User defined functions incorporated to plot and fit the histograms for low,...

User defined functions incorporated to plot and fit the histograms for low, mid and high amplitude cases.

gain_measurement.cpp

-void gain_measurement()
-{
-  TCanvas *c1 = new TCanvas();
-  TTree *tree = new TTree("tree", "tree");
-  TH1D *hist_255 = new TH1D("hist_255"," Threshold gain measurement",500,850,1750);
 
-  
-  tree->ReadFile("255_255.dat", "x/D:y/D");
-  tree->SetEstimate(-1);//Set the #entries to estimate variable limits. n=-1, estimate is set to current maximum of the tree.
+ /////////////////////////////////////////////////////////////
+ // The function fit_1d sets the cosmetics for the histograms/
+ // and fits the histogram with modified erf function.       /
+ /////////////////////////////////////////////////////////////
 
-  hist_255->SetMarkerStyle(3);
-  tree->Draw("x>>hist_255","y","HIST P");
-  
+TH1D *fit_1d(TH1D *hist_255, int i,int j, double low_limit, double up_limit)
+{
   hist_255->GetXaxis()->SetTitle("Threshold");
   hist_255->GetYaxis()->SetTitle("# signals above the threshold");
+  hist_255->SetMarkerStyle(i+1);
+  hist_255->SetMarkerColor(i+2);
 
-  //fitting the histogram with modified error function
-
-  TF1 *modified_erf = new TF1("modified_erf","([0]/2)*(1-TMath::Erf((x-[1])/(sqrt(2)*[2])))",1220,1700);
-
-
-  modified_erf->SetParNames("constant","mean","noise");
+  TF1 *fitfunc = new TF1("fitfunc","([0]/2)*(1-TMath::Erf((x-[1])/(sqrt(2)*[2])))",low_limit,up_limit);
 
-  // Seeting the initial values for the fit parameters
+  cout<<"The fit parameters for the amplitude amp_0"<<j<<""<<" are as follows :"<<std::endl;
+  fitfunc->SetParNames("constant","mean","noise");
 
+  //Assigning Initial values to the parameters
   
-  modified_erf->SetParameter(0,200.0);
+  fitfunc->SetParameter(0,200.0);
 
   double lastbin1 = hist_255->FindLastBinAbove(200);
   double mean = hist_255->GetBinCenter(lastbin1);
-  cout<<"The initial mean value assigned is : "<<mean<<std::endl;
-  modified_erf->SetParameter(1,mean);
+  cout<<"The initial mean value assigned for the data of amp_0 "<<j<<""<<" is "<<""<<mean<<std::endl;
+  fitfunc->SetParameter(1,mean);
 
   double lastbin2 = hist_255->FindLastBinAbove(150);
   double lastbin3 = hist_255->FindLastBinAbove(50);
   double sigma = lastbin3 -lastbin2;
-  cout<<"The initial noise assigned is :"<<sigma<<std::endl;
-  modified_erf->SetParameter(2,sigma);
+  cout<<"The initial noise assigned for the data of amp_0 "<<j<<""<<" is "<<""<<sigma<<std::endl;
+  fitfunc->SetParameter(2,sigma);
 
-  //Fitting histogram
-  
-  modified_erf->SetLineWidth(2);
-  modified_erf->SetLineColor(2);
-   
+  fitfunc->SetLineWidth(2);
+  fitfunc->SetLineColor(2);
+
+  hist_255->Fit("fitfunc"," R");
+  hist_255->GetListOfFunctions()->FindObject("fitfunc")->Draw("same");
+
+  hist_255->SetStats(0);
+  return hist_255;
+
+}
+
+void gain_measurement()
+{
+  //Initialising the histograms.
 
-  hist_255->Fit("modified_erf","R");
-  hist_255->GetListOfFunctions()->FindObject("modified_erf")->Draw("same");
+  TH1D *hist_255_amp03 = new TH1D("hist_255_amp03"," Threshold gain measurement",500,850,1750);
+  TH1D *hist_255_amp02 = new TH1D("hist_255_amp02"," Threshold gain measurement",500,850,1750);
+  TH1D *hist_255_amp01 = new TH1D("hist_255_amp01"," Threshold gain measurement",500,850,1750);
+
+  //Initialising the trees.
+
+  TTree *tree1 = new TTree("tree1", "tree1");
+  TTree *tree2 = new TTree("tree2", "tree2");
+  TTree *tree3 = new TTree("tree3", "tree3");
+
+  tree1->ReadFile("amp03_255_255.dat", "x/D:y/D");
+  tree2->ReadFile("amp02_255_255.dat", "x/D:y/D");
+  tree3->ReadFile("amp01_255_255.dat", "x/D:y/D");
   
-  cout<<"Code succesfull..."<<std::endl;
-}		  
+  tree1->Draw("x>>hist_255_amp03","y","HIST P ");
+  tree2->Draw("x>>hist_255_amp02","y","HIST SAMES P ");
+  tree3->Draw("x>>hist_255_amp01","y","HIST SAMES P ");
+
+
+  fit_1d(hist_255_amp03,1,3,1220.0,1700.0);
+  fit_1d(hist_255_amp02,2,2,1200.0,1420.0);
+  fit_1d(hist_255_amp01,3,1,1150.0,1240.0);
+
+  //Drawing the legend
+
+  TLegend *leg = new TLegend(0.7,0.7,0.9,0.9);
+  leg->AddEntry(hist_255_amp03, "high amplitude","p");
+  leg->AddEntry(hist_255_amp02,"mid amplitude","p");
+  leg->AddEntry(hist_255_amp01,"low amplitude","p");
+  leg->Draw();
+
+  cout<<"Done...";
+
+}
+
+
+
+
+