHistogram++) {
+ // writeHistogramToFile(curHistogram);
+ // }
return 0;
}
{
FindGoodTitle(ptCompareHistogramVector);
cout << "Returned from find good title" << endlr;
-
+
gROOT->SetStyle("RadHard_NoTitle");
// legend entries
Float_t height = ptCompareHistogramVector->size() * 0.03;
-// TLegend* leg1 = new TLegend(0.3,0.89-height,0.95,0.89);//(0.6,0.7,0.89,0.89);
+ // TLegend* leg1 = new TLegend(0.3,0.89-height,0.95,0.89);//(0.6,0.7,0.89,0.89);
TLegend* leg1 = new TLegend(0.7,0.89-height,0.95,0.89);//(0.6,0.7,0.89,0.89);
leg1->SetTextSize(0.025);
leg1->SetFillStyle(1001);
leg1->Draw("SAME");
curhistogramclone->SetAxisRange(0,lastbin1*1.1,"X");
-// curhistogramclone->GetYaxis()->UnZoom();
+ // curhistogramclone->GetYaxis()->UnZoom();
curhistogramclone->GetYaxis()->SetRangeUser(1,heighestval1*1.4);
if (curhistogramclone->GetNbinsX() < 20) {
curhistogramclone->GetXaxis()->UnZoom();
curhistogramclone->GetYaxis()->UnZoom();
}
-// canvas->Update();
+ // canvas->Update();
owntitle->Clear();
owntitle->AddText(trimRunnumberAtBegin(curhistogramclone->GetName()));
}
owntitle->Draw("SAME");
-// gPad->SetLogy(1);
-// curhistogramclone->GetYaxis()->UnZoom();
+ // gPad->SetLogy(1);
+ // curhistogramclone->GetYaxis()->UnZoom();
}
canvas->Update();
-// gPad->Modified(); gPad->Update();
+ // gPad->Modified(); gPad->Update();
MSaveBigPNG(canvas, savepathresults + folderadd + "/" + canvastitle + ".png");
TImageDump *img = new TImageDump(savepathresults + folderadd + "/" + canvastitle + ".png");
curhistogramclone->SetAxisRange(0,lastbin1*1.1,"X");
curhistogramclone->SetAxisRange(0,heighestval1*1.1,"Y");
curhistogramclone->GetYaxis()->SetRangeUser(1,heighestval1*1.2);
-// gPad->SetLogy(1);
+ // gPad->SetLogy(1);
gPad->SetGrid(1);
gPad->SetGridy(1);
owntitle->Clear();
// heighestval2 = (curhistogramclone->GetMaximum()>heighestval2?curhistogramclone->GetMaximum():heighestval2);
curhistogramclone->GetYaxis()->SetRangeUser(1,heighestval2*1.2);
curhistogramclone->Draw("SAME");
-// gPad->SetLogy(1);
+ // gPad->SetLogy(1);
gPad->SetGrid(1);
gPad->SetGridy(1);
if (ptCompareHistogramVector->size() == ptCompareHistogramClassVector->size())
{
mayBeSameRun = kTRUE; // no different classes were provided, only some TH1F histograms. Classes were constructed afterwards
-// same_RunNumber = kTRUE;
+ // same_RunNumber = kTRUE;
}
-// cout << "Trying to find good title" << endlr;
-
- headerStringsVector.clear();
+ // cout << "Trying to find good title" << endlr;
+
+ headerStringsVector.clear();
legendStringsVector.clear();
if (ptCompareHistogramClassVector->size() == 0 )
headerStringsVector.push_back(((TObjString *)(humanreadablestrings->At(0)))->String());
headerStringsVector.push_back(((TObjString *)(humanreadablestrings->At(1)))->String());
headerStringsVector.push_back(title2);
-
+
} else {
if (mayBeSameRun)
firsthistogramp = ptCompareHistogramVector->at(0);
same_Clock = kFALSE;
if (curlabbook.depletionV != firstlabbook.depletionV)
same_Depletion= kFALSE;
- // if (curlabbook.system != firstlabbook.system)
- // same_System = kFALSE;
+ // if (curlabbook.system != firstlabbook.system)
+ // same_System = kFALSE;
if (curlabbook.runnumber != firstlabbook.runnumber)
same_RunNumber= kFALSE;
same_HistType = kFALSE;
}
-// // DEBUG
-// cout << colorcyan << "same_Source: " << same_Source << endlr;
-// cout << colorcyan << "same_NonIonRad: " << same_NonIonRad << endlr;
-// cout << colorcyan << "same_IonRad: " << same_IonRad << endlr;
-// cout << colorcyan << "same_ChipNum: " << same_ChipNum << endlr;
-// cout << colorcyan << "same_ChipGen: " << same_ChipGen << endlr;
-// cout << colorcyan << "same_Matrix: " << same_Matrix << endlr;
-// cout << colorcyan << "same_Temp: " << same_Temp << endlr;
-// cout << colorcyan << "same_Clock: " << same_Clock << endlr;
-// cout << colorcyan << "same_Depletion: " << same_Depletion << endlr;
-// cout << colorcyan << "same_HistType: " << same_HistType << endlr;
-// cout << colorcyan << "same_RunNumber: " << same_RunNumber << endlr;
-// cout << colorcyan << "mayBeSameRun: " << mayBeSameRun << endlr;
+ // // DEBUG
+ // cout << colorcyan << "same_Source: " << same_Source << endlr;
+ // cout << colorcyan << "same_NonIonRad: " << same_NonIonRad << endlr;
+ // cout << colorcyan << "same_IonRad: " << same_IonRad << endlr;
+ // cout << colorcyan << "same_ChipNum: " << same_ChipNum << endlr;
+ // cout << colorcyan << "same_ChipGen: " << same_ChipGen << endlr;
+ // cout << colorcyan << "same_Matrix: " << same_Matrix << endlr;
+ // cout << colorcyan << "same_Temp: " << same_Temp << endlr;
+ // cout << colorcyan << "same_Clock: " << same_Clock << endlr;
+ // cout << colorcyan << "same_Depletion: " << same_Depletion << endlr;
+ // cout << colorcyan << "same_HistType: " << same_HistType << endlr;
+ // cout << colorcyan << "same_RunNumber: " << same_RunNumber << endlr;
+ // cout << colorcyan << "mayBeSameRun: " << mayBeSameRun << endlr;
// construct header string
TString title1 = "";
if (same_Depletion && firstlabbook.depletionV >= 0)
title1.Append(Form(", U_{dep}=%.1f V", firstlabbook.depletionV));
- // cout << colorred << title1 << endlr;
+ // cout << colorred << title1 << endlr;
if (title1.Length() > 3)
title1 = title1.Remove(0,2); // remove trailing " ,"
- headerStringsVector.push_back(title1);
- // TObjArray *humanreadablestrings = trimRunnumberAtBegin(title1).Tokenize("\n");
+ headerStringsVector.push_back(title1);
+ // TObjArray *humanreadablestrings = trimRunnumberAtBegin(title1).Tokenize("\n");
TObjArray *humanreadablestrings = title1.Tokenize("\n");
headerStringsVector.push_back(((TObjString *)(humanreadablestrings->At(0)))->String());
headerStringsVector.push_back(((TObjString *)(humanreadablestrings->At(1)))->String());
if (mayBeSameRun)
curhistogramp = ptCompareHistogramVector->at(histogrami);
-// if (!same_RunNumber) { if (legendstr.Length()) legendstr.Append(", ");
-// legendstr.Append(Form("%d", curhistogramclassp->labbook->runnumber)); }
+ // if (!same_RunNumber) { if (legendstr.Length()) legendstr.Append(", ");
+ // legendstr.Append(Form("%d", curhistogramclassp->labbook->runnumber)); }
if (!same_HistType && mayBeSameRun) { if (legendstr.Length()) legendstr.Append(", ");
legendstr.Append(Form("%s", trimRunnumberAtBegin(curhistogramp->GetName()).Data())); }
- if (!same_Source) { if (legendstr.Length()) legendstr.Append(", ");
- legendstr.Append(Form("%s", curlabbook.source.Data())); }
- if (!same_ChipGen) { if (legendstr.Length()) legendstr.Append(", ");
- legendstr.Append(Form("%s", curlabbook.chipGen.Data())); }
- if (!same_ChipNum) { if (legendstr.Length()) legendstr.Append(", ");
- legendstr.Append(Form("Chip# %s", curlabbook.chip.Data())); }
- if (!same_Matrix) { if (legendstr.Length()) legendstr.Append(", ");
- legendstr.Append(Form("%s, %.0fx%.0f #mum^{2} pitch, %s", curlabbook.matrix.Data(), curpixelinfo.pitchX, curpixelinfo.pitchY, curpixelinfo.comment.Data())); }
- if (!same_Temp) { if (legendstr.Length()) legendstr.Append(", ");
- legendstr.Append(Form("T=%.0f {}^{o}C", curlabbook.tempSens)); }
- if (!same_IonRad && curlabbook.radDoseIon != 0) { if (legendstr.Length()) legendstr.Append(", ");
- legendstr.Append(Form("%.1f MRad", firstlabbook.radDoseIon)); }
- if (!same_NonIonRad && curlabbook.radDoseNonIon != 0) { if (legendstr.Length()) legendstr.Append(", ");
- legendstr.Append(Form("%.1f*10^{13} n_{eq}/cm^{2}", curlabbook.radDoseNonIon)); }
- if (!same_Clock) { if (legendstr.Length()) legendstr.Append(", ");
- legendstr.Append(Form("%.2f Mhz", curlabbook.clock)); }
- if (!same_Depletion && curlabbook.depletionV >= 0) { if (legendstr.Length()) legendstr.Append(", ");
- legendstr.Append(Form("U_{dep}=%.1f V", curlabbook.depletionV)); }
- legendStringsVector.push_back(legendstr);
-
-// cout << colorred << legendstr << endlr;
+ if (!same_Source) { if (legendstr.Length()) legendstr.Append(", ");
+ legendstr.Append(Form("%s", curlabbook.source.Data())); }
+ if (!same_ChipGen) { if (legendstr.Length()) legendstr.Append(", ");
+ legendstr.Append(Form("%s", curlabbook.chipGen.Data())); }
+ if (!same_ChipNum) { if (legendstr.Length()) legendstr.Append(", ");
+ legendstr.Append(Form("Chip# %s", curlabbook.chip.Data())); }
+ if (!same_Matrix) { if (legendstr.Length()) legendstr.Append(", ");
+ legendstr.Append(Form("%s, %.0fx%.0f #mum^{2} pitch, %s", curlabbook.matrix.Data(), curpixelinfo.pitchX, curpixelinfo.pitchY, curpixelinfo.comment.Data())); }
+ if (!same_Temp) { if (legendstr.Length()) legendstr.Append(", ");
+ legendstr.Append(Form("T=%.0f {}^{o}C", curlabbook.tempSens)); }
+ if (!same_IonRad && curlabbook.radDoseIon != 0) { if (legendstr.Length()) legendstr.Append(", ");
+ legendstr.Append(Form("%.1f MRad", firstlabbook.radDoseIon)); }
+ if (!same_NonIonRad && curlabbook.radDoseNonIon != 0) { if (legendstr.Length()) legendstr.Append(", ");
+ legendstr.Append(Form("%.1f*10^{13} n_{eq}/cm^{2}", curlabbook.radDoseNonIon)); }
+ if (!same_Clock) { if (legendstr.Length()) legendstr.Append(", ");
+ legendstr.Append(Form("%.2f Mhz", curlabbook.clock)); }
+ if (!same_Depletion && curlabbook.depletionV >= 0) { if (legendstr.Length()) legendstr.Append(", ");
+ legendstr.Append(Form("U_{dep}=%.1f V", curlabbook.depletionV)); }
+ legendStringsVector.push_back(legendstr);
+
+ // cout << colorred << legendstr << endlr;
}
} // end else ptCompareHistogramClassVector->size() == 1
-
+
// Folder name suffix
folderadd = "";
if (same_RunNumber)
if (!same_Matrix)
for (UInt_t histogrami=0; histogrami < ptCompareHistogramClassVector->size(); histogrami++)
folderadd.Append(Form(" -%s", ptCompareHistogramClassVector->at(histogrami)->labbook->matrix.Data()));
- if (same_Depletion && firstlabbook.depletionV >= 0)
- folderadd.Append(Form(" %.1fV", firstlabbook.depletionV));
- if (!same_Depletion && firstlabbook.depletionV >= 0)
- for (UInt_t histogrami=0; histogrami < ptCompareHistogramClassVector->size(); histogrami++)
- folderadd.Append(Form(" %.1fV", ptCompareHistogramClassVector->at(histogrami)->labbook->depletionV));
- if (same_Temp)
- folderadd.Append(Form(" %.0fC", firstlabbook.tempSens));
- if (same_IonRad && firstlabbook.radDoseIon != 0)
- folderadd.Append(Form("%.1fMRad", firstlabbook.radDoseIon));
- if (same_NonIonRad && firstlabbook.radDoseNonIon != 0)
- folderadd.Append(Form(" %.1fe13neq", firstlabbook.radDoseNonIon));
- if (same_Clock)
- folderadd.Append(Form(" %.2fMhz", firstlabbook.clock));
- if (!same_Clock)
- for (UInt_t histogrami=0; histogrami < ptCompareHistogramClassVector->size(); histogrami++)
- folderadd.Append(Form(" %.2fMhz", ptCompareHistogramClassVector->at(histogrami)->labbook->clock));
-
- removeForbiddenChar(&folderadd);
-
- system("mkdir \""+ savepathresults + folderadd + "/\"" + " -p");
-// cout << colorred << savepathresults << folderadd << endlr;
-
- return false;
+ if (same_Depletion && firstlabbook.depletionV >= 0)
+ folderadd.Append(Form(" %.1fV", firstlabbook.depletionV));
+ if (!same_Depletion && firstlabbook.depletionV >= 0)
+ for (UInt_t histogrami=0; histogrami < ptCompareHistogramClassVector->size(); histogrami++)
+ folderadd.Append(Form(" %.1fV", ptCompareHistogramClassVector->at(histogrami)->labbook->depletionV));
+ if (same_Temp)
+ folderadd.Append(Form(" %.0fC", firstlabbook.tempSens));
+ if (same_IonRad && firstlabbook.radDoseIon != 0)
+ folderadd.Append(Form("%.1fMRad", firstlabbook.radDoseIon));
+ if (same_NonIonRad && firstlabbook.radDoseNonIon != 0)
+ folderadd.Append(Form(" %.1fe13neq", firstlabbook.radDoseNonIon));
+ if (same_Clock)
+ folderadd.Append(Form(" %.2fMhz", firstlabbook.clock));
+ if (!same_Clock)
+ for (UInt_t histogrami=0; histogrami < ptCompareHistogramClassVector->size(); histogrami++)
+ folderadd.Append(Form(" %.2fMhz", ptCompareHistogramClassVector->at(histogrami)->labbook->clock));
+
+ removeForbiddenChar(&folderadd);
+
+ system("mkdir \""+ savepathresults + folderadd + "/\"" + " -p");
+ // cout << colorred << savepathresults << folderadd << endlr;
+
+ return false;
}
initHistogramCustom(LeakageCurrentInPixel, "Leakage current per pixel" + histogramdescription, color, style, 0, cursensorinfo->columns*cursensorinfo->rows, cursensorinfo->columns*cursensorinfo->rows, "Pixel index", "Average CDS");
initHistogramCustom(LeakageCurrentInPixelSorted, "Leakage current per pixel sorted" + histogramdescription, color, style, 0, cursensorinfo->columns*cursensorinfo->rows, cursensorinfo->columns*cursensorinfo->rows, "Pixel index", "Average CDS");
initHistogramCustom(LeakageCurrentDistrib, "Average Leakage current per pixel" + histogramdescription, color, style, 0, 20, 200, "Average CDS", "Count");
-// initHistogram(LeakageCurrentInPixelSorted, "Leakage current" + histogramdescription, color, style);
+ // initHistogram(LeakageCurrentInPixelSorted, "Leakage current" + histogramdescription, color, style);
initHistogramCustom(pixelHadGoodVeto, "Number of times pixel had good veto" + histogramdescription, color, style, 0, cursensorinfo->columns*cursensorinfo->rows, cursensorinfo->columns*cursensorinfo->rows, "Pixel index", "Counter good veto");
SeedPerc->GetXaxis()->SetRangeUser(0,50);
Noise->SetBins(cursystempar->nbinsnoise, 0, cursystempar->maxbinnoise);
NoiseEnd->SetBins(cursystempar->nbinsnoise, 0, cursystempar->maxbinnoise);
-// LeakageCurrentInPixelSorted->SetBins(cursystempar->nbinsnoise*10, 0, cursystempar->maxbinnoise*30);
+ // LeakageCurrentInPixelSorted->SetBins(cursystempar->nbinsnoise*10, 0, cursystempar->maxbinnoise*30);
if( labbook->chipGen.EqualTo("FSBB") || labbook->chipGen.EqualTo("Pipper2") || labbook->chipGen.EqualTo("Pegasus")) {
Sum = &Sum9;
histogrampointer->GetXaxis()->CenterTitle();
histogrampointer->GetYaxis()->CenterTitle();
histogrampointer->itsHistogramType = this;
-
+
histogramarraypointer->push_back(histogrampointer);
}
}
scalefactor = gain;
for(int i=0; i <= nbins; i++){
new_bins[i] = histogrampointernew->GetBinLowEdge(i)*scalefactor;
