/*
* From here on, the code can also be used as a macro
* Note though, that CINT may report errors where there are none
in C++. E.g. this happens here where CINT says that f1 is
out of scope ...
==>> put your code here
(remember to update the name of you Macro in the
lines above if you intend to comile the code)
*/
void ExampleMacro() {
// Create a histogram, fill it with random gaussian numbers
TH1F *h = new TH1F ("h", "example histogram", 100, -5.,5.);
h->FillRandom("gaus",1000);
// draw the histogram
h->DrawClone();
/* - Create a new ROOT file for output
- Note that this file may contain any kind of ROOT objects, histograms,
pictures, graphics objects etc.
- the new file is now becoming the current directory */
TFile *f1 = new TFile("ExampleMacro.root","RECREATE","ExampleMacro");
// write Histogram to current directory (i.e. the file just opened)
h->Write();
// Close the file.
// (You may inspect your histogram in the file using the TBrowser class)
f1->Close();
}
void SPEFit(char * fLEDname, char * fPEDname, int run, int LED_amp, double cutmax = 250.0)
{
//set plotting styles
gStyle->SetCanvasColor(0);
gStyle->SetPadColor(0);
gStyle->SetCanvasBorderMode(0);
gStyle->SetFrameBorderMode(0);
gStyle->SetStatColor(0);
gStyle->SetPadTickX(1);
gStyle->SetPadTickY(1);
//set file names
stringstream out_fname;
stringstream out_fname1;
out_fname<<"SPEconstants_Run_"<<run<<".txt";
out_fname1<<"SPEspec_Run_"<<run<<".txt";
ofstream constants_file(out_fname.str().c_str(),ios_base::trunc);
//ofstream constants_file1(out_fname1.str().c_str(),ios_base::trunc);
constants_file<<"Run "<<run<<endl;
constants_file<<"type SPE"<<endl;
constants_file<<"LED_amplitude "<<LED_amp<<endl<<endl;
constants_file<<endl<<"LED_amplitude Depth Phi Eta Ped_mean Ped_mean_err Ped_RMS Ped_RMS_err SPEPeak_RMS SPEPeak_RMS_err Gain Gain_err Normalized_Chi2 MeanPE_fit MeanPE_fit_err MeanPE_estimate PE5flag"<<endl;
out_fname.str("");
out_fname<<"SPEdistributions_Run_"<<run<<".txt";
out_fname.str("");
out_fname<<"SPEextra_Run_"<<run<<".txt";
//ofstream extra_file(out_fname.str().c_str(),ios_base::trunc);
double scale = 1.0;
scale = 2.6; //Need to scale up HF charge
double fC2electrons = 6240.; //convert fC to #electrons
char spename[128], pedname[128], spehistname[128];
TFile *tfLED = new TFile(fLEDname);
TFile *tfPED = new TFile(fPEDname);
//const int NnewBins = 106;
//double binsX[NnewBins] = {0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58,60,62,64,66,68,70,72,74,76,78,80,82,84,86,88,90,92,94,96,98,100,102,104,106,108,110,112,114,116,118,120,122,124,126,128,130,132,134,136,138,140,142,144,146,148,150,152,154,156,158,160,162,164,166,168,170,180,190,200,210,220,230,240,250,266,282,298,316,336,356,378,404,430,456,482,500};
const int NnewBins = 80;
double binsX[NnewBins] = {0,3,6,9,12,15,18,21,24,27,30,33,36,39,42,45,48,51,54,57,60,63,66,69,72,75,78,81,84,87,90,93,96,99,102,105,108,111,114,117,120,123,126,129,132,135,138,141,144,147,150,153,156,159,162,165,168,171,174,177,180,190,200,210,220,230,240,250,266,282,298,316,336,356,378,404,430,456,482,500};
TH1F* hspe = new TH1F("hspe","hspe",NnewBins-1,binsX);
int NDepth = 2; //number of depths
int MinDepth = 1;
int MaxDepth = 2;
int MinEta = 29;
int MaxEta = 41;
int MinPhi = 41;
int MaxPhi = 53;
TCanvas *Carray[NDepth+1][MaxPhi+1];
bool drawflag[NDepth+1][MaxPhi+1];
TH1F *LED[NDepth+1][MaxEta+1][MaxPhi+1];
TH1F *PED[NDepth+1][MaxEta+1][MaxPhi+1];
for(int iDepth = MinDepth; iDepth <= MaxDepth; iDepth++){
for(int iPhi = MinPhi; iPhi <= MaxPhi; iPhi++){
bool nonNull = false;
for(int iEta = MinEta; iEta <= MaxEta; iEta++){
sprintf(spename,"Analyzer/CommonDir/ResPlotDir/Histo_for_Depth_%d_Eta_%d_Phi_%d",iDepth,iEta,iPhi);
LED[iDepth][iEta][iPhi]=(TH1F *)tfLED->Get(spename);
if(LED[iDepth][iEta][iPhi]) nonNull = true;
sprintf(spename,"Analyzer/CommonDir/ResPlotDir/Histo_for_Depth_%d_Eta_%d_Phi_%d",iDepth,iEta,iPhi);
PED[iDepth][iEta][iPhi]=(TH1F *)tfPED->Get(spename);
}
drawflag[iDepth][iPhi] = false;
char canvname[16];
sprintf(canvname, "c_%d_%d", iDepth,iPhi);
if(nonNull){ //only create canvas if distributions exist
Carray[iDepth][iPhi] = new TCanvas(canvname,canvname,1200,700);
Carray[iDepth][iPhi]->Divide(5,3);
}
}
}
int HV=0;
for(int iDepth = MinDepth; iDepth <= MaxDepth; iDepth++){
for(int iPhi = MinPhi; iPhi <= MaxPhi; iPhi++){
for(int iEta = MinEta; iEta <= MaxEta; iEta++){
//cout<<iDepth<<" "<<iPhi<<" "<<iEta<<endl;
if(!LED[iDepth][iEta][iPhi]) continue;
sprintf(spehistname,"led %d %d %d",iDepth,iEta,iPhi);
TH1F *hspe_temp = (TH1F *)LED[iDepth][iEta][iPhi]->Clone(spehistname);
sprintf(spehistname,"ped %d %d %d",iDepth,iEta,iPhi);
TH1F *hped = (TH1F *)PED[iDepth][iEta][iPhi]->Clone(spehistname);
hspe->Reset();
sprintf (spehistname, "SumLED_Depth_%d_Eta_%d_Phi_%d",iDepth,iEta,iPhi);
hspe->SetTitle(spehistname);
//combine bins of original SPE histogram
for(int ib=1; ib<=hspe_temp->GetNbinsX(); ib++) {
double bin_center = hspe_temp->GetBinCenter(ib);
if(bin_center>hspe->GetXaxis()->GetXmax()) continue;
int newbin = hspe->FindBin(bin_center);
double new_content = hspe->GetBinContent(newbin) + hspe_temp->GetBinContent(ib);
