C++ TCanvas::GetTopMargin方法代码示例

  //____________________________________________________________________
  void Run(const char* newName,        const char* oldName,
	   const char* newTitle="New", const char* oldTitle="Old")
  {
    TFile* newFile = TFile::Open(newName,"READ");
    TFile* oldFile = TFile::Open(oldName,"READ");
    if (!newFile || !oldFile) return;

    TH1* newCent = GetH1(newFile, "realCent");
    TH1* oldCent = GetH1(oldFile, "realCent");
    if (!newCent || !oldCent) return;

    TString  t; t.Form("#it{R}=#frac{%s}{%s}", newTitle, oldTitle);
    TCanvas* c     = new TCanvas("c", t, 1200, 800);
    c->SetTopMargin(0.01);
    c->SetRightMargin(0.20);
    fLegend = new TLegend(1-c->GetRightMargin(),
			  c->GetBottomMargin(),
			  1, 1-c->GetTopMargin(),
			  t);
    fLegend->SetFillStyle(0);
    fLegend->SetBorderSize(0);
    THStack* stack = new THStack("ratios","");
			       
    fMin = +1e6;
    fMax = -1e6;
    TH1* one = 0;
    for (Int_t i = newCent->GetNbinsX(); i--;) {
      Double_t c1 = newCent->GetXaxis()->GetBinLowEdge(i+1);
      Double_t c2 = newCent->GetXaxis()->GetBinUpEdge(i+1);
      Info("", "c1=%f c2=%f", c1, c2);
      TH1*     r  = One(newFile, oldFile, c1, c2);    
      if (!r) continue;
      if (!one) {
	one = static_cast<TH1*>(r->Clone("one"));
	one->SetDirectory(0);
	one->Reset();
	for (Int_t j = 1; j <= one->GetNbinsX(); j++) {
	  one->SetBinContent(j,1);
	  one->SetBinError  (j,0);
	}
      }
      // r->Add(one, i-1);
      // r->Scale(TMath::Power(10,i));
      stack->Add(r);
    }
    stack->Draw("nostack");
    stack->SetMinimum(0.95*fMin);
    stack->SetMaximum(1.05*fMax);
    stack->GetHistogram()->SetXTitle("#eta");
    stack->GetHistogram()->SetYTitle("#it{R}");
    fLegend->Draw();
    c->Modified();
    c->Update();
    c->cd();
    c->SaveAs(Form("%sover%s.png", newTitle, oldTitle));
  }  

void annconvergencetest( TDirectory *lhdir )
{
   TCanvas* c = new TCanvas( "MLPConvergenceTest", "MLP Convergence Test", 150, 0, 600, 580*0.8 ); 
  
   TH1* estimatorHistTrain = (TH1*)lhdir->Get( "estimatorHistTrain" );
   TH1* estimatorHistTest  = (TH1*)lhdir->Get( "estimatorHistTest"  );

   Double_t m1  = estimatorHistTrain->GetMaximum();
   Double_t m2  = estimatorHistTest ->GetMaximum();
   Double_t max = TMath::Max( m1, m2 );
   m1  = estimatorHistTrain->GetMinimum();
   m2  = estimatorHistTest ->GetMinimum();
   Double_t min = TMath::Min( m1, m2 );
   estimatorHistTrain->SetMaximum( max + 0.1*(max - min) );
   estimatorHistTrain->SetMinimum( min - 0.1*(max - min) );
   estimatorHistTrain->SetLineColor( 2 );
   estimatorHistTrain->SetLineWidth( 2 );
   estimatorHistTrain->SetTitle( TString("MLP Convergence Test") );
  
   estimatorHistTest->SetLineColor( 4 );
   estimatorHistTest->SetLineWidth( 2 );

   estimatorHistTrain->GetXaxis()->SetTitle( "Epochs" );
   estimatorHistTrain->GetYaxis()->SetTitle( "Estimator" );
   estimatorHistTrain->GetXaxis()->SetTitleOffset( 1.20 );
   estimatorHistTrain->GetYaxis()->SetTitleOffset( 1.65 );

   estimatorHistTrain->Draw();
   estimatorHistTest ->Draw("same");