-// cout << "histogrampointernew->GetBinCenter(i): " << histogrampointernew->GetBinLowEdge(i) << " * gain " << gain << " = " << histogrampointernew->GetBinLowEdge(i)*gain << endl;
+ // cout << "histogrampointernew->GetBinCenter(i): " << histogrampointernew->GetBinLowEdge(i) << " * gain " << gain << " = " << histogrampointernew->GetBinLowEdge(i)*gain << endl;
}
histogrampointernew->SetBins(nbins, new_bins);
histogrampointernew->GetYaxis()->SetTitle(Form("Entries [1/%.1f e]",histogrampointernew->GetBinWidth(1)));
if (normalized->LeakageCurrentDistrib != 0) normalized->LeakageCurrentDistrib = (TH1FO*)LeakageCurrentDistrib->Clone();
if (normalized->LeakageCurrentInPixel != 0)normalized->LeakageCurrentInPixel = (TH1FO*)LeakageCurrentInPixel->Clone();
if (normalized->LeakageCurrentInPixelSorted != 0)normalized->LeakageCurrentInPixelSorted = (TH1FO*)LeakageCurrentInPixelSorted->Clone();
-
+
normalized->frames_found = frames_found;
normalized->posSeed = posSeed;
normalized->posSum = posSum;
}
histogrampointernew->SetBins(nbins, new_bins);
histogrampointernew->itsHistogramType = histogrampointerold->itsHistogramType;
-// histogrampointernew->GetYaxis()->SetTitle(Form("%s\b/(%d/1000000)]",histogrampointernew->GetYaxis()->GetTitle(), frames_found));
+ // histogrampointernew->GetYaxis()->SetTitle(Form("%s\b/(%d/1000000)]",histogrampointernew->GetYaxis()->GetTitle(), frames_found));
}
else if (noisethresholdborder>=0 )
noiseborder = noisethresholdborder;
-// cout << colorred << " noiseborder " << noiseborder << " : " << endlr;
+ // cout << colorred << " noiseborder " << noiseborder << " : " << endlr;
-// cout << colorred << " " << histogrampointer->GetName() << " : " << endlr;
+ // cout << colorred << " " << histogrampointer->GetName() << " : " << endlr;
if (fitFuncType.EqualTo("gaus"))
{
parameters = (Double_t *)calloc(10, sizeof(Double_t));
- histogrampointer->GetXaxis()->SetRange(histogrampointer->GetXaxis()->FindBin(noiseborder),histogrampointer->GetXaxis()->FindBin(posMaxValHist)); // look only for maxima with x greater than noiseborder, cut away noise
- // Int_t xValMax = histogrampointer->GetBinCenter(histogrampointer->GetMaximumBin());
-// cout << colorcyan << "Begin search for fit at: " << histogrampointer->GetXaxis()->FindBin(noiseborder) << endlr;
-// cout << colorcyan << "End search for fit at: " << histogrampointer->GetXaxis()->FindBin(posMaxValHist) << endlr;
+ histogrampointer->GetXaxis()->UnZoom(); // resets range
+ Int_t binPosMaxHist = histogrampointer->FindLastBinAbove(1,1);
+ Int_t binPosMaxPeak = 0;
+ TString histogramname = histogrampointer->GetName();
+ posMaxValHist = (histogrampointer->GetBinCenter(binPosMaxHist));
+ Bool_t do_loop = kTRUE;
+ Int_t loopi = 0;
+ do {
+ histogrampointer->GetXaxis()->SetRange(histogrampointer->GetXaxis()->FindBin(noiseborder*(++loopi)),histogrampointer->GetXaxis()->FindBin(posMaxValHist)); // look only for maxima with x greater than noiseborder, cut away noise
+ binPosMaxPeak = histogrampointer->GetMaximumBin();
+ // if Sum peak, than the peak must be in the right region of the whole histogram, so search for it
+ if (!histogramname.Contains("Sum") || ( binPosMaxPeak > binPosMaxHist/2) || (loopi > 3) ) {
+// cout << "Exit loop, loopi: " << loopi << " binPosMaxPeak > binPosMaxHist/2: " << binPosMaxPeak << " > " << binPosMaxHist/2 << endlr;
+ do_loop = kFALSE;
+ noiseborder = noiseborder*loopi;
+ }
+ } while ( do_loop );
+ if (histogramname.Contains("Sum")) {
+ noiseborder = (histogrampointer->GetBinCenter(binPosMaxPeak/2)); // if Sum peak is fitted, otherwise fits fails too often
+ }
+
+ if (verbose) {
+ cout << colorcyan << "maxvalhist: " << posMaxValHist << endlr;
+ cout << colorcyan << "noiseborder: " << noiseborder << endlr;
+ }
+
TF1* fitFunc = new TF1("fitFunc",fitFuncType,noiseborder,posMaxValHist);
- if (TString(histogrampointer->GetName()).Contains("Veto")) // not used any more
- {
-// if (verbose)
-// cout << "Range: " << histogrampointer->GetXaxis()->FindBin(noiseborder) << " to " << histogrampointer->GetXaxis()->FindBin(posMaxValHist) << endl;
- Float_t peak1 = histogrampointer->GetMaximumBin();
- Float_t peak2;
-// if (verbose)
-// cout << "histogrampointer->GetBinCenter(peak1) " << histogrampointer->GetBinCenter(peak1) << endl;
- if (histogrampointer->GetBinCenter(peak1)<3.3*noiseborder) // vermutlich ist veto peak nicht am höchsten
- {
-// if (verbose)
-// cout << "histogrampointer->GetBinCenter(peak1) " << histogrampointer->GetBinCenter(peak1) << " < 3 * noiseborder " << noiseborder << endl;
- Float_t avg = 0;
- for(Int_t bin=histogrampointer->GetXaxis()->FindBin(noiseborder);bin<histogrampointer->FindLastBinAbove(0);bin++)
- avg += histogrampointer->GetBinContent(bin);
- avg /= histogrampointer->FindLastBinAbove(0) - histogrampointer->GetXaxis()->FindBin(noiseborder);
- peak2 = histogrampointer->FindLastBinAbove(avg/3);
- }
- else
+ const Double_t def_amplitude=histogrampointer->GetBinContent(binPosMaxPeak);
+ const Double_t def_peakcenter=histogrampointer->GetBinCenter(binPosMaxPeak);
+ const Double_t def_gausssig=10;
+
+ if (verbose) {
+ cout << colorcyan << "def_amplitude: " << def_amplitude << endlr;
+ cout << colorcyan << "def_peakcenter: " << def_peakcenter << endlr;
+ }
+
+ fitFunc->SetLineWidth(4);
+ fitFunc->SetLineColor(kGreen);
+ // set start values for some parameters
+ fitFunc->SetParName(0,"amplitude of peak");
+ fitFunc->SetParameter(0,def_amplitude);
+ fitFunc->SetParError(0, def_amplitude*0.01);
+ fitFunc->SetParName(1,"peak centroid");
+ fitFunc->SetParameter(1,def_peakcenter);
+ fitFunc->SetParLimits(1,def_peakcenter*0.8,def_peakcenter*1.2);
+ fitFunc->SetParError(1, def_peakcenter*0.01);
+ fitFunc->SetParName(2,"Gaussian sigma");
+ fitFunc->SetParameter(2,def_gausssig);
+ fitFunc->SetParLimits(2,0.0,100.0);
+ fitFunc->SetParError(2, def_gausssig*0.01);
+
+ int fittries = 0;
+ Bool_t failed = false;
+ do {
+ failed = false;
+ fit_result_ptr = histogrampointer->Fit(fitFunc, "NMWQS", "", noiseborder, posMaxValHist);
+ if (gMinuit == nullptr) {
+ failed = true;
+ } else
{
- peak2 = peak1;
- peak1 = histogrampointer->GetXaxis()->FindBin(noiseborder);
- }
- histogrampointer->GetXaxis()->SetRange(peak1,peak2-1); // look only for maxima with x greater than noiseborder, cut away noise
- Float_t min = histogrampointer->GetMinimumBin();
- histogrampointer->GetXaxis()->SetRange(min,histogrampointer->FindLastBinAbove(0)); // look only for maxima with x greater than noiseborder, cut away noise
- // DEBUG
-// if (verbose)
-// {
-// cout << colorred << " " << histogrampointer->GetName() << " : " << endlr;
-// cout << coloryellow << "noisethresholdborder " << noisethresholdborder << endlr;
-// cout << coloryellow << "peak1 " << histogrampointer->GetXaxis()->GetBinCenter(peak1) << endlr;
-// cout << coloryellow << "peak1val " << histogrampointer->GetBinContent(peak1) << endlr;
-// cout << coloryellow << "peak2 " << histogrampointer->GetXaxis()->GetBinCenter(peak2) << endlr;
-// cout << coloryellow << "peak2val " << histogrampointer->GetBinContent(peak2) << endlr;
-// cout << coloryellow << "min " << histogrampointer->GetXaxis()->GetBinCenter( min ) << endlr;
-// cout << coloryellow << "lastbin " << histogrampointer->FindLastBinAbove(0) << endl;
-// cout << coloryellow << "posMaxValHist " << posMaxValHist << endl;
-// }
-// cout << colorred << gMinuit->fCstatu.Data() << endlr;
-// cout << colorred << gMinuit->GetStatus() << endlr;
-// cout << colorred << fitFunc->GetChisquare() << endlr;
- //histogrampointer->Fit(fitFunc, "N,Q,W", "", 70, 500);
- int fittries = 0;
- do {
-// cout << fittries << ": New range: " << histogrampointer->GetXaxis()->GetBinCenter(min+fittries*min/20) << " to " << posMaxValHist << endl;
- fit_result_ptr = histogrampointer->Fit(fitFunc, "NQWS", "", histogrampointer->GetXaxis()->GetBinCenter(min+fittries*min/20), posMaxValHist);
-// cout << colorred << gMinuit->fCstatu.Data() << endlr;
- } while (gMinuit->fCstatu.Contains("FAILED") && fittries++ < 5);
- posMax = histogrampointer->GetXaxis()->GetBinCenter(histogrampointer->GetMaximumBin()); // Methode 1
- integralPeak = histogrampointer->IntegralAndError(min+fittries*min/20, histogrampointer->GetXaxis()->FindBin(posMaxValHist), integralPeakError, "width");
-// if (verbose)
-// {
-// cout << coloryellow << "min " << histogrampointer->GetXaxis()->GetBinCenter( min ) << endlr;
-// cout << coloryellow << "posMax " << posMax << endlr;
-// }
- histogrampointer->GetXaxis()->SetRange(histogrampointer->GetXaxis()->FindBin(noiseborder),histogrampointer->GetXaxis()->FindBin(posMaxValHist)); // look only for maxima with x greater than noiseborder, cut away noise
-// TCanvas* canvas = new TCanvas("2121", "212121212", 900, 700);
- // histogrampointer->Draw();if (verbose)
- fitFunc->SetLineStyle(1); // normal for the following fits
- if (verbose)
- fitFunc->DrawCopy("same");
- } else {
- // modified the gaussian approuch to be more powerful, escpecially the
- // integral is calculated in a +- 3 sigma region.
-
- const Double_t def_amplitude=histogrampointer->GetBinContent(histogrampointer->GetMaximumBin());
- const Double_t def_peakcenter=histogrampointer->GetBinCenter(histogrampointer->GetMaximumBin());
-// cout << colorcyan << "def_amplitude: " << def_amplitude << endlr;
-// cout << colorcyan << "def_peakcenter: " << def_peakcenter << endlr;
- const Double_t def_gausssig=10;
- // set start values for some parameters
- fitFunc->SetParName(0,"amplitude of peak");
- fitFunc->SetParameter(0,def_amplitude);
- fitFunc->SetParName(1,"peak centroid");
- fitFunc->SetParameter(1,def_peakcenter);
- fitFunc->SetParLimits(1,def_peakcenter*0.8,def_peakcenter*1.2);
- fitFunc->SetParName(2,"Gaussian sigma");
- fitFunc->SetParameter(2,def_gausssig);
- fitFunc->SetParLimits(2,0.0,100.0);
- fitFunc->SetLineWidth(4);
- fitFunc->SetLineColor(kGreen);
-
- int fittries = 0;
- Bool_t failed = false;
- do {
- failed = false;
- fit_result_ptr = histogrampointer->Fit(fitFunc, "NMWQS", "", noiseborder, posMaxValHist);
- if (gMinuit == nullptr) {
+ if (gMinuit->fCstatu == "NOT POSDEF" || gMinuit->fCstatu.Contains("FAILED")) {
failed = true;
- } else
- {
- if (gMinuit->fCstatu == "NOT POSDEF" || gMinuit->fCstatu.Contains("FAILED")) {
- failed = true;
- }
- }
- if (failed)
- {
- fitFunc->SetParameter(0,def_amplitude*(1.0-0.1*++fittries));
- fitFunc->SetParameter(1,def_peakcenter);
- fitFunc->SetParameter(2,def_gausssig);
- } else fittries = 100;
- } while (fittries < 6);
-
- // get parameters
- for (Int_t pari=0; pari<3; pari++) {
- //cout << colorcyan << fitFunc->GetParameter(pari) << endlr;
- parameters[pari]=fitFunc->GetParameter(pari);
- }
- if (failed || ( parameters[2]/parameters[0] > 100 ) )
+ }
+ }
+ if (failed)
{
- fitFunc->SetParameter(0,def_amplitude);
+ fitFunc->SetParameter(0,def_amplitude*(1.0-0.1*++fittries));
fitFunc->SetParameter(1,def_peakcenter);
fitFunc->SetParameter(2,def_gausssig);
- histogrampointer->GetXaxis()->SetRange(histogrampointer->GetXaxis()->FindBin(def_peakcenter*0.7),histogrampointer->GetXaxis()->FindBin(def_peakcenter*1.3)); // look only for maxima with x greater than noiseborder, cut away noise
- fit_result_ptr = histogrampointer->Fit(fitFunc, "NMWQS", "", def_peakcenter*0.7, def_peakcenter*1.3);
- }
- if (failed)
- {
- cout << colorred << " Could not find " << histogrampointer->GetName() << " peak" << endlr;
- parameters = (Double_t *)calloc(8, sizeof(Double_t));
- return parameters;
- }
-
- // get parameters
- for (Int_t pari=0; pari<3; pari++) {
- //cout << colorcyan << fitFunc->GetParameter(pari) << endlr;
- parameters[pari]=fitFunc->GetParameter(pari);
- }
- // https://suchideas.com/articles/maths/applied/histogram-errors/#The_Sensible_Way
- // make an error estimate, in case of rare events one can use the poisson distribution
- // error bars become +- sqrt(n) for each bin, where n is the bin content.
-
- parameters[7] = parameters[1] - 2*parameters[2] ; // starting point of histogram integration
- parameters[8] = parameters[1] + 2*parameters[2] ; // end point of histogram integration
- integralPeak = histogrampointer->IntegralAndError(histogrampointer->GetXaxis()->FindBin( parameters[7] ), histogrampointer->GetXaxis()->FindBin( parameters[8]), integralPeakError, "width"); // integral value of histogram (NOT fit), normaliezed with bin size!
- posMax = fitFunc->GetMaximumX(); // Methode 2
- fitFunc->SetLineStyle(1); // normal for the following fits
-
- if (verbose)
- fitFunc->Draw("SAME");
+ } else fittries = 100;
+ } while (fittries < 6);
+
+ // get parameters
+ for (Int_t pari=0; pari<3; pari++) {
+ //cout << colorcyan << fitFunc->GetParameter(pari) << endlr;
+ parameters[pari]=fitFunc->GetParameter(pari);
+ }
+ if (failed || ( parameters[2]/parameters[0] > 100 ) )
+ {
+ fitFunc->SetParameter(0,def_amplitude);
+ fitFunc->SetParameter(1,def_peakcenter);
+ fitFunc->SetParameter(2,def_gausssig);
+ histogrampointer->GetXaxis()->SetRange(histogrampointer->GetXaxis()->FindBin(def_peakcenter*0.7),histogrampointer->GetXaxis()->FindBin(def_peakcenter*1.3)); // look only for maxima with x greater than noiseborder, cut away noise
+ fit_result_ptr = histogrampointer->Fit(fitFunc, "NMWQS", "", def_peakcenter*0.7, def_peakcenter*1.3);
+ }
+ if (failed)
+ {
+ cout << colorred << " Could not find " << histogrampointer->GetName() << " peak" << endlr;
+ parameters = (Double_t *)calloc(8, sizeof(Double_t));
+ return parameters;
}
-
+
+ // get parameters
+ for (Int_t pari=0; pari<3; pari++) {
+ //cout << colorcyan << fitFunc->GetParameter(pari) << endlr;
+ parameters[pari]=fitFunc->GetParameter(pari);
+ }
+ // https://suchideas.com/articles/maths/applied/histogram-errors/#The_Sensible_Way
+ // make an error estimate, in case of rare events one can use the poisson distribution
+ // error bars become +- sqrt(n) for each bin, where n is the bin content.