double new_error = sqrt(pow(hspe->GetBinError(newbin),2)+pow(hspe_temp->GetBinError(ib),2));
hspe->SetBinContent(newbin,new_content);
hspe->SetBinError(newbin,new_error);
}
TH1F* hspe_unscaled = (TH1F*)hspe->Clone("hspe_unscaled");
//renormalize bins of new SPE histogram
for(int ib=1; ib<=hspe->GetNbinsX(); ib++) {
double new_content = hspe->GetBinContent(ib)/hspe->GetXaxis()->GetBinWidth(ib)*hspe_temp->GetXaxis()->GetBinWidth(1);
double new_error = hspe->GetBinError(ib)/hspe->GetXaxis()->GetBinWidth(ib)*hspe_temp->GetXaxis()->GetBinWidth(1);
hspe->SetBinContent(ib,new_content);
hspe->SetBinError(ib,new_error);
}
if(hspe_temp->Integral()==0) continue;
else drawflag[iDepth][iPhi] = true;
Nev = hspe_temp->Integral()*hspe_temp->GetXaxis()->GetBinWidth(1);
TF1 *fped = new TF1("fped","gaus",0, 80);
hped->Fit(fped,"NQR");
double pploc = fped->GetParameter(1), ppwidth = fped->GetParameter(2);
hspe->Fit(fped, "NQ", "", pploc - 3*ppwidth, pploc + ppwidth);
//estimate SPE peak location
int max_SPE_bin, maxbin, Nbins;
double max_SPE_height=0, minheight, max_SPE_location;
bool minflag = false;
maxbin=hspe->FindBin(fped->GetParameter(1)); //location of pedestal peak
minheight=hspe->GetBinContent(maxbin); //initialize minheight
Nbins = hspe->GetNbinsX();
for(int j=maxbin+1; j<Nbins-1; j++) { //start from pedestal peak and loop through bins
if(hspe->GetBinContent(j) > minheight && !minflag) minflag=true; //only look for SPE peak when minflag=true
if(hspe->GetBinContent(j) < minheight ) minheight = hspe->GetBinContent(j);
if(minflag && hspe->GetBinContent(j) > max_SPE_height){
max_SPE_bin = j;
max_SPE_location = hspe->GetBinCenter(max_SPE_bin);
max_SPE_height = hspe->GetBinContent(j);
}
} //start from pedestal peak and loop through bins
//find minimum bin between pedestal and SPE peaks
hspe->GetXaxis()->SetRange(maxbin,max_SPE_bin);
int minbin = hspe->GetMinimumBin();
double minbin_location = hspe->GetBinCenter(minbin);
hspe->GetXaxis()->SetRange(1,Nbins);
TF1 *fit = new TF1("fit", FitFun, 0, 500, 5);
double mu = - log(fped->Integral(0,100)/Nev);
if(mu<0) mu=0.01;
double gain_est = max_SPE_location-1.0*fped->GetParameter(1);
if(max_SPE_bin > (minbin+1)) fit->SetParameters(mu, 20, 1, gain_est, gain_est*0.5);
else fit->SetParameters(mu, 20, 1, 2.1*fped->GetParameter(2), 10); //case of no clear minimum; start looking for SPE peak at 2sigma away from pedestal peak
fit->SetParLimits(0, 0, 10);
fit->FixParameter(1, fped->GetParameter(1));
fit->FixParameter(2, fped->GetParameter(2));
fit->SetParLimits(3, fped->GetParameter(2)*2, 350);
fit->SetParLimits(4, fped->GetParameter(2)*1.01, 250);
double maxfitrange = 500.;
double minfitrange = 0.;
hspe->Fit(fit, "MNQL", "", minfitrange, maxfitrange);
maxfitrange = fped->GetParameter(1)+4*fit->GetParameter(3)+fit->GetParameter(4);
if(500<maxfitrange) maxfitrange = 500;
hspe->Fit(fit, "MNQL", "", minfitrange, maxfitrange);
//calculate NDOF of fit excluding bins with 0 entries
int myNDOF=-3; //three free parameters
for(int j=hspe->FindBin(minfitrange); j<=hspe->FindBin(maxfitrange); j++) { //loop through fitted spe bins
if(hspe->GetBinContent(j)) myNDOF++;
} //loop through fitted spe bins
//calculate means and integrals of the fit and data
double fint, fint_error, hint, favg, havg;
int temp_lowbin, temp_highbin;
temp_lowbin = hspe->FindBin(minfitrange);
temp_highbin = hspe->FindBin(maxfitrange);
hspe_unscaled->GetXaxis()->SetRangeUser(minfitrange, maxfitrange);
havg = hspe_unscaled->GetMean();
hint = hspe->Integral(temp_lowbin,temp_highbin,"width");
double min_frange = hspe->GetBinLowEdge(temp_lowbin);
favg = fit->Mean(min_frange, maxfitrange);
fint = fit->Integral(min_frange, maxfitrange);
//fint_error = fit->IntegralError(min_frange, maxfitrange);
double PE5int = 0; //integral of events with >=5 PE
double PE5loc = fped->GetParameter(1)+ 5*fit->GetParameter(3);
if(PE5loc>500) PE5int = 0;
else {
int PE5bin = hspe_temp->FindBin(PE5loc);
temp_highbin = hspe_temp->FindBin(maxfitrange)-1;
PE5int = hspe_temp->Integral(PE5bin,temp_highbin,"width");
}
int PE5flag = 0;
if(PE5int/hint>0.05) PE5flag = 1; //set flag if more than 5% of events in the fit correspond to >=5PE
//=========================================
//for(int i1=1;i1<hspe->GetNbinsX();i1++){
//constants_file1<<HV<<"\t"<<iDepth<<"\t"<<iEta<<"\t"<<iPhi<<"\t"<<2.6*hspe->GetBinCenter(i1)<<"\t"<<hspe->GetBinContent(i1)<<"\t"<<fit->Eval(hspe->GetBinCenter(i1))<<"\n";
//}
//=========================================
//printf("%d\n",myNDOF);
//output calibrations constants
//constants_file<<endl<<"LED_amplitude HV Spigot Channel Ped_mean Ped_mean_err Ped_RMS Ped_RMS_err SPEPeak_RMS SPEPeak_RMS_err Gain Gain_err Normalized_Chi2 MeanPE_fit MeanPE_fit_err MeanPE_estimate PE5flag"<<endl;
constants_file<<LED_amp<<" "<<iDepth<<" "<<iPhi<<" "<<iEta<<" "<<scale*fped->GetParameter(1)<<" "<<scale*fped->GetParError(1)<<" "<<scale*fped->GetParameter(2)<<" "<<scale*fped->GetParError(2)<<" "<<scale*fit->GetParameter(4)<<" "<<scale*fit->GetParError(4)<<" "<<scale*fit->GetParameter(3)*fC2electrons<<" "<<scale*fit->GetParError(3)*fC2electrons<<" "<<fit->GetChisquare()/myNDOF/*fit->GetNDF()*/<<" "<<fit->GetParameter(0)<<" "<<fit->GetParError(0)<<" "<<mu<<" "<<PE5flag<<endl;
