*.MOV
*/results/*
*runlist.txt
-ChargeSpektrum.c
+#ChargeSpektrum.c
MABS_run_analyzer/html/*
MABS_run_analyzer/latex/*
\ No newline at end of file
--- /dev/null
+/**
+ * @file ChargeSpektrum.c
+ * @brief Use brief, otherwise the index won't have a brief explanation.
+ *
+ * Detailed explanation.
+ *
+ *
+ */
+
+#include "MAPS.c"
+#include "Run.c"
+#include "CSVRow.h"
+#include "CSVRow.C"
+#include <TTimeStamp.h>
+#include "help.h"
+
+Run** runs;
+Int_t numberRuns;
+Bool_t isBatch = kFALSE;
+TString savepathresults = "./results/";
+
+#include "ChargeSpektrumFunctions.c"
+
+void ChargeSpektrum(TString runnumber = "")
+{
+ #include "SetStyle.c"
+ cout << endl << endl;
+ if (gROOT->IsBatch())
+ isBatch = kTRUE;
+
+ numberRuns=0;
+ std::vector<int> runList;
+ std::vector<TString> sumuprunList;
+ if (runnumber.Length() > 0)
+ {
+ if (runnumber.Contains("-")) {
+ TObjArray* runarray = runnumber.Tokenize("-");
+ if (runarray->GetEntries()==2)
+ {
+ TObjString* tempstrobj;
+ tempstrobj=static_cast<TObjString*>(runarray->At(0));
+ if (tempstrobj->GetString().Length()>0)
+ {
+ Int_t tempintstart = tempstrobj->GetString().Atoi();
+ tempstrobj=static_cast<TObjString*>(runarray->At(1));
+ if (tempstrobj->GetString().Length()>0)
+ {
+ Int_t tempintend = tempstrobj->GetString().Atoi();
+ if (tempintend-tempintstart > 0)
+ {
+ for (Int_t i=tempintstart; i <= tempintend; i++)
+ {
+ runList.push_back(i);
+ numberRuns++;
+ }
+ }
+ else
+ cout << coloryellow << "Invalid run number range "<< colorreset << colorwhite << tempintstart << " till " << tempintend << endlr;
+ }
+ else
+ cout << coloryellow << "Invalid run number "<< colorreset << colorwhite << tempstrobj->GetString() << endlr;
+
+ }
+ else
+ cout << coloryellow << "Invalid run number "<< colorreset << colorwhite << tempstrobj->GetString() << endlr;
+ }
+ else
+ {
+ cout << endl << colorred << "Given parameters have wrong format, please enter integer run numbers devided by '" << colorreset << colorwhite << "," << colorreset << colorred << " or 2 runnumbers devided by " << colorreset << colorwhite << "-" << colorreset << colorred << "' and surrounded by '" << colorreset << colorwhite << "\"" << colorreset << colorred << "'." << endlr;
+ cout << "For example run: " << colorwhite << "root -l 'ChargeSpektrum.c+(\"342815,342816\")'" << endl;
+ exit(1);
+ }
+
+ } else {
+ TObjArray* runarray = runnumber.Tokenize(",");
+ if (runarray->GetEntries()>0)
+ {
+ TObjString* tempstrobj;
+ for (Int_t i=0; i < runarray->GetEntries(); i++)
+ {
+ tempstrobj=static_cast<TObjString*>(runarray->At(i));
+ if (tempstrobj->GetString().Length()>0)
+ {
+ TString sumrunsstr = "";
+ TObjArray* sumrunarray = tempstrobj->GetString().Tokenize("+");
+ TObjString* sumuprunsstrobj;
+ for (Int_t j=0; j < sumrunarray->GetEntries(); j++)
+ {
+ sumuprunsstrobj=static_cast<TObjString*>(sumrunarray->At(j));
+ Int_t tempint = sumuprunsstrobj->GetString().Atoi();
+ if (tempint > 0)
+ {
+ runList.push_back(tempint);
+ sumrunsstr.Append(Form("%d,",tempint));
+ numberRuns++;
+ }
+ else
+ cout << coloryellow << "Invalid run number "<< colorreset << colorwhite << tempint << endlr;
+ }
+ sumuprunList.push_back(sumrunsstr);
+ }
+ else
+ cout << coloryellow << "Invalid run number "<< colorreset << colorwhite << tempstrobj->GetString() << endlr;
+ }
+ }
+ else
+ {
+ cout << endl << colorred << "Given parameters have wrong format, please enter integer run numbers devided by '" << colorreset << colorwhite << "," << colorreset << colorred << "' and surrounded by '" << colorreset << colorwhite << "\"" << colorreset << colorred << "'." << endlr;
+ cout << "For example run: " << colorwhite << "root -l 'ChargeSpektrum.c+(\"342815,342816\")'" << endl;
+ exit(1);
+ }
+ }
+ }
+ else
+ {
+ /// number of runs to be analyzed, number of lines read by @c ReadRunList()
+ ReadRunList(&runList);
+ }
+ runs = new Run*[numberRuns];
+
+ cout << "Found " << numberRuns << " run(s) in 'runlist.txt' or given as parameters." << endl;
+ for(Int_t runi=0;runi<numberRuns;runi++) // loop over runs read from file
+ {
+ if (runList[runi]>0)
+ {
+ runs[runi] = new Run(runList[runi], runi);
+ if (!runs[runi]->error)
+ {
+ runs[runi]->setResultsPath(savepathresults);
+ runs[runi]->error=runs[runi]->initRun();
+ runs[runi]->setDynamicalNoiseMode("simple");
+ runs[runi]->useDynamicalNoise(true);
+ runs[runi]->useCommonModeFilter(false);