+
+ parameters[7] = parameters[1] - 2*parameters[2] ; // starting point of histogram integration
+ parameters[8] = parameters[1] + 2*parameters[2] ; // end point of histogram integration
+ integralPeak = histogrampointer->IntegralAndError(histogrampointer->GetXaxis()->FindBin( parameters[7] ), histogrampointer->GetXaxis()->FindBin( parameters[8]), integralPeakError, "width"); // integral value of histogram (NOT fit), normaliezed with bin size!
+ posMax = fitFunc->GetMaximumX(); // Methode 2
+ fitFunc->SetLineStyle(1); // normal for the following fits
+
+ if (verbose)
+ fitFunc->Draw("SAME");
+
// parameters are
// parameters[0]: amplitude of peak
parameters[9]=integralPeakError;
Float_t sigma = fitFunc->GetParameter(2);
posMax2 = fitFunc->GetMaximumX(); // Methode 2
-// if (verbose)
-// cout << coloryellow << "posMax2 " << posMax2 << endlr;
+ // if (verbose)
+ // cout << coloryellow << "posMax2 " << posMax2 << endlr;
Float_t peakposdifperc = abs(posMax-posMax2)/min(posMax,posMax2);
if (sigma > 260 || peakposdifperc>0.3)
{
-// if (verbose)
-// {
- if (sigma > 260)
- {
- cout << "Sigma suspiciously height when fitting " << histogrampointer->GetName() << " spectrum: " << sigma << endl;
- cout << colorred << " Could not find " << histogrampointer->GetName() << " peak" << endlr;
- }
- else if (peakposdifperc>0.3)
- {
- cout << "Maximum peak position and fit gaussian peak position doesn't match in " << histogrampointer->GetName() << " spectrum. Difference: " << peakposdifperc*100 <<" % " << endl;
- cout << colorred << " Could not find " << histogrampointer->GetName() << " peak" << endlr;
- }
-// }
+ // if (verbose)
+ // {
+ if (sigma > 260)
+ {
+ cout << "Sigma suspiciously height when fitting " << histogrampointer->GetName() << " spectrum: " << sigma << endl;
+ cout << colorred << " Could not find " << histogrampointer->GetName() << " peak" << endlr;
+ }
+ else if (peakposdifperc>0.3)
+ {
+ cout << "Maximum peak position and fit gaussian peak position doesn't match in " << histogrampointer->GetName() << " spectrum. Difference: " << peakposdifperc*100 <<" % " << endl;
+ cout << colorred << " Could not find " << histogrampointer->GetName() << " peak" << endlr;
+ }
+ // }
parameters[1] = -1;
return parameters;
}
else if (sigma > 40 || peakposdifperc>0.1)
{
-// if (verbose)
-// {
- if (sigma > 260)
- {
- cout << "Sigma or suspiciously height when fitting " << histogrampointer->GetName() << " spectrum: " << sigma << endl;
- cout << coloryellow << " Please check " << histogrampointer->GetName() << " peak position: " << colorreset << colorwhite << posMax << endlr;
- }
- else if (peakposdifperc>0.1)
- {
- cout << "Maximum peak position and fit gaussian peak position in " << histogrampointer->GetName() << " have difference of " << peakposdifperc*100 <<" % " << endl;
- cout << coloryellow << " Please check " << histogrampointer->GetName() << " peak position: " << colorreset << colorwhite << posMax << endlr;
- }
-// }
+ // if (verbose)
+ // {
+ if (sigma > 260)
+ {
+ cout << "Sigma or suspiciously height when fitting " << histogrampointer->GetName() << " spectrum: " << sigma << endl;
+ cout << coloryellow << " Please check " << histogrampointer->GetName() << " peak position: " << colorreset << colorwhite << posMax << endlr;
+ }
+ else if (peakposdifperc>0.1)
+ {
+ cout << "Maximum peak position and fit gaussian peak position in " << histogrampointer->GetName() << " have difference of " << peakposdifperc*100 <<" % " << endl;
+ cout << coloryellow << " Please check " << histogrampointer->GetName() << " peak position: " << colorreset << colorwhite << posMax << endlr;
+ }
+ // }
}
if (verbose) {
- cout << colorcyan << "Depletion voltage: " << labbook->depletionV << endlr;
+ cout << colorcyan << "Depletion voltage: " << labbook->depletionV << endlr;
cout << colorcyan << "Integral from bin : " << histogrampointer->FindBin(parameters[7]) << " to " << histogrampointer->GetXaxis()->FindBin(parameters[8]) << endlr;
cout << colorcyan << "Integral from val : " << parameters[7] << " to " << parameters[8] << endlr;
cout << colorcyan << "Integral value without bg: " << parameters[6] << endlr;
cout << colorcyan << "Integral error: " << parameters[9] << endlr;
- cout << colorcyan << "Gauss Sigma: " << parameters[2] << endlr;
+ cout << colorcyan << "Gauss Sigma: " << parameters[2] << endlr;
cout << colorcyan << "Number of events : " << frames_found << endlr;
(fit_result_ptr.Get())->Print("V");
-// cout << fitFunc->GetParError(0) << endlr; // retrieve the error for the parameter 0
+ // cout << fitFunc->GetParError(0) << endlr; // retrieve the error for the parameter 0
}
-// TString legendEntry = TString(Form("%s","Gaus fit"));
-// TLegend* leg = new TLegend(0.5,0.5,0.89,0.89);//(0.6,0.7,0.89,0.89);
-// // leg->SetHeader();//"Legend Title");
-// leg->SetFillStyle(0);
-// leg->AddEntry((TObject*) 0, legendEntry, "");
-// leg->SetTextSize(0.05);
+ // TString legendEntry = TString(Form("%s","Gaus fit"));
+ // TLegend* leg = new TLegend(0.5,0.5,0.89,0.89);//(0.6,0.7,0.89,0.89);
+ // // leg->SetHeader();//"Legend Title");
+ // leg->SetFillStyle(0);
+ // leg->AddEntry((TObject*) 0, legendEntry, "");
+ // leg->SetTextSize(0.05);
// leg->Draw();
-//
+ //
}
else if (fitFuncType=="landauSIMPLE")
{
if (verbose)
fitFunc->DrawCopy("same");
- } else if (fitFuncType=="landau")
+ }
+ else if (fitFuncType=="landau")
{
fitFuncType = "landau";
if (posVeto > 0)
fitFunc->SetLineStyle(1); // normal for the following fits
if (verbose)
fitFunc->DrawCopy("same");
-// posMax = fitFunc->GetParameter(1); // new method, just use MPV of fit, as noise border is well known. Compare with old method anyway and warn if something suspecious.
-// parameters[1]=fitFunc->GetMaximumX();
+ // posMax = fitFunc->GetParameter(1); // new method, just use MPV of fit, as noise border is well known. Compare with old method anyway and warn if something suspecious.
+ // parameters[1]=fitFunc->GetMaximumX();
posMax = fitFunc->GetMaximumX(); // new method, just use MPV of fit, as noise border is well known. Compare with old method anyway and warn if something suspecious.
-// cout << "fitFunc->GetParameter(0): " << fitFunc->GetParameter(0) << endl;
-// cout << "fitFunc->GetParameter(1): " << fitFunc->GetParameter(1) << endl;
-// cout << "fitFunc->GetParameter(2): " << fitFunc->GetParameter(2) << endl;
-// cout << "fitFunc->GetMaximumX(): " << fitFunc->GetMaximumX() << endl;
-// cout << colorred << "noiseborder: " << noiseborder << endlr;
+ // cout << "fitFunc->GetParameter(0): " << fitFunc->GetParameter(0) << endl;
+ // cout << "fitFunc->GetParameter(1): " << fitFunc->GetParameter(1) << endl;
+ // cout << "fitFunc->GetParameter(2): " << fitFunc->GetParameter(2) << endl;
+ // cout << "fitFunc->GetMaximumX(): " << fitFunc->GetMaximumX() << endl;
+ // cout << colorred << "noiseborder: " << noiseborder << endlr;
fitMax1 = fitFunc->GetMaximumX();
-// fitFunc->DrawCopy("same");
+ // fitFunc->DrawCopy("same");
fit_result_ptr = histogrampointer->Fit(fitFunc, "N,Q,W,S", "", noiseborder, fitMax1*1.1);
fitMax2 = fitFunc->GetMaximumX();
fitFunc->SetLineColor(kBlue);
fitFunc->SetLineStyle(2); // dashed
-// fitFunc->DrawCopy("same");
+ // fitFunc->DrawCopy("same");
fit_result_ptr = histogrampointer->Fit(fitFunc, "N,Q,W,S", "", fitMax1*0.9, posMaxValHist);
// histogrampointer->Fit(fitFunc, "N,Q,W", "", fitMax1, histogrampointer->GetBinCenter(bini));
fitMax3 = fitFunc->GetMaximumX();
//fitLandauErrorLeft.push_back(posMax - minFitMax);
//fitLandauErrorRight.push_back(maxFitMax - posMax);
- } else if (fitFuncType=="lorentz")
+ }
+ else if (fitFuncType=="lorentz")
{
// create a TF1 with the range from 0 to 3 and 6 parameters
TF1 *fitFcn = new TF1("fitFcn",lorentzianPeak,0,160,4);
parameters = (Double_t *)calloc(4, sizeof(Double_t));
for (Int_t pari=0; pari<4; pari++)
parameters[pari]=fitFcn->GetParameter(pari);
-// if (verbose)
-// {
- Printf("width: %.6f ",fitFcn->GetParameter(1));
- cout << "width: " << fitFcn->GetParameter(1) << endl;
- cout << "peak: " << fitFcn->GetParameter(2) << endl;
- cout << "y-shift:" << fitFcn->GetParameter(3) << endl;
-// }
- } else if (fitFuncType=="GaussTail") // this option is used when fitting the calibration peak
+ // if (verbose)
+ // {
+ Printf("width: %.6f ",fitFcn->GetParameter(1));
+ cout << "width: " << fitFcn->GetParameter(1) << endl;
+ cout << "peak: " << fitFcn->GetParameter(2) << endl;
+ cout << "y-shift:" << fitFcn->GetParameter(3) << endl;
+ // }
+ }
+ else if (fitFuncType=="GaussTail") // this option is used when fitting the calibration peak
{
+ parameters = (Double_t *)calloc(10, sizeof(Double_t));
// for Cadmium, the Veto spectrum is not so clean, set the noise border to higher values
// this way the other peaks which come not from the K-Alpha line will be ignored.
- if (labbook->source.Contains("Cd")) {
- noiseborder = 100;
- cout << "Set noiseborder to: " << noiseborder << endlr;
- }
-
+ // if (labbook->source.Contains("Cd")) {
+ // noiseborder = 100;
+ // cout << " Set noiseborder to: " << noiseborder << endlr;
+ // }
histogrampointer->GetXaxis()->UnZoom(); // resets range
- posMaxValHist = (histogrampointer->GetBinCenter(histogrampointer->FindLastBinAbove(1,1)));
-
+ Int_t binPosMaxHist = histogrampointer->FindLastBinAbove(1,1);
+ Int_t binPosMaxPeak = 0;
+ TString histogramname = histogrampointer->GetName();
+ posMaxValHist = (histogrampointer->GetBinCenter(binPosMaxHist));
+ Bool_t do_loop = kTRUE;
+ Int_t loopi = 0;
+ do {
+ histogrampointer->GetXaxis()->SetRange(histogrampointer->GetXaxis()->FindBin(noiseborder*++loopi),histogrampointer->GetXaxis()->FindBin(posMaxValHist)); // look only for maxima with x greater than noiseborder, cut away noise
+ binPosMaxPeak = histogrampointer->GetMaximumBin();
+ // if Sum peak, than the peak must be in the right region of the whole histogram, so search for it
+ if (( binPosMaxPeak > binPosMaxHist/2) || (loopi > 3) ) {
+ do_loop = kFALSE;
+ noiseborder = noiseborder*loopi;
+ }
+ } while ( do_loop );
if (verbose) {
cout << colorcyan << "maxvalhist: " << posMaxValHist << endlr;
cout << colorcyan << "noiseborder: " << noiseborder << endlr;
}
- histogrampointer->GetXaxis()->SetRange(histogrampointer->GetXaxis()->FindBin(noiseborder),histogrampointer->GetXaxis()->FindBin(posMaxValHist)); // look only for maxima with x greater than noiseborder, cut away noise
TF1* fitFunc = new TF1("fitFunc",GaussTail,noiseborder,posMaxValHist,6);
- parameters = (Double_t *)calloc(10, sizeof(Double_t));
- const Double_t def_amplitude=histogrampointer->GetBinContent(histogrampointer->GetMaximumBin());
- const Double_t def_peakcenter=histogrampointer->GetBinCenter(histogrampointer->GetMaximumBin());
+ const Double_t def_amplitude=histogrampointer->GetBinContent(binPosMaxPeak);
+ const Double_t def_peakcenter=histogrampointer->GetBinCenter(binPosMaxPeak);
const Double_t def_gausssig=8.68052;
const Double_t def_distgauss=20.4;
const Double_t def_bgslope=0;
const Double_t def_bgoffs=histogrampointer->GetBinContent(histogrampointer->FindBin((noiseborder+def_peakcenter)/2));
-// cout << colorcyan << "histogrampointer->FindBin((noiseborder+def_peakcenter)/2): " << histogrampointer->FindBin((noiseborder+def_peakcenter)/2) << endlr;
+ // cout << colorcyan << "histogrampointer->FindBin((noiseborder+def_peakcenter)/2): " << histogrampointer->FindBin((noiseborder+def_peakcenter)/2) << endlr;
if (verbose) {
cout << colorcyan << "def_amplitude: " << def_amplitude << endlr;
// set start values for some parameters
fitFunc->SetParName(0,"amplitude of peak");
fitFunc->SetParameter(0,def_amplitude);
+ fitFunc->SetParError(0, def_amplitude*0.01);
fitFunc->SetParName(1,"peak centroid");
fitFunc->SetParameter(1,def_peakcenter);
-// fitFunc->SetParLimits(1,def_peakcenter*0.8,def_peakcenter*1.2);
+ fitFunc->SetParError(1, def_peakcenter*0.01);
+ // fitFunc->SetParLimits(1,def_peakcenter*0.8,def_peakcenter*1.2);
fitFunc->SetParName(2,"Gaussian sigma");
fitFunc->SetParameter(2,def_gausssig);
fitFunc->SetParLimits(2,0,150);
+ fitFunc->SetParError(2, def_gausssig*0.01);
fitFunc->SetParName(3,"Distance from Gauss");
fitFunc->SetParameter(3,def_distgauss);
fitFunc->SetParLimits(3,0,def_distgauss*4);
+ fitFunc->SetParError(3, def_distgauss*0.01);
fitFunc->SetParName(4,"background slope");
fitFunc->SetParameter(4,def_bgslope);
-// fitFunc->SetParLimits(4,def_bgslope-0.1,def_bgslope+0.1);
+ fitFunc->SetParError(4, def_bgslope*0.01);
+ // fitFunc->SetParLimits(4,def_bgslope-0.1,def_bgslope+0.1);
fitFunc->SetParName(5,"background offset");
fitFunc->SetParameter(5,def_bgoffs);
fitFunc->SetParLimits(5,0,def_bgoffs*4);
+ fitFunc->SetParError(5, def_bgoffs*0.01);
// TODO: This fix disables the background
-// fitFunc->FixParameter(4,0);
-// fitFunc->FixParameter(5,0);
+ // fitFunc->FixParameter(4,0);
+ // fitFunc->FixParameter(5,0);
int fittries = 0;