/*
if(iDepth==2 && iPhi==53 && iEta==36){
cout<<iDepth<<" "<<iPhi<<" "<<iEta<<" "<<gain_est<<" "<<fit->GetParameter(3)<<endl;
cout<<LED_amp<<" "<<iDepth<<" "<<iPhi<<" "<<iEta<<" "<<scale*fped->GetParameter(1)<<" "<<scale*fped->GetParError(1)<<" "<<scale*fped->GetParameter(2)<<" "<<scale*fped->GetParError(2)<<" "<<scale*fit->GetParameter(4)<<" "<<scale*fit->GetParError(4)<<" "<<scale*fit->GetParameter(3)*fC2electrons<<" "<<scale*fit->GetParError(3)*fC2electrons<<" "<<fit->GetChisquare()/myNDOF<<" "<<fit->GetParameter(0)<<" "<<fit->GetParError(0)<<" "<<mu<<" "<<PE5flag<<endl;
}
*/
Carray[iDepth][iPhi]->cd(iEta-MinEta+1);
gPad->SetBorderMode(0);
gPad->SetBorderSize(0);
gPad->SetRightMargin(0.01);
gPad->SetBottomMargin(0.1);
gPad->SetLogy(true);
hspe->GetXaxis()->SetRangeUser(0, 200 /*300*//*508*/);
hspe->SetLineColor(kBlue);
hspe->DrawClone("hist");
fit->SetLineWidth(2);
fit->Draw("same");
}
if(drawflag[iDepth][iPhi]) { //draw plots of fit if data for the HV is present
stringstream plot_name;
plot_name<<"Plots/SPEFits_Run_"<<run<<"_Depth"<<iDepth<<"_Phi"<<iPhi<<".pdf";
Carray[iDepth][iPhi]->SaveAs(plot_name.str().c_str());
plot_name.str( std::string() );
}
}
}
constants_file.close();
//constants_file1.close();
}
void analysis() {
Int_t nbins = 800;
Int_t j;
char name[20];
char title[100];
TH1F *HistoEvent[2214];
for (Int_t z=0;z<2214;z++) {
sprintf(name,"HistoEvent%d",z-1);
sprintf(title,"Event%d Histo", z-1);
HistoEvent[z] = new TH1F(name,title,nbins, -0.1, 159.9);
}
TH1F *NewHistoEvent[2214];
for (Int_t z=0;z<2214;z++) {
sprintf(name,"NewHistoEvent%d",z-1);
sprintf(title,"Event%d Histo", z-1);
NewHistoEvent[z] = new TH1F(name,title,nbins, -0.1, 159.9);
}
TH1F *NewHistoEventFFT[2214];
for (Int_t z=0;z<2214;z++) {
sprintf(name,"NewHistoEventFFT%d",z-1);
sprintf(title,"Event%d Histo", z-1);
NewHistoEventFFT[z] = new TH1F(name,title,nbins, 0, 5);
}
Double_t mean;
Double_t rms;
Double_t meansum = 0;
Double_t count = 0;
Double_t meanrms = 0;
TFile f("/home/marko/H4Analysis/ntuples/analysis_4443.root"); //ntuple generated by H4Analysis tool
TFile f1("/home/marko/H4Analysis/ntuples/analysis_3905.root");
TFile f2("/home/marko/Desktop/TB Timing Res/NormalizedSignalNoise.root", "read");
TH1F* BestSignal = (TH1F*) f2.Get("BetterSignal");
TFile outputfile("myoutput.root", "recreate");
TCanvas* TimeandFreq = new TCanvas("TimeandFreq","Time and Frequency",1500,900);
TCanvas* Freq = new TCanvas("Freq","Frequency",800,1200);
TCanvas* TimeSignal = new TCanvas("TimeSignal","Pure Signal",800,1200);
TimeandFreq->Divide(2,2);
TTree* h4 = (TTree*) f.Get("h4");
TTree* h4_2 = (TTree*) f1.Get("h4");
TString plot;
TString cut;
TH2F* WavePulse = new TH2F ("WavePulse", "Wave Pulse", nbins, -0.1, 159.9, 850, -50, 800);
TH2F* NoisePulse = new TH2F ("NoisePulse", "Noise", nbins, -0.1, 159.9, 100, -50, 50);
TH1F* PulseTime = new TH1F ("PulseTime", "Original Wave Pulse", nbins, -0.1, 159.9); //nanoseconds
TH2F* TempHisto = new TH2F ("TempHisto", "Temp Histo", nbins, -0.1, 159.9, 1000, -15, 15); //nanoseconds
h4->Draw("WF_val:WF_time>>WavePulse", "WF_ch==2 && event==1 && spill==1");
h4_2->Draw("WF_val:WF_time>>NoisePulse","WF_ch==APD1 && amp_max[APD3]<25 && b_rms[APD3]<5. && charge_tot[APD3]<20000 && amp_max[APD5]<25 && b_rms[APD5]<5. && amp_max[APD6]<25 && b_rms[APD6]<5. && amp_max[APD4]<25 && b_rms[APD4]<5. && amp_max[SiPM1]<20 && amp_max[SiPM2]<20 && amp_max[APD1]<40 && amp_max[APD2]<40 && b_rms[APD1]<5. && b_rms[APD2]<5. && WF_time<160");
for (Int_t i=0; i<nbins; i++) {
for (Int_t k=0; k<4096; k++) {
if (WavePulse->GetBinContent(i+1, k) != 0) {
PulseTime->SetBinContent(i+1,k-50);
}
}
}
TH1F *NoiseTime = new TH1F ("NoiseTime", "Noise", nbins, -0.1, 159.9);
for (Int_t i=0; i<nbins; i++) {
for (Int_t k=0; k<4096; k++) {
if (NoisePulse->GetBinContent(i+1, k) != 0) {
NoiseTime->SetBinContent(i+1,k-62.9087);
}
}
}
//TH1F* NormNoiseFFT = new TH1F ("NormNoiseFFT", "Normalized Noise FFT", nbins, 0, 5);
//TStopwatch t;
//t.Start(); //1 hour runtime
//for (j=10;j<20;j++) {
// plot = "WF_val:WF_time>>TempHisto";
// cut = "WF_ch==APD1 && amp_max[APD3]<25 && b_rms[APD3]<5. && charge_tot[APD3]<20000 && amp_max[APD5]<25 && b_rms[APD5]<5. && amp_max[APD6]<25 && b_rms[APD6]<5. && amp_max[APD4]<25 && b_rms[APD4]<5. && amp_max[SiPM1]<20 && amp_max[SiPM2]<20 && amp_max[APD1]<40 && amp_max[APD2]<40 && b_rms[APD1]<5. && b_rms[APD2]<5. && WF_time<160 && event==";
// cut += j;
// h4_2->Draw(plot, cut, "goff");
// if (TempHisto->GetMaximum() == 0) {
// delete HistoEvent[j+1];
// continue;
// }
// for (Int_t i=0; i<nbins; i++) {
// for (Int_t k=0; k<1000; k++) {
// if (TempHisto->GetBinContent(i+1, k) != 0) {
// HistoEvent[j+1]->SetBinContent(i+1,k*0.03-15);
// }
// }
// }
// mean = TempHisto->GetMean(2);
// rms = TempHisto->GetRMS(2);
// for (Int_t q=0;q<nbins;q++) {
// NewHistoEvent[j+1]->SetBinContent(q+1, HistoEvent[j+1]->GetBinContent(q+1)-mean);
// }
// NewHistoEvent[j+1]->Scale(1/rms);
// NewHistoEvent[j+1]->FFT(NewHistoEventFFT[j+1], "MAG");
// NormNoiseFFT->Add(NormNoiseFFT, NewHistoEventFFT[j+1]);
// TempHisto->Write();
// NewHistoEvent[j+1]->Write();
