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Commit 76dbc9ea authored by Keerthi Nakkalil's avatar Keerthi Nakkalil
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Functions added to do a linear fit on the mean values to get the slope distribution

parent ba5e38a5
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gain_measurement.cpp
View file @ 76dbc9ea
double xmin=850.0,xmax = 1750.0,nbins=450.0;
void fit_gaussian_noise(TH1D* hist_255,int colors,int markers,int amplitude,double fitmin,double fitmax)
void fit_gaussian_noise(TH1D* hist_255,int colors,int markers,double fitmin,double fitmax, int pixel_address)
{
cout<<"The histograms are fitted with gaussian function..."<<std::endl;
hist_255->SetMarkerColor(colors);
hist_255->SetMarkerStyle(markers);
......@@ -18,35 +19,33 @@ void fit_gaussian_noise(TH1D* hist_255,int colors,int markers,int amplitude,doub
fitgauss->SetParameter(0,200.0);
int lastbin1 = hist_255->FindLastBinAbove(200);
double mean = hist_255->GetBinCenter(lastbin1);
// cout<<"The initial mean value assigned for the data of amp_0 "<<amplitude<<""<<" is "<<""<<mean<<std::endl;
fitgauss->SetParameter(1,mean);
int lastbin2 = hist_255->FindLastBinAbove(150);
int lastbin3 = hist_255->FindLastBinAbove(50);
int sigma = lastbin3 -lastbin2;
// cout<<"The initial noise assigned for the data of amp_0 "<<amplitude<<""<<" is "<<""<<sigma<<std::endl;
fitgauss->SetParameter(2,sigma);
fitgauss->SetLineWidth(2);
fitgauss->SetLineColor(2);
hist_255->Fit("fitgauss"," R");
/*std::ofstream fitpars;
fitpars.open("fit_parameters.txt",std::ofstream::app);
fitpars<<pixel_address<<"_"<<pixel_address<< " "<< fitgauss->GetParameter(1)<<std::endl;*/
hist_255->GetListOfFunctions()->FindObject("fitgauss")->Draw("same");
hist_255->SetStats(0);
}
void fit_modified_erf(TH1D* hist_255,int colors,int markers,int amplitude,double fitmin,double fitmax)
void fit_modified_erf(TH1D* hist_255,int colors,int markers,double injected_voltage,double fitmin,double fitmax,int pixel_address)
{
// hist_255->GetXaxis()->SetTitle("Threshold");
// hist_255->GetYaxis()->SetTitle("# signals above the threshold");
cout<<"The histograms are fitted with modified error function..."<<std::endl;
hist_255->SetMarkerColor(colors);
hist_255->SetMarkerStyle(markers);
TF1 *fiterf = new TF1("fiterf","([0]/2)*(1-TMath::Erf((x-[1])/(sqrt(2)*[2])))",fitmin,fitmax);
// cout<<"The fit parameters for the amplitude amp_0"<<amplitude<<""<<" are as follows :"<<std::endl;
/*Setting parameter names*/
fiterf->SetParNames("constant","mean","noise");
......@@ -56,22 +55,24 @@ void fit_modified_erf(TH1D* hist_255,int colors,int markers,int amplitude,double
fiterf->SetParameter(0,200.0);
int lastbin1 = hist_255->FindLastBinAbove(200);
double mean = hist_255->GetBinCenter(lastbin1);
// cout<<"The initial mean value assigned for the data of amp_0 "<<amplitude<<""<<" is "<<""<<mean<<std::endl;
fiterf->SetParameter(1,mean);
int lastbin2 = hist_255->FindLastBinAbove(150);
int lastbin3 = hist_255->FindLastBinAbove(50);
int sigma = lastbin3 -lastbin2;
// cout<<"The initial noise assigned for the data of amp_0 "<<amplitude<<""<<" is "<<""<<sigma<<std::endl;
fiterf->SetParameter(2,sigma);
fiterf->SetLineWidth(2);
fiterf->SetLineColor(2);
hist_255->Fit("fiterf"," R");
std::ofstream fitpars;
fitpars.open("fit_parameters.txt",std::ofstream::app);
fitpars<< std::setw(3)<< std::setfill('0')<< pixel_address <<"_"
<< std::setw(3)<< std::setfill('0')<<pixel_address<<"\t"
<<injected_voltage<<"\t"<< fiterf->GetParameter(1)<<std::endl;
hist_255->GetListOfFunctions()->FindObject("fiterf")->Draw("same");
hist_255->SetStats(0);
}
std::vector<TH1D*> gain_measurement_pixel(int i, int j)
......@@ -81,6 +82,8 @@ std::vector<TH1D*> gain_measurement_pixel(int i, int j)
std::vector<double>fitmin ={1220.,1200.,1150.,1000.0};
std::vector<double>fitmax={1700.,1420.,1240.,1500.0};
std::vector<TH1D*> hist_255;