   // need a legend
   TLegend *legend= new TLegend( 1 - c->GetRightMargin() - 0.45, 1-c->GetTopMargin() - 0.20, 
                                 1 - c->GetRightMargin() - 0.05, 1-c->GetTopMargin() - 0.05 );

   legend->AddEntry(estimatorHistTrain,"Training Sample","l");
   legend->AddEntry(estimatorHistTest,"Test sample","l");
   legend->Draw("same");
   legend->SetMargin( 0.3 );

   c->cd();
   TMVAGlob::plot_logo(); // don't understand why this doesn't work ... :-(
   c->Update();

   TString fname = "plots/annconvergencetest";
   TMVAGlob::imgconv( c, fname );
}

TCanvas* makeNiceCanvasByPixMargins(Int_t pixelPerBinX, Int_t pixelPerBinY, Int_t nbinx, Int_t nbiny, Int_t top, Int_t bottom, Int_t left, Int_t right) {
  
  Int_t rubaX = 4; //determinato sperimentalmente                                                                          
  Int_t rubaY = 28; //determinato sperimentalmente                                                                                                        

  TString name = generateRandomName();

  Int_t plotBaseDimX = pixelPerBinX*nbinx;
  Int_t plotBaseDimY = pixelPerBinY*nbiny;
  Int_t XX = (Int_t)(plotBaseDimX+left+right);
  Int_t YY = (Int_t)(plotBaseDimY+top+bottom);
  TCanvas* can = new TCanvas(name,name,XX+rubaX,YY+rubaY);
  can->SetTopMargin((1.*top)/(1.*YY));
  can->SetBottomMargin((1.*bottom)/(1.*YY));
  can->SetRightMargin(right/(1.*XX));
  can->SetLeftMargin(left/(1.*XX));
  can->SetBorderMode(0);
  std::cout << "Nice canvas " << XX << " * " << YY << " Margin: t " << can->GetTopMargin() << " b " << can->GetBottomMargin() << " l " << can->GetLeftMargin() << " r " << can->GetRightMargin() << std::endl;

  return can;

}

/** 
 * Extract ALICE PbPb @ 5.02TeV over |eta|<2
 * 
 * @param filename  Input file name 
 * @param outname   Output file name 
 * @param reweigh   Whether it is reweighed 
 */
void
Extract(const char* filename="dndneta.pbpb502.20151124.root",
	const char* outname="TRACKLETS_5023_PbPb.input",
	Bool_t      reweigh=false)
{
  if (filename == 0) return;
  TFile* file = TFile::Open(filename, "READ");
  TObjArray* arr = static_cast<TObjArray*>(file->Get("TObjArray"));
  // Now count number of bins
  Int_t nBins = 0;
  TIter next(arr);
  TObject* obj = 0;
  while ((obj = next())) {
    if (TString(obj->GetName()).Contains("DataCorrSignal")) 
      nBins++;
  }
  Info("ExtractdNdeta", "Defining %d centrality bins", nBins);
  TArrayD c(nBins+1);
  if (nBins == 5) {
    c[0] = 0; c[1] = 10; c[2] = 20; c[3] = 40; c[4] = 60; c[5] = 80;
  }
  else if (nBins >= 9) {
    c[0] =  0; c[1] =  5; c[2] = 10; c[3] = 20; c[4] = 30; c[5] = 40;
    c[6] = 50; c[7] = 60; c[8] = 70; c[9] = 80;
    if (nBins >= 10) c[10] =  90;
    if (nBins >= 11) c[11] = 100;
  }
  
  THStack* all = new THStack("all","all");
  std::ofstream out(outname);
  std::ostream& o = out; // std::cout;
  // std::ostream& o = std::cout;
  
  o << "*author: SHAHOYAN : 2015\n"
    << "*title: Full centrality dependence of the charged "
    << "particle pseudo-rapidity density over the widest "
    << "possible pseudo-rapidity range in Pb-Pb collisions "
    << "at 5.02 TeV\n"
    << "*detector: TRACKLETS\n"
    << "*experiment: CERN-LHC-TRACKLETS\n"
    << "*comment: CERN-LHC: We present the charged particle pseudo-rapidity "
    << "density of charged particles in Pb-Pb collisions at sqrt(s)/nucleon "
    "= 5.02 over the widest possible pseudo-rapidity and centrality range "
    << "possible.\n"  << std::endl;
  
  for (Int_t i = 0; i < nBins; i++) {
    TString hName = Form("bin%d_DataCorrSignal_PbPb",i);
    TH1* h = static_cast<TH1*>(arr->FindObject(hName));
    if (!h) {
      hName.ReplaceAll("PbPb", "PBPB");
      h = static_cast<TH1*>(arr->FindObject(hName));
      if (!h) {
	Warning("", "Histogram (%s) missing for bin %d", hName.Data(), i);
	arr->Print();
	continue;
      }
    }
    