// NewHistoEventFFT[j+1]->Write();
// cout << "Event " << j << ", Mean = " << mean << ", RMS = " << rms << endl;
// count += 1;
//}
//NormNoiseFFT->Scale(1/count);
//NormNoiseFFT->Write();
//t.Stop();
//t.Print();
new TFile("/home/marko/H4Analysis/ntuples/analysis_4443.root"); // ignore this reloading of the same file, it is required or else the plots do not show up (when I tried)
TimeandFreq->cd(1);
PulseTime->GetXaxis()->SetTitle("Time (ns)");
PulseTime->GetYaxis()->SetTitle("Amplitude");
PulseTime->DrawClone(); //Wave Pulse in Time domain
TimeandFreq->cd(2);
TH1F* PulseFreq = new TH1F ("PulseFreq", "Pulse FFT", nbins, 0, 5);
TH1F* PulsePhase = new TH1F ("PulsePhase", "Pulse Phase", nbins, -0.1, 799.9);
PulseTime->FFT(PulseFreq, "MAG");
PulseTime->FFT(PulsePhase, "PH");
PulseFreq->SetLineColor(kRed);
PulseFreq->GetXaxis()->SetTitle("Frequency (GHz)");
PulseFreq->GetYaxis()->SetTitle("Amplitude");
PulseFreq->DrawClone(); //Wave Pulse in Frequency domain
gPad->SetLogy();
TimeandFreq->cd(3);
NoiseTime->GetXaxis()->SetTitle("Time (ns)");
NoiseTime->GetYaxis()->SetTitle("Amplitude");
NoiseTime->DrawClone(); // Noise from pedestal in Time domain
TimeandFreq->cd(4);
TH1F* NoiseFreq = new TH1F ("NoiseFreq", "Noise FFT", nbins, 0, 5);
NoiseTime->FFT(NoiseFreq, "MAG");
NoiseFreq->GetXaxis()->SetTitle("Frequency (GHz)");
NoiseFreq->GetYaxis()->SetTitle("Amplitude");
NoiseFreq->Draw(); // Noise from pedestal in Frequency domain
gPad->SetLogy();
Freq->Divide(1,3);
Freq->cd(1);
PulseFreq->DrawClone();
gPad->SetLogy();
Freq->cd(2);
NoiseFreq->DrawClone();
gPad->SetLogy();
Freq->cd(3);
PulseFreq->SetTitle("Pulse and Noise FFT Comparison");
PulseFreq->Draw();
NoiseFreq->Draw("same");
gPad->SetLogy();
TH1F* UnscaledSignalFreq = new TH1F ("UnscaledSignalFreq", "Unscaled Signal Frequency", nbins, -0.1, 799.9);
for (Int_t l=0; l<nbins; l++) {
UnscaledSignalFreq->SetBinContent(l+1, (PulseFreq->GetBinContent(l+1)-NoiseFreq->GetBinContent(l+1))/PulseFreq->GetBinContent(l+1));
}
TH1F* SignalFreq = new TH1F ("SignalFreq", "Signal Frequency", nbins, 0, 799.9);
for (Int_t m=0; m<nbins; m++) {
SignalFreq->SetBinContent(m+1, UnscaledSignalFreq->GetBinContent(m+1)*PulseFreq->GetBinContent(m+1));
}
Double_t *re_full = new Double_t[nbins];
Double_t *im_full = new Double_t[nbins];
for (Int_t n=0; n<nbins; n++) {
(re_full)[n]=(SignalFreq->GetBinContent(n+1)*cos(PulsePhase->GetBinContent(n+1)));
(im_full)[n]=(SignalFreq->GetBinContent(n+1)*sin(PulsePhase->GetBinContent(n+1)));
}
TVirtualFFT *invFFT = TVirtualFFT::FFT(1, &nbins, "C2R M K");
invFFT->SetPointsComplex(re_full, im_full);
invFFT->Transform();
TH1 *Signal = 0;
Signal = TH1::TransformHisto(invFFT,Signal,"Re");
Signal->SetTitle("Recovered Signal 'S'");
TH1F* BetterSignal = new TH1F ("BetterSignal", "Recovered Signal", nbins, -0.1, 159.9);
for (Int_t p=0; p<nbins; p++) {
BetterSignal->SetBinContent(p+1, Signal->GetBinContent(p+1)/nbins);
}
TimeSignal->Divide(1,2);
TimeSignal->cd(1);
PulseTime->DrawClone(); //Original Wave Pulse
TimeSignal->cd(2);
BetterSignal->GetXaxis()->SetTitle("Time (ns)");
BetterSignal->GetYaxis()->SetTitle("Amplitude");
BetterSignal->SetLineColor(kRed);
//BetterSignal->Draw(); // Recovered Wave Pulse with decreased contribution from background noise
BestSignal->SetLineColor(kGreen);
BestSignal->DrawClone("same");
PulseTime->DrawClone("same");
}
void SPEFit(char * fname, int run, int LED_amp, double cutmax = 250.0)
{
//set plotting styles
gStyle->SetCanvasColor(0);
gStyle->SetPadColor(0);
gStyle->SetCanvasBorderMode(0);
gStyle->SetFrameBorderMode(0);
gStyle->SetStatColor(0);
gStyle->SetPadTickX(1);
gStyle->SetPadTickY(1);
//set file names
stringstream out_fname;
stringstream out_fname1;
out_fname<<"SPEconstants_Run_"<<run<<".txt";
out_fname1<<"SPEspec_Run_"<<run<<".txt";
ofstream constants_file(out_fname.str().c_str(),ios_base::trunc);
ofstream constants_file1(out_fname1.str().c_str(),ios_base::trunc);
constants_file<<"Run "<<run<<endl;
constants_file<<"type SPE"<<endl;
constants_file<<"LED_amplitude "<<LED_amp<<endl<<endl;
//constants_file<<endl<<"LED_amplitude HV Spigot Channel Ped_mean Ped_mean_err Ped_RMS Ped_RMS_err SPEPeak_RMS SPEPeak_RMS_err Gain Gain_err Normalized_Chi2 MeanPE_fit MeanPE_fit_err MeanPE_estimate PE5flag"<<endl;
constants_file<<endl<<"LED_amplitude HV Spigot Channel Ped_mean Ped_mean_err Ped_RMS Ped_RMS_err SPEPeak_RMS SPEPeak_RMS_err Gain Gain_err Normalized_Chi2 MeanPE_fit MeanPE_fit_err MeanPE_estimate PE5flag Polya_shape Polya_shape_err Polya_mode"<<endl;
out_fname.str("");
out_fname<<"SPEdistributions_Run_"<<run<<".txt";
out_fname.str("");
out_fname<<"SPEextra_Run_"<<run<<".txt";
//ofstream extra_file(out_fname.str().c_str(),ios_base::trunc);
//extra_file<<endl<<"LED_amplitude HV Spigot Channel PedSubtracted_mean Gain Gain_err Normalized_Chi2 MeanPE_fit MeanPE_fit_err MeanPE_estimate PE5flag"<<endl;
double scale = 1.0;
scale = 2.6; //Need to scale up HF charge
double fC2electrons = 6240.; //convert fC to #electrons
char spename[128], pedname[128], spehistname[128];
bool drawflag;
TFile *tf = new TFile(fname);
TCanvas *c1 = new TCanvas("c1","c1",1200,700);
c1->Divide(6,4);
