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