    Color_t      col = PbPbColor(c[i], c[i+1]);
    h->SetLineColor(col);
    h->SetMarkerColor(col);
    h->SetFillColor(col);
    all->Add(h);
    Info("","Making GSE for %0d%% to %3d%% (%d)",
	 Int_t(c[i]), Int_t(c[i+1]), col);
    
    MakeGSE(o, h, c[i], c[i+1], reweigh);
  }
  // all->Draw("nostack");
  o << "*E" << std::endl;
  out.close();

  TCanvas*        can = new TCanvas("c","C", 1600, 800);
  can->SetRightMargin(0.2);
  can->SetTopMargin(0.01);

  TLegend*        cl = new TLegend(1-can->GetRightMargin(),
				   can->GetBottomMargin(),.99,
				   1-can->GetTopMargin());
  cl->SetFillStyle(0);
  cl->SetBorderSize(0);
  
  gROOT->LoadMacro("$HOME/GraphSysErr/GraphSysErr.C+");
  TList* ll = GraphSysErr::Import(outname);
  // ll->ls();

  TIter next(ll);
  TObject* obj = 0;
  Bool_t first = true;
  TH1* frame = 0;
  Double_t min=100000, max=0;
  Int_t i = 0;
  while ((obj = next())) {
//.........这里部分代码省略.........

//.........这里部分代码省略.........
            Float_t nrms = 4;
            cout << "--- Mean and RMS (S): " << sig->GetMean() << ", " << sig->GetRMS() << endl;
            cout << "--- Mean and RMS (B): " << bgd->GetMean() << ", " << bgd->GetRMS() << endl;
            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 maxMult = (htype == CompareType) ? 1.3 : 1.2;
            Float_t ymax = TMath::Max( sig->GetMaximum(), bgd->GetMaximum() )*maxMult;
   
            // build a frame
            Int_t nb = 500;
            TString hFrameName(TString("frame") + methodTitle);
            TObject *o = gROOT->FindObject(hFrameName);
            if(o) delete o;
            TH2F* frame = new TH2F( hFrameName, sig->GetTitle(), 
                                    nb, xmin, xmax, nb, ymin, ymax );
            frame->GetXaxis()->SetTitle( methodTitle + ((htype == MVAType || htype == CompareType) ? " response" : "") );
            if      (htype == ProbaType  ) frame->GetXaxis()->SetTitle( "Signal probability" );
            else if (htype == RarityType ) 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 );

            // Draw legend               
            TLegend *legend= new TLegend( c->GetLeftMargin(), 1 - c->GetTopMargin() - 0.12, 
                                          c->GetLeftMargin() + (htype == CompareType ? 0.40 : 0.3), 1 - c->GetTopMargin() );
            legend->SetFillStyle( 1 );
            legend->AddEntry(sig,TString("Signal")     + ((htype == CompareType) ? " (test sample)" : ""), "F");
            legend->AddEntry(bgd,TString("Background") + ((htype == CompareType) ? " (test sample)" : ""), "F");
            legend->SetBorderSize(1);
            legend->SetMargin( (htype == CompareType ? 0.2 : 0.3) );
            legend->Draw("same");

            // overlay signal and background histograms
            sig->Draw("samehist");
            bgd->Draw("samehist");
   
            if (htype == CompareType) {
               // if overtraining check, load additional histograms
               TH1* sigOv = 0;
               TH1* bgdOv = 0;

               TString ovname = hname += "_Train";
               sigOv = dynamic_cast<TH1*>(titDir->Get( ovname + "_S" ));
               bgdOv = dynamic_cast<TH1*>(titDir->Get( ovname + "_B" ));
      
               if (sigOv == 0 || bgdOv == 0) {
                  cout << "+++ Problem in \"mvas.C\": overtraining check histograms do not exist" << endl;
               }
               else {
                  cout << "--- Found comparison histograms for overtraining check" << endl;

                  TLegend *legend2= new TLegend( 1 - c->GetRightMargin() - 0.42, 1 - c->GetTopMargin() - 0.12,
                                                 1 - c->GetRightMargin(), 1 - c->GetTopMargin() );
                  legend2->SetFillStyle( 1 );
                  legend2->SetBorderSize(1);
                  legend2->AddEntry(sigOv,"Signal (training sample)","P");

