compareanapp.cxx

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#include "TMVA/compareanapp.h"
#include "TMVA/Types.h"
#include "TH2.h"
 
 
#define CheckDerivedPlots 0
//TString DerivedPlotName = "Proba";
TString DerivedPlotName = "Rarity";
 
void TMVA::compareanapp( TString finAn , TString finApp ,
                         HistType htype , bool useTMVAStyle )
{
   cout << "=== Compare histograms of two files ===" << endl;
   cout << "    File-1: " << finAn << endl;
   cout << "    File-2: " << finApp << endl;
 
   // set style and remove existing canvas'
   TMVAGlob::Initialize( useTMVAStyle );
 
   // switches
   const Bool_t Draw_CFANN_Logy = kFALSE;
   const Bool_t Save_Images     = kTRUE;
 
   TFile* file    = TMVAGlob::OpenFile( finAn );
   TFile* fileApp = new TFile( finApp );
   file->cd();
 
   // define Canvas layout here!
   const Int_t width = 600;   // size of canvas
 
   // counter variables
   Int_t countCanvas = 0;
 
   TList methods;
   TIter next(&methods);
   TKey *key;
   while ( (key = (TKey*)next()) ) {
 
      TString dirname = ((TDirectory*)key->ReadObj())->GetName();
      if (dirname.Contains( "Cuts" )) {
         cout << "--- Found directory: " << dirname << " --> ignoring" << endl;
         continue;
      }
      cout << "--- Found directory: " << dirname
           << " --> going in" << endl;
 
      TString methodName;
      TMVAGlob::GetMethodName(methodName,key);
 
      cout << "--- Method: " << methodName << endl;
 
      //TDirectory* mDir = (TDirectory*)
      key->ReadObj();
      TList titles;
      //      UInt_t ninst = TMVAGlob::GetListOfTitles(mDir,titles);
      TIter nextTitle(&titles);
      TKey *titkey;
      TDirectory *titDir;
      while ( (titkey = TMVAGlob::NextKey(nextTitle,"TDirectory")) ) {
 
         titDir = (TDirectory *)titkey->ReadObj();
         TString methodTitle;
         TMVAGlob::GetMethodTitle(methodTitle,titDir);
         TString hname = "MVA_" + methodTitle;
         if (CheckDerivedPlots) hname += TString("_") + DerivedPlotName;
 
         TH1* sig = dynamic_cast<TH1*>(titDir->Get( hname + "_S" ));
         TH1* bgd = dynamic_cast<TH1*>(titDir->Get( hname + "_B" ));
 
         if (sig==0 || bgd==0) continue;
 
         // chop off useless stuff
         sig->SetTitle( TString::Format("TMVA output for classifier: %s", methodTitle.Data()) );
         if (htype == kProbaType)
            sig->SetTitle( TString::Format("TMVA probability for classifier: %s", methodTitle.Data()) );
         else if (htype == kRarityType)
            sig->SetTitle( TString::Format("TMVA Rarity for classifier: %s", methodTitle.Data()) );
 
         // create new canvas
         TString ctitle = ((htype == TMVA::kMVAType) ?
                           TString::Format("TMVA output %s",methodTitle.Data()) :
                           (htype == kProbaType) ?
                           TString::Format("TMVA probability %s",methodTitle.Data()) :
                           TString::Format("TMVA rarity %s",methodTitle.Data()));
 
         TString cname = ((htype == TMVA::kMVAType) ?
                          TString::Format("output_%s",methodTitle.Data()) :
                          (htype == kProbaType) ?
                          TString::Format("probability_%s",methodTitle.Data()) :
                          TString::Format("rarity_%s",methodTitle.Data()));
 
         TCanvas* c = new TCanvas( TString::Format("canvas%d", countCanvas+1), ctitle,
                                   countCanvas*50+200, countCanvas*20, width, width*0.78 );
 
         // set the histogram style
         TMVAGlob::SetSignalAndBackgroundStyle( sig, bgd );
 
         // normalise both signal and background
         TMVAGlob::NormalizeHists( sig, bgd );
 
