C++ TCanvas::GetLeftMargin方法代码示例

//.........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");
}

void allInOneLifetime(double lumi=4560., double maxInstLumi=5000.) {

  ExtraLimitPlots plots(lumi);
  plots.calculateCrossSections(4,6,3,39,9);
  
  // graphs - observed
  TGraph* g_obs      = plots.getObsLimit();
  TGraph* g_exp      = plots.getExpLimit();
  TGraphAsymmErrors* g_exp_1sig = plots.getExpLimit1Sig();
  TGraphAsymmErrors* g_exp_2sig = plots.getExpLimit2Sig();

  TGraph* g_obs_gluino = plots.getLimitGluino();
  double gluino2ref    = g_obs_gluino->GetY()[0] / g_obs->GetY()[0];
  TGraph* g_obs_stop   = plots.getLimitStop();
  double stop2ref      = g_obs_stop->GetY()[0] / g_obs->GetY()[0];
  TGraph* g_obs_stau   = plots.getLimitStau();
  double stau2ref      = g_obs_stau->GetY()[0] / g_obs->GetY()[0];

  cout << "scales: " << g_obs->GetY()[0] 
       << '/' <<g_obs_gluino->GetY()[0]
       << '/' <<g_obs_stop->GetY()[0]
       << '/' <<g_obs_stau->GetY()[0]
       <<endl;

  
  TCanvas *canvas = new TCanvas("allLifetime", "allLifetime", 1000, 600);
  
  canvas->SetLogx();
  canvas->SetLogy();

  canvas->SetRightMargin(0.8*canvas->GetLeftMargin());
  canvas->SetLeftMargin(1.2*canvas->GetLeftMargin());
  canvas->SetTicks (canvas->GetTickx(), 0);
  
  TH1F* h = new TH1F ("h", "", 1, 7.5e-8, 1e6);
  h->SetStats (0);
  h->SetMinimum (.0001);
  h->SetMaximum (0.99e1);
  // TH1* h = canvas->DrawFrame(7.5e-8, .001, 1e6, 1e2, "Y+");
  h->SetTitle("Beamgap Expt");
  //  h->GetXaxis()->SetTitle("#tau_{#tilde{g},#tilde{t},#tilde{#tau}} [s]");
  h->GetXaxis()->SetTitle("#tau [s]");
  h->GetYaxis()->SetTitle("#sigma #times BF #times #varepsilon_{stopping} #times #varepsilon_{reco}   [pb]  ");
  h->Draw ("Y+");

  ExtraAxis aGluino = anotherScale (h, gluino2ref, kRed+2, "#sigma(pp #rightarrow #tilde{g}#tilde{g}) #times BF(#tilde{g} #rightarrow g#tilde{#chi}^{0})   [pb]  ", 0.0);

  ExtraAxis aStop = anotherScale (h, stop2ref, kBlue+2, "#sigma(pp #rightarrow #tilde{t}#tilde{t}) #times BF(#tilde{t} #rightarrow t#tilde{#chi}^{0})   [pb]  ", 0.2);

  ExtraAxis aStau = anotherScale (h, stau2ref, kGreen+2, "#sigma(pp #rightarrow #tilde{#tau}#tilde{#tau}) #times BF(#tilde{#tau} #rightarrow #tau#tilde{#chi}^{0})   [pb]  ", 0.4);


  
  
  TPaveText* blurb = new TPaveText(0.25, 0.57, 0.50, 0.87, "NDC");

  blurb->AddText("CMS Preliminary 2015");
  // std::stringstream label;
  // label<<"#int L dt = "<<lumi<<" pb^{-1}";
  // blurb->AddText(label.str().c_str());
  // double peakInstLumi=maxInstLumi;
  // int exponent=30;
  // while (peakInstLumi>10) {
  //   peakInstLumi/=10;
  //   ++exponent;
  // }
  // std::stringstream label2;
  // label2<<"L^{max}_{inst} = "<<peakInstLumi<<" x 10^{"<<exponent<<"} cm^{-2}s^{-1}";
  // blurb->AddText(label2.str().c_str());

  //blurb->AddText("CMS 2011");
  blurb->AddText("#int L dt = 2.46 fb^{-1}");//,  #int L_{eff} dt = 935 pb^{-1}");
  //blurb->AddText("L^{max}_{inst} = 3.5 #times 10^{33} cm^{-2}s^{-1}");
  blurb->AddText("#sqrt{s} = 13 TeV");
  blurb->AddText("E_{g} > 120 GeV, E_{t} > 150 GeV");
  blurb->AddText("E_{jet} > 70 GeV");
  //blurb->AddText("m_{#tilde{g}} = 300 GeV/c^{2}");
  //blurb->AddText("m_{#tilde{#chi}^{0}} = 200 GeV/c^{2}");
  blurb->SetTextFont(42);
  blurb->SetBorderSize(0);
  blurb->SetFillColor(0);
  blurb->SetShadowColor(0);
  blurb->SetTextAlign(12);
  blurb->SetTextSize(0.033);
  blurb->Draw();
  
  
  // 2 sigma band
  if (g_exp_2sig) {
    g_exp_2sig->SetLineColor(0);
    g_exp_2sig->SetLineStyle(0);
    g_exp_2sig->SetLineWidth(0);
    g_exp_2sig->SetFillColor(kYellow);
    g_exp_2sig->SetFillStyle(1001);
    g_exp_2sig->Draw("3");
  }
  
  // 1 sigma band
  if (g_exp_1sig) {
    // g_exp_1sig->SetLineColor(8);
//.........这里部分代码省略.........

//.........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* 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;

}

//.........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);            
   }
}