//------------------------------------------------------------------------------
// DrawIt
//------------------------------------------------------------------------------
void DrawIt(TString filename,
	    TString hname,
	    TString cname,
	    TString title)
{
  TFile* inputfile = TFile::Open("../AuxiliaryFilesWZXS8TeV/" + filename + ".root");

  TH2F* h = (TH2F*)inputfile->Get(hname)->Clone(cname);

  h->SetDirectory(0);

  inputfile->Close();

  TString name = h->GetName();

  TCanvas* canvas = new TCanvas(name, name, 600, 600);

  if (name.Contains("PR")) canvas->SetLogx();
  if (name.Contains("SF")) canvas->SetLogx();

  canvas->SetLeftMargin (0.9 * canvas->GetLeftMargin());
  canvas->SetRightMargin(3.5 * canvas->GetRightMargin());
  canvas->SetTopMargin  (1.2 * canvas->GetTopMargin());

  TH2FAxisFonts(h, "x", "p_{T} [GeV]");
  TH2FAxisFonts(h, "y", "#eta");

  h->Draw("colz");

  h->SetTitle("");

  DrawTLatex(42, 0.940, 0.976, _bigLabelSize, 33, title);

  if (!title.Contains("trigger")) {

    Double_t hmin = h->GetMinimum();
    Double_t hmax = h->GetMaximum();

    for (Int_t i=1; i<=h->GetNbinsX(); i++) {
      for (Int_t j=1; j<=h->GetNbinsY(); j++) {

	Double_t value = h->GetBinContent(i,j);

	Double_t ypos = h->GetYaxis()->GetBinCenter(j);
	Double_t xpos = h->GetXaxis()->GetBinCenter(i);
      
	if (gPad->GetLogx()) xpos = h->GetXaxis()->GetBinCenterLog(i);

	TLatex* latex = new TLatex(xpos, ypos, Form("%.2f", value));

	latex->SetTextAlign(   22);
	latex->SetTextFont (   42);
	latex->SetTextSize (0.027);

	if (value < hmin + 0.3*(hmax - hmin)) latex->SetTextColor(kWhite);
	
	latex->Draw();
      }
    }
  }


  // Set the palette font
  //----------------------------------------------------------------------------
  canvas->Update();

  TPaletteAxis* palette = (TPaletteAxis*)h->GetListOfFunctions()->FindObject("palette");

  palette->SetLabelFont(42);


  // Save the plot
  //----------------------------------------------------------------------------
  canvas->Update();
  
  canvas->Modified();

  canvas->GetFrame()->DrawClone();

  canvas->SaveAs("pdf/scale_factors/" + name + ".pdf");
  canvas->SaveAs("png/scale_factors/" + name + ".png");
}

//.........这里部分代码省略.........
                    }
                    if ((sigF == NULL || bkgF == NULL) &&!hname.Contains("hist") ) {
                        cout << "*** probas.C: big troubles - did not found histogram " << hspline.Data() << " "
                             << sigF << " " << bkgF << endl;
                        return;
                    }
                    else  {
                        // remove the signal suffix

                        // check that exist
                        if (NULL != sigF && NULL != bkgF && NULL!=sig && NULL!=bgd) {

                            TString hname = sig->GetName();

                            // chop off useless stuff
                            sig->SetTitle( TString("TMVA output for classifier: ") + methodTitle );

                            // create new canvas
                            cout << "--- Book canvas no: " << countCanvas << endl;
                            char cn[20];
                            sprintf( cn, "canvas%d", countCanvas+1 );
                            c = new TCanvas( cn, Form("TMVA Output Fit Variables %s",methodTitle.Data()),
                                             countCanvas*50+200, countCanvas*20, width, width*0.78 );

                            // set the histogram style
                            TMVAGlob::SetSignalAndBackgroundStyle( sig, bgd );
                            TMVAGlob::SetSignalAndBackgroundStyle( sigF, bkgF );

                            // 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() )*1.5;

                            if (Draw_CFANN_Logy && mvaName[imva] == "CFANN") ymin = 0.01;

                            // build a frame
                            Int_t nb = 500;
                            TH2F* frame = new TH2F( TString("frame") + sig->GetName() + "_proba", sig->GetTitle(),
                                                    nb, xmin, xmax, nb, ymin, ymax );
                            frame->GetXaxis()->SetTitle(methodTitle);
                            frame->GetYaxis()->SetTitle("Normalized");
                            TMVAGlob::SetFrameStyle( frame );

