C++ TH1F::GetTitle方法代码示例

void superimposeHistos()
{
  TFile* bFile = TFile::Open("Electron_In_Jets_900GeV_bJets.root");
  TFile* cFile = TFile::Open("Electron_In_Jets_900GeV_cJets.root");
  TFile* udsgFile = TFile::Open("Electron_In_Jets_900GeV_udsgJets.root");
  
  TIter next(bFile->GetListOfKeys());
  TFile* newFile = new TFile("testFile.root", "RECREATE");
  while(TKey* key = (TKey*)next())
  {
    TH1F* bHist = (TH1F*)bFile->Get(key->GetName());
    bHist->SetFillColor(2);
    
    TH1F* cHist = (TH1F*)cFile->Get(key->GetName());
    cHist->SetFillColor(3);
    
    TH1F* udsgHist = (TH1F*)udsgFile->Get(key->GetName());
    udsgHist->SetFillColor(4);
    
    THStack* stack = new THStack(bHist->GetName(), bHist->GetTitle());
    stack->Add(udsgHist, "hist ][");
    stack->Add(cHist, "hist ][");
    stack->Add(bHist, "hist ][");
    
    TLegend* legend = new TLegend(0.5, 0.68, 0.88, 0.88);
    legend->AddEntry(bHist, "b-Jets");
    legend->AddEntry(cHist, "c-Jets");
    legend->AddEntry(udsgHist, "udsg-Jets");
    
    TCanvas* canvas = new TCanvas(bHist->GetName());
    stack->Draw();
    stack->GetXaxis()->SetTitle(bHist->GetXaxis()->GetTitle());
    legend->Draw();
    canvas->Write(canvas->GetName());
  }
  
  newFile->Close();
  bFile->Close();
  cFile->Close();
  udsgFile->Close();
}

// Called just after the main event loop
// Can be used to write things out, dump a summary etc
// Return non-zero to indicate a problem
int IslandAmplitude::AfterLastEntry(TGlobalData* gData,const TSetupData *setup){

  // Print extra info if we're debugging this module:
  if(Debug()){
     cout<<"-----IslandAmplitude::AfterLastEntry(): I'm debugging!"<<endl;
  }

  double run_norm = fAmpNorm->Integral(0,-1);
  for(mapSH_t::iterator it = fAmpHist.begin(); it != fAmpHist.end(); ++it)
    {
      TH1F* h = it->second;
      TObject* obj = h->Clone((std::string(h->GetName()) + "_RunNorm").c_str());
      TH1* hn = static_cast<TH1*>(obj);
      hn->SetTitle((std::string(h->GetTitle()) + " (run normalized)").c_str());
      hn->Scale(1.0/run_norm);
    }

  for(mapSH_t::iterator it = fAmpHistNorm.begin(); it != fAmpHistNorm.end(); ++it)
    it->second->Scale(1.0/fNProcessed);

  return 0;
}

void changeAxis(bool armed, TString iExprMatch,float iMin, const char* filename, const char* pattern="", unsigned int debug=0)
{
  std::vector<std::string> histnames; histnames.clear();
  if( debug>0 ){
    std::cout << "file  = " << filename             << std::endl;
    std::cout << "old   = " << iExprMatch.Data()    << std::endl;    
    std::cout << "armed = " << armed                << std::endl;
  }
  TFile* file = new TFile(filename, "update");
  TIter nextDirectory(file->GetListOfKeys());
  std::vector<std::string> buffer;
  TKey* idir;
  while((idir = (TKey*)nextDirectory())){
    buffer.clear();
    if( idir->IsFolder() ){
      file->cd(); // make sure to start in directory head 
      if( debug>0 ){ std::cout << "Found directory: " << idir->GetName() << std::endl; }
      if( file->GetDirectory(idir->GetName()) ){
	file->cd(idir->GetName()); // change to sub-directory
	buffer = signalList(idir->GetName(), pattern,iExprMatch.Data(), debug);
      }
      // append to the vector of histograms to be rescaled
      for(std::vector<std::string>::const_iterator elem=buffer.begin(); elem!=buffer.end(); ++elem){
	histnames.push_back(*elem);
      }
      if(debug>1){
	std::cout << "added " << buffer.size() << " elements to histnames [" << histnames.size() << "] for directory " << idir->GetName() << std::endl;
      }
    }
  }
  // pick up files which are not kept in an extra folder
  file->cd(); buffer.clear();
  buffer = signalList("", pattern,iExprMatch.Data(), debug);
  // append to the vector of histograms to be rescaled
  for(std::vector<std::string>::const_iterator elem=buffer.begin(); elem!=buffer.end(); ++elem){
    histnames.push_back(*elem);
  }
  if(debug>1){
    std::cout << "added " << buffer.size() << " elements to histnames [" << histnames.size() << "] for file head" << std::endl;
  }

