Exemplo n.º 1
0
void PlotAlignmentValidation::
setDMRHistStyleAndLegend(TH1F* h, PlotAlignmentValidation::DMRPlotInfo& plotinfo, int direction, int layer)
{
  std::pair<float,float> fitResults(9999., 9999.);

  h->SetDirectory(0);

  // The whole DMR plot is plotted with wider line than the split plots
  // If only split plots are plotted, they will be stronger too, though
  h->SetLineWidth((direction == 0 || (plotinfo.plotSplits && !plotinfo.plotPlain)) ? 2 : 1);

  // These lines determine the style of the plots according to rules:
  // -If the plot is for direction != 0, +1 or +2 is added to the given style for distinction
  // -However if only direction split plots are to be plotted, the additions should be 0 and +1 respectively
  // -Modulo 4 arithmetic, because the styles run from 1..4
  int linestyle = plotinfo.vars->getLineStyle() - 1, linestyleplus = 0;
  if (direction == 1) { linestyleplus = 1; }
  if (direction == -1) { linestyleplus = 2; }
  if (direction != 0 && plotinfo.plotSplits && !plotinfo.plotPlain) { linestyleplus--; }
  linestyle = (linestyle + linestyleplus) % 4 + 1;

  int linecolor = plotinfo.vars->getLineColor();
  if (plotinfo.plotLayers && layer > 0) { linecolor += layer - 1; }

  if (plotinfo.firsthisto) {
    setHistStyle(*h, plotinfo.variable.c_str(), "#modules", 1); //set color later
    plotinfo.firsthisto = false;
  }

  h->SetLineColor( linecolor );
  h->SetLineStyle( linestyle );
	  
  if (plotinfo.maxY<h->GetMaximum()){
    plotinfo.maxY=h->GetMaximum();
  }
	  
  //fit histogram for median and mean
  if (plotinfo.variable == "medianX" || plotinfo.variable == "meanX") {
    fitResults = fitGauss(h, linecolor );
  }
	  
  plotinfo.hstack->Add(h);

  std::ostringstream legend;
  legend.precision(2);

  // Legend: header part
  if (direction == -1 && plotinfo.subDetId != 2) { legend << "rDirection < 0: "; }
  else if (direction == 1 && plotinfo.subDetId != 2) { legend << "rDirection > 0: "; }
  else if (direction == -1 && plotinfo.subDetId == 2) { legend << "zDirection < 0: "; }
  else if (direction == 1 && plotinfo.subDetId == 2) { legend << "zDirection > 0: "; }
  else {
    legend  << plotinfo.vars->getName();
    if (layer > 0) {
      legend << ", layer " << layer << "";
    }
    legend << ":";
  }

  // Legend: Statistics
  if (plotinfo.variable == "medianX" || plotinfo.variable == "meanX" ||
      plotinfo.variable == "medianY" || plotinfo.variable == "meanY") {
    if (useFit_) {
      legend << "#mu = " << fitResults.first << " #mum, #sigma = " << fitResults.second << " #mum";
    } else {
      legend << "#mu = " << h->GetMean(1)*10000 << " #mum, rms = " << h->GetRMS(1)*10000 << " #mum";
    }
  } else if (plotinfo.variable == "rmsX" || plotinfo.variable == "rmsY") {
    legend << "#mu = " << h->GetMean(1)*10000 << " #mum, rms = " << h->GetRMS(1)*10000 << " #mum";
  } else if (plotinfo.variable == "meanNormX" || plotinfo.variable == "meanNormY" ||
	     plotinfo.variable == "rmsNormX" || plotinfo.variable == "rmsNormY") {
    legend << "#mu = " << h->GetMean(1) << ", rms = " << h->GetRMS(1);
  }

  // Legend: Delta mu for split plots
  if (plotinfo.h1 != 0 && plotinfo.h2 != 0 && plotinfo.plotSplits &&
      plotinfo.plotPlain && direction == 0) {
    std::string unit = " #mum";
    float factor = 10000.0f;
    if (plotinfo.variable == "meanNormX" || plotinfo.variable == "meanNormY" ||
	plotinfo.variable == "rmsNormX" || plotinfo.variable == "rmsNormY") {
      factor = 1.0f;
      unit = "";
    }
    float deltamu = factor*(plotinfo.h2->GetMean(1) - plotinfo.h1->GetMean(1));
    legend << ", #Delta#mu = " << deltamu << unit;
  }

  plotinfo.legend->AddEntry(h, legend.str().c_str(), "l");

}
Exemplo n.º 2
0
void  PlotAlignmentValidation::plotDMR(const std::string variable, Int_t minHits )
{
 setNiceStyle(); 
 gStyle->SetOptStat(0);

 // TList treeList=getTreeList();

 TCanvas *c = new TCanvas("canv", "canv", 600, 600);
 setCanvasStyle( *c );
 //loop over sub-detectors 
 for (int i=1;i<7;++i){
 
   int histo_Counter=1;
   TLegend *leg_hist = new TLegend(0.17,0.8,0.85,0.88);
   setLegendStyle(*leg_hist);
   //loop over file list
   //TTree *tree= (TTree*)treeList.First();
   //binning
   int nbinsX=100;
   double xmin=0;
   double xmax=0;
   float maxY=0;
   bool isHisto = false;
   std::string plotVar=variable;
   THStack *hstack=new THStack("hstack","hstack");

   for(std::vector<TkOfflineVariables*>::iterator it = sourceList.begin();
       it != sourceList.end(); ++it){
      