                            // eventually: draw the frame
                            frame->Draw();

                            if (Draw_CFANN_Logy && mvaName[imva] == "CFANN") c->SetLogy();

                            // overlay signal and background histograms
                            sig->SetMarkerColor( TMVAGlob::c_SignalLine );
                            sig->SetMarkerSize( 0.7 );
                            sig->SetMarkerStyle( 20 );
                            sig->SetLineWidth(1);

                            bgd->SetMarkerColor( TMVAGlob::c_BackgroundLine );
                            bgd->SetMarkerSize( 0.7 );
                            bgd->SetMarkerStyle( 24 );
                            bgd->SetLineWidth(1);

                            sig->Draw("samee");
                            bgd->Draw("samee");

                            sigF->SetFillStyle( 0 );
                            bkgF->SetFillStyle( 0 );
                            sigF->Draw("samehist");
                            bkgF->Draw("samehist");

                            // redraw axes
                            frame->Draw("sameaxis");

                            // Draw legend
                            TLegend *legend= new TLegend( c->GetLeftMargin(), 1 - c->GetTopMargin() - 0.2,
                                                          c->GetLeftMargin() + 0.4, 1 - c->GetTopMargin() );
                            legend->AddEntry(sig,"Signal data","P");
                            legend->AddEntry(sigF,"Signal PDF","L");
                            legend->AddEntry(bgd,"Background data","P");
                            legend->AddEntry(bkgF,"Background PDF","L");
                            legend->Draw("same");
                            legend->SetBorderSize(1);
                            legend->SetMargin( 0.3 );

                            // save canvas to file
                            c->Update();
                            TMVAGlob::plot_logo();
                            sprintf( fname, "plots/mva_pdf_%s_c%i", methodTitle.Data(), countCanvas+1 );
                            if (Save_Images) TMVAGlob::imgconv( c, fname );
                            countCanvas++;
                        }
                    }
                }
            }
        }
    }
}

TCanvas* DrawKs(const char* filename)
{

  TFile* file = TFile::Open(filename, "READ");
  if (!file) {
    Warning("DrawKs", "File %s couldn't be opened", filename);
    return 0;
  }

  TH1* cent = static_cast<TH1*>(file->Get("cent"));
  if (!cent) {
    Warning("DrawKs", "Failed to find cent in %s", file->GetName());
    return 0;
  }

  TString t(filename);
  t.ReplaceAll("results/", "");
  t.ReplaceAll("combine_","");
  t.ReplaceAll("_0x3.root", "");
  TString nm(filename);
  nm.ReplaceAll(".root", "");
  nm.ReplaceAll("results/", "plots/");
  nm.ReplaceAll("combine", "ks");
  if (t.Contains("none")) 
    t.ReplaceAll("none", "No weights");
  else
    t.Append(" weights");
  
  Int_t cW = 1200;
  Int_t cH =  800;
  TCanvas* c = new TCanvas(nm,t,cW, cH);
  c->SetTopMargin(0.07);
  c->SetRightMargin(0.20);
  c->SetTicks();
  
  TLegend* l = new TLegend(1-c->GetRightMargin(),
			   c->GetBottomMargin(), 
			   .99,
			   1-c->GetTopMargin());
  l->SetFillStyle(0);
  l->SetBorderSize(0);
  
  THStack* s = new THStack("ks", "");
  Int_t nCent = cent->GetXaxis()->GetNbins();
  for (Int_t i = 1; i <= nCent; i++) {
    Double_t c1 = cent->GetXaxis()->GetBinLowEdge(i);
    Double_t c2 = cent->GetXaxis()->GetBinUpEdge(i);

    TH1*     h  = GetCentK(file, c1, c2, nCent-i+1-2, l);
    if (!h) continue;

    s->Add(h);
  }
  s->Draw("nostack");
  TH1* f = s->GetHistogram();
  if (f) {
    f->SetXTitle("#eta");
    f->SetYTitle("#it{k}(#eta)");
  }
  