+ runs[runi]->setFixedThresholdValueElectrons(1440);
+
+// runs[runi]->analyzeFrame(57826);
+// runs[runi]->analyzeFrame(57827);
+// runs[runi]->analyzeFrame(983603);
+
+ // creates or opens .root file, can analyze the RAW data
+ runs[runi]->error=runs[runi]->analyzeRun(false); // creates or opens .root file, can analyze the RAW data
+ if (runs[runi]->error) // first time analysis without forcing new ROOT file failed, retry with forcing new analysis
+ {
+ runs[runi]->error = false;
+ runs[runi]->error=runs[runi]->analyzeRun(true);
+ }
+ if (!runs[runi]->error)
+ {
+ // gROOT->SetBatch(kTRUE);
+ if (!isBatch)
+ gROOT->SetBatch(kFALSE);
+// runs[runi]->plot1DHistogram(runs[runi]->histogram,runs[runi]->histogram->Seed,"landau","Test");
+// runs[runi]->compareHistogramClassVector.push_back(runs[runi]->histogram->calibrated);
+// runs[runi]->compareHistogramClassVector.push_back(runs[runi]->histogramthreshold->calibrated);
+// runs[runi]->compareHistogramClassVector.push_back(runs[runi]->histogramfixedthreshold);
+// runs[runi]->plotCompareHistograms();
+ runs[runi]->plotAllHistograms(runs[runi]->histogramthreshold);
+ compareHistogramClassVector.push_back(runs[runi]->histogramthreshold->calibrated);
+// compareHistogramClassVector2.push_back(runs[runi]->histogram->calibrated);
+ // runs[runi]->plot1DHistogram(runs[runi]->histogramthreshold, runs[runi]->histogramthreshold->Veto, "gaus");
+// runs[runi]->plot1DHistogram(runs[runi]->histogramthreshold, runs[runi]->histogramthreshold->SeedPerc, "landau", 0);
+ compareHistogramVector.push_back(runs[runi]->histogramthreshold->calibrated->Seed);
+ runs[runi]->writeAllHistogramsToFile();
+ }
+ //cout << runs[runi]->histogram
+ }
+ }
+ }
+ plotAllRuns(&compareHistogramClassVector);
+ printSummaryTable(&compareHistogramClassVector);
+// plotAllRuns(&compareHistogramClassVector2);
+// plotAllRuns(&compareHistogramClassVector3);
+ writeObservableToFile();
+// plotAllRuns("seed threshold calibrated");
+// setCustomPath("Excel/");
+// writeObservableToFile("seed threshold calibrated");
+// writeObservableToFile("seed threshold");
+// writeObservableToFile("seed threshold");
+// writeObservableToFile("sum threshold");
+}
#include <fstream>
#include <iostream>
#include <iomanip>
+#include <TPaveText.h>
+#include <TLatex.h>
using namespace std;
+TString trimRunnumberAtBegin(TString str);
Int_t* ReadRunList();
Int_t ReadRunList(std::vector<int>*);
Bool_t plotAllRuns();
if (testifMixingCalibration(ptCompareHistogramClassVector)) return 1;
// legend entries
- Float_t height = ptCompareHistogramClassVector->size() * 0.04;
- TLegend* leg1 = new TLegend(0.4,0.89-height,0.89,0.89);//(0.6,0.7,0.89,0.89);
- leg1->SetTextSize(0.02);
+ Float_t height = ptCompareHistogramClassVector->size() * 0.045;
+ TLegend* leg1 = new TLegend(0.35,0.89-height,0.89,0.89);//(0.6,0.7,0.89,0.89);
+ leg1->SetTextSize(0.025);
+ leg1->SetFillStyle(0);
+ leg1->SetTextFont(12);
leg1->SetFillColor(0); leg1->SetBorderSize(0);
TLegend* leg2 = (TLegend*) leg1->Clone();
TString legendEntry;
+ TPaveText *owntitle = new TPaveText(0.15,0.9,0.930401,0.995,"nbNDC");
+ owntitle->SetFillStyle(0);
+ owntitle->SetBorderSize(0);
+ owntitle->SetTextAlign(22);
+ owntitle->SetTextSize(0.05);
+ owntitle->SetTextFont(42);
+ TPaveText *owntitle2 = (TPaveText*)owntitle->Clone();
+ TPaveText *owntitle3 = (TPaveText*)owntitle->Clone();
+ TPaveText *owntitle4 = (TPaveText*)owntitle->Clone();
+ gStyle->SetOptTitle(0);
+
Float_t lastbin1=0;
Float_t lastbin2=0;
Float_t lastbin3=0;
- Float_t lastbin4=0;
- TString canvastitle = Form("Summary");
- TTimeStamp* time = new TTimeStamp();
+ Float_t lastbin4=0;
+ TString canvastitle = Form("Summary");
+ for (UInt_t histogrami=0; histogrami < ptCompareHistogramClassVector->size(); histogrami++)
+ {
+ HistogramType* curhistogramclassp = ptCompareHistogramClassVector->at(histogrami);
+ canvastitle+= Form("_%d",curhistogramclassp->labbook->runnumber);
+ }
+ TTimeStamp* time = new TTimeStamp();
TString canvasname = Form("%d",time->GetNanoSec());
TCanvas* canvas = new TCanvas(canvasname, canvastitle, 1200, 800);
canvas->Divide(2,2);
{
HistogramType* curhistogramclassp = ptCompareHistogramClassVector->at(histogrami);
TH1F* curhistogramclone;
+
canvas->cd(1);
curhistogramclone = (TH1F*) curhistogramclassp->Seed->Clone();
+// TLatex Tl;
+// Tl.SetNDC();
+// Tl.DrawText(0.3, 0.2, "Titel titel");