Bool_t failed = false;
do {
failed = false;
fit_result_ptr = histogrampointer->Fit(fitFunc, "N,M,W,Q,S", "", noiseborder, posMaxValHist);
-// cout << colorcyan << " AFTER fit " << endlr;
+ // cout << colorcyan << " AFTER fit " << endlr;
if (gMinuit == nullptr) {
failed = true;
} else
}
else
fittries = 100;
-// cout << colorcyan << gMinuit->fCstatu.Data() << " fit tries: " << fittries << endlr;
+ // cout << colorcyan << gMinuit->fCstatu.Data() << " fit tries: " << fittries << endlr;
} while (fittries < 6);
fittries = 0;
if (failed)
fitFunc->SetParameter(3,def_distgauss);
fitFunc->SetParameter(4,def_bgslope);
fitFunc->SetParameter(5,def_bgoffs);
-
+
fit_result_ptr = histogrampointer->Fit(fitFunc, "N,M,W,Q,S", "", noiseborder, posMaxValHist);
if (gMinuit == nullptr) {
failed = true;
}
}
}
-
+
if (failed)
{
cout << colorred << " Could not find " << histogrampointer->GetName() << " calibration peak" << endlr;
parameters = (Double_t *)calloc(10, sizeof(Double_t));
return parameters;
}
-// fitFunc->FixParameter(1,parameters[1]+histogrampointer->GetBinWidth(0));
-// histogrampointer->Fit(fitFunc, "N,M,W,Q", "", noiseborder, posMaxValHist);
-
+ // fitFunc->FixParameter(1,parameters[1]+histogrampointer->GetBinWidth(0));
+ // histogrampointer->Fit(fitFunc, "N,M,W,Q", "", noiseborder, posMaxValHist);
+
// parameters are
// parameters[0]: amplitude of peak
// parameters[1]: x position of peak
parameters[7] = parameters[1] - 3*parameters[2] ; // starting point of histogram integration
parameters[8] = parameters[1] + 3*parameters[2] ; // end point of histogram integration
integralPeak = histogrampointer->IntegralAndError(histogrampointer->GetXaxis()->FindBin( parameters[7] ), histogrampointer->GetXaxis()->FindBin( parameters[8]), integralPeakError, "width"); // integral value of histogram (NOT fit),
-
+
parameters[6]=integralPeak;
parameters[9]=integralPeakError;
parameters[6] -= integralbg;
if (verbose) {
- cout << colorcyan << "Depletion voltage: " << labbook->depletionV << endlr;
+ cout << colorcyan << "Depletion voltage: " << labbook->depletionV << endlr;
cout << colorcyan << "Integral from bin : " << histogrampointer->FindBin(parameters[7]) << " to " << histogrampointer->GetXaxis()->FindBin(parameters[8]) << endlr;
cout << colorcyan << "Integral from val : " << parameters[7] << " to " << parameters[8] << endlr;
cout << colorcyan << "Integral bg: " << integralbg << endlr;
cout << colorcyan << "Integral value without bg: " << parameters[6] << endlr;
- cout << colorcyan << "Integral value with bg: " << parameters[6] + integralbg << endlr;
- cout << colorcyan << "Gauss Sigma: " << parameters[2] << endlr;
+ cout << colorcyan << "Integral value with bg: " << parameters[6] + integralbg << endlr;
+ cout << colorcyan << "Gauss Sigma: " << parameters[2] << endlr;
cout << colorcyan << "Number of events : " << frames_found << endlr;
- (fit_result_ptr.Get())->Print("V");
-
+ (fit_result_ptr.Get())->Print("V");
+
}
-
-// DEBUG
-// fitFunc->Draw("SAME");
-
+
+ // DEBUG
+ // fitFunc->Draw("SAME");
+
fitFunc->SetLineStyle(1); // normal for the following fits
if (verbose)
{
-// TCanvas* canvas = new TCanvas(histogrampointer->GetName(), histogrampointer->GetName(), 900, 700);
-// histogrampointer->Draw();
+ // TCanvas* canvas = new TCanvas(histogrampointer->GetName(), histogrampointer->GetName(), 900, 700);
+ // histogrampointer->Draw();
fitFunc->Draw("SAME");
}
}
-
-
+
+
fit_result_giveback = fit_result_ptr.Get();
-// cout << "Correct address:" << endl;
-// cout << fit_result_ptr.Get() << endl;
-//
-// fit_result_ptr_giveback = new TFitResultPtr();
-//
-// fit_result_ptr_giveback = &fit_result_ptr;
-// cout << "Gave pointer address:" << endl;
-// cout << fit_result_ptr_giveback->Get() << endl;
+ // cout << "Correct address:" << endl;
+ // cout << fit_result_ptr.Get() << endl;
+ //
+ // fit_result_ptr_giveback = new TFitResultPtr();
+ //
+ // fit_result_ptr_giveback = &fit_result_ptr;
+ // cout << "Gave pointer address:" << endl;
+ // cout << fit_result_ptr_giveback->Get() << endl;
-// TFitResult resultnew = new TFitResult(fit_result_ptr.Get());
-// cout << "saved address:" << endl;
-// cout << &resultnew << endl;
+ // TFitResult resultnew = new TFitResult(fit_result_ptr.Get());
+ // cout << "saved address:" << endl;
+ // cout << &resultnew << endl;
return parameters;
}
{
savetoclass = kTRUE;
}
-// cout << colorcyan << "Find border" << endl;
+ // cout << colorcyan << "Find border" << endl;
Float_t posMaxValHist = histogrampointer->GetXaxis()->GetXmax();
TH1FO* smoothedcurce = (TH1FO*)histogrampointer->Clone();
// smoothedcurce->Smooth(4); // not working method, rescaling is easier and more reliable
Int_t rebinningfactor = 2;
+// if (labbook->source.Contains("Cd") && labbook->chipGen.Contains("Mi19")) {
+// rebinningfactor *= 2.0;
+// }
smoothedcurce->RebinX(rebinningfactor);
smoothedcurce->SetAxisRange(0,histogrampointer->GetBinCenter(histogrampointer->GetNbinsX()));
cout << "falling at bin " << bini << ":" << smoothedcurce->GetXaxis()->GetBinCenter(bini) << " as " << curval << " < " << smoothedcurce->GetBinContent(bini) << endl; // debug
}
} while (rising < 3 && bini<smoothedcurce->GetNbinsX());
+// if (labbook->source.Contains("Cd") && thresholdbincurcandidate < 40) {
+// thresholdbincurcandidate *= 2.0;
+// }
thresholdbincurcandidate *= rebinningfactor;
Float_t temp_noisethresholdborder = histogrampointer->GetXaxis()->GetBinUpEdge(thresholdbincurcandidate);
if (verbose) {
- cout << colorcyan << "max value: " << peakval << endlr;
- cout << colorwhite << histogrampointer->GetName() << endlr;
- TString canvastitle = Form("%s border search", histogrampointer->GetName());
- TString canvasname = Form("%s border search", histogrampointer->GetName());
-// TCanvas* canvas = new TCanvas(canvasname, canvastitle, 900, 700);
-// smoothedcurce->SetLineColor(color+1);
-// smoothedcurce->Draw("SAME");
-// histogrampointer->Draw("SAME");
-// canvas->Update();
- }
+ cout << colorcyan << "max value: " << peakval << endlr;
+ cout << colorwhite << histogrampointer->GetName() << endlr;
+ TString canvastitle = Form("%s border search", histogrampointer->GetName());
+ TString canvasname = Form("%s border search", histogrampointer->GetName());
+ // TCanvas* canvas = new TCanvas(canvasname, canvastitle, 900, 700);
+ // smoothedcurce->SetLineColor(color+1);
+ // smoothedcurce->Draw("SAME");
+ // histogrampointer->Draw("SAME");
+ // canvas->Update();
+ }
Int_t bini = smoothedcurce->FindBin(startVal);
Int_t rising = 0;
Int_t bincurcandidate = bini;
}
Bool_t HistogramType::integrateSr90Spectra(TH1FO* histogrampointer, Int_t frames_found, Float_t thresholdborder, Bool_t verbose) {
-
+
Int_t thresholdbincurcandidate = 0;
if (thresholdborder < 0)
{
if (noisethresholdborder < 0) {
-// cout << "noisethresholdborder is not set, searching" << endl;
+ // cout << "noisethresholdborder is not set, searching" << endl;
FindNoisethresholdborder(histogrampointer, true, verbose);
}
thresholdbincurcandidate = histogrampointer->GetXaxis()->FindBin(noisethresholdborder);
-// cout << colorcyan << "noisethresholdborder: " << noisethresholdborder << endl;
-// cout << colorcyan << "thresholdbincurcandidate: " << thresholdbincurcandidate << endl;
+ // cout << colorcyan << "noisethresholdborder: " << noisethresholdborder << endl;
+ // cout << colorcyan << "thresholdbincurcandidate: " << thresholdbincurcandidate << endl;
}
else
{
sr90IntegralVal = histogrampointer->IntegralAndError(thresholdbincurcandidate,histogrampointer->GetNbinsX()+1, sr90IntegralErr, "width");
-// histogrampointer->Integral(min+fittries*min/20, histogrampointer->GetXaxis()->FindBin(posMaxValHist), "width");
-// for (
-// cout << "Integrate from bin " << thresholdbincurcandidate << " to " << histogrampointer->GetNbinsX() << endl;
-// sr90IntegralErr /= sr90IntegralVal/100;
-// cout << " Unscaled integral is " << Form("%e",sr90IntegralVal) << ", error " << sr90IntegralErr << "%" << endl;
+ // histogrampointer->Integral(min+fittries*min/20, histogrampointer->GetXaxis()->FindBin(posMaxValHist), "width");
+ // for (
+ // cout << "Integrate from bin " << thresholdbincurcandidate << " to " << histogrampointer->GetNbinsX() << endl;
+ // sr90IntegralErr /= sr90IntegralVal/100;
+ // cout << " Unscaled integral is " << Form("%e",sr90IntegralVal) << ", error " << sr90IntegralErr << "%" << endl;
// cout << " ";
if (verbose)
cout << " ";
cout << "Scaled ";
}
if (verbose) {
-// cout << "Integral is " << colorgreen << Form("%e",sr90IntegralVal) << colorreset << ", error " << sr90IntegralErr << "%" << endl;
+ // cout << "Integral is " << colorgreen << Form("%e",sr90IntegralVal) << colorreset << ", error " << sr90IntegralErr << "%" << endl;
cout << "Integral is " << colorgreen << Form("%e",sr90IntegralVal)<< "+-" << Form("%e",sr90IntegralErr) << endlr;
}
}
Bool_t HistogramType::calculteStoN(Bool_t verbose) {
-// cout << "posSeed: " << posSeed << endl << "avgNoise: " << avgNoise << endlr;
+ // cout << "posSeed: " << posSeed << endl << "avgNoise: " << avgNoise << endlr;
if (posSeed > 0 && avgNoise > 0) {
StoN = posSeed / avgNoise;
if (verbose)
if (labbook.storepath.Length() > 0)
{
storepathRAWLinux = labbook.storepath;
-// storepathRAWLinux = storepathRAWLinux.ReplaceAll("H:","/jspc53_H");
-// storepathRAWLinux = storepathRAWLinux.ReplaceAll("h:","/jspc53_H");
+ // storepathRAWLinux = storepathRAWLinux.ReplaceAll("H:","/jspc53_H");
+ // storepathRAWLinux = storepathRAWLinux.ReplaceAll("h:","/jspc53_H");
storepathRAWLinux = storepathRAWLinux.ReplaceAll("H:","/d/garlic");
storepathRAWLinux = storepathRAWLinux.ReplaceAll("h:","/d/garlic");
-// if (TString(hostname).EqualTo("jspc48"))
-// {
- storepathRAWLinux = storepathRAWLinux.ReplaceAll("U:","/d/garlic");
- storepathRAWLinux = storepathRAWLinux.ReplaceAll("u:","/d/garlic");
-// }
-// else
-// {
-// storepathRAWLinux = storepathRAWLinux.ReplaceAll("U:","/jspc53_U");
-// storepathRAWLinux = storepathRAWLinux.ReplaceAll("u:","/jspc53_U");
-// }
+ // if (TString(hostname).EqualTo("jspc48"))
+ // {
+ storepathRAWLinux = storepathRAWLinux.ReplaceAll("U:","/d/garlic");
+ storepathRAWLinux = storepathRAWLinux.ReplaceAll("u:","/d/garlic");
+ // }
+ // else
+ // {
+ // storepathRAWLinux = storepathRAWLinux.ReplaceAll("U:","/jspc53_U");
+ // storepathRAWLinux = storepathRAWLinux.ReplaceAll("u:","/jspc53_U");
+ // }
storepathRAWLinux = storepathRAWLinux.ReplaceAll("F:","/jspc12_F");
storepathRAWLinux = storepathRAWLinux.ReplaceAll("f:","/jspc12_F");
storepathRAWLinux = storepathRAWLinux.ReplaceAll("O:","/d/garlic");
storepathRAWLinux = storepathRAWLinux.ReplaceAll("o:","/d/garlic");
storepathRAWLinux = storepathRAWLinux.ReplaceAll("S:","/d/garlic");
storepathRAWLinux = storepathRAWLinux.ReplaceAll("s:","/d/garlic");
-// storepathRAWLinux = storepathRAWLinux.ReplaceAll("O:","/home/blinnik/garlic/local");
-// storepathRAWLinux = storepathRAWLinux.ReplaceAll("o:","/home/blinnik/garlic/local");
-// storepathRAWLinux = storepathRAWLinux.ReplaceAll("S:","/home/blinnik/garlic/local");
-// storepathRAWLinux = storepathRAWLinux.ReplaceAll("s:","/home/blinnik/garlic/local");
+ // storepathRAWLinux = storepathRAWLinux.ReplaceAll("O:","/home/blinnik/garlic/local");
+ // storepathRAWLinux = storepathRAWLinux.ReplaceAll("o:","/home/blinnik/garlic/local");
+ // storepathRAWLinux = storepathRAWLinux.ReplaceAll("S:","/home/blinnik/garlic/local");
+ // storepathRAWLinux = storepathRAWLinux.ReplaceAll("s:","/home/blinnik/garlic/local");
storepathRAWLinux = storepathRAWLinux.ReplaceAll("\\","/");
} else {
storepathRAWLinux=Form("/d/garlic/%s/%d",labbook.chipGen.Data(),runnumber); // default empty path
labbook.StoN = (rowsql->GetField(22) != NULL)?atof(rowsql->GetField(22)):-1;
labbook.comment = (rowsql->GetField(23) != NULL)?std::string(rowsql->GetField(23)):"";
labbook.depletionV = (rowsql->GetField(24) != NULL)?atof(rowsql->GetField(24)):-1;
- // labbook.frames_Analyzed = (rowsql->GetField(20) != NULL)?atoi(rowsql->GetField(20)):-1;
+ // labbook.frames_Analyzed = (rowsql->GetField(20) != NULL)?atoi(rowsql->GetField(20)):-1;
delete res;
if (labbook.chipGen.Length() > 0)
{
}
}
}
-// if (!(labbook.posVetoDB > 0) && (labbook.source != "Fe55")) // no veto peak position found for this run
- if (labbook.source != "Fe55" || labbook.chipGen == "Mi19") // no veto peak position found for this run
+ // if (!(labbook.posVetoDB > 0) && (labbook.source != "Fe55")) // no veto peak position found for this run
+ if ((labbook.source != "Fe55" && labbook.source != "Cd109")|| labbook.chipGen == "Mi19") // no veto peak position found for this run
{
cout << colorwhite << "getVetoPeakPositionFromFe55Run():" << endlr;
getVetoPeakPositionFromFe55Run();
// dynamical threshold cut
histogramdynamicalthreshold = new HistogramType(" dynamical Threshold", &cursystemparam, &cursensorinfo, humanreadablestr, &labbook, this, rootcolors[plotStyle], rootlinestyle[plotStyle]);