  TLatex* tit = new TLatex(0.55, 0.99, t);
  tit->SetTextFont(42);
  tit->SetTextAlign(23);
  tit->SetTextSize(0.03);
  tit->SetNDC();
  tit->Draw();
  l->SetBorderSize(0);
  l->Draw();

  c->Modified();
  c->Update();
  c->cd();

  return c;
}

//.........这里部分代码省略.........
  band_exp1_4->Draw("3same");
  limit_obs_4->Draw("Lsame");
  limit_obs_4->SetLineWidth(2);
  limit_obs_4->SetMarkerSize(1.0);
  limit_obs_4->SetMarkerStyle(20);

  limit_exp_2->Draw("L same");
  limit_exp_2->SetLineStyle(2);
  limit_exp_2->SetLineWidth(2);
  limit_exp_2->SetMarkerSize(1.0);
  limit_exp_3->Draw("L same");
  limit_exp_3->SetLineStyle(2);
  limit_exp_3->SetLineWidth(2);
  limit_exp_3->SetMarkerSize(1.0);
  limit_exp_4->Draw("L same");
  limit_exp_4->SetLineStyle(2);
  limit_exp_4->SetLineWidth(2);
  limit_exp_4->SetMarkerSize(1.0);








    canvas->RedrawAxis();

  double x1 = 595; 
  double y1 = 1.0;
  double x2 = 905;
  double y2 = 1.0;
  TLine * line = new TLine(x1, y1, x2, y2);
  theory->SetLineColor(2);
  theory->SetLineWidth(2);
  theory->Draw("same");
	theory2->SetLineColor(kBlue);
	theory2->SetLineWidth(2);
	theory2->Draw("same");
	theory3->SetLineColor(kMagenta);
	theory3->SetLineWidth(2);
	theory3->Draw("same");
	theory4->SetLineColor(kCyan);
	theory4->SetLineWidth(2);
	theory4->Draw("same");

  CMS_lumi(canvas, 4, 10);

  float t = canvas->GetTopMargin();
  float r = canvas->GetRightMargin();

  //Legend
  TLegend *l = new TLegend(0.51,0.63,0.99-r,0.99-t);
  l->AddEntry(limit_obs,"Observed", "L");
  l->AddEntry(limit_exp,"Expected", "L");
  l->AddEntry(band_exp1,"#pm1 #sigma Exp.", "F");
  l->AddEntry(band_exp2,"#pm2 #sigma Exp.", "F");
    l->AddEntry(theory, "Z' 1 TeV (NLO)", "L");
    l->AddEntry(theory2, "Z' 2 TeV (NLO)", "L");
    l->AddEntry(theory3, "Z' 3 TeV (NLO x 0.1)", "L");
    l->AddEntry(theory4, "Z' 4 TeV (NLO x 0.01)", "L");
  l->SetFillColor(0);
  l->SetLineColor(0);
  l->SetTextSize(0.04);
  l->SetTextFont(42);
  l->Draw();

  //TLatex * label = new TLatex();
  //label->SetNDC();
  //label->DrawLatex(0.2,0.86,"CMS Preliminary, 19.7 fb^{-1}");
  //label->DrawLatex(0.2,0.80,"#sqrt{s} = 8 TeV");
  //label->DrawLatex(0.6,0.80, Form("BR(b'#rightarrow %s) = 1", channel.Data()));
  //label->DrawLatex(0.55,0.80, "BR(b'#rightarrow tW) = 0.5");
  //label->DrawLatex(0.55,0.74, "BR(b'#rightarrow bH) = 0.25");
  //label->DrawLatex(0.55,0.68, "BR(b'#rightarrow bZ) = 0.25");
  //label->DrawLatex(0.2,0.74, lepton.Data());

  canvas->SetLogy(1);
  canvas->SetLogx(1);
  canvas->SetTickx(1);
  canvas->SetTicky(1);


  if (signal == 0){
    canvas->Print("Limits/comb_ZPN_limit.pdf");
    canvas->Print("Limits/comb_ZPN_limit.root");
  }
  else if (signal == 1){
    canvas->Print("Limits/comb_ZPW_limit.pdf");
    canvas->Print("Limits/comb_ZPW_limit.root");
  }
  else if (signal == 2){
    canvas->Print("Limits/comb_ZPXW_limit.pdf");
    canvas->Print("Limits/comb_ZPXW_limit.root");
  }
  else if (signal == 3){
    canvas->Print("Limits/comb_RSG_limit.pdf");
    canvas->Print("Limits/comb_RSG_limit.root");
  }
}

//.........这里部分代码省略.........