+ //TPaveText *t = new TPaveText(0.0, 0.9, 0.3, 1.0, "brNDC"); // left-up
// curhistogramclone->SetLineColor(rootcolors[histogrami]);
+
curhistogramclone->Draw("SAME");
legendEntry = Form("%d %s", curhistogramclassp->labbook->runnumber, curhistogramclone->GetTitle());
leg1->AddEntry(curhistogramclone, legendEntry, "l");
lastbin1 = (curhistogramclone->GetBinCenter(curhistogramclone->FindLastBinAbove(2,1))>lastbin1)?curhistogramclone->GetBinCenter(curhistogramclone->FindLastBinAbove(2,1)):lastbin1;
curhistogramclone->SetAxisRange(0,lastbin1*1.1,"X");
gPad->SetLogy(1);
+ owntitle->Clear();
+ owntitle->AddText(trimRunnumberAtBegin(curhistogramclone->GetName()));
+ owntitle->Draw("SAME");
+
canvas->cd(2);
curhistogramclone = (TH1F*) curhistogramclassp->Sum->Clone();
// curhistogramclone->SetLineColor(rootcolors[histogrami]);
lastbin2 = (curhistogramclone->GetBinCenter(curhistogramclone->FindLastBinAbove(2,1))>lastbin2)?curhistogramclone->GetBinCenter(curhistogramclone->FindLastBinAbove(2,1)):lastbin2;
curhistogramclone->SetAxisRange(0,lastbin2*1.1,"X");
gPad->SetLogy(1);
+ owntitle2->Clear();
+ owntitle2->AddText(trimRunnumberAtBegin(curhistogramclone->GetName()));
+ owntitle2->Draw("SAME");
+
canvas->cd(3);
curhistogramclone = (TH1F*) curhistogramclassp->Veto->Clone();
// curhistogramclone->SetLineColor(rootcolors[histogrami]);
leg1->Draw("SAME");
lastbin3 = (curhistogramclone->GetBinCenter(curhistogramclone->FindLastBinAbove(2,1))>lastbin3)?curhistogramclone->GetBinCenter(curhistogramclone->FindLastBinAbove(2,1)):lastbin3;
curhistogramclone->SetAxisRange(0,lastbin3*1.1,"X");
+ owntitle3->Clear();
+ owntitle3->AddText(trimRunnumberAtBegin(curhistogramclone->GetName()));
+ owntitle3->Draw("SAME");
+
canvas->cd(4);
curhistogramclone = (TH1F*) curhistogramclassp->Noise->Clone();
// curhistogramclone->SetLineColor(rootcolors[histogrami]);
legendEntry = Form("%d Noise: %.2f + %.2f - %.2f",curhistogramclassp->labbook->runnumber, curhistogramclassp->avgNoise, curhistogramclassp->avgNoisePlus, curhistogramclassp->avgNoiseMinus);
leg2->AddEntry(curhistogramclone, legendEntry, "l");
leg2->Draw();
+ owntitle4->Clear();
+ owntitle4->AddText(trimRunnumberAtBegin(curhistogramclone->GetName()));
+ owntitle4->Draw("SAME");
}
+ canvas->Update();
+ //gStyle->SetOptTitle(1);
+
+ TImageDump *img = new TImageDump(savepathresults + "/" + canvastitle + ".png");
+ canvas->Paint();
+ img->Close();
+
+ TFile *f = new TFile(savepathresults + "/" + canvastitle + ".root","RECREATE");
+ f->cd();
+ f->Append(canvas);
+ f->Append(img);
+ f->Write();
+
return 0;
}
return 1;
cout << left << setw(width*1) << setfill(' ') << "Cut type: "<< left << setw(width*8) << setfill(' ') << ptCompareHistogramClassVector->at(0)->histogramdescription << endl;
cout << left << setw(width-5) << setfill(' ') << "Runnumber";
+ cout << left << setw(width-10) << setfill(' ') << "Chp#";
cout << left << setw(width-10) << setfill(' ') << "Mtrx";
Float_t printradion = 0;
for (vector<HistogramType*>::iterator curHistogramClass = ptCompareHistogramClassVector->begin(); curHistogramClass != ptCompareHistogramClassVector->end(); curHistogramClass++)
printIntegral += (*curHistogramClass)->sr90IntegralVal;
if (printIntegral != 0) cout << left << setw(width) << setfill(' ') << "Integral";
cout << left << setw(width) << setfill(' ') << "Seed Peak";
+ cout << left << setw(width) << setfill(' ') << "Veto Peak";
cout << left << setw(width) << setfill(' ') << "Noise";
+ cout << left << setw(width) << setfill(' ') << "Noise threshold";
+ //cout << left << setw(width) << setfill(' ') << "Frames";
cout << endl;
for (UInt_t histogrami=0; histogrami < ptCompareHistogramClassVector->size(); histogrami++)
{
HistogramType* curhistogramclassp = ptCompareHistogramClassVector->at(histogrami);
cout << left << setw(width-5) << setfill(' ') << curhistogramclassp->labbook->runnumber;
+ cout << left << setw(width-10) << setfill(' ') << curhistogramclassp->labbook->chip;
cout << left << setw(width-10) << setfill(' ') << curhistogramclassp->labbook->matrix;
if (printradion != 0) cout << left << setw(width-5) << setfill(' ') << curhistogramclassp->labbook->radDoseIon;
if (printradnonion != 0) cout << left << setw(width-5) << setfill(' ') << curhistogramclassp->labbook->radDoseNonIon;
if (printStoN != 0) cout << left << setw(width) << setfill(' ') << printTableElement(curhistogramclassp->StoN,ptCompareHistogramClassVector->at(0)->StoN);