     //while ( tree ){
     plotVar=variable;
     TString subdet = "entries>=";
     subdet+=minHits; 
     subdet+=" && subDetId==";
     subdet+=i;
      
     char binning [50]="";
     sprintf (binning, ">>myhisto(%d,  %f , %f)", nbinsX, xmin, xmax);
     TH1F *h = 0;
     
     if (histo_Counter==1&&plotVar=="meanX")(*it)->getTree()->Draw( (plotVar+=">>myhisto(50,-0.005,0.005)").c_str(),subdet,"goff");
     else if (histo_Counter==1&&plotVar=="meanY")(*it)->getTree()->Draw( (plotVar+=">>myhisto(50,-0.005,0.005)").c_str(),subdet,"goff");
     else if (histo_Counter==1&&plotVar=="medianX")(*it)->getTree()->Draw( (plotVar+=">>myhisto(50,-0.005,0.005)").c_str(),subdet,"goff");
     else if (histo_Counter==1&&plotVar=="meanNormX")(*it)->getTree()->Draw( (plotVar+=">>myhisto(100,-2,2)").c_str(),subdet,"goff");
     else if (histo_Counter==1&&plotVar=="rmsX")(*it)->getTree()->Draw( (plotVar+=">>myhisto(100,0.,0.1)").c_str(),subdet,"goff");
     else if (histo_Counter!=1)(*it)->getTree()->Draw( (plotVar+=binning).c_str(),subdet,"goff");

     if (gDirectory) gDirectory->GetObject("myhisto", h);
     std::pair<float,float> fitResults(9999., 9999.);
     if (h){
       if (h->GetEntries()>0) {
	 isHisto = true;
	 h->SetDirectory(0);
	 //general draw options
	 h->SetLineWidth(2);
	 //first histo only, setting optStat...
	 if (histo_Counter==1)
	   setHistStyle(*h,plotVar.c_str() ,"#modules", 1 ); //set color later

	 h->SetLineColor( (*it)->getLineColor() );
	 h->SetLineStyle( (*it)->getLineStyle() );
	   //h->SetMarkerStyle(20+file_Counter);
      
	 //draw options
	 
	 if (maxY<h->GetMaximum()){
	   maxY=h->GetMaximum();
	 }
      
	 //fit histogram for median and mean
	 if (variable=="medianX"||variable =="meanX")fitResults=fitGauss(h, (*it)->getLineColor() );

	 if (histo_Counter==1){
	   //get mean and sigma from fit: gauss for 2sigma range
	   hstack->Add(h);
	   nbinsX=h->GetXaxis()->GetNbins();
	   xmin=h->GetXaxis()->GetXmin();
	   xmax=h->GetXaxis()->GetXmax();
	  
	 }else if (histo_Counter!=1 &&  h->GetEntries()>0)hstack->Add(h);
     
	 char legend [50]="";
	 std::string legEntry = (*it)->getName();
	 if (variable=="medianX"||variable =="meanX")sprintf (legend, "%s: #mu = %4.2f#mum, #sigma = %4.2f#mum ",legEntry.c_str(),fitResults.first ,fitResults.second);
	 else sprintf (legend, "%s ",legEntry.c_str());
	 if(h)
	   leg_hist->AddEntry(h,legend,"l");
	 else
	   std::cerr<< "histogram did not exist!";
       }
     }
     //     tree= (TTree*)treeList.After( tree );
     //     file_Counter++;
     histo_Counter++;
        
   }
    
   if (isHisto){
     hstack->Draw("nostack");
     hstack->SetMaximum(maxY*1.3);
     setTitleStyle(*hstack,plotVar.c_str() ,"#modules",i);
     setHistStyle(*hstack->GetHistogram(),plotVar.c_str() ,"#modules", 1 );
     leg_hist->Draw(); 

     std::string histName="D";
     if (variable=="medianX") histName+="medianR_";
     else if (variable=="meanX") histName+="meanR_";
     else if (variable=="meanY") histName+="meanYR_";
     else if (variable=="rmsX") histName+="rmsR_";
     std::string subDetector ="";
     switch (i){
     case 1 : subDetector+="TPB";break;
     case 2 : subDetector+="TPE";break;
     case 3 : subDetector+="TIB";break;
     case 4 : subDetector+="TID";break;
     case 5 : subDetector+="TOB";break;
     case 6 : subDetector+="TEC";break;
     }
 
     char PlotName[100];
     sprintf( PlotName, "%s/%s%s.eps",outputDir.c_str(), histName.c_str(), subDetector.c_str() );
     c->Update(); 
     c->Print(PlotName);
     //c->Update();
     //c->Close();
    
   }
   delete hstack;
   hstack=0; 
  
 }
 
 delete c;
 c=0;
}