  if ( hptFOR != 0 ) {
    for (int b = 0; b < hptFOR->GetNbinsX(); b++) {

      Double_t mainHistoContent   = hptFOR->GetBinContent(b);
      Double_t systUpHistoContent = hptSUR->GetBinContent(b);
      Double_t systDnHistoContent = hptSDR->GetBinContent(b);
      Double_t systDiffUp = fabs( (double) systUpHistoContent - mainHistoContent );
      Double_t systDiffDn = fabs( (double) mainHistoContent - systDnHistoContent );

      // use average error for histogram
      Double_t systDiff = ( systDiffUp + systDiffDn ) / 2.;
      
      Double_t statErr   = hptFOR->GetBinError(b);
      Double_t combError = sqrt( systDiff * systDiff + statErr * statErr );
      hptFOR->SetBinError(b, combError);
    } //for
  }//if
    
  cPt->SetLogy(1);
  gPad->Update();
  cPt->Update();

  //  hptR->Scale(1,"width");
  //  hptR->SetMinimum(0.02);
  //  hptR->SetMaximum(1000); 
  hptR->GetXaxis()->SetTitle("1^{st} photon p_{T} [GeV]");
  hptR->GetYaxis()->SetTitle("Number of Events / GeV");

  if(isMC) hptR->SetMarkerSize(0);
  if(isMC) hptR->Draw("histE");
  else     hptR->Draw("E X0");


  hptFOR->SetMarkerSize(0);
  hptFOR->SetLineColor(2);
  hptFOR->SetFillColor(2);
  hptFOR->SetFillStyle(3004);
  hptFOR->Draw("same hist ][ E2");

  legend->Clear();
  if(isMC) legend->SetHeader("#gamma/QCD (Sim)");
  else     legend->SetHeader("#gamma/QCD (Data)");
  if(isMC) legend->AddEntry(hptR, "#gamma", "l");
  else     legend->AddEntry(hptR, "#gamma", "p");
  legend->AddEntry(hptFOR, "Pred (from #gamma_{jet})", "f");
  legend->Draw();

  as->DrawLatex(0.17, 0.93, outLumi.c_str() );
  cPt->Update();
  cPt->SetBottomMargin(0.2 + 0.8 * cPt->GetBottomMargin() - 0.2 * cPt->GetTopMargin());

  TPad *ratioPt = new TPad("BottomPad", "", 0, 0, 1, 1);
  ratioPt->SetTopMargin(0.8 - 0.8 * ratioPt->GetBottomMargin() + 0.2 * ratioPt->GetTopMargin());
  ratioPt->SetFillStyle(0);
  ratioPt->SetFrameFillColor(10);
  ratioPt->SetFrameBorderMode(0);
  ratioPt->Draw();

  ratioPt->cd();
  ratioPt->SetLogy(0);

  TH1F *hptRat = (TH1F*) divideHistosForRatio(hptR,hptFOR);
  hptRat->SetMinimum(0.);
  hptRat->SetMaximum(10.);
  hptRat->GetXaxis()->SetNdivisions(505);
  if(isMC) hptRat->GetYaxis()->SetTitle("Sim/Pred");
  else     hptRat->GetYaxis()->SetTitle("Data/Pred");
  hptRat->GetYaxis()->SetTitleSize(0.04);
  hptRat->GetYaxis()->SetLabelSize(0.03);
  hptRat->GetYaxis()->SetTitleOffset(1.3);
  hptRat->GetYaxis()->SetNdivisions(505);
  hptRat->SetMarkerStyle(20);
  hptRat->SetMarkerSize(1);
  hptRat->SetMarkerColor(1);
  hptRat->SetLineColor(1);
  hptRat->Draw("E X0");

  TH1F *hptFRat = (TH1F*) getSystErrForRatio(hptFOR);
  hptFRat->SetLineColor(2);
  hptFRat->SetFillColor(2);
  hptFRat->SetFillStyle(3004);
  hptFRat->Draw("same hist ][ E2");


  TLine * line = new TLine( hptRat->GetXaxis()->GetXmin(), 1., hptRat->GetXaxis()->GetXmax(), 1. );
  line->SetLineColor(1);
  line->SetLineWidth(0.5);
  line->SetLineStyle(1);
  line->Draw("same");

  hptR->GetXaxis()->SetLabelSize(0);
  hptR->GetXaxis()->SetTitle("");
  cPt->RedrawAxis();
  gPad->Update();
  cPt->Update();


  return;
}

//.........这里部分代码省略.........
      countCanvas++;
      TString ctitle = Form("TMVA response %s",methodTitle.Data());
      c = new TCanvas( Form("canvas%d", countCanvas), ctitle, 0, 0, width, (Int_t)width*0.78 ); 
      