c1->SetBorderMode(0);
c1->SetBorderSize(0);
TCanvas *c2 = new TCanvas("c2","c2",1200,700);
c2->Divide(6,4);
c2->SetBorderMode(0);
c2->SetBorderSize(0);
TCanvas *c3 = new TCanvas("c3","c3",1200,700);
c3->Divide(6,4);
c3->SetBorderMode(0);
c3->SetBorderSize(0);
const int NnewBins = 106;
double binsX[NnewBins] = {0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58,60,62,64,66,68,70,72,74,76,78,80,82,84,86,88,90,92,94,96,98,100,102,104,106,108,110,112,114,116,118,120,122,124,126,128,130,132,134,136,138,140,142,144,146,148,150,152,154,156,158,160,162,164,166,168,170,180,190,200,210,220,230,240,250,266,282,298,316,336,356,378,404,430,456,482,500};
TH1F* hspe = new TH1F("hspe","hspe",NnewBins-1,binsX);
int Npoints;
TH2D *tmp;
for(Npoints=0;Npoints<10;Npoints++){
sprintf(spename,"spetest/spigot_%d/bb_%d/LED_HVset_%d_sp_%d_BB_%d",0,1,Npoints,0,1);
tmp=(TH2D *)tf->Get(spename);
if(tmp==0) break;
}
TH2D *LED[3][3][20];
TH2D *PED[3][3];
for(int iSpig = 0; iSpig < 3; iSpig++)for(int bb = 1; bb < 4; bb++){
for(int ii=0; ii<Npoints; ii++){
sprintf(spename,"spetest/spigot_%d/bb_%d/LED_HVset_%d_sp_%d_BB_%d",iSpig,bb,ii,iSpig,bb);
LED[iSpig][bb-1][ii]=(TH2D *)tf->Get(spename);
}
sprintf(spename,"spetest/spigot_%d/bb_%d/PED_sp_%d_BB_%d",iSpig,bb,iSpig,bb);
PED[iSpig][bb-1]=(TH2D *)tf->Get(spename);
}
for(int ii=0; ii<Npoints; ii++) {
drawflag=false;
int HV=0;
for (int iSpig = 0; iSpig < 3; iSpig++) {
for(int i = 0; i < 24; i++) {
int bb=BB_MAP[i];
int pmt=PMT_MAP[i];
sprintf(spehistname,"led %d %d %d",ii,iSpig,i);
TH1D *hspe_temp = (TH1D *)LED[iSpig][bb-1][ii]->ProjectionX(spehistname,pmt,pmt,"")->Clone();
sprintf(spehistname,"ped %d %d %d",ii,iSpig,i);
TH1D *hped = (TH1D *)PED[iSpig][bb-1]->ProjectionX(spehistname,pmt,pmt,"")->Clone();
sscanf(&hspe_temp->GetTitle()[7],"%d",&HV);
hspe->Reset();
sprintf (spehistname, "SumLED%d_sp_%d_ch_%d", HV, iSpig, i);
hspe->SetTitle(spehistname);
//combine bins of original SPE histogram
for(int ib=1; ib<=hspe_temp->GetNbinsX(); ib++) {
double bin_center = hspe_temp->GetBinCenter(ib);
if(bin_center>hspe->GetXaxis()->GetXmax()) continue;
int newbin = hspe->FindBin(bin_center);
double new_content = hspe->GetBinContent(newbin) + hspe_temp->GetBinContent(ib);
double new_error = sqrt(pow(hspe->GetBinError(newbin),2)+pow(hspe_temp->GetBinError(ib),2));
hspe->SetBinContent(newbin,new_content);
hspe->SetBinError(newbin,new_error);
}
TH1F* hspe_unscaled = (TH1F*)hspe->Clone("hspe_unscaled");
//renormalize bins of new SPE histogram
for(int ib=1; ib<=hspe->GetNbinsX(); ib++) {
double new_content = hspe->GetBinContent(ib)/hspe->GetXaxis()->GetBinWidth(ib)*hspe_temp->GetXaxis()->GetBinWidth(1);
double new_error = hspe->GetBinError(ib)/hspe->GetXaxis()->GetBinWidth(ib)*hspe_temp->GetXaxis()->GetBinWidth(1);
hspe->SetBinContent(ib,new_content);
hspe->SetBinError(ib,new_error);
}
if(hspe_temp->Integral()==0) continue;
else drawflag=true;
Nev = hspe_temp->Integral()*hspe_temp->GetXaxis()->GetBinWidth(1);
TF1 *fped = new TF1("fped","gaus",0, 80);
hped->Fit(fped,"NQR");
double pploc = fped->GetParameter(1), ppwidth = fped->GetParameter(2);
//cout<<"Ped only: ped mean "<<fped->GetParameter(1)<<", ped width "<<fped->GetParameter(2)<<" normalization "<<fped->GetParameter(0)<<endl;
hspe->Fit(fped, "NQ", "", pploc - 3*ppwidth, pploc + ppwidth);
//cout<<"SPE distribution: ped mean "<<fped->GetParameter(1)<<", ped width "<<fped->GetParameter(2)<<" normalization "<<fped->GetParameter(0)<<endl;
//estimate SPE peak location
int max_SPE_bin, maxbin, Nbins;
double max_SPE_height=0, minheight, max_SPE_location;
bool minflag = false;
maxbin=hspe->FindBin(fped->GetParameter(1)); //location of pedestal peak
minheight=hspe->GetBinContent(maxbin); //initialize minheight
/*
int maxped_bin = hspe->GetMaximumBin();
int maxped_binheight = hspe->GetBinContent(maxped_bin);
minheight = maxped_binheight;
*/
Nbins = hspe->GetNbinsX();
for(int j=/*maxped_bin*/maxbin+1; j<Nbins-1; j++) { //start from pedestal peak and loop through bins
if(hspe->GetBinContent(j) > minheight && !minflag) minflag=true; //only look for SPE peak when minflag=true
if(hspe->GetBinContent(j) < minheight ) minheight = hspe->GetBinContent(j);
if(minflag && hspe->GetBinContent(j) > max_SPE_height){
max_SPE_bin = j;
max_SPE_location = hspe->GetBinCenter(max_SPE_bin);
max_SPE_height = hspe->GetBinContent(j);
}
} //start from pedestal peak and loop through bins
//find minimum bin between pedestal and SPE peaks
hspe->GetXaxis()->SetRange(maxbin,max_SPE_bin);
int minbin = hspe->GetMinimumBin();
double minbin_location = hspe->GetBinCenter(minbin);
hspe->GetXaxis()->SetRange(1,Nbins);
TF1 *fit = new TF1("fit", FitFun, 0, 500, 5);
double mu = - log(fped->Integral(0,100)/Nev);
if(mu<0) mu=0.01;
double gain_est = max_SPE_location-1.0*fped->GetParameter(1);
if(max_SPE_bin > (minbin+1)) fit->SetParameters(mu, 20, 1, gain_est, 3.0);
else fit->SetParameters(mu, 20, 1, 2.1*fped->GetParameter(2), 3.0); //case of no clear minimum; start looking for SPE peak at 2sigma away from pedestal peak
fit->SetParLimits(0, 0, 10);
fit->FixParameter(1, fped->GetParameter(1));
fit->FixParameter(2, fped->GetParameter(2));