         // frame limits (choose judicuous x range)
         Float_t nrms = 4;
         Float_t xmin = std::max( std::min(sig->GetMean() - nrms*sig->GetRMS(),
                                               bgd->GetMean() - nrms*bgd->GetRMS() ),
                                    sig->GetXaxis()->GetXmin() );
         Float_t xmax = std::min( std::max(sig->GetMean() + nrms*sig->GetRMS(),
                                               bgd->GetMean() + nrms*bgd->GetRMS() ),
                                    sig->GetXaxis()->GetXmax() );
         Float_t ymin = 0;
         Float_t ymax = std::max( sig->GetMaximum(), bgd->GetMaximum() )*1.2 ;
 
         if (Draw_CFANN_Logy && methodName == "CFANN") ymin = 0.01;
 
         // build a frame
         Int_t nb = 500;
         TH2F* frame = new TH2F( TString("frame") + methodTitle, sig->GetTitle(),
                                 nb, xmin, xmax, nb, ymin, ymax );
         frame->GetXaxis()->SetTitle(methodTitle);
         if      (htype == kProbaType ) frame->GetXaxis()->SetTitle( "Signal probability" );
         else if (htype == kRarityType) frame->GetXaxis()->SetTitle( "Signal rarity" );
         frame->GetYaxis()->SetTitle("Normalized");
         TMVAGlob::SetFrameStyle( frame );
 
         // eventually: draw the frame
         frame->Draw();
 
         c->GetPad(0)->SetLeftMargin( 0.105 );
         frame->GetYaxis()->SetTitleOffset( 1.2 );
 
         if (Draw_CFANN_Logy && methodName == "CFANN") c->SetLogy();
 
         // Draw legend
         TLegend *legend= new TLegend( c->GetLeftMargin(), 1 - c->GetTopMargin() - 0.12,
                                       c->GetLeftMargin() + 0.3, 1 - c->GetTopMargin() );
         legend->SetFillStyle( 1 );
         legend->AddEntry(sig,"Signal","F");
         legend->AddEntry(bgd,"Background","F");
         legend->SetBorderSize(1);
         legend->SetMargin( 0.3 );
         legend->Draw("same");
 
         // overlay signal and background histograms
         sig->Draw("samehist");
         bgd->Draw("samehist");
 
         // retrieve corresponding histogram from TMVApp.root
         TString hStem(hname);
         cout << "--- Searching for histogram: " << hStem.Data() << " in application file" << endl;
 
         TH1* testHist = (TH1*)fileApp->Get( hStem );
         if (testHist != 0) {
            cout << "--> Found application histogram: " << testHist->GetName() << " --> superimpose it" << endl;
            // compute normalisation factor
            TMVAGlob::NormalizeHists( testHist );
            testHist->SetLineWidth( 3 );
            testHist->SetLineColor( 1 );
            testHist->Draw("samehist");
         }
 
         // redraw axes
         frame->Draw("sameaxis");
 
         // text for overflows
         Int_t    nbin = sig->GetNbinsX();
         Double_t dxu  = sig->GetBinWidth(0);
         Double_t dxo  = sig->GetBinWidth(nbin+1);
         TString uoflow = TString::Format( "U/O-flow (S,B): (%.1f, %.1f)%% / (%.1f, %.1f)%%",
                                sig->GetBinContent(0)*dxu*100, bgd->GetBinContent(0)*dxu*100,
                                sig->GetBinContent(nbin+1)*dxo*100, bgd->GetBinContent(nbin+1)*dxo*100 );
         TText* t = new TText( 0.975, 0.115, uoflow );
         t->SetNDC();
         t->SetTextSize( 0.030 );
         t->SetTextAngle( 90 );
         t->AppendPad();
 
         // save canvas to file
         c->Update();
         TMVAGlob::plot_logo();
         if (Save_Images) {
            if      (htype == TMVA::kMVAType)   TMVAGlob::imgconv( c, TString::Format("plots/mva_%s",    methodTitle.Data()) );
            else if (htype == TMVA::kProbaType) TMVAGlob::imgconv( c, TString::Format("plots/proba_%s",  methodTitle.Data()) );
            else                         TMVAGlob::imgconv( c, TString::Format("plots/rarity_%s", methodTitle.Data()) );
         }
         countCanvas++;
      }
   }
}