      TH1F* sig = (TH1F*)titkeyTit->ReadObj();
      sig->SetTitle( Form("TMVA response for classifier: %s", methodTitle.Data()) );
      
      TString dataType = (name.Contains("_train_") ? "(training sample)" : "(test sample)");
      
      // find background
      TString nbn = sig->GetName(); nbn[nbn.Length()-1] = 'B';            
      TH1F* bgd = dynamic_cast<TH1F*>(epochDir->Get( nbn ));
      if (bgd == 0) {
         cout << "Big troubles with histogram: " << bgd << " -> cannot find!" << endl;
         exit(1);
      }
      
      cout << "sig = " << sig->GetName() << endl;
      cout << "bgd = " << bgd->GetName() << endl;
      
      // set the histogram style
      TMVAGlob::SetSignalAndBackgroundStyle( sig, bgd );
      
      // normalise both signal and background
      TMVAGlob::NormalizeHists( sig, bgd );
      
      // set only first time, then same for all plots
      if (first) {
         if (xmin == 0 && xmax == 0) {
            xmin = TMath::Max( TMath::Min(sig->GetMean() - nrms*sig->GetRMS(), 
                                          bgd->GetMean() - nrms*bgd->GetRMS() ),
                               sig->GetXaxis()->GetXmin() );
            xmax = TMath::Min( TMath::Max(sig->GetMean() + nrms*sig->GetRMS(), 
                                          bgd->GetMean() + nrms*bgd->GetRMS() ),
                               sig->GetXaxis()->GetXmax() );
         }
         ymin = 0;
         ymax = TMath::Max( sig->GetMaximum(), bgd->GetMaximum() )*maxMult;
         first = kFALSE;
      }
      
      // build a frame
      Int_t nb = 100;
      TString hFrameName(TString("frame") + methodTitle);
      TObject *o = gROOT->FindObject(hFrameName);
      if(o) delete o;
      TH2F* frame = new TH2F( hFrameName, sig->GetTitle(), 
                              nb, xmin, xmax, nb, ymin, ymax );
      frame->GetXaxis()->SetTitle( methodTitle + " response" );
      frame->GetYaxis()->SetTitle("(1/N) dN^{ }/^{ }dx");
      TMVAGlob::SetFrameStyle( frame );
      
      // find epoch number (4th token)
      TObjArray* tokens = name.Tokenize("_");
      TString es = ((TObjString*)tokens->At(4))->GetString();
      if (!es.IsFloat()) {
         cout << "Big troubles in epoch parsing: \"" << es << "\" is not float" << endl;
         exit(1);
      }
      Int_t epoch = es.Atoi();
      
      // eventually: draw the frame
      frame->Draw();  
      
      c->GetPad(0)->SetLeftMargin( 0.105 );
      frame->GetYaxis()->SetTitleOffset( 1.2 );
      
      // Draw legend               
      TLegend *legend= new TLegend( c->GetLeftMargin(), 1 - c->GetTopMargin() - 0.12, 
                                    c->GetLeftMargin() + 0.5, 1 - c->GetTopMargin() );
      legend->SetFillStyle( 1 );
      legend->AddEntry(sig,TString("Signal ")     + dataType, "F");
      legend->AddEntry(bgd,TString("Background ") + dataType, "F");
      legend->SetBorderSize(1);
      legend->SetMargin( 0.15 );
      legend->Draw("same");
      
      TText* t = new TText();            
      t->SetTextSize( 0.04 );
      t->SetTextColor( 1 );
      t->SetTextAlign( 31 );
      t->DrawTextNDC( 1 - c->GetRightMargin(), 1 - c->GetTopMargin() + 0.015, Form( "Epoch: %i", epoch) );
      
      // overlay signal and background histograms
      sig->Draw("samehist");
      bgd->Draw("samehist");
      
      // save to file
      TString dirname  = "movieplots";
      TString foutname = dirname + "/" + name;
      foutname.Resize( foutname.Length()-2 );
      foutname.ReplaceAll("convergencetest___","");
      foutname += ".gif";
      
      cout << "storing file: " << foutname << endl;
      
      c->Update();
      c->Print(foutname);            
   }
}