6 bad data points still remains.

gain_measurement.cpp

@@ -45,6 +45,7 @@ void fit_modified_erf(TH1D* hist_255,int colors,int markers,double injected_volt
 
 
   TF1 *fiterf = new TF1("fiterf","([0]/2)*(1-TMath::Erf((x-[1])/(sqrt(2)*[2])))",fitmin,fitmax);
+  ROOT::Math::MinimizerOptions::SetDefaultMaxFunctionCalls(10000);
 
   /*Setting parameter names*/
   fiterf->SetParNames("constant","mean","noise");
@@ -52,20 +53,28 @@ void fit_modified_erf(TH1D* hist_255,int colors,int markers,double injected_volt
 
   //Assigning Initial values to the parameters
 
+
   fiterf->SetParameter(0,200.0);
-  int lastbin1 = hist_255->FindLastBinAbove(200);
+  int lastbin1 = hist_255->FindLastBinAbove(200,1);
   double mean = hist_255->GetBinCenter(lastbin1);
   fiterf->SetParameter(1,mean);
+  cout<<"The initial mean value is "<<mean<<std::endl;
 
-  int lastbin2 = hist_255->FindLastBinAbove(150);
-  int lastbin3 = hist_255->FindLastBinAbove(50);
+  int lastbin2 = hist_255->FindLastBinAbove(150,1);
+  int lastbin3 = hist_255->FindLastBinAbove(50,1);
   int sigma = lastbin3 -lastbin2;
   fiterf->SetParameter(2,sigma);
+  cout<<"The initial noise value is "<<sigma<<std::endl;
 
   fiterf->SetLineWidth(2);
   fiterf->SetLineColor(2);
 
-  hist_255->Fit("fiterf"," R");
+  /* if(mean<1000&&sigma<0){
+    TF1::RejectPoint();
+    return 0;
+  }
+  else{*/
+  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 <<"_"
@@ -75,6 +84,7 @@ void fit_modified_erf(TH1D* hist_255,int colors,int markers,double injected_volt
   // fitpars <<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)
@@ -140,59 +150,52 @@ std::vector<TH1D*> gain_measurement_pixel(int i, int j)
   return hist_255;
 }
 
-void linear_fit(int x){
-  ifstream fitpars;
-  fitpars.open("fit_parameters.txt");
+void linear_fit(){
+  ifstream fitpars("fit_parameters.txt");
   std::string pixel_address;
-  std::vector<double>amp_vec,mean_vec;
   double amp_vals,mean_vals;
   std::vector<TGraph*>gr;
-  std::vector<TGraph*>gr3;
-  TGraph* gr2 = new TGraph();
-  int ctr=0;
-  int k=0;
-
+  auto mg = new TMultiGraph();
+  int ctr =0;
 
   while(fitpars>>pixel_address){
+    cout << "ctr: " << ctr << " modulo: " << ctr%3 << endl;
+    if(ctr%3==0){
+      gr.push_back(new TGraph());
+    }
+
     fitpars>>amp_vals>>mean_vals;
-    amp_vec.push_back(amp_vals);
-    mean_vec.push_back(mean_vals);
-    gr.push_back(new TGraph(amp_vec.size(),&amp_vec[0],&mean_vec[0]));
+    gr.back()->SetPoint(ctr%3, amp_vals, mean_vals);
     ctr++;
   }
 
-  for(ctr=0;ctr<amp_vec.size();ctr++){
-    if(ctr%3==0&&ctr>=0&&ctr<amp_vec.size()){
-      for(k=ctr;k<ctr+3;k++){
-	gr2->SetPoint(gr.at(k)->GetN(),amp_vec[k],mean_vec[k]);
-      }
-      gr3.push_back(gr2);
-    }
-  }
-  cout<<gr3.size()<<std::endl;
-  for(int j=0;j<gr3.size();j++){
+  cout<<gr.size()<<std::endl;
+  for(int j=0;j<gr.size();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);
-    gr3.at(j)->Fit(linear_fit);
-    gr3.at(j)->SetTitle("injected voltage vs mean vals for 256 graphs ");
-    gr3.at(j)->GetXaxis()->SetTitle("injected voltage");
-    gr3.at(j)->GetYaxis()->SetTitle("mean vals");
-    gr3.at(j)->Draw("A*");
+    cout<<"graph "<<j<<" Number of points : "<<gr.at(j)->GetN()<<std::endl;
+    gr.at(j)->Fit(linear_fit);
+
+    mg->Add(gr.at(j));
+    mg->SetTitle("injected voltage vs mean vals for 256 graphs ;injected voltage;mean values");
+
     std::ofstream slopes;
     slopes.open("slopes.txt",std::ofstream::app);
     slopes<<linear_fit->GetParameter(0)<<" ";
   }
+  mg->Draw("A*");
 }
 
 
-void slope_distribution(int y)
+
+void slope_distribution()
 {
   ifstream slopes("slopes.txt");
   double slopeval;
-  TH1D* hist = new TH1D("slope","slope distribution",200,-0.24540,-.24510);
+  TH1D* hist = new TH1D("slope","slope distribution",200,0,3);
 
   if(slopes.is_open()){
     while(!slopes.eof()){
@@ -207,7 +210,7 @@ void slope_distribution(int y)
 
 
 
-void gain_9()
+void gain_measurement()
 {
   int row,col;
   THStack* hs = new THStack("hs", "Gain measurements");
@@ -264,9 +267,9 @@ void gain_9()
   leg->Draw("SAME");
 
   c1->cd(2);
-  linear_fit(5);
+  linear_fit();
 
   c1->cd(3);
-  slope_distribution(5);
+  slope_distribution();
 
 }