if (printIntegral != 0) cout << left << setw(width) << setfill(' ') << printTableElement(curhistogramclassp->sr90IntegralVal,ptCompareHistogramClassVector->at(0)->sr90IntegralVal);
cout << left << setw(width) << setfill(' ') << printTableElement(curhistogramclassp->posSeed,ptCompareHistogramClassVector->at(0)->posSeed);
+ cout << left << setw(width) << setfill(' ') << printTableElement(curhistogramclassp->posVeto,ptCompareHistogramClassVector->at(0)->posVeto);
cout << left << setw(width) << setfill(' ') << printTableElement(curhistogramclassp->avgNoise,ptCompareHistogramClassVector->at(0)->avgNoise);
+ cout << left << setw(width) << setfill(' ') << printTableElement(curhistogramclassp->noisethresholdborder,ptCompareHistogramClassVector->at(0)->noisethresholdborder);
+ //cout << left << setw(width) << setfill(' ') << printTableElement(curhistogramclassp->frames_found,ptCompareHistogramClassVector->at(0)->frames_found);
cout << "" << endl;
}
cout << right << setw(width*9) << setfill('=') << " " << endl;
string to_str_w_prec(const Float_t a_value, const int precision)
{
std::ostringstream out;
- if (abs(a_value) > 1) {
+ if (abs(a_value) > 1 && abs(a_value) < 10000) {
out << std::fixed << std::setprecision(precision) << a_value;
} else {
out << std::scientific << std::setprecision(precision) << a_value << std::fixed; out.setf(ios_base::fixed);
return out.str();
}
+TString trimRunnumberAtBegin(TString str) {
+ size_t i = 0;
+ while(isdigit(str(i++)));
+ return str.Remove(0, i);
+}
+
#define __HISTOGRAMTYPE__C
#include "HistogramType.h"
+#include <Rtypes.h>
using namespace std;
initHistogram(Sum, "Sum" + histogramdescription, color, style);
initHistogram(Veto, "Veto" + histogramdescription, color, style);
initHistogram(Noise, "Noise" + histogramdescription, color, style);
+ initHistogram(SeedPerc, "Seed Percentage" + histogramdescription, color, style);
+ SeedPerc->SetBins(120, 0, 120);
+ SeedPerc->GetXaxis()->SetRangeUser(0,50);
+ SeedPerc->GetYaxis()->SetTitle(Form("Entries [1/%%]"));
+ SeedPerc->GetXaxis()->SetTitle("Q_coll [%]");
Noise->SetBins(cursystempar->nbinsnoise, 0, cursystempar->maxbinnoise);
}
if (Sum != 0) calibrateHistogram(calibrated->Sum, Sum);
if (Veto != 0) calibrateHistogram(calibrated->Veto, Veto);
if (Noise != 0) calibrateHistogram(calibrated->Noise, Noise);
+ if (SeedPerc != 0) calibrated->SeedPerc = SeedPerc;
if (histAvgCluster != 0) calibrate2DHistogramCounts(calibrated->histAvgCluster, histAvgCluster);
calibrated->posSeed = posSeed * gain;
calibrated->posSum = posSum * gain;
calibrated->posVeto = posVeto * gain;
+ calibrated->posSeedPerc = posSeedPerc;
+ calibrated->sigmaSeedPerc = sigmaSeedPerc;
calibrated->avgNoise = avgNoise * gain;
calibrated->avgNoisePlus = avgNoisePlus * gain;
calibrated->avgNoiseMinus = avgNoiseMinus * gain;
void HistogramType::calibrateHistogram(TH1F* &histogrampointernew, TH1F* &histogrampointerold) {
histogrampointernew = (TH1F*)histogrampointerold->Clone();
- histogrampointernew->SetName(Form("%sC", histogrampointerold->GetName()));
- histogrampointernew->SetTitle(Form("%sC", histogrampointerold->GetTitle()));
+ histogrampointernew->SetName(Form("%s Calibr.", histogrampointerold->GetName()));
+ histogrampointernew->SetTitle(Form("%s Calibr.", histogrampointerold->GetTitle()));
histogrampointernew->GetXaxis()->SetTitle("Q_coll [e]");
int nbins = histogrampointernew->GetXaxis()->GetNbins();
double new_bins[nbins+1];
void HistogramType::calibrate2DHistogramCounts(TH2F* &histogrampointernew, TH2F* &histogrampointerold ) {
histogrampointernew = (TH2F*)histogrampointerold->Clone();
- histogrampointernew->SetName(Form("%sC", histogrampointerold->GetName()));
- histogrampointernew->SetTitle(Form("%sC", histogrampointerold->GetTitle()));
+ histogrampointernew->SetName(Form("%s Calibr.", histogrampointerold->GetName()));
+ histogrampointernew->SetTitle(Form("%s Calibr.", histogrampointerold->GetTitle()));
histogrampointernew->GetZaxis()->SetTitle("Q_coll [e]");
int nbinsx = histogrampointernew->GetXaxis()->GetNbins();
int nbinsy = histogrampointernew->GetYaxis()->GetNbins();
}
}
-Float_t HistogramType::FitPerform(TH1F* histogrampointer, TString fitFuncType, Bool_t verbose, Double_t* parameters) {
+Double_t* HistogramType::FitPerform(TH1F* histogrampointer, TString fitFuncType, Bool_t verbose, Float_t fitstart) {
+ Double_t* parameters = 0;
Float_t posMax = 0;