HistogramClassVector.push_back(histogramdynamicalthreshold);
- // fixed threshold cut
+ // fixed threshold cut
histogramfixedthreshold = new HistogramType(" fixed Threshold", &cursystemparam, &cursensorinfo, humanreadablestr, &labbook, this, rootcolors[plotStyle], rootlinestyle[plotStyle]);
HistogramClassVector.push_back(histogramfixedthreshold);
// RTS pixel removed histograms
HistogramClassVector.push_back(histogramwoRTSthreshold);
- histogramwoRTSAggresive = new HistogramType(" more RTS cleaned", &cursystemparam, &cursensorinfo, humanreadablestr, &labbook, this, rootcolors[plotStyle], rootlinestyle[plotStyle]);
- histogramwoRTSAggresive->maskRTSpixel = true;
- histogramwoRTSAggresive->RTSthreshold = 4;
- HistogramClassVector.push_back(histogramwoRTSAggresive);
+ histogramwoRTSAggresive = new HistogramType(" more RTS cleaned", &cursystemparam, &cursensorinfo, humanreadablestr, &labbook, this, rootcolors[plotStyle], rootlinestyle[plotStyle]);
+ histogramwoRTSAggresive->maskRTSpixel = true;
+ histogramwoRTSAggresive->RTSthreshold = 4;
+ HistogramClassVector.push_back(histogramwoRTSAggresive);
// histogramwoRTSAggresivethreshold = new HistogramType(" Threshold, more RTS cleaned", &cursystemparam, &cursensorinfo, humanreadablestr, &labbook, this, rootcolors[plotStyle], rootlinestyle[plotStyle] );
-// histogramwoRTSAggresivethreshold->maskRTSpixel = true;
-// histogramwoRTSAggresivethreshold->RTSthreshold = 1.0;
-// HistogramClassVector.push_back(histogramwoRTSAggresivethreshold);
+ // histogramwoRTSAggresivethreshold->maskRTSpixel = true;
+ // histogramwoRTSAggresivethreshold->RTSthreshold = 1.0;
+ // HistogramClassVector.push_back(histogramwoRTSAggresivethreshold);
// histogram with pixel, which have a good veto spectrum
// histogramGoodVeto = new HistogramType(" good Veto", &cursystemparam, &cursensorinfo, humanreadablestr, &labbook, this, rootcolors[plotStyle], rootlinestyle[plotStyle] );
-// HistogramClassVector.push_back(histogramGoodVeto);
+ // HistogramClassVector.push_back(histogramGoodVeto);
debugDBreadout();
}
void Run::setSystemSpecificParameters()
{
-// systemparam systemparamUSB (2800/*maxbin*/,2800/4/*nbins*/, 25/*vetothreshold*/, 10/*maxbinnoise*/, 100/*nbinsnoise*/); // TODO: uncomment and add again old binning
+ // systemparam systemparamUSB (2800/*maxbin*/,2800/4/*nbins*/, 25/*vetothreshold*/, 10/*maxbinnoise*/, 100/*nbinsnoise*/); // TODO: uncomment and add again old binning
systemparam systemparamUSB (1400/*maxbin*/,1400/2/*nbins*/, 25/*vetothreshold*/, 10/*maxbinnoise*/, 100/*nbinsnoise*/);
systemparam systemparamPegasus (2800,2800/2,20,10,100);
systemparam systemparamPXI (800*16,800,75,150,150);
Bool_t Run::fillTTreeWithMoreThenInitialNoiseValues(Bool_t var)
{
- cout<<" Time noise analysis : " << colorwhite << (var?"1":"0") << colorreset << " <-- only used if RAW files are analyzed, force analysis to make sure" << endl;
+ cout<<" Time noise analysis : " << colorwhite << (var?"1":"0") << colorreset << " <-- only used if RAW files are analyzed, force analysis to make sure" << endl;
processed->RefillNoiseBranch = var;
return 0;
}
Bool_t Run::setFixedThresholdValueADU(HistogramType* HistogramTypepointer, Float_t thresholdValue)
{
cout<<" Fixed threshold value : " << colorwhite << thresholdValue << " ADU" << colorreset << endl;
-// processed->fFixedThresholdValueInADU = thresholdValue;
+ // processed->fFixedThresholdValueInADU = thresholdValue;
HistogramTypepointer->fixedThresholdValue = thresholdValue;
return 0;
}
processed->InitialDynNoise();
int start = 0;
int nframes = processed->GetNumberFrames();
-// for(int i=0; i<1000;i++) // TODO remove 100000 run 342272
+ // for(int i=0; i<1000;i++) // TODO remove 100000 run 342272
for(int i=0; i<nframes;i++) // TODO remove 100000 run 342272
{
-// cout << "getframe " << i << endl;
+ // cout << "getframe " << i << endl;
processed->getFrame(i);
if (commonModeFilter)
processed->filterCommonMode();
-// cout << "hitana " << i << endl;
+ // cout << "hitana " << i << endl;
processed->hitana();
-// cout << "regetDynNoise " << endl;
+ // cout << "regetDynNoise " << endl;
if (dynamicalNoise)
processed->regetDynNoise();
progress = (Int_t)(((i-start)*100)/(nframes-1)*10);
if (progress!=progress_tmp) { print_progress( (((i-start)*100.)/(nframes-1)) ); progress_tmp=progress;}
}
-// cout << processed->plus << " vs. " << processed->minus << " : " << (processed->plus*1.0)/processed->minus<< endl;
-
+ // cout << processed->plus << " vs. " << processed->minus << " : " << (processed->plus*1.0)/processed->minus<< endl;
+
// print a dummy file to indicate, that a root file was created once
if (!processed->used_default_config)
{
}
if (processed->initOldRootFile()) return 1;
frames_found = processed->GetNumberFrames();
-// cout << colorwhite << "plotPixSignal():"<< flush << endlr;
-// processed->plotPixSignal(0,10000000,351);
-
+ // cout << colorwhite << "plotPixSignal():"<< flush << endlr;
+ // processed->plotPixSignal(0,10000000,351);
+
// do preperations before binning seed sum and veto
cout << "---------- 1. loop over all classes --------" << endl;
for (vector<HistogramType*>::iterator curHistogramClass = HistogramClassVector.begin(); curHistogramClass != HistogramClassVector.end(); curHistogramClass++) {
cout << "Processing histograms in class: <" << colorwhite << (*curHistogramClass)->histogramdescription << colorreset << " >" << endlr;
if ((*curHistogramClass)->maskRTSpixel) {
-// if (labbook.chipGen=="Mi19") {
- cout << colorwhite << " FindRTSPixelToMask():" << endlr;
- FindRTSPixelToMask(*curHistogramClass);
-// }
+ // if (labbook.chipGen=="Mi19") {
+ cout << colorwhite << " FindRTSPixelToMask():" << endlr;
+ FindRTSPixelToMask(*curHistogramClass);
+ // }
}
}
cout << "--------------------------------------------" << endl;
binF0();
cout << colorwhite << "binSeedSumVeto():" << endlr;
binSeedSumVeto();
-// cout << colorwhite << "binCluster():" << endlr;
-// binCluster();
+ // cout << colorwhite << "binCluster():" << endlr;
+ // binCluster();
cout << "---------- 2. loop over all classes --------" << endl;
+ HistogramType* curHistogramClassPt;
for (vector<HistogramType*>::iterator curHistogramClass = HistogramClassVector.begin(); curHistogramClass != HistogramClassVector.end(); curHistogramClass++) {
- cout << "Processing histograms in class: <" << colorwhite << (*curHistogramClass)->histogramdescription << colorreset << " >" << endlr;
- binNoise((*curHistogramClass));
- binLeakageCurrent((*curHistogramClass));
+ curHistogramClassPt = (*curHistogramClass);
+ cout << "Processing histograms in class: <" << colorwhite << curHistogramClassPt->histogramdescription << colorreset << " >" << endlr;
+ binNoise(curHistogramClassPt);
+ binLeakageCurrent(curHistogramClassPt);
if (noisethresholdborderADU > -1)
- (*curHistogramClass)->noisethresholdborder = noisethresholdborderADU;
+ curHistogramClassPt->noisethresholdborder = noisethresholdborderADU;
if (noisethresholdborderE > -1) {
if (labbook.gainDB > 0) {
- (*curHistogramClass)->noisethresholdborder = noisethresholdborderE / labbook.gainDB;
- cout << colorcyan << "Set noisethresholdborder to : " << (*curHistogramClass)->noisethresholdborder << " (" << noisethresholdborderE << " e)" << endlr;
+ curHistogramClassPt->noisethresholdborder = noisethresholdborderE / labbook.gainDB;
+ cout << colorcyan << "Set noisethresholdborder to : " << curHistogramClassPt->noisethresholdborder << " (" << noisethresholdborderE << " e)" << endlr;
} else {
cout << colorred << "Could not set noise threshold border in units of electrons to " << noisethresholdborderE << "e, no calibration done yet. Please rerun after first analysis." <<endlr;
}
}
if (labbook.source.Contains("Fe")||labbook.source.Contains("Cd")) {
- cout << colorwhite << " calculateCCE():" << endlr;
- (*curHistogramClass)->calculteCCE(false);
+ // cout << colorwhite << " calculateCCE():" << endlr;
+ curHistogramClassPt->calculteCCE(false);
}
if (labbook.source.Contains("Sr90")) {
//cout << colorwhite << " integrateSr90Spectra():" << endlr;
- (*curHistogramClass)->integrateSr90Spectra((*curHistogramClass)->Seed, frames_found, -1, false);
- (*curHistogramClass)->integrateSr90Spectras(frames_found, 58, false);
- cout << colorwhite << " calculteStoN():" << endlr;
- (*curHistogramClass)->calculteStoN(true);
- }
+ curHistogramClassPt->integrateSr90Spectra(curHistogramClassPt->Seed, frames_found, -1, false);
+ curHistogramClassPt->integrateSr90Spectras(frames_found, 58, false);
+ // cout << colorwhite << " calculteStoN():" << endlr;
+ curHistogramClassPt->calculteStoN(true);
+ }
+ // cout << colorwhite << "normalizeHistogramClasses():" << endlr;
+ normalizeHistogramClasses(curHistogramClassPt);
+ // cout << colorwhite << "rescaleHistogramClasses():" << endlr;
+ rescaleHistogramClasses(curHistogramClassPt);
}
cout << "--------------------------------------------" << endl;
if (labbook.source.Contains("Sr90")) {
histogramdynamicalthreshold->integrateSr90Spectras(frames_found, -1, false);
}
}
- cout << colorwhite << "normalizeHistogramClasses():" << endlr;
- normalizeHistogramClasses();
- cout << colorwhite << "rescaleHistogramClasses():" << endlr;
- rescaleHistogramClasses();
cout << colorwhite << "updateDatabase():" << endlr;
updateDatabase();
-// cout << colorwhite << "delete MAPS class:" << endlr;
+ // cout << colorwhite << "delete MAPS class:" << endlr;
//delete processed;
return 0;
}
for(Int_t hiti=0; (unsigned int)hiti<processed->fFrameInfo.hits;hiti++) { // loop over hits in a frame
pixelnumber = processed->fFrameInfo.pixel[hiti];
binnumber = HistogramTypepointer->pixeltimefired->Fill(pixelnumber);
-// cout << "binnumber: " << binnumber; // Pixel #10 will be saved in bin number 11 (!)
-// cout << colorcyan << " Pixel " << pixelnumber << " fired in frame " << framei << " hiti " << hiti << endlr;
+ // cout << "binnumber: " << binnumber; // Pixel #10 will be saved in bin number 11 (!)
+ // cout << colorcyan << " Pixel " << pixelnumber << " fired in frame " << framei << " hiti " << hiti << endlr;
}
}
HistogramTypepointer->pixeltimefiredDistrib->Fill(HistogramTypepointer->pixeltimefired->GetBinContent(pixeli));
meanpixeltimesfired += HistogramTypepointer->pixeltimefired->GetBinContent(pixeli);
numberofactivepixel++;
-// HistogramTypepointer->pixeltimefiredsorted->Fill(2000);
+ // HistogramTypepointer->pixeltimefiredsorted->Fill(2000);
}
}
meanpixeltimesfired /= numberofactivepixel; // Very rough estimate of a mean firing time
meanpixeltimesfired = meanpixeltimesfired2;
}
- // Estimate new standard deviation
+ // Estimate new standard deviation
RTSpixel =false;
numberofconsideredpixel=0;
poscounter = 0;
// cout << colorcyan << "Mean value own: " << meanpixeltimesfired << endlr;
}
-// for (Int_t pixeli=0; pixeli < HistogramTypepointer->pixeltimefired->GetNbinsX(); pixeli++) {
-// cout << colorcyan << HistogramTypepointer->pixeltimefired->GetBinContent(pixeli)<< endlr;
-// }
- //if (processed->fFrameInfo.pixel[hiti] == histogramwoRTS->RTSpixel[RTSpixeli])
-
-
+ // for (Int_t pixeli=0; pixeli < HistogramTypepointer->pixeltimefired->GetNbinsX(); pixeli++) {
+ // cout << colorcyan << HistogramTypepointer->pixeltimefired->GetBinContent(pixeli)<< endlr;
+ // }
+ //if (processed->fFrameInfo.pixel[hiti] == histogramwoRTS->RTSpixel[RTSpixeli])
+
+
HistogramTypepointer->percentageofRTSpixel = (HistogramTypepointer->RTSpixel.size()*1.0)/(numberofactivepixel*1.0)*100.0;
- cout << " cutted away evertyhing with more then " << std::right<< Form("%.1f",HistogramTypepointer->RTSthreshold * stdeviation+meanpixeltimesfired2) << " hits" << endlr;
+ cout << " cutted away evertyhing with more then " << std::right<< Form("%.1f",HistogramTypepointer->RTSthreshold * stdeviation+meanpixeltimesfired2) << " hits" << endlr;
if (HistogramTypepointer->percentageofRTSpixel > 0.1)
cout << coloryellow << "Pixel with RTS noise: " << std::right<< HistogramTypepointer->RTSpixel.size() << " out of " << numberofactivepixel << std::cout.width(10) << " (" << HistogramTypepointer->percentageofRTSpixel << " %)" << endlr;
else
- cout << " Pixel with RTS noise: " << std::right<< HistogramTypepointer->RTSpixel.size() << " out of " << numberofactivepixel << std::cout.width(10) << " (" << HistogramTypepointer->percentageofRTSpixel << " %)" << endlr;
+ cout << " Pixel with RTS noise: " << std::right<< HistogramTypepointer->RTSpixel.size() << " out of " << numberofactivepixel << std::cout.width(10) << " (" << HistogramTypepointer->percentageofRTSpixel << " %)" << endlr;
if ((RTSpixelHits/totalHits * 100.0) > 5)
- cout << coloryellow << " Account for: " << std::right<< RTSpixelHits << " out of " << totalHits << " (" << (RTSpixelHits/totalHits * 100.0) << " %) of Hits" << endlr;
+ cout << coloryellow << " Account for: " << std::right<< RTSpixelHits << " out of " << totalHits << " (" << (RTSpixelHits/totalHits * 100.0) << " %) of Hits" << endlr;