fit->SetParLimits(3, fped->GetParameter(2)*2, 350);
fit->SetParLimits(4, 1.01, 100.);
double maxfitrange = 500.;
double minfitrange = 0.;
hspe->Fit(fit, "MNQL", "", minfitrange, maxfitrange);
double rms_estimate = fit->GetParameter(3)/sqrt(fit->GetParameter(4));
maxfitrange = fped->GetParameter(1)+4*fit->GetParameter(3)+rms_estimate;
// cout<<"estimate of gain "<<gain_est<<", fit "<<fit->GetParameter(3)<<endl;
// cout<<"Shape Parameter "<<fit->GetParameter(4)<<endl;
// cout<<"SPE width "<<rms_estimate<<endl;
// cout<<"maxfitrange "<<maxfitrange<<endl;
if(500<maxfitrange) maxfitrange = 500;
hspe->Fit(fit, "MNQL", "", minfitrange, maxfitrange);
//calculate NDOF of fit excluding bins with 0 entries
int myNDOF=-3; //three free parameters
for(int j=hspe->FindBin(minfitrange); j<=hspe->FindBin(maxfitrange); j++) { //loop through fitted spe bins
if(hspe->GetBinContent(j)) myNDOF++;
} //loop through fitted spe bins
// cout<<"estimate of gain "<<gain_est<<", fit "<<fit->GetParameter(3)<<endl;
// cout<<"Shape Parameter "<<fit->GetParameter(4)<<endl;
// double SPE_rms = fit->GetParameter(3)/sqrt(fit->GetParameter(4));
// cout<<"SPE width "<<SPE_rms<<endl;
//cout<<"SPE width "<<fit->GetParameter(4)<<endl;
//cout<<"Fit normalization constant: estimate "<<mu<<" fit "<<fit->GetParameter(0)<<endl;
//cout<<spename<<endl;
//calculate means and integrals of the fit and data
double fint, fint_error, hint, favg, havg;
int temp_lowbin, temp_highbin;
temp_lowbin = hspe->FindBin(minfitrange);
temp_highbin = hspe->FindBin(maxfitrange);
hspe_unscaled->GetXaxis()->SetRangeUser(minfitrange, maxfitrange);
havg = hspe_unscaled->GetMean();
hint = hspe->Integral(temp_lowbin,temp_highbin,"width");
double min_frange = hspe->GetBinLowEdge(temp_lowbin);
favg = fit->Mean(min_frange, maxfitrange);
fint = fit->Integral(min_frange, maxfitrange);
//fint_error = fit->IntegralError(min_frange, maxfitrange);
double PE5int = 0; //integral of events with >=5 PE
double PE5loc = fped->GetParameter(1)+ 5*fit->GetParameter(3);
if(PE5loc>500) PE5int = 0;
else {
int PE5bin = hspe_temp->FindBin(PE5loc);
temp_highbin = hspe_temp->FindBin(maxfitrange)-1;
PE5int = hspe_temp->Integral(PE5bin,temp_highbin,"width");
}
int PE5flag = 0;
if(PE5int/hint>0.05) PE5flag = 1; //set flag if more than 5% of events in the fit correspond to >=5PE
//=========================================
for(int i1=1;i1<hspe->GetNbinsX();i1++){
constants_file1<<HV<<"\t"<<iSpig<<"\t"<<i<<"\t"<<2.6*hspe->GetBinCenter(i1)<<"\t"<<hspe->GetBinContent(i1)<<"\t"<<fit->Eval(hspe->GetBinCenter(i1))<<"\n";
}
//=========================================
//output calibrations constants
//constants_file<<endl<<"LED_amplitude HV Spigot Channel Ped_mean Ped_mean_err Ped_RMS Ped_RMS_err SPEPeak_RMS SPEPeak_RMS_err Gain Gain_err Normalized_Chi2 MeanPE_fit MeanPE_fit_err MeanPE_estimate PE5flag Polya_shape Polya_shape_err Polya_mode"<<endl;
constants_file<<LED_amp<<" "<<HV<<" "<<iSpig<<" "<<(bb-1)*8+pmt<<" "<<scale*fped->GetParameter(1)<<" "<<scale*fped->GetParError(1)<<" "<<scale*fped->GetParameter(2)<<" "<<scale*fped->GetParError(2)<<" "<<scale*fit->GetParameter(3)/sqrt(fit->GetParameter(4))<<" "<<0<<" "<<scale*fit->GetParameter(3)*fC2electrons<<" "<<scale*fit->GetParError(3)*fC2electrons<<" "<<fit->GetChisquare()/myNDOF/*fit->GetNDF()*/<<" "<<fit->GetParameter(0)<<" "<<fit->GetParError(0)<<" "<<mu<<" "<<PE5flag<<" "<<fit->GetParameter(4)<<" "<<fit->GetParError(4)<<" "<<scale*(fit->GetParameter(4)-1.0)/fit->GetParameter(4)*fit->GetParameter(3)*fC2electrons<<endl;
// cout<<LED_amp<<" "<<HV<<" "<<iSpig<<" "<<QIECh[i]<<" "<<scale*fped->GetParameter(1)<<" "<<scale*fped->GetParError(1)<<" "<<scale*fped->GetParameter(2)<<" "<<scale*fped->GetParError(2)<<" "<<scale*fit->GetParameter(4)<<" "<<scale*fit->GetParError(4)<<" "<<scale*fit->GetParameter(3)*fC2electrons<<" "<<scale*fit->GetParError(3)*fC2electrons<<" "<<fit->GetChisquare()/fit->GetNDF()<<" "<<fit->GetChisquare()<<" "<<fit->GetNDF()<<" "<<myNDOF<<" "<<fit->GetParameter(0)<<" "<<fit->GetParError(0)<<" "<<mu<<endl;
//extra_file<<endl<<"LED_amplitude HV Spigot Channel SignalAvg_inFitRange FitAvg_inFitRange SignalInt_inFitRange FitInt_inFitRange PEge5Int Gain(fC) Gain_err Normalized_Chi2 MeanPE_fit MeanPE_fit_err MeanPE_estimate PE5flag"<<endl;
//extra_file<<LED_amp<<" "<<HV<<" "<<iSpig<<" "<<QIECh[i]<<" "<<scale*havg<<" "<<scale*favg<<" "<<hint<<" "<<fint<<" "<<PE5int<<" "<<scale*fit->GetParameter(3)<<" "<<scale*fit->GetParError(3)<<" "<<fit->GetChisquare()/myNDOF<<" "<<fit->GetParameter(0)<<" "<<fit->GetParError(0)<<" "<<mu<<" "<<PE5flag<<endl;
//cout<<"# Spigot Channel Ped_mean Ped_RMS SPE_PeakRMS Gain Normalized_Chi2 Avg_PE"<<endl;
//cout<<iSpig<<" "<<i<<" "<<scale*fped->GetParameter(1)<<" "<<scale*fped->GetParameter(2)<<" "<<scale*fit->GetParameter(4)<<" "<<scale*fit->GetParameter(3)*fC2electrons<<" "<<fit->GetChisquare()/fit->GetNDF()<<" "<<fit->GetParameter(0)<<endl<<endl;
if(iSpig==0) c1->cd(i+1);
else if(iSpig==1) c2->cd(i+1);
else if(iSpig==2) c3->cd(i+1);
gPad->SetBorderMode(0);
gPad->SetBorderSize(0);
gPad->SetRightMargin(0.01);
gPad->SetBottomMargin(0.1);
gPad->SetLogy(true);
hspe->GetXaxis()->SetRangeUser(0, /*300*/508);