Float_t posMax2 = 0;
Float_t posMaxValHist = histogrampointer->GetXaxis()->GetXmax();
// posMaxValHist/10 for USB system, the value is 90
Float_t noiseborder = 90;
- if (noisethresholdborder>=0)
+ if (fitstart >= 0)
+ noiseborder = fitstart;
+ else if (noisethresholdborder>=0 )
noiseborder = noisethresholdborder;
- if (fitFuncType.Contains("gaus"))
+ if (fitFuncType.EqualTo("gaus"))
{
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());
histogrampointer->Fit(fitFunc, "N,Q,W", "", noiseborder, posMaxValHist);
posMax = fitFunc->GetMaximumX(); // Methode 2
}
+ parameters = (Double_t *)calloc(3, sizeof(Double_t));
+ for (Int_t pari=0; pari<3; pari++) {
+ //cout << colorcyan << fitFunc->GetParameter(pari) << endlr;
+ parameters[pari]=fitFunc->GetParameter(pari);
+ }
Float_t sigma = fitFunc->GetParameter(2);
posMax2 = fitFunc->GetMaximumX(); // Methode 2
// if (verbose)
cout << colorred << " Could not find " << histogrampointer->GetName() << " peak" << endlr;
}
}
- return 0;
+ parameters[1] = 0;
+ return parameters;
}
else if (sigma > 40 || peakposdifperc>0.1)
{
Float_t minFitMax = 1000;
Float_t maxFitMax = 1000;
histogrampointer->Fit(fitFunc, "N,Q,W", "", noiseborder, posMaxValHist);
+ parameters = (Double_t *)calloc(3, sizeof(Double_t));
+ for (Int_t pari=0; pari<3; pari++)
+ parameters[pari]=fitFunc->GetParameter(pari);
+
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.
// cout << "fitFunc->GetParameter(0): " << fitFunc->GetParameter(0) << endl;
// cout << "fitFunc->GetParameter(1): " << fitFunc->GetParameter(1) << endl;
posMax2 = fitMax1 + fitMax2 + fitMax3 - minFitMax - maxFitMax;
if (abs(posMax-posMax2)/posMax > 0.11)
{
- cout << coloryellow << " Please check the Landau MPV value fit, as two alternate methods revealed results wich differ " << abs(posMax-posMax2)/posMax*100 << " %." << endlr;
+ cout << coloryellow << " Please check the Landau MPV value fit of " << histogrampointer->GetName() << ", as two alternate methods revealed results wich differ " << abs(posMax-posMax2)/posMax*100 << " %." << endlr;
cout << " Primary, new MPV method: " << posMax << endl;
cout << " Secondary, mean maxima mathod: " << posMax2 << endl;
}
// fitFcn->FixParameter(3,-22.43016284);
//histogrampointer->Fit("fitFcn","V+","ep");
- histogrampointer->Fit("fitFcn","Q,W","ep");
+ histogrampointer->Fit("fitFcn","Q,W","ep");
+ parameters = (Double_t *)calloc(4, sizeof(Double_t));
for (Int_t pari=0; pari<4; pari++)
parameters[pari]=fitFcn->GetParameter(pari);
if (verbose)
}
}
- return posMax;
+ return parameters;
}
Bool_t HistogramType::calculteCCE(Bool_t verbose) {
TH1F* Noise = 0;
/// histogram with cluster data, rotated if staggered
TH2F* histAvgCluster = 0;
+ /// Percentage of charge gathered by seed pixel (Seed to Sum ratio)
+ TH1F* SeedPerc = 0;
//*****************
// FITTING RESULTS OF TH1F HISTOGRAMS
Double_t sr90IntegralVal = -1;
Double_t sr90IntegralErr = -1;
+ /// Peak and sigma of Seed to Sum ratio
+ Float_t posSeedPerc = 0;
+ Float_t sigmaSeedPerc = 0;
+
+
/// threshold for integrating the Sr90 spectrum, is set dynamically in @c integrateSr90Spectra()
Float_t noisethresholdborder = -1;
* @return peak position of the fit
*
*/
- Float_t FitPerform(TH1F* histogrampointer, TString fitFuncType, Bool_t verbose = 0, Double_t* parameters = 0);
+ Double_t* FitPerform(TH1F* histogrampointer, TString fitFuncType, Bool_t verbose = 0, Float_t fitstart = -1);
/** @brief calculates Charge Collection Efficiency if Fe55 run */
Bool_t calculteCCE(Bool_t verbose=false);
/**
fOk = true;
}
cout<<"-----------------------"<<endl;
- cout<< "TOTAL FRAMES FOUND: "<<fEventsSum<<endl;
+ cout << "TOTAL FRAMES FOUND: "<< colorwhite << std::scientific << fEventsSum*1.0 << endlr; std::cout.unsetf ( std::ios::scientific );
if (FileTotalEvNbInConfig != fEventsSum)
{
cout<< "-----------------------"<<endl;
cout << "| CCE_in_Perc_1DB: " << std::right << colorwhite << labbook.CCE_in_Perc_1DB << endlr;
cout << "| StoN: " << std::right << colorwhite << labbook.StoN << endlr;
cout << "| Sr90IntegralVal: " << std::right << colorwhite << std::scientific << labbook.Sr90IntegralVal << endlr; std::cout.unsetf ( std::ios::scientific );
- cout << "| frames_foundDB : " << std::right << colorwhite << labbook.frames_foundDB << endlr;
+ cout << "| frames_foundDB : " << std::right << colorwhite << std::scientific << labbook.frames_foundDB*1.0 << endlr; std::cout.unsetf ( std::ios::scientific );