else
- cout << " Account for: " << std::right<< RTSpixelHits << " out of " << totalHits << " (" << (RTSpixelHits/totalHits * 100.0) << " %) of Hits" << endlr;
-// HistogramTypepointer->pixeltimefired->Draw();
+ cout << " Account for: " << std::right<< RTSpixelHits << " out of " << totalHits << " (" << (RTSpixelHits/totalHits * 100.0) << " %) of Hits" << endlr;
+ // HistogramTypepointer->pixeltimefired->Draw();
return 0;
}
return 0;
}
-Bool_t Run::rescaleHistogramClasses()
+Bool_t Run::rescaleHistogramClasses(HistogramType* curHistogramClassPt)
{
float_t vetopeakposition = -1;
- if ( histogramdynamicalthreshold->posVeto > 0 )
+ Float_t gain;
+
+ if ( curHistogramClassPt->posVeto > 0 )
{
- vetopeakposition = histogramdynamicalthreshold->posVeto;
- cout << " Use calibration obtained from this run, position veto: " << vetopeakposition << endlr;
+ vetopeakposition = curHistogramClassPt->posVeto;
+ cout << " Use calibration obtained from this run, position veto: " << vetopeakposition << endlr;
}
else if ( labbook.posVetoDB > 0 )
{
vetopeakposition = labbook.posVetoDB;
- cout << " Use calibration obtained from database value of this run, position veto: " << vetopeakposition << endlr;
+ cout << " Use calibration obtained from database value of this run, position veto: " << vetopeakposition << endlr;
}
else if ( Fe55run.posVeto > 0 )
{
vetopeakposition = Fe55run.posVeto;
- cout << " Use calibration obtained from Fe55 run in database, position veto: " << vetopeakposition << endlr;
- cout << " Run number: " << Fe55run.posVetorunnumber << endl;
- cout << " Temperature: " << Fe55run.temperature << endl;
+ cout << " Use calibration obtained from Fe55 run in database, position veto: " << vetopeakposition << endlr;
+ cout << " Run number: " << Fe55run.posVetorunnumber << endl;
+ cout << " Temperature: " << Fe55run.temperature << endl;
}
else
{
- cout << coloryellow << "Cannot rescale run from [ADU] to [e] units, no calibration peak found." << endlr;
+ cout << coloryellow << " Cannot rescale run from [ADU] to [e] units, no calibration peak found." << endlr;
return 0;
}
- Float_t gain = 1;
+ gain = 1;
if (labbook.source.Contains("Fe"))
gain = 1640.0/vetopeakposition;
else if (labbook.source.Contains("Cd"))
- gain = 6140.0/vetopeakposition;
- for (vector<HistogramType*>::iterator curHistogramClass = HistogramClassVector.begin(); curHistogramClass != HistogramClassVector.end(); curHistogramClass++) {
- (*curHistogramClass)->calibrateHistograms(gain);
- (*curHistogramClass)->normalized->calibrateHistograms(gain);
- }
+ gain = 6140.0/vetopeakposition;
+ curHistogramClassPt->calibrateHistograms(gain);
+ curHistogramClassPt->normalized->calibrateHistograms(gain);
+
return 1;
}
-Bool_t Run::normalizeHistogramClasses()
+Bool_t Run::normalizeHistogramClasses(HistogramType* curHistogramClassPt)
{
- cout << " For normalization use: " << frames_found << " frames" << endl;
- for (vector<HistogramType*>::iterator curHistogramClass = HistogramClassVector.begin(); curHistogramClass != HistogramClassVector.end(); curHistogramClass++) {
- (*curHistogramClass)->normalizeHistograms(frames_found);
- }
+ if (curHistogramClassPt->histogramdescription.EqualTo("")) {
+ cout << " For normalization use: " << frames_found << " frames" << endl; }
+ curHistogramClassPt->normalizeHistograms(frames_found);
return 1;
}
if (dynamicalNoise)
processed->regetDynNoise();
processed->plotFrame(frame);
-// delete processed;
+ // delete processed;
return 0;
}
else
cout << "\033[1;33mFrame number too big, max frame: " << entries << "\033[0m" << endl;
}
}
-// delete processed;
+ // delete processed;
return 1;
}
{
if (newlabel.Length() == 0)
newlabel = humanreadablestr;
-// histogramthreshold->Seed->SetTitle(newlabel);
+ // histogramthreshold->Seed->SetTitle(newlabel);
for (vector<HistogramType*>::iterator curHistogramClass = HistogramClassVector.begin(); curHistogramClass != HistogramClassVector.end(); curHistogramClass++) {
(*curHistogramClass)->Seed->SetTitle(newlabel);
(*curHistogramClass)->Veto->SetTitle(newlabel);
Bool_t Run::generateReadableRunCode()
{
humanreadablestr = Form("%s, %s, %s, %.0fx%.0f #mum^{2} pitch, %s, T=%.0f {}^{o}C, %.1f MRad, %.1f*10^{13} n_{eq}/cm^{2}, %.2f Mhz, U_{dep}=%.1f V", labbook.source.Data(),
- labbook.chipGen.Data(), labbook.matrix.Data(), curpixelinfo.pitchX, curpixelinfo.pitchY, curpixelinfo.comment.Data(),
- labbook.tempSens, labbook.radDoseIon, labbook.radDoseNonIon, labbook.clock, labbook.depletionV);
+ labbook.chipGen.Data(), labbook.matrix.Data(), curpixelinfo.pitchX, curpixelinfo.pitchY, curpixelinfo.comment.Data(),
+ labbook.tempSens, labbook.radDoseIon, labbook.radDoseNonIon, labbook.clock, labbook.depletionV);
//humanreadablestr = Form("%s, %s, chip %s, %s, %sT=%.1f", labbook.source.Data(), labbook.chipGen.Data(), labbook.chip.Data(), labbook.matrix.Data(), humanreadablesuffix.Data(), labbook.temp);
cout << colorwhite << " " << colorgreen << humanreadablestr << colorwhite <<" " << endlr;
void Run::selectSubMatrixFSBB(TString matrixname)
{
-
+
if (matrixname.EqualTo("A0")) {
setSubMatrixBorders(0, cursensorinfo.columns/2-2, 0, cursensorinfo.rows, false);
runcodesuffix += "_A0_";
{
stringstream ss;
ss << statement;
- cout << ss.str() << endl << endl; // for debugging
+// cout << ss.str() << endl << endl; // for debugging
return ss.str();
}
{
// query database and print results
// ignore temperature
-// TString query=prepareSQLStatement("select COALESCE(VetoPeak,-1) as VetoPeak, runnumber from radhard.labbook WHERE ChipNum='" + numberToString<>(labbook.chip) + "' AND MABS_comment IS NULL AND RadiationSource='Fe55' AND Matrix='" + numberToString<>(labbook.matrix) + "' AND TempCooling=" + to_str_w_prec(labbook.temp,3) + " AND System='" + numberToString<>(labbook.system) + "'");
+ // TString query=prepareSQLStatement("select COALESCE(VetoPeak,-1) as VetoPeak, runnumber from radhard.labbook WHERE ChipNum='" + numberToString<>(labbook.chip) + "' AND MABS_comment IS NULL AND RadiationSource='Fe55' AND Matrix='" + numberToString<>(labbook.matrix) + "' AND TempCooling=" + to_str_w_prec(labbook.temp,3) + " AND System='" + numberToString<>(labbook.system) + "'");
TString query=prepareSQLStatement("select COALESCE(VetoPeak,-1) as VetoPeak, runnumber, TempCooling from radhard.labbook WHERE ChipNum='" + numberToString<>(labbook.chip) + "' AND MABS_comment IS NULL AND RadiationSource='Fe55' AND Matrix='" + numberToString<>(labbook.matrix) + "' AND System='" + numberToString<>(labbook.system) + "' ORDER BY TempCooling ASC");
res = db->Query(query.Data());
nrows = res->GetRowCount();
void Run::constructUpdateString(string *sqlupdatequery, const string databasevaluename, const Double_t value, const int precision=3, const Double_t minval=-1e100, const Double_t maxval = 1e100, const TString defaultval = "NULL")
{
-// cout << colorred << databasevaluename << " : " << value << endlr;
+ // cout << colorred << databasevaluename << " : " << value << endlr;
if (std::isnan(value)) {
cout << colorred << "Error in updating SQL value for '" << databasevaluename << ", it is 'NaN'." << endlr;
return; }
- if (std::isinf(value)) {
- cout << colorred << "Error in updating SQL value for '" << databasevaluename << ", it is 'NaN'." << endlr;
- return; }
- if (!(abs(value)>=0.0)) {
- cout << colorred << "Error in updating SQL value for '" << databasevaluename << ", it is 'NaN'." << endlr;
- return; }
- if (value > maxval) {
- cout << colorred << "Error in updating SQL value for '" << databasevaluename << ", it is out of range: " << value << " > " << maxval << "." << endlr;
- return; }
- if (value < minval) {
- cout << colorred << "Error in updating SQL value for '" << databasevaluename << ", it is out of range: " << value << " < " << maxval << "." << endlr;
- return; }
- if ((*sqlupdatequery).length() > 0)
- *sqlupdatequery+= ", ";
- *sqlupdatequery += "`" + databasevaluename + "`="+ to_str_w_prec(value, precision);
+ if (std::isinf(value)) {
+ cout << colorred << "Error in updating SQL value for '" << databasevaluename << ", it is 'NaN'." << endlr;
+ return; }
+ if (!(abs(value)>=0.0)) {
+ cout << colorred << "Error in updating SQL value for '" << databasevaluename << ", it is 'NaN'." << endlr;
+ return; }
+ if (value > maxval) {
+ cout << colorred << "Error in updating SQL value for '" << databasevaluename << ", it is out of range: " << value << " > " << maxval << "." << endlr;
+ return; }
+ if (value < minval) {
+ cout << colorred << "Error in updating SQL value for '" << databasevaluename << ", it is out of range: " << value << " < " << maxval << "." << endlr;
+ return; }
+ if ((*sqlupdatequery).length() > 0)
+ *sqlupdatequery+= ", ";
+ *sqlupdatequery += "`" + databasevaluename + "`="+ to_str_w_prec(value, precision);
}
void Run::updateDatabase() {
- HistogramType* histogramclassToUseForDB = 0;
- // Add code to set the pointer histogramclassToUseForDB to class to use for database values
- // histogramclassToUseForDB = histogramthreshold;
+ HistogramType* histogramclassToUseForDB = 0;
+ // Add code to set the pointer histogramclassToUseForDB to class to use for database values
+ // histogramclassToUseForDB = histogramthreshold;
if (labbook.chipGen.EqualTo("Pipper2")) {
histogramclassToUseForDB = histogramdynamicalthreshold;
- } else {
- histogramclassToUseForDB = histogramwoRTSthreshold;
- }
-
+ } else {
+ histogramclassToUseForDB = histogramwoRTSthreshold;
+ }
+
string sqlupdatequery = "";
constructUpdateString(&sqlupdatequery, "Gain", histogramclassToUseForDB->normalized->gain, 3, 0, 100);
constructUpdateString(&sqlupdatequery, "SumPeak", histogramclassToUseForDB->normalized->posSum, 4, 0, 1000);
if (histogramclassToUseForDB->normalized->calibrated != 0)
if (labbook.source.Contains("Sr") && histogramclassToUseForDB->normalized->calibrated->sr90IntegralVal > 0)
constructUpdateString(&sqlupdatequery, "Sr90IntegralVal", histogramclassToUseForDB->normalized->calibrated->sr90IntegralVal, 1000000000, 0,1e7);
-
- if (sqlupdatequery.length()>0)
- {
- try
+
+ if (sqlupdatequery.length()>0)
{
- sqlupdatequery = prepareSQLStatement(" UPDATE `radhard`.`labbook` SET " + sqlupdatequery + " WHERE `runnumber`=" + numberToString<>(labbook.runnumber));
- Bool_t sucess = db->Exec(sqlupdatequery.c_str());
- if (!sucess)
+ try
+ {
+ sqlupdatequery = prepareSQLStatement(" UPDATE `radhard`.`labbook` SET " + sqlupdatequery + " WHERE `runnumber`=" + numberToString<>(labbook.runnumber));
+ Bool_t sucess = db->Exec(sqlupdatequery.c_str());
+ if (!sucess)
+ {
+ cout << "\033[1;31mError while writing laboratory book TO SQL database (run number " << labbook.runnumber << ")!\033[0m\n";
+ }
+ }
+ catch(...)
{
cout << "\033[1;31mError while writing laboratory book TO SQL database (run number " << labbook.runnumber << ")!\033[0m\n";
+ //exit(EXIT_FAILURE);
}
}
- catch(...)
- {
- cout << "\033[1;31mError while writing laboratory book TO SQL database (run number " << labbook.runnumber << ")!\033[0m\n";
- //exit(EXIT_FAILURE);
- }
- }
}
string Run::to_str_w_prec(const Float_t a_value, int precision = 3)
{
Double_t const probabilities[] = {0.158655254, 0.5, 1-0.158655254}; // sigma/2 from gaus to the left and to the right //{0.17, 0.5, 1-0.17};
-// Double_t const probabilities[] = {0.25, 0.5, 0.75}; // sigma/2 from gaus to the left and to the right, an area of 68% must be within the interesting range //{0.17, 0.5, 1-0.17};
+ // Double_t const probabilities[] = {0.25, 0.5, 0.75}; // sigma/2 from gaus to the left and to the right, an area of 68% must be within the interesting range //{0.17, 0.5, 1-0.17};
Double_t pedestals [cursensorinfo.columns*cursensorinfo.rows];
for (Int_t pixeli=0; pixeli<cursensorinfo.columns*cursensorinfo.rows ; pixeli++) { // loop over all pixel
pedestals[pixeli]=0;
}
else
{
-// cout << colorcyan << "Excluded: " << pixeli << endlr;
+ // cout << colorcyan << "Excluded: " << pixeli << endlr;
}
}
oneHistogramClass->LeakageCurrentDistrib->Fill(oneHistogramClass->LeakageCurrentInPixel->GetBinContent(pixeli));
sortedHistogram.push_back(oneHistogramClass->LeakageCurrentInPixel->GetBinContent(pixeli));
}
-// cout << oneHistogramClass->LeakageCurrentInPixel->GetBinContent(pixeli) << " " << endl;
+ // cout << oneHistogramClass->LeakageCurrentInPixel->GetBinContent(pixeli) << " " << endl;
}
std::sort(sortedHistogram.begin(),sortedHistogram.end());
-// oneHistogramClass->LeakageCurrentInPixelSorted->SetBins(sortedHistogram.size(), 0, sortedHistogram.size());
+ // oneHistogramClass->LeakageCurrentInPixelSorted->SetBins(sortedHistogram.size(), 0, sortedHistogram.size());
for (UInt_t pixeli=0; pixeli < sortedHistogram.size(); pixeli++) {
oneHistogramClass->LeakageCurrentInPixelSorted->SetBinContent(pixeli+1, sortedHistogram.at(pixeli)); // be aware that, histograms in root start at 1 and vectors start at 0 !