hspe->SetLineColor(kBlue);
hspe->DrawClone("hist");
fit->SetLineWidth(2);
fit->Draw("same");
}
}
if(drawflag) { //draw plots of fit if data for the HV is present
stringstream plot_name;
//plot_name<<"Plots/SPEFits_Spigot0_Run_"<<run<<"_HV"<<HV<<".pdf";
plot_name<<"Plots/SPEFits_Spigot0_Run_"<<run<<"_HV"<<HV<<"_config"<<ii<<".pdf";
c1->SaveAs(plot_name.str().c_str());
plot_name.str( std::string() );
//plot_name<<"Plots/SPEFits_Spigot1_Run_"<<run<<"_HV"<<HV<<".pdf";
plot_name<<"Plots/SPEFits_Spigot1_Run_"<<run<<"_HV"<<HV<<"_config"<<ii<<".pdf";
c2->SaveAs(plot_name.str().c_str());
plot_name.str( std::string() );
//plot_name<<"Plots/SPEFits_Spigot2_Run_"<<run<<"_HV"<<HV<<".pdf";
plot_name<<"Plots/SPEFits_Spigot2_Run_"<<run<<"_HV"<<HV<<"_config"<<ii<<".pdf";
c3->SaveAs(plot_name.str().c_str());
}
} //HV loop
constants_file.close();
constants_file1.close();
}
void readTree_background() {
Char_t *filename = "Background.root";
// Retrieve the TTree
TFile* myFile = TFile::Open(filename);
TTree* tree = (TTree*)(myFile->Get("tree"));
Double_t Et1, eta1, phi1, Et2, eta2, phi2;
tree->SetBranchAddress("Et1" ,&Et1 );
tree->SetBranchAddress("eta1",&eta1);
tree->SetBranchAddress("phi1",&phi1);
tree->SetBranchAddress("Et2" ,&Et2 );
tree->SetBranchAddress("eta2",&eta2);
tree->SetBranchAddress("phi2",&phi2);
// Book histograms
TH1F* hmass = new TH1F("hmass","m_{#gamma#gamma}",60,100.,160.);
hmass->GetXaxis()->SetTitle("Invariant mass [GeV]");
hmass->GetYaxis()->SetTitle("Events");
// Loop over the events
Long64_t events = tree->GetEntries();
for (int i=0; i<events; i++) {
tree->GetEntry(i);
TLorentzVector g1,g2;
g1.SetPtEtaPhiM(Et1,eta1,phi1,0.);
g2.SetPtEtaPhiM(Et2,eta2,phi2,0.);
TLorentzVector gg=g1+g2;
hmass->Fill( gg.M() );
}
// Test of different background options
hmass->DrawClone("e");
TCanvas* myCanvas = new TCanvas("myCanvas","Background fits",800,800);
myCanvas->Divide(2,2);
// Linear background
TF1* myBack1 = new TF1("myBack1","[0]+[1]*x",100.,160.);
myBack1->SetParameter(0,events);
myBack1->SetParameter(1,-100.);
myCanvas->cd(1);
hmass->Fit(myBack1);
hmass->DrawClone("e");
EvaluatePvalue(myBack1);
// Quadratic background
TF1* myBack2 = new TF1("myBack2","[0]+[1]*x+[2]*x**2",100.,160.);
myBack2->SetParameter(0,events);
myBack2->SetParameter(1,-100.);
myBack2->SetParameter(1,0.);
myCanvas->cd(2);
hmass->Fit(myBack2);
hmass->DrawClone("e");
EvaluatePvalue(myBack2);
// Exponential background
TF1* myBack3 = new TF1("myBack3","[0]*exp(-x/[1])",100.,160.);
myBack3->SetParameter(0,events);
myBack3->SetParameter(1,100.);
myCanvas->cd(3);
hmass->Fit(myBack3);
hmass->DrawClone("e");
EvaluatePvalue(myBack3);
// Cubic background
TF1* myBack4 = new TF1("myBack4","[0]+[1]*x+[2]*x**2+[3]*x**3",100.,160.);
myBack4->SetParameter(0,0.);
myBack4->SetParameter(1,0.);
myBack4->SetParameter(2,0.);
myBack4->SetParameter(3,0.);
myCanvas->cd(4);
TFitResultPtr fit4 = hmass->Fit(myBack4,"S");
hmass->DrawClone("e");
EvaluatePvalue(myBack4);
}
int main() {
Int_t nbins = 800, count = 0;
Double_t integral;
TFile *input = new TFile("FilterRMSComparison.root");
TFile *templatefile = new TFile("/home/marko/Desktop/H4Analysis/ntuples/Templates_APDs.old.root");
TTree *MyTree = (TTree*) input->Get("RMS");
TCanvas *can1 = new TCanvas("can1", "canvas", 1200,900);
TCanvas *can2 = new TCanvas("can2", "canvas", 1200,1200);
TCanvas *can3 = new TCanvas("can3", "canvas", 1200,1200);
can1->Divide(1,3);
can2->Divide(1,2);
can3->Divide(1,2);
MyTree->SetEntryList(0);
TString listcut = "abs(unfilteredbslope)<6 && unfilteredampfit>700";
MyTree->Draw(">>myList", listcut, "entrylist");
TEntryList *myList = (TEntryList*) gDirectory->Get("myList");
MyTree->SetEntryList(myList);
Int_t nevents = myList->GetN();
MyTree->Draw("unfilteredevent", "abs(unfilteredbslope)<6 && unfilteredampfit>700", "goff");
Double_t *vTemp = MyTree->GetV1();
Int_t *vEvent = new Int_t[nevents];
for (int iEntry = 0; iEntry<nevents; iEntry++) {
vEvent[iEntry] = vTemp[iEntry];
}
TString plot, plot2, cut;
char name[50];
TH1F *histoave = new TH1F("histoave","Wave Pulse Average", nbins, -40, 120);
TH1F *histoavefft = new TH1F("histoavefft","Wave Pulse Average FFT", nbins, 0, 5);
TH1F *histoaveph = new TH1F("histoaveph","Wave Pulse Average Phase", nbins, 0, 800);
TH1F *originaltemplate = (TH1F*) templatefile->Get("APD2_E50_G50_prof");
originaltemplate->Rebin(16);
TH1F *templatehisto = new TH1F("templatehisto", "Template = Green, Average = Red", nbins, -40, 120);
TH1F *difference = new TH1F("difference","Template vs. Average Difference", nbins, -40, 120);
TH1F *percentdifference = new TH1F("percentdifference","Template vs. Average Percent Difference", nbins, -40, 120);
for (Int_t i=0;i<nbins;i++) {
templatehisto->SetBinContent(i+1, originaltemplate->GetBinContent(i+1));
}
templatehisto->SetLineColor(kGreen+3);
templatehisto->SetLineWidth(4);
can2->cd(2);
histoave->GetYaxis()->SetRangeUser(-.120,1.2);
//templatehisto->Draw();
histoave->SetStats(0);
histoave->Draw();
for (Int_t i=0;i<nevents;i++) {
//for (Int_t i=0;i<10;i++) {
if (vEvent[i]==513) continue; //event for which electronics die out for a bit halfway through
TString histoname = "TempHisto_";