  for(std::vector<std::string>::const_iterator hist=histnames.begin(); hist!=histnames.end(); ++hist){
    file->cd();
    TH1F* h = (TH1F*)file->Get(hist->c_str());
    std::string histName;
    if(hist->find("/")!=std::string::npos){
      histName = hist->substr(hist->find("/")+1);
    }
    else{
      histName = *hist;
    }
    TH1F* hout = (TH1F*)h->Clone(histName.c_str());
    if(debug>1){
      std::cout << "...folder    : " << hist->substr(0, hist->find("/")).c_str() << std::endl;
      std::cout << "...histogram : " << hout->GetName () << " / " << hist->c_str() << std::endl; 
    }
    for(int i0 = 0; i0 < hout->GetNbinsX()+1; i0++) if(hout->GetXaxis()->GetBinCenter(i0) < iMin) hout->SetBinContent(i0,0);
    if(debug>1){ 
      std::cout << "...new name  : " << hout->GetName() << std::endl; 
      std::cout << "...new title : " << hout->GetTitle() << std::endl; 
    }
    if(armed){
      if(hist->find("/")!=std::string::npos){
	file->cd(hist->substr(0, hist->find("/")).c_str());
      }
      else{
	file->cd();
      }
      std::cout << "writing to file: " << hout->GetName() << " -- " << hist->substr(hist->find("/")+1).c_str() << std::endl;
      hout->Write(hist->substr(hist->find("/")+1).c_str(), TObject::kOverwrite); 
    }
  }
  file->Close();
  return;
}

void plotTree(TTree *tree_, std::string whichfit, std::string selectString){

	// Create a map for plotting the pullsummaries:
	std::map < const char*, std::pair <double,double> > pullSummaryMap;
	int nPulls=0;

	TObjArray *l_branches = tree_->GetListOfBranches();
	int nBranches = l_branches->GetEntries();

	TCanvas *c = new TCanvas("c","",960,800);

	std::string treename = tree_->GetName();
	c->SaveAs(Form("%s.pdf[",treename.c_str()));

	for (int iobj=0;iobj<nBranches;iobj++){

		TBranch *br =(TBranch*) l_branches->At(iobj);

		// Draw the normal histogram
		const char* name = br->GetName();
		bool fitPull=false;
		bool plotLH=false;

		TGraph *gr=0;
		double p_mean =0;
		double p_err  =0;

		int nToysInTree = tree_->GetEntries();
		if (doPull && findNuisancePre(name)){
			
			p_mean = bfvals_[name].first;	// toy constrainits thrown about best fit to data
			p_err  = prevals_[name].second; // uncertainties taken from card

			const char* drawInput = Form("(%s-%f)/%f",name,p_mean,p_err);
			tree_->Draw(Form("%s>>%s",drawInput,name),"");
			tree_->Draw(Form("%s>>%s_fail",drawInput,name),selectString.c_str(),"same");
			fitPull = true;
			if (doLH) {
			  gr = graphLH(name,p_err,whichfit);
			  plotLH=true;
			}
			
		}

		else{
			tree_->Draw(Form("%s>>%s",name,name),"");
			tree_->Draw(Form("%s>>%s_fail",name,name),"mu<0","same");
		}
		
		TH1F* bH  = (TH1F*) gROOT->FindObject(Form("%s",name))->Clone();
		TH1F* bHf = (TH1F*) gROOT->FindObject(Form("%s_fail",name))->Clone();
		bHf->SetLineColor(2);
		bH->GetXaxis()->SetTitle(bH->GetTitle());
		bH->GetYaxis()->SetTitle(Form("no toys (%d total)",nToysInTree));
		bH->GetYaxis()->SetTitleOffset(1.32);
		
		bH->SetTitle("");	

		if (fitPull) bH->Fit("gaus");
	
		c->Clear();
		TPad pad1("t1","",0.01,0.02,0.59,0.98);
		TPad pad2("t2","",0.59,0.04,0.98,0.62);
		TPad pad3("t3","",0.59,0.64,0.98,0.90);