}
oneHistogramClass->avgLeakageCurrentInChip /= numberofconsideredpixel;
-// cout << "avgLeakageCurrentInChip: " << oneHistogramClass->avgLeakageCurrentInChip << endl;
+ // cout << "avgLeakageCurrentInChip: " << oneHistogramClass->avgLeakageCurrentInChip << endl;
-// oneHistogramClass->LeakageCurrentInPixelSorted->GetQuantiles( 3, leakagequantiles, probabilities);
+ // oneHistogramClass->LeakageCurrentInPixelSorted->GetQuantiles( 3, leakagequantiles, probabilities);
Int_t lastbinabovezero = oneHistogramClass->LeakageCurrentInPixelSorted->FindLastBinAbove(0);
-// cout << "lastbinabovezero: " << lastbinabovezero << endl;
+ // cout << "lastbinabovezero: " << lastbinabovezero << endl;
oneHistogramClass->medianLeakageCurrent = oneHistogramClass->LeakageCurrentInPixelSorted->GetBinContent(lastbinabovezero*probabilities[1]);
oneHistogramClass->medianLeakageCurrentPlus = oneHistogramClass->LeakageCurrentInPixelSorted->GetBinContent(lastbinabovezero*probabilities[2]);
oneHistogramClass->medianLeakageCurrentPlus = oneHistogramClass->medianLeakageCurrentPlus - oneHistogramClass->medianLeakageCurrent;
oneHistogramClass->medianLeakageCurrentMinus = oneHistogramClass->LeakageCurrentInPixelSorted->GetBinContent(lastbinabovezero*probabilities[0]);
oneHistogramClass->medianLeakageCurrentMinus = oneHistogramClass->medianLeakageCurrentMinus - oneHistogramClass->medianLeakageCurrent;
-// TCanvas *c1 = new TCanvas("c1","c1",600,400);
-// oneHistogramClass->LeakageCurrentInPixelSorted->Draw("");
-// c1->Update();
-// TCanvas *c2 = new TCanvas("c2","c2",600,400);
-// oneHistogramClass->LeakageCurrentDistrib->Draw("");
-// c2->Update();
-// cout << "medianLeakageCurrent: " << oneHistogramClass->medianLeakageCurrent << endl;
-// cout << "medianLeakageCurrentPlus: " << oneHistogramClass->medianLeakageCurrentPlus << endl;
-// cout << "medianLeakageCurrentMinus: " << oneHistogramClass->medianLeakageCurrentMinus << endl;
-//
-//
-// oneHistogramClass->medianLeakageCurrent = leakagequantiles[1];
-// oneHistogramClass->medianLeakageCurrentPlus = leakagequantiles[2];
-// oneHistogramClass->medianLeakageCurrentMinus = leakagequantiles[0];
-// cout << "medianLeakageCurrent: " << oneHistogramClass->medianLeakageCurrent << endl;
-// cout << "medianLeakageCurrentPlus: " << oneHistogramClass->medianLeakageCurrentPlus << endl;
-// cout << "medianLeakageCurrentMinus: " << oneHistogramClass->medianLeakageCurrentMinus << endl;
-
-// cout << colorcyan << "oneHistogramClass->avgLeakageCurrentInChip: " << oneHistogramClass->avgLeakageCurrentInChip << endlr;
-// cout << colorcyan << "oneHistogramClass->medianLeakageCurrent: " << oneHistogramClass->medianLeakageCurrent << endlr;
-
-// TH2F *hcandle = new TH2F("hcandle","Option CANDLE6 example ",40,-4,4,40,-20,20);
-// Float_t px, py;
-// for (Int_t pixeli=0; pixeli < oneHistogramClass->LeakageCurrentInPixel->GetNbinsX(); pixeli++) {
-// hcandle->Fill(1,oneHistogramClass->LeakageCurrentInPixel->GetBinContent(pixeli));
-// }
-// hcandle->SetMarkerSize(0.5);
-// hcandle->SetBarWidth(1.0);
-// hcandle->Draw("CANDLEX5");
-// gPad->BuildLegend(0.6,0.7,0.7,0.8);
+ // TCanvas *c1 = new TCanvas("c1","c1",600,400);
+ // oneHistogramClass->LeakageCurrentInPixelSorted->Draw("");
+ // c1->Update();
+ // TCanvas *c2 = new TCanvas("c2","c2",600,400);
+ // oneHistogramClass->LeakageCurrentDistrib->Draw("");
+ // c2->Update();
+ // cout << "medianLeakageCurrent: " << oneHistogramClass->medianLeakageCurrent << endl;
+ // cout << "medianLeakageCurrentPlus: " << oneHistogramClass->medianLeakageCurrentPlus << endl;
+ // cout << "medianLeakageCurrentMinus: " << oneHistogramClass->medianLeakageCurrentMinus << endl;
+ //
+ //
+ // oneHistogramClass->medianLeakageCurrent = leakagequantiles[1];
+ // oneHistogramClass->medianLeakageCurrentPlus = leakagequantiles[2];
+ // oneHistogramClass->medianLeakageCurrentMinus = leakagequantiles[0];
+ // cout << "medianLeakageCurrent: " << oneHistogramClass->medianLeakageCurrent << endl;
+ // cout << "medianLeakageCurrentPlus: " << oneHistogramClass->medianLeakageCurrentPlus << endl;
+ // cout << "medianLeakageCurrentMinus: " << oneHistogramClass->medianLeakageCurrentMinus << endl;
+
+ // cout << colorcyan << "oneHistogramClass->avgLeakageCurrentInChip: " << oneHistogramClass->avgLeakageCurrentInChip << endlr;
+ // cout << colorcyan << "oneHistogramClass->medianLeakageCurrent: " << oneHistogramClass->medianLeakageCurrent << endlr;
+
+ // TH2F *hcandle = new TH2F("hcandle","Option CANDLE6 example ",40,-4,4,40,-20,20);
+ // Float_t px, py;
+ // for (Int_t pixeli=0; pixeli < oneHistogramClass->LeakageCurrentInPixel->GetNbinsX(); pixeli++) {
+ // hcandle->Fill(1,oneHistogramClass->LeakageCurrentInPixel->GetBinContent(pixeli));
+ // }
+ // hcandle->SetMarkerSize(0.5);
+ // hcandle->SetBarWidth(1.0);
+ // hcandle->Draw("CANDLEX5");
+ // gPad->BuildLegend(0.6,0.7,0.7,0.8);
return 0;
}
Bool_t Run::binNoise(HistogramType* oneHistogramClass)
{
Double_t const probabilities[] = {0.3415/2, 0.5, 1-0.3415/2}; // sigma/2 from gaus to the left and to the right //{0.17, 0.5, 1-0.17};
-// cout << "processed->fNoiseTree->GetEntries: " << processed->fNoiseTree->GetEntries() << endl;
+ // cout << "processed->fNoiseTree->GetEntries: " << processed->fNoiseTree->GetEntries() << endl;
Bool_t RTSpixel =false;
u_int numberofconsideredpixel=0;
numberofconsideredpixel++;
}
}
-
+
oneHistogramClass->Noise->GetQuantiles( 3, noisequantiles, probabilities);
oneHistogramClass->avgNoise = noisequantiles[1];
oneHistogramClass->avgNoisePlus = noisequantiles[2] - noisequantiles[1];
Double_t avgF0InCurFrame = processed->fNoiseInfo.AvgF0;
averageF0Hist->SetBinContent(framei, avgF0InCurFrame);
labbook.averageF0+=avgF0InCurFrame;
-// labbook.averageF0 + = avgF0InCurFrame;
+ // labbook.averageF0 + = avgF0InCurFrame;
}
labbook.averageF0 /= processed->fHitTree->GetEntries();
for (Int_t framei=0; framei<processed->fHitTree->GetEntries(); framei++) // loop over all frames
averageF1Distr->SetLineColor(4);
averageF1Distr->itsHistogramType = histogram;
-
+
Double_t const probabilities[] = {0.158655254, 0.5, 1-0.158655254}; // sigma/2 from gaus to the left and to the right //{0.17, 0.5, 1-0.17};
Double_t avgF0ForPixel [cursensorinfo.columns*cursensorinfo.rows];
Double_t avgF1ForPixel [cursensorinfo.columns*cursensorinfo.rows];
avgF0ForPixel[pixeli]=0;
avgF1ForPixel[pixeli]=0;
}
-
+
for (Int_t framei=processed->fHitTree->GetEntries()-1000; framei<processed->fHitTree->GetEntries(); framei++) { // loop over all frames
processed->getFrame(framei);
for (Int_t pixeli=0; pixeli<cursensorinfo.columns*cursensorinfo.rows ; pixeli++) { // loop over all pixel
}
-// TCanvas *c1 = new TCanvas("c1","c1",600,400);
-// averageF0DistrStart->Draw("");
-// averageF0DistrEnd->Draw("SAME");
-// c1->Update();
-//
-// TCanvas *c2 = new TCanvas("c2","c2",600,400);
-// averageF0PixelwiseStart->Draw("");
-// averageF0PixelwiseEnd->Draw("SAME");
-// c2->Update();
+ // TCanvas *c1 = new TCanvas("c1","c1",600,400);
+ // averageF0DistrStart->Draw("");
+ // averageF0DistrEnd->Draw("SAME");
+ // c1->Update();
+ //
+ // TCanvas *c2 = new TCanvas("c2","c2",600,400);
+ // averageF0PixelwiseStart->Draw("");
+ // averageF0PixelwiseEnd->Draw("SAME");
+ // c2->Update();
return 0;
}
}
}
-
- // DEBUG
- // for (Int_t clusteri=0; clusteri<sqrt(completeclustersize); clusteri++) {
- // for (Int_t clusterj=0; clusterj<sqrt(completeclustersize); clusterj++)
- // cout << " " << processed->fFrameInfo.p[clusteri*5+clusterj][hiti];
- // cout << endl;
- // }
- // cout << "......." << endl;
-
+
+ // DEBUG
+ // for (Int_t clusteri=0; clusteri<sqrt(completeclustersize); clusteri++) {
+ // for (Int_t clusterj=0; clusterj<sqrt(completeclustersize); clusterj++)
+ // cout << " " << processed->fFrameInfo.p[clusteri*5+clusterj][hiti];
+ // cout << endl;
+ // }
+ // cout << "......." << endl;
+
Float_t clusterArray9[9]; // temp variable clusterArray necessary, because Sort only accepts 1-dim arrays
clusterArray9[0]=clusterArray25[6];
clusterArray9[1]=clusterArray25[7];
// veto spectrum
if (TMath::Abs(notSeedSum) < cursystemparam.vetothreshold && (labbook.source.Contains("Fe")||labbook.source.Contains("Cd")))
histogram->Veto->Fill(processed->fFrameInfo.p[12][hiti]); // histogram with the single pixel
-
-
- if (processed->fFrameInfo.pixelthreshold[hiti]>0)
- {
- histogramthreshold->numberofhits++;
- fillAHistogramsinclass(histogramthreshold, hiti, completeclustersize, pixelSum, notSeedSum, &a_pixelSum[0], &a_notSeedSum[0], pixelSum25, notSeedSum25, &a_pixelSum25[0], &a_notSeedSum25[0], pixelSum9, notSeedSum9, &a_pixelSum9[0], &a_notSeedSum9[0]);
+
+
+ if (processed->fFrameInfo.pixelthreshold[hiti]>0)
+ {
+ histogramthreshold->numberofhits++;
+ fillAHistogramsinclass(histogramthreshold, hiti, completeclustersize, pixelSum, notSeedSum, &a_pixelSum[0], &a_notSeedSum[0], pixelSum25, notSeedSum25, &a_pixelSum25[0], &a_notSeedSum25[0], pixelSum9, notSeedSum9, &a_pixelSum9[0], &a_notSeedSum9[0]);
+
+ // bin the RTS cleaned histogram class
+ if (histogramwoRTSthreshold != 0) {
+ RTSpixel = false;
+ for (u_int RTSpixeli=0; RTSpixeli < histogramwoRTSthreshold->RTSpixel.size(); RTSpixeli++) {
+ if (pixelno == histogramwoRTSthreshold->RTSpixel[RTSpixeli])
+ {
+ RTSpixel = true;
+ }
+ }
+ if (!RTSpixel) {
+ fillAHistogramsinclass(histogramwoRTSthreshold, hiti, completeclustersize, pixelSum, notSeedSum, &a_pixelSum[0], &a_notSeedSum[0], pixelSum25, notSeedSum25, &a_pixelSum25[0], &a_notSeedSum25[0], pixelSum9, notSeedSum9, &a_pixelSum9[0], &a_notSeedSum9[0]);
+ }
+ }
+ // bin the more agressive RTS histogram class
+ if (histogramwoRTSAggresivethreshold != 0) {
+ RTSpixel = false;
+ for (u_int RTSpixeli=0; RTSpixeli < histogramwoRTSAggresivethreshold->RTSpixel.size(); RTSpixeli++) {
+ if (pixelno == histogramwoRTSAggresivethreshold->RTSpixel[RTSpixeli])
+ {
+ RTSpixel = true;
+ // cout << "not binned! RTS pixel #" << pixelno << endl;
+ }
+ }
+ if (!RTSpixel) {
+ fillAHistogramsinclass(histogramwoRTSAggresivethreshold, hiti, completeclustersize, pixelSum, notSeedSum, &a_pixelSum[0], &a_notSeedSum[0], pixelSum25, notSeedSum25, &a_pixelSum25[0], &a_notSeedSum25[0], pixelSum9, notSeedSum9, &a_pixelSum9[0], &a_notSeedSum9[0]);
+ }
+ }
+ }
// bin the RTS cleaned histogram class
- if (histogramwoRTSthreshold != 0) {
+ if (histogramwoRTS != 0) {
RTSpixel = false;
- for (u_int RTSpixeli=0; RTSpixeli < histogramwoRTSthreshold->RTSpixel.size(); RTSpixeli++) {
- if (pixelno == histogramwoRTSthreshold->RTSpixel[RTSpixeli])
+ for (u_int RTSpixeli=0; RTSpixeli < histogramwoRTS->RTSpixel.size(); RTSpixeli++) {
+ if (pixelno == histogramwoRTS->RTSpixel[RTSpixeli])
{
RTSpixel = true;
+ break;
}
+
}
- if (!RTSpixel) {
- fillAHistogramsinclass(histogramwoRTSthreshold, hiti, completeclustersize, pixelSum, notSeedSum, &a_pixelSum[0], &a_notSeedSum[0], pixelSum25, notSeedSum25, &a_pixelSum25[0], &a_notSeedSum25[0], pixelSum9, notSeedSum9, &a_pixelSum9[0], &a_notSeedSum9[0]);
- }
- }
+ if (!RTSpixel) {
+ fillAHistogramsinclass(histogramwoRTS, hiti, completeclustersize, pixelSum, notSeedSum, &a_pixelSum[0], &a_notSeedSum[0], pixelSum25, notSeedSum25, &a_pixelSum25[0], &a_notSeedSum25[0], pixelSum9, notSeedSum9, &a_pixelSum9[0], &a_notSeedSum9[0]);
+ }
+ }
// bin the more agressive RTS histogram class
- if (histogramwoRTSAggresivethreshold != 0) {
+ if (histogramwoRTSAggresive != 0) {
RTSpixel = false;
- for (u_int RTSpixeli=0; RTSpixeli < histogramwoRTSAggresivethreshold->RTSpixel.size(); RTSpixeli++) {
- if (pixelno == histogramwoRTSAggresivethreshold->RTSpixel[RTSpixeli])
+ for (u_int RTSpixeli=0; RTSpixeli < histogramwoRTSAggresive->RTSpixel.size(); RTSpixeli++) {
+ if (pixelno == histogramwoRTSAggresive->RTSpixel[RTSpixeli])
{
RTSpixel = true;
- // cout << "not binned! RTS pixel #" << pixelno << endl;
+ // cout << "not binned! RTS pixel #" << processed->fFrameInfo.pixel[hiti] << " with charge: " << processed->fFrameInfo.p[12][hiti] << endl;
+ // cout << "not binned! RTS pixel #" << processed->fFrameInfo.pixel[hiti] << " with charge: " << processed->fFrameInfo.p[12][hiti] << endl;
}
}
if (!RTSpixel) {
- fillAHistogramsinclass(histogramwoRTSAggresivethreshold, hiti, completeclustersize, pixelSum, notSeedSum, &a_pixelSum[0], &a_notSeedSum[0], pixelSum25, notSeedSum25, &a_pixelSum25[0], &a_notSeedSum25[0], pixelSum9, notSeedSum9, &a_pixelSum9[0], &a_notSeedSum9[0]);
- }
- }
-
- }
- // bin the RTS cleaned histogram class
- if (histogramwoRTS != 0) {
- RTSpixel = false;
- for (u_int RTSpixeli=0; RTSpixeli < histogramwoRTS->RTSpixel.size(); RTSpixeli++) {
- if (pixelno == histogramwoRTS->RTSpixel[RTSpixeli])
- {
- RTSpixel = true;
- break;
- }
-
+ fillAHistogramsinclass(histogramwoRTSAggresive, hiti, completeclustersize, pixelSum, notSeedSum, &a_pixelSum[0], &a_notSeedSum[0], pixelSum25, notSeedSum25, &a_pixelSum25[0], &a_notSeedSum25[0], pixelSum9, notSeedSum9, &a_pixelSum9[0], &a_notSeedSum9[0]);
+ }
}
- if (!RTSpixel) {
- fillAHistogramsinclass(histogramwoRTS, hiti, completeclustersize, pixelSum, notSeedSum, &a_pixelSum[0], &a_notSeedSum[0], pixelSum25, notSeedSum25, &a_pixelSum25[0], &a_notSeedSum25[0], pixelSum9, notSeedSum9, &a_pixelSum9[0], &a_notSeedSum9[0]);
- }
- }
- // bin the more agressive RTS histogram class
- if (histogramwoRTSAggresive != 0) {
- RTSpixel = false;
- for (u_int RTSpixeli=0; RTSpixeli < histogramwoRTSAggresive->RTSpixel.size(); RTSpixeli++) {
- if (pixelno == histogramwoRTSAggresive->RTSpixel[RTSpixeli])
- {
- RTSpixel = true;
- // cout << "not binned! RTS pixel #" << processed->fFrameInfo.pixel[hiti] << " with charge: " << processed->fFrameInfo.p[12][hiti] << endl;
- // cout << "not binned! RTS pixel #" << processed->fFrameInfo.pixel[hiti] << " with charge: " << processed->fFrameInfo.p[12][hiti] << endl;
- }
- }
- if (!RTSpixel) {
- fillAHistogramsinclass(histogramwoRTSAggresive, hiti, completeclustersize, pixelSum, notSeedSum, &a_pixelSum[0], &a_notSeedSum[0], pixelSum25, notSeedSum25, &a_pixelSum25[0], &a_notSeedSum25[0], pixelSum9, notSeedSum9, &a_pixelSum9[0], &a_notSeedSum9[0]);
- }
- }
} else if (filli == 1) { // second fill round, some histograms are allready filled
// histogramdynamicalthreshold relies on "histogram", therefore 'histogram' has to be completly filled before a threshold can be Set
}
}
- // histogramfixedthreshold relies on "histogram", therefore 'histogram' has to be completly filled before a threshold can be Set
+ // histogramfixedthreshold relies on "histogram", therefore 'histogram' has to be completly filled before a threshold can be Set
// bin the fixed threshold for charge histogram class
if (histogramfixedthreshold != 0 && histogram != 0) {
if (histogramfixedthreshold->fixedThresholdValue <= 0) {
}// if good veto
}
}
-
+
} else if (filli == 2) { // third fill round, some histograms are allready filled
if (histogramGoodVeto != 0 && histogram != 0) {// histogramGoodVeto not used any more