cout << "|______________________________ " << endlr;
cout << endlr;
return 0;
constructUpdateString(&sqlupdatequery, "SumPeak", histogram->posSum, 4);
constructUpdateString(&sqlupdatequery, "SeedPeak", histogram->posSeed, 4);
constructUpdateString(&sqlupdatequery, "VetoPeak", histogram->posVeto, 4);
- constructUpdateString(&sqlupdatequery, "Avg.Noise", histogram->calibrated->avgNoise);
- constructUpdateString(&sqlupdatequery, "Avg.Noise+", histogram->calibrated->avgNoisePlus, 2);
- constructUpdateString(&sqlupdatequery, "Avg.Noise-", histogram->calibrated->avgNoiseMinus, 2);
+ if (histogram->calibrated != 0)
+ constructUpdateString(&sqlupdatequery, "Avg.Noise", histogram->calibrated->avgNoise);
+ if (histogram->calibrated != 0)
+ constructUpdateString(&sqlupdatequery, "Avg.Noise+", histogram->calibrated->avgNoisePlus, 2);
+ if (histogram->calibrated != 0)
+ constructUpdateString(&sqlupdatequery, "Avg.Noise-", histogram->calibrated->avgNoiseMinus, 2);
constructUpdateString(&sqlupdatequery, "CCE_1", histogram->CCE_in_Perc_1);
constructUpdateString(&sqlupdatequery, "CCE_25", histogram->CCE_in_Perc_25);
constructUpdateString(&sqlupdatequery, "StoN", histogram->StoN, 3);
constructUpdateString(&sqlupdatequery, "Avg.NoiseADC", histogram->avgNoise);
constructUpdateString(&sqlupdatequery, "Frames_found", frames_found,100000000);
- constructUpdateString(&sqlupdatequery, "Sr90IntegralVal", histogramfixedthreshold->calibrated->sr90IntegralVal,1000000000);
+ if (histogram->calibrated != 0)
+ constructUpdateString(&sqlupdatequery, "Sr90IntegralVal", histogramfixedthreshold->calibrated->sr90IntegralVal,1000000000);
if (sqlupdatequery.length()>0)
{
notSeedSum += processed->fFrameInfo.p[clusteri][hiti];
}
}
- histogram->Sum->Fill(pixelSum);
+ histogram->Sum->Fill(pixelSum);
+
+ // seed percentage spectrum
+ histogram->SeedPerc->Fill(processed->fFrameInfo.p[12][hiti]/pixelSum*100);
// veto spectrum
if (TMath::Abs(notSeedSum) < cursystemparam.vetothreshold && (labbook.source.Contains("Fe")||labbook.source.Contains("Cd")))
histogramthreshold->Seed->Fill(processed->fFrameInfo.p[12][hiti]);
histogramthreshold->Sum->Fill(pixelSum);
+ histogramthreshold->SeedPerc->Fill(processed->fFrameInfo.p[12][hiti]/pixelSum*100);
if (TMath::Abs(notSeedSum) < cursystemparam.vetothreshold && (labbook.source.Contains("Fe")||labbook.source.Contains("Cd")))
histogramthreshold->Veto->Fill(processed->fFrameInfo.p[12][hiti]); // histogram with the single pixel
}
histogramfixedthreshold->Seed->Fill(processed->fFrameInfo.p[12][hiti]);
histogramfixedthreshold->Sum->Fill(pixelSum);
+ histogramfixedthreshold->SeedPerc->Fill(processed->fFrameInfo.p[12][hiti]/pixelSum*100);
if (TMath::Abs(notSeedSum) < cursystemparam.vetothreshold && (labbook.source.Contains("Fe")||labbook.source.Contains("Cd")))
histogramfixedthreshold->Veto->Fill(processed->fFrameInfo.p[12][hiti]); // histogram with the single pixel
}
// gROOT->SetBatch(kTRUE);
for (vector<HistogramType*>::iterator curHistogramClass = HistogramClassVector.begin(); curHistogramClass != HistogramClassVector.end(); curHistogramClass++) {
+ Double_t* parameters = (Double_t *)calloc(3, sizeof(Double_t));
(*curHistogramClass)->FindNoisethresholdborder((*curHistogramClass)->Seed, false);
if (labbook.source.Contains("Fe")||labbook.source.Contains("Cd"))
- (*curHistogramClass)->posVeto=(*curHistogramClass)->FitPerform((*curHistogramClass)->Veto, "gaus", true);
- (*curHistogramClass)->posSeed=(*curHistogramClass)->FitPerform((*curHistogramClass)->Seed, "landau", true);
- (*curHistogramClass)->posSum=(*curHistogramClass)->FitPerform((*curHistogramClass)->Sum, "gaus", true);
+ parameters = (*curHistogramClass)->FitPerform((*curHistogramClass)->Veto, "gaus", true);
+ (*curHistogramClass)->posVeto = parameters[1];
+ parameters = (*curHistogramClass)->FitPerform((*curHistogramClass)->Seed, "landau", true);
+ (*curHistogramClass)->posSeed = parameters[1];
+ parameters = (*curHistogramClass)->FitPerform((*curHistogramClass)->Sum, "gaus", true);
+ (*curHistogramClass)->posSum = parameters[1];
+
+ parameters =(*curHistogramClass)->FitPerform((*curHistogramClass)->SeedPerc, "landau", true);
+ (*curHistogramClass)->posSeedPerc = parameters[1];
+ (*curHistogramClass)->sigmaSeedPerc = parameters[2];
+
for (Int_t bini=1; bini <= cursystemparam.nbins; bini++) { // TODO: rescaled histogram to number of frames found, remove the inner for loop later