histoname += i;
TString histoname2 = "TempHisto2_";
histoname2 += i;
TH2F* TempHisto = new TH2F (histoname, "Temp Histo", nbins, -40, 120, 1000, -120, 800); //nanoseconds
TH2F* TempHisto2 = new TH2F (histoname2, "Temp Histo", nbins, -40, 120, 1000, -120, 800); //nanoseconds
TString h1name = "h1001_";
h1name += i;
TString h1name2 = "h1002_";
h1name2 += i;
TString h1name2fft = "h1002fft_";
h1name2 += i;
TString h1name2ph = "h1002ph_";
h1name2 += i;
TString h1name3 = "h1003_";
h1name3 += i;
TString h1name4 = "h1004_";
h1name4 += i;
TH1F *h1001 = new TH1F(h1name,"Red = Unfiltered, Blue = Filtered", nbins, -40, 120);
TH1F *h1002 = new TH1F(h1name2,"h1002", nbins, -40, 120);
TH1F *h1002fft = new TH1F(h1name2fft,"h1002fft", nbins, 0, 5);
TH1F *h1002ph = new TH1F(h1name2ph,"h1002ph", nbins, 0, 800);
TH1F *h1003 = new TH1F(h1name3,"Filtered WF - Unfiltered WF", nbins, -40, 120);
TH1F *h1004 = new TH1F(h1name4,"Percent Change in Filtered WF - Unfiltered WF", nbins, -40, 120);
plot = "unfilteredwfval:(unfilteredwftime-unfilteredtimeref)>>";
plot += histoname;
plot2 = "filteredwfval:(filteredwftime-filteredtimeref)>>";
plot2 += histoname2;
cut = "abs(unfilteredbslope)<6 && unfilteredampfit>700 && unfilteredevent==";
cut += vEvent[i];
MyTree->Draw(plot, cut, "goff");
TempHisto = (TH2F*) gDirectory->Get(histoname);
h1001 = transform2Dto1D(TempHisto);
MyTree->Draw(plot2, cut, "goff");
TempHisto2 = (TH2F*) gDirectory->Get(histoname2);
h1002 = transform2Dto1D(TempHisto2);
if (h1002->GetBinCenter(h1002->GetMaximumBin()) < 30) continue;
sprintf(name, "Good Events/Event%d", vEvent[i]);
strcat(name, ".png");
h1001->SetLineColor(kRed);
h1002->SetLineColor(kBlue);
h1001->SetStats(0);
h1002->SetStats(0);
//can1->cd(1);
can1->cd();
h1001->GetXaxis()->SetTitle("Time (ns)");
h1001->GetYaxis()->SetTitle("Amplitude");
h1001->Draw();
h1002->Draw("same");
//for (Int_t i=0;i<nbins;i++) {
// h1003->SetBinContent(i+1, (h1002->GetBinContent(i+1))-(h1001->GetBinContent(i+1)));
// if (h1001->GetBinContent(i+1) != 0) h1004->SetBinContent(i+1, ((h1002->GetBinContent(i+1))-(h1001->GetBinContent(i+1)))/(h1001->GetBinContent(i+1)));
// else h1004->SetBinContent(i+1, 0);
//}
//can1->cd(2);
//h1003->Draw();
//can1->cd(3);
//h1004->Draw();
//h1004->GetYaxis()->SetRangeUser(-0.1,0.1);
//gPad->SetGrid();
can1->SaveAs(name);
//h1002->FFT(h1002fft, "MAG");
//h1002->FFT(h1002ph, "PH");
//histoavefft->Add(histoavefft, h1002fft);
//histoaveph->Add(histoaveph, h1002ph);
histoave->Add(histoave, h1002);
can2->cd(2);
h1002->Scale(1./(h1002->GetMaximum()));
h1002->Draw("same");
count++;
delete TempHisto, TempHisto2, h1001, h1002, h1003, h1004, histoname, histoname2, h1name, h1name2, h1name3, h1name4;
gDirectory->Clear();
}
can2->cd(1);
//histoavefft->Scale(1./count);
//histoaveph->Scale(1./count);
histoave->Scale(1./count);
//Double_t *re_full = new Double_t[nbins];
//Double_t *im_full = new Double_t[nbins];
//TH1 *Throwaway = 0;
//TH1F *invhistoave = new TH1F(invhistoave, "Average Pulse", nbins, -40, 120);
//TVirtualFFT *invFFT = TVirtualFFT::FFT(1, &nbins, "C2R M K");
//for (Int_t n=0; n<nbins; n++) {
// (re_full)[n]=(histoavefft->GetBinContent(n+1)*cos(histoaveph->GetBinContent(n+1)));
// (im_full)[n]=(histoavefft->GetBinContent(n+1)*sin(histoaveph->GetBinContent(n+1)));
//}
//invFFT->SetPointsComplex(re_full, im_full);
//invFFT->Transform();
//Throwaway = TH1::TransformHisto(invFFT, Throwaway, "Re");
//for (Int_t p=0; p<nbins; p++) {
// histoave->SetBinContent(p+1, Throwaway->GetBinContent(p+1)/nbins);
//}
histoave->Scale(1./(histoave->GetMaximum()));
histoave->SetLineColor(kRed);
histoave->SetLineWidth(4);
integral = templatehisto->Integral();
templatehisto->Scale(1./integral);
templatehisto->SetStats(0);
templatehisto->Draw();
integral = histoave->Integral();
histoave->Scale(1./integral);
histoave->DrawClone("same");
histoave->Scale(integral);
can2->cd(2);
histoave->GetXaxis()->SetTitle("Time (ns)");
histoave->GetYaxis()->SetTitle("Normalized Amplitude");
histoave->DrawClone("same");
can2->SaveAs("AmpSpread.png");
can2->SaveAs("AmpSpreadRoot.root");
TFile *output = new TFile("Alignment.root", "recreate");
output->cd();
originaltemplate->Write();
histoave->Write();
templatehisto->Write();
output->Close();
can3->cd(1);
histoave->Scale(1./integral);
for (int i=0;i<nbins;i++) {
difference->SetBinContent(i+1, histoave->GetBinContent(i+1) - templatehisto->GetBinContent(i+1));
if (templatehisto->GetBinContent(i+1) != 0) percentdifference->SetBinContent(i+1, (histoave->GetBinContent(i+1) - templatehisto->GetBinContent(i+1))/templatehisto->GetBinContent(i+1));
else percentdifference->SetBinContent(i+1, 0);
}
difference->GetXaxis()->SetTitle("Time (ns)");
difference->GetYaxis()->SetTitle("Average - Template");
difference->SetStats(0);
difference->Draw();
can3->cd(2);
percentdifference->GetXaxis()->SetTitle("Time (ns)");
percentdifference->GetYaxis()->SetTitle("Percent Difference Average - Template");
percentdifference->SetStats(0);
percentdifference->Draw();
percentdifference->GetYaxis()->SetRangeUser(-0.1,0.1);
gPad->SetGrid();
can3->SaveAs("Difference.png");
can3->SaveAs("Difference.root");
}