// double amplitude[3]={298.2559,149.6258,49.1753};
std::vector<double>injected_voltage = {298.2559,149.6258,49.1753};
//The data files are named as following : 000_000.dat to 256_256.dat
stringstream sfilename;
......@@ -98,12 +101,15 @@ std::vector<TH1D*> gain_measurement_pixel(int i, int j)
for(int amp = 0; amp < 4; amp++) {
// std::vector<std::ifstream>amplitude_file;
// amplitude_file.open(filenames.at(amp).c_str());
std::ifstream amplitude_file(filenames.at(amp).c_str());
if(amplitude_file.is_open()) {
cout<<"The data file " << filenames.at(amp)<< " is opened..."<<std::endl;
std::string hist_name = "h" + std::to_string(amp) + "_" + std::to_string(j);
TH1D* h1 = new TH1D(hist_name.c_str(),"Threshold gain measurement",nbins,xmin,xmax);
std::string hist_title = "Threshold gain measurement for the pixel " + std::to_string(i) + "_" + std::to_string(i);
TH1D* h1 = new TH1D(hist_name.c_str(),hist_title.c_str(),nbins,xmin,xmax);
std::string line;
while(!amplitude_file.eof()) {
......@@ -122,17 +128,77 @@ std::vector<TH1D*> gain_measurement_pixel(int i, int j)
} else {
cout << "Error opening file. Exit." <<std::endl;
}
if(filenames.at(amp)==0||filenames.at(amp)==1||filenames.at(amp)==2){
fit_modified_erf(hist_255.at(amp),colors.at(amp),markers.at(amp),amp,fitmin.at(amp),fitmax.at(amp));
if(amp==0||amp==1||amp==2){
fit_modified_erf(hist_255.at(amp),colors.at(amp),markers.at(amp),injected_voltage.at(amp),fitmin.at(amp),fitmax.at(amp),i);
}
else{
fit_gaussian_noise(hist_255.at(amp),colors.at(amp),markers.at(amp),amp,fitmin.at(amp),fitmax.at(amp));
fit_gaussian_noise(hist_255.at(amp),colors.at(amp),markers.at(amp),fitmin.at(amp),fitmax.at(amp),i);
}
}
return hist_255;
}
void gain_measurement()
void linear_fit(int x)
{
ifstream fitpars("fit_parameters.txt");
std::string pixel_address;
std::vector<double>injected_amp_vec,signals_vec;
double injected_amplitude,signals;
std::vector<TGraph*>gr;
if(fitpars.is_open()){
while(!fitpars.eof()){
while(fitpars>>pixel_address){
// cout<<"The injected amplitudes and the corresponding mean values for "<<pixel_address<<"are : " <<std::endl;
fitpars>>injected_amplitude>>signals;
//cout<<injected_amplitude<<" "<<signals<<std::endl;
injected_amp_vec.push_back(injected_amplitude);
signals_vec.push_back(signals);
for(int i=0;i<3;i++){
gr.push_back(new TGraph(injected_amp_vec.size(),&(injected_amp_vec[i]),&(signals_vec[i])));
}
}
for(int j=0;j<256;j++){
auto linear_fit = new TF1("linear_fit","[0]*x +[1]",0,300);
linear_fit->SetParNames("slope","offset");
linear_fit->SetParameter(0,2);
linear_fit->SetParameter(1,1200);
linear_fit->SetLineColor(2);
gr.at(j)->Fit(linear_fit);
gr.at(j)->Draw("AL*");
gr.at(j)->GetXaxis()->SetTitle("Injected amplitude");
gr.at(j)->GetYaxis()->SetTitle("mean values");
std::ofstream slopes;
slopes.open("slopes.txt",std::ofstream::app);
slopes<<linear_fit->GetParameter(0)<<" ";
}
}
}
}
void slope_distribution(int y)
{
ifstream slopes("slopes.txt");
double slopeval;
TH1D* hist = new TH1D("slope","slope distribution",200,-2.0,10.0);
if(slopes.is_open()){
while(!slopes.eof()){
slopes>>slopeval;
hist->Fill(slopeval);
hist->GetXaxis()->SetTitle("Slope values");
hist->GetYaxis()->SetTitle("#entries");
hist->Draw();
}
}
}
void gain_9()
{
int row,col;
THStack* hs = new THStack("hs", "Gain measurements");
......@@ -157,10 +223,11 @@ void gain_measurement()
}
// cout<<"The size of pixel_histogram vector is"<<pixel_histograms.size()<<std::endl;
}
TCanvas* c1 = new TCanvas("c1");
c1->Divide(2,2);
c1->cd(1);
cout<<"The histograms are added to the stack..."<<std::endl;
hs->Draw("HIST P nostack");
hs->GetXaxis()->SetTitle("Threshold");
hs->GetYaxis()->SetTitle("# signals above the threshold");
......@@ -187,4 +254,10 @@ void gain_measurement()
leg->Draw("SAME");
c1->cd(2);
linear_fit(5);
c1->cd(3);
slope_distribution(5);
}
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