// (*curHistogramClass)->Seed->SetBinContent(bini,(*curHistogramClass)->Seed->GetBinContent(bini)/(frames_found*1.0));
// (*curHistogramClass)->Sum->SetBinContent(bini,(*curHistogramClass)->Sum->GetBinContent(bini)/(frames_found*1.0));
}
+ for (Int_t bini=1; bini <= 100; bini++) {
+ (*curHistogramClass)->SeedPerc->SetBinContent(bini,(*curHistogramClass)->SeedPerc->GetBinContent(bini)/0.01/((*curHistogramClass)->SeedPerc->GetEntries()));
+ }
}
histogramfixedthreshold->noisethresholdborder=0;
// gROOT->SetBatch(kFALSE);
// create lorentz fit of a slice
TH1F* xslicetroughcluster = new TH1F(Form("%s_xslice", HistogramTypepointer->histAvgCluster->GetTitle()),"X slice",HistogramTypepointer->histAvgCluster->GetXaxis()->GetNbins(),HistogramTypepointer->histAvgCluster->GetXaxis()->GetBinLowEdge(1),HistogramTypepointer->histAvgCluster->GetXaxis()->GetBinUpEdge(HistogramTypepointer->histAvgCluster->GetXaxis()->GetNbins()));
- Double_t xslicetroughclusterpar[4];
+ Double_t* xslicetroughclusterpar = (Double_t *)calloc(4, sizeof(Double_t)); // allocate 6 parameters for safety, maximum 4 used at the moment
Int_t middlebin = (int)(HistogramTypepointer->histAvgCluster->GetXaxis()->GetNbins()/2.0 + 0.5);
for (Int_t bini=1; bini <= HistogramTypepointer->histAvgCluster->GetXaxis()->GetNbins(); bini++)
xslicetroughcluster->SetBinContent(bini,HistogramTypepointer->histAvgCluster->GetBinContent(bini,middlebin));
TH1F* yslicetroughcluster = new TH1F(Form("%s_yslice", HistogramTypepointer->histAvgCluster->GetTitle()),"Y slice",HistogramTypepointer->histAvgCluster->GetYaxis()->GetNbins(),HistogramTypepointer->histAvgCluster->GetYaxis()->GetBinLowEdge(1),HistogramTypepointer->histAvgCluster->GetYaxis()->GetBinUpEdge(HistogramTypepointer->histAvgCluster->GetYaxis()->GetNbins()));
- Double_t yslicetroughclusterpar[4];
+ Double_t* yslicetroughclusterpar = (Double_t *)calloc(4, sizeof(Double_t)); // allocate 6 parameters for safety, maximum 4 used at the moment
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));
canvas->cd(1);
TPad* firstpart = (TPad*)canvas->GetPad(1);
firstpart->SetGrid();
- HistogramTypepointer->FitPerform(xslicetroughcluster,"lorentz", false, &xslicetroughclusterpar[0]);
-
+ xslicetroughclusterpar = HistogramTypepointer->FitPerform(xslicetroughcluster,"lorentz");
canvas->cd(2);
TPad* secondpart = (TPad*)canvas->GetPad(2);
secondpart->SetGrid();
- HistogramTypepointer->FitPerform(yslicetroughcluster,"lorentz", false, &yslicetroughclusterpar[0]);
+ yslicetroughclusterpar = HistogramTypepointer->FitPerform(yslicetroughcluster,"lorentz");
canvas->Draw();
l->SetLineStyle(2); // dashed
l->Draw("same");
- TString legendEntry = TString(Form("peak position: %.1f",xVal ));
+ TString legendEntry;
+ if (abs(xVal) < 1)
+ legendEntry = TString(Form("peak position: %.2f",xVal ));
+ else
+ legendEntry = TString(Form("peak position: %.1f",xVal ));
TLegend* leg = new TLegend(0.65,0.65,0.80,0.80);//(0.6,0.7,0.89,0.89);
leg->SetFillColor(0);
leg->SetBorderSize(0);
+ leg->SetFillStyle(0);
leg->AddEntry((TObject*) 0, legendEntry, "");
leg->SetTextSize(0.025);
leg->Draw();
}
}
-TCanvas* Run::plot1DHistogram(HistogramType* HistogramTypepointer, TH1F* onehistogram, TString fitFuncType, TString titlestr, TString legendstr)
+TCanvas* Run::plot1DHistogram(HistogramType* HistogramTypepointer, TH1F* onehistogram, TString fitFuncType, Float_t fitstart, TString titlestr, TString legendstr)
{
if (onehistogram != nullptr)
{
TCanvas* canvas = new TCanvas(canvasname, canvastitle, 900, 700);
onehistogram->SetTitle(titlestr);
onehistogram->Draw();
- Float_t maxValue = HistogramTypepointer->FitPerform(onehistogram, fitFuncType, true);
+ Double_t* parameters = (Double_t *)calloc(6, sizeof(Double_t)); // allocate 6 parameters for safety, maximum 4 used at the moment
+ parameters = HistogramTypepointer->FitPerform(onehistogram, fitFuncType, true, fitstart);
+ Float_t maxValue = parameters[1];
plotVerticalLine(onehistogram, maxValue);
- TLegend* leg = new TLegend(0.4,0.8,0.89,0.89);//(0.6,0.7,0.89,0.89);
+ Float_t startvalue = onehistogram->GetBinLowEdge(onehistogram->FindFirstBinAbove(0));
+ Float_t endrange = onehistogram->GetBinCenter(onehistogram->FindLastBinAbove(0));
+ onehistogram->GetXaxis()->SetRangeUser(startvalue,endrange);
+ 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(0.03);
+ leg->SetTextSize(0.025);
