#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(titDir->Get( hname + "_S" )); TH1* bgd = dynamic_cast(titDir->Get( hname + "_B" )); if (sig==0 || bgd==0) continue; // chop off useless stuff sig->SetTitle( Form("TMVA output for classifier: %s", methodTitle.Data()) ); if (htype == kProbaType) sig->SetTitle( Form("TMVA probability for classifier: %s", methodTitle.Data()) ); else if (htype == kRarityType) sig->SetTitle( Form("TMVA Rarity for classifier: %s", methodTitle.Data()) ); // create new canvas TString ctitle = ((htype == TMVA::kMVAType) ? Form("TMVA output %s",methodTitle.Data()) : (htype == kProbaType) ? Form("TMVA probability %s",methodTitle.Data()) : Form("TMVA rarity %s",methodTitle.Data())); TString cname = ((htype == TMVA::kMVAType) ? Form("output_%s",methodTitle.Data()) : (htype == kProbaType) ? Form("probability_%s",methodTitle.Data()) : Form("rarity_%s",methodTitle.Data())); TCanvas* c = new TCanvas( Form("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 = TMath::Max( TMath::Min(sig->GetMean() - nrms*sig->GetRMS(), bgd->GetMean() - nrms*bgd->GetRMS() ), sig->GetXaxis()->GetXmin() ); Float_t xmax = TMath::Min( TMath::Max(sig->GetMean() + nrms*sig->GetRMS(), bgd->GetMean() + nrms*bgd->GetRMS() ), sig->GetXaxis()->GetXmax() ); Float_t ymin = 0; Float_t ymax = TMath::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 = Form( "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, Form("plots/mva_%s", methodTitle.Data()) ); else if (htype == TMVA::kProbaType) TMVAGlob::imgconv( c, Form("plots/proba_%s", methodTitle.Data()) ); else TMVAGlob::imgconv( c, Form("plots/rarity_%s", methodTitle.Data()) ); } countCanvas++; } } }