fillAHistogramsinclass(histogramGoodVeto, hiti, completeclustersize, pixelSum, notSeedSum, &a_pixelSum[0], &a_notSeedSum[0], pixelSum25, notSeedSum25, &a_pixelSum25[0], &a_notSeedSum25[0], pixelSum9, notSeedSum9, &a_pixelSum9[0], &a_notSeedSum9[0]);
}
}
-
+
} // if fill round == 2 (third round)
} // end if in range for submatrix analysis
}// end loop over hits in frame
}
} // end loop over all frames
} // end of loop of fill round counter
-
-
+
+
// gROOT->SetBatch(kTRUE);
for (vector<HistogramType*>::iterator curHistogramClass = HistogramClassVector.begin(); curHistogramClass != HistogramClassVector.end(); curHistogramClass++) {
+ cout << "Processing histograms in class: <" << colorwhite << (*curHistogramClass)->histogramdescription << colorreset << " >" << endlr;
Double_t* parameters = (Double_t *)calloc(11, sizeof(Double_t)); // allocate 11 parameters for safety, maximum 10 used at the moment
-// cout << colorcyan << (*curHistogramClass)->histogramdescription << endlr;
- (*curHistogramClass)->FindNoisethresholdborder((*curHistogramClass)->Seed, false, false);
+ // cout << colorcyan << (*curHistogramClass)->histogramdescription << endlr;
if (labbook.source.Contains("Fe")||labbook.source.Contains("Cd")) {
+ (*curHistogramClass)->FindNoisethresholdborder((*curHistogramClass)->Veto);
parameters = (*curHistogramClass)->FitPerform((*curHistogramClass)->Veto, "GaussTail");
(*curHistogramClass)->posVeto = parameters[1];
(*curHistogramClass)->integralVeto = parameters[6];
}
+ (*curHistogramClass)->FindNoisethresholdborder((*curHistogramClass)->Seed);
if (labbook.chipGen.EqualTo("Pipper2") || labbook.chipGen.EqualTo("Pegasus"))
parameters = (*curHistogramClass)->FitPerform((*curHistogramClass)->Seed, "gaus", 0, false, (*curHistogramClass)->fixedThresholdValue);
else
for (Int_t bini = 1; bini <= (*curHistogramClass)->clustermultiplicity->GetNbinsX(); bini++) {
(*curHistogramClass)->clustermultiplicity->SetBinContent(bini, (*curHistogramClass)->clustermultiplicity->GetBinContent(bini)/(*curHistogramClass)->numberofhits); }
-
- for (u_int sumi = 0; sumi < (*curHistogramClass)->a_Sum9.size(); sumi++) {
- // Float_t integratestart = (*curHistogramClass)->FindNoisethresholdborder((*curHistogramClass)->a_Sum[sumi], false, false);
- // parameters = (*curHistogramClass)->FitPerform((*curHistogramClass)->a_Sum[sumi], "gaus", 0, false, integratestart); //TODO change back to gauss
- parameters = (*curHistogramClass)->FitPerform((*curHistogramClass)->a_Sum9[sumi], "gaus", 0, false, (*curHistogramClass)->fixedThresholdValue); //TODO change back to gauss
- (*curHistogramClass)->a_posSum9.push_back(parameters[1]);
- (*curHistogramClass)->a_integralSum9.push_back(parameters[6]);
- (*curHistogramClass)->a_integralSumErr9.push_back(parameters[9]);
- }
- for (u_int sumi = 0; sumi < (*curHistogramClass)->a_Sum25.size(); sumi++) {
- // Float_t integratestart = (*curHistogramClass)->FindNoisethresholdborder((*curHistogramClass)->a_Sum[sumi], false, false);
-// parameters = (*curHistogramClass)->FitPerform((*curHistogramClass)->a_Sum[sumi], "gaus", 0, false, integratestart); //TODO change back to gauss
- parameters = (*curHistogramClass)->FitPerform((*curHistogramClass)->a_Sum25[sumi], "gaus", 0, false, (*curHistogramClass)->fixedThresholdValue); //TODO change back to gauss
- (*curHistogramClass)->a_posSum25.push_back(parameters[1]);
- (*curHistogramClass)->a_integralSum25.push_back(parameters[6]);
- (*curHistogramClass)->a_integralSumErr25.push_back(parameters[9]);
- }
-
- parameters =(*curHistogramClass)->FitPerform((*curHistogramClass)->SeedPerc, "landau");
- (*curHistogramClass)->posSeedPerc = parameters[1];
- (*curHistogramClass)->sigmaSeedPerc = parameters[2];
-
- for (Int_t bini=1; bini <= 100; bini++) {
- (*curHistogramClass)->SeedPerc->SetBinContent(bini,(*curHistogramClass)->SeedPerc->GetBinContent(bini));///((*curHistogramClass)->SeedPerc->GetEntries()));
- }
+
+ for (u_int sumi = 0; sumi < (*curHistogramClass)->a_Sum9.size(); sumi++) {
+ // Float_t integratestart = (*curHistogramClass)->FindNoisethresholdborder((*curHistogramClass)->a_Sum[sumi], false, false);
+ // parameters = (*curHistogramClass)->FitPerform((*curHistogramClass)->a_Sum[sumi], "gaus", 0, false, integratestart); //TODO change back to gauss
+ parameters = (*curHistogramClass)->FitPerform((*curHistogramClass)->a_Sum9[sumi], "gaus", 0, false, (*curHistogramClass)->fixedThresholdValue); //TODO change back to gauss
+ (*curHistogramClass)->a_posSum9.push_back(parameters[1]);
+ (*curHistogramClass)->a_integralSum9.push_back(parameters[6]);
+ (*curHistogramClass)->a_integralSumErr9.push_back(parameters[9]);
+ }
+ for (u_int sumi = 0; sumi < (*curHistogramClass)->a_Sum25.size(); sumi++) {
+ // Float_t integratestart = (*curHistogramClass)->FindNoisethresholdborder((*curHistogramClass)->a_Sum[sumi], false, false);
+ // parameters = (*curHistogramClass)->FitPerform((*curHistogramClass)->a_Sum[sumi], "gaus", 0, false, integratestart); //TODO change back to gauss
+ parameters = (*curHistogramClass)->FitPerform((*curHistogramClass)->a_Sum25[sumi], "gaus", 0, false, (*curHistogramClass)->fixedThresholdValue); //TODO change back to gauss
+ (*curHistogramClass)->a_posSum25.push_back(parameters[1]);
+ (*curHistogramClass)->a_integralSum25.push_back(parameters[6]);
+ (*curHistogramClass)->a_integralSumErr25.push_back(parameters[9]);
+ }
+
+ parameters =(*curHistogramClass)->FitPerform((*curHistogramClass)->SeedPerc, "landau");
+ (*curHistogramClass)->posSeedPerc = parameters[1];
+ (*curHistogramClass)->sigmaSeedPerc = parameters[2];
+
+ for (Int_t bini=1; bini <= 100; bini++) {
+ (*curHistogramClass)->SeedPerc->SetBinContent(bini,(*curHistogramClass)->SeedPerc->GetBinContent(bini));///((*curHistogramClass)->SeedPerc->GetEntries()));
+ }
}
if (histogramdynamicalthreshold != 0) {
if (TMath::Abs(notSeedSum) < cursystemparam.vetothreshold && (labbook.source.Contains("Fe")||labbook.source.Contains("Cd"))) {
histogramtypepointer->Veto->Fill(processed->fFrameInfo.p[12][hiti]); // histogram with the single pixel
}
-
+
if (pt_a_pixelSum[5]-pt_a_pixelSum[0]-pt_a_pixelSum[1]-pt_a_pixelSum[2]-pt_a_pixelSum[3]-pt_a_pixelSum[4] > labbook.NoiseAvgADC_DB*5)
histogramtypepointer->clustermultiplicity->Fill(6);
else if (pt_a_pixelSum[4]-pt_a_pixelSum[0]-pt_a_pixelSum[1]-pt_a_pixelSum[2]-pt_a_pixelSum[3] > labbook.NoiseAvgADC_DB*5)
xcoord = xcoord*TMath::Cos(rotateangle/180*TMath::Pi())-ycoord*TMath::Sin(rotateangle/180*TMath::Pi());
ycoord = xcoord_old*TMath::Sin(rotateangle/180*TMath::Pi())+ycoord*TMath::Cos(rotateangle/180*TMath::Pi());
}
- // cout << colorwhite << "oben: xcoord: " << xcoord << ", ycoord: " << ycoord << endl;
+ // cout << colorwhite << "oben: xcoord: " << xcoord << ", ycoord: " << ycoord << endl;
histogram->histAvgCluster->Fill(xcoord,ycoord,processed->fFrameInfo.p[clusteri][hiti]);
if (processed->fFrameInfo.pixelthreshold[hiti]>0)
owntitle4->AddText(trimRunnumberAtBegin(HistogramTypepointer->Noise->GetName()));
owntitle4->Draw("SAME");
-// canvas -> Print( savepathresults + "/" + canvastitle + ".eps");
+ // canvas -> Print( savepathresults + "/" + canvastitle + ".eps");
canvas->Update();
TImageDump *img = new TImageDump(savepathresults + "/" + canvastitle + ".png");
f->Append(img);
f->Write();
-// gStyle->SetPaperSize(10.,10.);
-// canvas->Print(savepathresults + "/" + canvastitle + ".tex");
+ // gStyle->SetPaperSize(10.,10.);
+ // canvas->Print(savepathresults + "/" + canvastitle + ".tex");
return 0;
}
Canvas_1->Modified();
Canvas_1->cd();
Canvas_1->SetSelected(Canvas_1);
-
+
TImageDump *img = new TImageDump(savepathresults + "/" + canvastitle + ".png");
Canvas_1->Paint();
img->Close();
middlebin = (int)(HistogramTypepointer->histAvgCluster->GetYaxis()->GetNbins()/2.0 + 0.5);
for (Int_t bini=1; bini <= HistogramTypepointer->histAvgCluster->GetYaxis()->GetNbins(); bini++)
yslicetroughcluster->SetBinContent(bini,HistogramTypepointer->histAvgCluster->GetBinContent(middlebin,bini));
-
+
random = random1->Rndm()*100000;
canvastitle = Form("%s Cluster slices", runcode.Data());
if (HistogramTypepointer->iscalibrated)
canvas->Draw();
-// TImageDump *img2 = new TImageDump(savepathresults + "/" + canvastitle + ".png");
-// canvas->Paint();
-// img2->Close();
-//
-// f->Append(canvas);
-// f->Append(img2);
-// f->Write();
+ // TImageDump *img2 = new TImageDump(savepathresults + "/" + canvastitle + ".png");
+ // canvas->Paint();
+ // img2->Close();
+ //
+ // f->Append(canvas);
+ // f->Append(img2);
+ // f->Write();
// .Data(), Form("Avg. cluster distribution; x; y %s", humanreadablestr.Data()),sizearrrotx, xcoord_abs_min,xcoord_abs_max,sizearrroty,ycoord_abs_min,ycoord_abs_max);
return 0;
{
if (onehistogram != nullptr)
{
+ onehistogram->GetYaxis()->UnZoom();
+ onehistogram->GetXaxis()->UnZoom();
+
Int_t random = random1->Rndm()*100000;
TFitResult* fit_result;
-// TFitResultPtr* fit_result_ptr;
+ // TFitResultPtr* fit_result_ptr;
fit_result = new TFitResult();
-// fit_result_ptr = new TFitResultPtr();
+ // fit_result_ptr = new TFitResultPtr();
TString canvastitle = Form("%s %s", onehistogram->GetName(), runcode.Data());
TString canvasname = Form("%s %s %d", onehistogram->GetName(), runcode.Data(), random);
TCanvas* canvas = new TCanvas(canvasname, canvastitle, 900, 700);
}
Float_t startvalue = onehistogram->GetBinLowEdge(onehistogram->FindFirstBinAbove(0));
- Float_t endrange = onehistogram->GetBinCenter(onehistogram->FindLastBinAbove(1));
+ Float_t endrange = onehistogram->GetBinCenter(onehistogram->FindLastBinAbove(0));
+ onehistogram->GetXaxis()->SetRange(fitstart, endrange);
Float_t endrangeY = onehistogram->GetMaximum();
- onehistogram->GetXaxis()->SetRangeUser(startvalue,endrange);
+ onehistogram->GetXaxis()->SetRangeUser(fitstart,endrange*1.1);
if (logscale)
- onehistogram->GetYaxis()->SetRangeUser(0.1,endrangeY*1.4);
+ onehistogram->GetYaxis()->SetRangeUser(0.1,endrangeY*5);
else
- onehistogram->GetYaxis()->SetRangeUser(0,endrangeY*1.4);
+ onehistogram->GetYaxis()->SetRangeUser(0,endrangeY*1.25);
TLegend* leg = new TLegend(0.2,0.85,0.89,0.89);//(0.6,0.7,0.89,0.89);
leg->SetFillColor(0);
leg->SetBorderSize(0);
if (legendstr.Length() < 1)
legendstr = Form("%s",onehistogram->GetTitle());
leg->AddEntry(onehistogram, legendstr, "l");
-
+
leg->SetTextSize(0.025);
leg->Draw();
-// canvas->Draw();
-// canvas->Update();
-
+ // canvas->Draw();
+ // canvas->Update();
+
if (fitFuncType=="GaussTail" || fitFuncType=="gaus")
{
Float_t integralstart = parameters[7];
Float_t integralend = parameters[8];
Float_t integralval = parameters[6];
TString integrallbl = Form("Integral: %.0f", integralval);
-// cout << colorcyan << " " << HistogramTypepointer->histogramdescription << endlr;
-// cout << colorcyan << ": " << parameters[7] << endlr;
+ // cout << colorcyan << " " << HistogramTypepointer->histogramdescription << endlr;
+ // cout << colorcyan << ": " << parameters[7] << endlr;
plotVerticalLineHeigher(onehistogram, integralstart);
plotVerticalLineHeigher(onehistogram, integralend, "Integral to:");
plotTextAtVal(onehistogram, maxValue, integrallbl);
cout << "background slope : " << parameters[4] << endl;
cout << "background offset: " << parameters[5] << endl;
cout << "FWHM : " << parameters[2]*sqrt(8*log(2)) << endl;
-// cout << "got address2:" << endl;
-// cout << fit_result << endl;
-// fit_result->Print("V");
+ // cout << "got address2:" << endl;
+ // cout << fit_result << endl;
+ // fit_result->Print("V");
//TF1 *f1 = new TF1("f1","[0] +[1]*x +gaus(2)",0,5);
TF1 *f1 = new TF1("f1","[0] +[1]*x",0,1000);
f1->Draw("SAME");
}
}
-// if (fitFuncType=="gaus")
-// {
-// Float_t integralstart = parameters[4];
-// Float_t integralval = parameters[3];
-// TString integrallbl = Form("Integral: %.0f", integralval);
-// // cout << colorcyan << " " << HistogramTypepointer->histogramdescription << endlr;
-// // cout << colorcyan << ": " << parameters[4] << endlr;
-// plotVerticalLineHeigher(onehistogram, integralstart);
-// plotTextAtVal(onehistogram, maxValue, integrallbl);
-// }
-
-// canvas -> SaveAs( savepathresults + "/" + runcode + " " + onehistogram->GetName() + ".eps");
-
+ // if (fitFuncType=="gaus")
+ // {
+ // Float_t integralstart = parameters[4];
+ // Float_t integralval = parameters[3];
+ // TString integrallbl = Form("Integral: %.0f", integralval);
+ // // cout << colorcyan << " " << HistogramTypepointer->histogramdescription << endlr;
+ // // cout << colorcyan << ": " << parameters[4] << endlr;
+ // plotVerticalLineHeigher(onehistogram, integralstart);
+ // plotTextAtVal(onehistogram, maxValue, integrallbl);
+ // }
+
+ // canvas -> SaveAs( savepathresults + "/" + runcode + " " + onehistogram->GetName() + ".eps");
+
TImageDump *img = new TImageDump(savepathresults + "/" + runcode + " " + onehistogram->GetName() + ".png");
canvas->Paint();
img->Close();
}
header += Form("\n");
-// header += Form("#");
-// for (vector<TH1F*>::iterator curHistogram = compareHistogramVector.begin(); curHistogram != compareHistogramVector.end(); curHistogram++) {
-// header += Form("bin\t%s\t",(*curHistogram)->GetName());
-// }
-// *fout << header << endl;
+ // header += Form("#");
+ // for (vector<TH1F*>::iterator curHistogram = compareHistogramVector.begin(); curHistogram != compareHistogramVector.end(); curHistogram++) {
+ // header += Form("bin\t%s\t",(*curHistogram)->GetName());
+ // }
+ // *fout << header << endl;
header += Form("#posSeed, run: %.1f, DB: %.1f\n", histogram->posSeed, labbook.posSeedDB);
header += Form("#posSum, run: %.1f, DB: %.1f\n", histogram->posSum, labbook.posSumDB);
/** @brief overwrite value from which the integral should be taken, overwrite noise cut in ADU */
Float_t noisethresholdborderADU = -1;
/** @brief Uses a found calibration peak value to rescale all the different cuts and histograms of type #HistogramType from ADU to e */
- Bool_t rescaleHistogramClasses();
+ Bool_t rescaleHistogramClasses(HistogramType* oneHistogramClass);
/** @brief Uses the number of frames found (#frames_found) for calculation to normalize the histograms of type #HistogramType */
- Bool_t normalizeHistogramClasses();
+ Bool_t normalizeHistogramClasses(HistogramType* oneHistogramClass);
/** @brief finds and and masks RTS pixel if maskRTSpixel isset to true */
Bool_t FindRTSPixelToMask(HistogramType* histogramtypepointer, Bool_t verbose = kFALSE);
};
/// sensor information to use in analysis, is the system read out by USB or PXI? Number of rows differ
-const TString colorwhite = "\033[1;29m";
-const TString colorred = "\033[1;31m";
+const TString colorwhite = "\033[1;29m";
+const TString colorred = "\033[1;31m";
const TString coloryellow = "\033[1;33m";
-const TString colorgreen = "\033[1;32m";
+const TString colorgreen = "\033[1;32m";
const TString colorpurple = "\033[1;35m";
-const TString colorcyan = "\033[1;36m";
-const TString colorreset = "\033[0m";
-const TString endlr = "\033[0m\n";
+const TString colorcyan = "\033[1;36m";
+const TString colorreset = "\033[0m";
+const TString endlr = "\033[0m\n";
Int_t* rootcolors = new Int_t[13]{1, 2, 4, 6, 8, 13, 46, 28, 32, 33, 12, 20, 40};
/**
jspc29 / radhard.git / commitdiff