leg->Draw();
canvas -> SaveAs( savepathresults + "/" + runcode + " " + onehistogram->GetName() + ".eps");
*/
Bool_t plotClusterDistribution(HistogramType*);
- TCanvas* plot1DHistogram(HistogramType* histogramtypepointer, TH1F* onehistogram, TString fitFuncType = "landau", TString titlestr = "", TString legendstr = "");
+ TCanvas* plot1DHistogram(HistogramType* histogramtypepointer, TH1F* onehistogram, TString fitFuncType = "landau", Float_t fitstart=-1, TString titlestr = "", TString legendstr = "");
pixelinfo pixelinfoMi34[32];
--- /dev/null
+{
+ ////////////////////////////////////////////////////////////////////////////
+ // //
+ // who: Pete Alonzi (lpa2a@virginia.edu) //
+ // what: rootlogon file (~/.rootlogon.C) //
+ // when: last update: 2009_June_11 //
+ // where: galileo.phys.virginia.edu //
+ // why: change the default root canvas to acceptable configuration //
+ // //
+ // This file is run when you open root. //
+ // Just place it in your home directory and it works automatically. //
+ // If you make a change to this file simply start //
+ // a new root session and the changes will be implemented. //
+ // //
+ // If you did not install roofit then there will be an error //
+ // message when you login, it can be ignored. //
+ // //
+ ////////////////////////////////////////////////////////////////////////////
+
+ // Definition of new styles
+ TStyle *Nab_collaboration = new TStyle("Nab_Collaboration","How Nab_Collaboration likes it");
+ TStyle *Nab_collaboration_work = new TStyle("Nab_Collaboration_Work","How Nab_Collaboration likes it with stats");
+
+ // Set the default parameters for style Nab_collaboration
+ Nab_collaboration->SetCanvasBorderMode(0); // Removes Canvas Border
+ Nab_collaboration->SetPadBorderMode(0); // Removes Pad Border
+ Nab_collaboration->SetCanvasColor(0); // Changes Canvas color to white
+ Nab_collaboration->SetPadColor(0); // Changes Pad color to white
+ Nab_collaboration->SetStatColor(0); // Changes Stats bg color to white
+ Nab_collaboration->SetTitleFillColor(0); // Changes Title bg color to white
+ Nab_collaboration->SetLabelFont(42,"xyz"); // Changes Label Font
+ Nab_collaboration->SetTitleFont(42,"xyz"); // Changes Axis Title Font
+ Nab_collaboration->SetPadTickX(1); // Sets tic marks on both horizontal axes
+ Nab_collaboration->SetPadTickY(1); // Sets tic marks on both vertical axes
+ Nab_collaboration->SetTickLength(0.018,"xyz"); // Sets tic length
+ Nab_collaboration->SetOptStat(0); // Turns off Statistics display
+ Nab_collaboration->SetOptTitle(0); // Turns off Title display
+ Nab_collaboration->SetHistLineWidth(2); // Changes Histogram Line width
+ Nab_collaboration->SetFrameBorderMode(0); // Removes the Frame Border
+ Nab_collaboration->SetFrameFillStyle(0);
+ Nab_collaboration->SetCanvasDefH(494); // Sets Default Canva Height
+ Nab_collaboration->SetCanvasDefW(800); // Sets Default Canvas Width
+ Nab_collaboration->SetPalette(1);
+
+
+ // The next for commands set the default margin size
+ // n.b. the margins do not take axis labels into account! grr!!
+ Nab_collaboration->SetPadTopMargin(0.1); // Set Margin Top
+ Nab_collaboration->SetPadRightMargin(0.1); // Set Margin Right
+ Nab_collaboration->SetPadBottomMargin(0.1); // Set Margin Bottom
+ Nab_collaboration->SetPadLeftMargin(0.1); // Set Margin Left
+
+ //make a nice palette
+ int NRGBs = 7, NCont = 999;
+ Nab_collaboration->SetNumberContours(NCont);
+ Double_t stops[7] = { 0.00, 0.10, 0.25, 0.45, 0.60, 0.75, 1.00 };
+ Double_t red[7] = { 1.00, 0.00, 0.00, 0.00, 0.97, 0.97, 0.10 };
+ Double_t green[7] = { 1.00, 0.97, 0.30, 0.40, 0.97, 0.00, 0.00 };
+ Double_t blue[7] = { 1.00, 0.97, 0.97, 0.00, 0.00, 0.00, 0.00 };
+ TColor::CreateGradientColorTable(NRGBs, stops, red, green, blue, NCont);
+
+ // Make Nab_collaboration_work a copy of Nab_collaboration and remove stats
+ Nab_collaboration->Copy(*Nab_collaboration_work);
+ Nab_collaboration_work->SetOptStat(1);
+ Nab_collaboration_work->SetOptTitle(1);
+ Nab_collaboration_work->SetPadTopMargin(0.1);
+ Nab_collaboration_work->SetPadRightMargin(0.1);
+
+ // Select Which Style to
+ gROOT->SetStyle("Nab_Collaboration_Work");
+ // gROOT->SetStyle("Nab_Collaboration");
+
+
+ // Use the RooFit functions
+ // using namespace RooFit;
+
+ // Force Root to run Nab_collaboration/Nab_collaboration_work style
+ gROOT->ForceStyle();
+
+}
jspc29 / radhard.git / commitdiff