		pad1.SetNumber(1); pad2.SetNumber(2); pad3.SetNumber(3);
		pad1.Draw(); pad2.Draw();pad3.Draw();
		pad2.SetGrid(true);

		c->cd(1); bH->Draw(); bHf->Draw("same");
		TLatex *titletext = new TLatex();titletext->SetNDC();titletext->SetTextSize(0.04); titletext->DrawLatex(0.1,0.95,name);
		TLegend *legend = new TLegend(0.6,0.8,0.9,0.89);
		legend->SetFillColor(0);
		legend->AddEntry(bH,"All Toys","L");
		legend->AddEntry(bHf,selectString.c_str(),"L");
		legend->Draw();

		if (doPull && plotLH) {
			c->cd(2); gr->Draw("ALP");
		}
		if (fitPull){
			c->cd(3);
			TLatex *tlatex = new TLatex(); tlatex->SetNDC(); tlatex->SetTextSize(0.12);
			tlatex->DrawLatex(0.15,0.75,Form("Mean    : %.3f #pm %.3f",bH->GetFunction("gaus")->GetParameter(1),bH->GetFunction("gaus")->GetParError(1)));
			tlatex->DrawLatex(0.15,0.60,Form("Sigma   : %.3f #pm %.3f",bH->GetFunction("gaus")->GetParameter(2),bH->GetFunction("gaus")->GetParError(2)));
			tlatex->DrawLatex(0.15,0.35,Form("Pre-fit : %.3f ",prevals_[name].first));
			tlatex->DrawLatex(0.15,0.2,Form("Best-fit (B)  : %.3f ",p_mean));
			tlatex->DrawLatex(0.15,0.05,Form("Best-fit (S+B): %.3f ",bfvals_sb_[name].first));
			
			pullSummaryMap[name]=std::make_pair<double,double>(bH->GetFunction("gaus")->GetParameter(1),bH->GetFunction("gaus")->GetParameter(2));
			nPulls++;

		}

		c->SaveAs(Form("%s.pdf",treename.c_str()));
	}
	
	if (doPull && nPulls>0){
	   
	    int nRemainingPulls = nPulls;
//.........这里部分代码省略.........

void plottingmacro()
{
 setTDRStyle();
 gROOT->ForceStyle();
 initOptions();

 std::vector<Sample> s = samples();
 Sample data(1,"fake data","S1.root",0,true,1000);

 for(size_t i=0;i< s.size();i++) if(s[i].data) {data=s[i];break;}
 data.file()->ls(); 
 for(size_t i=0;i< s.size();i++) s[i].dump(data.lumi());

 std::vector<std::string> names;

 TList * subs = data.file()->GetListOfKeys();
 for(size_t i=0;i< subs->GetSize();i++)
  {
    TList * objs = ((TDirectoryFile *) data.file()->Get(subs->At(i)->GetName()))->GetListOfKeys();
     for(size_t j=0;j< objs->GetSize();j++)
     {
         names.push_back(subs->At(i)->GetName()+std::string("/")  + objs->At(j)->GetName());
 //      std::cout << subs->At(i)->GetName() << "/"  << objs->At(j)->GetName() << std::endl;
         //TODO: select plots via regexp
     }
    
  }

 for(size_t i = 0 ; i < names.size() ; i++) 
  {
   std::map<std::string,TH1F *> grouped;
   TString n=names[i];
   if(!n.Contains(TRegexp("V.*RegionH.*mu.*HiggsMass"))) continue;
   TCanvas *c = new TCanvas();
   c->SetLogy(true);
   c->SetTitle(names[i].c_str());
   TH1F *hd = ((TH1F*)data.file()->Get(names[i].c_str()));
   Options o=options[names[i]];
   hd->Rebin(o.rebin);
   hd->SetMarkerStyle(21);
   hd->Draw("E1");
   hd->SetYTitle(o.yaxis.c_str());
   THStack * sta = new THStack("sta",hd->GetTitle());
   TLegend * l = new TLegend(o.legendx1,o.legendy1,o.legendx2,o.legendy2); //0.7,0.1,0.9,0.6);
  
   l->AddEntry(hd, "Data","LP");

   for(size_t j=0;j< s.size() ;j++) 
   { 
       if(!s[j].data) 
      {
       TH1F * h = ((TH1F*)s[j].file()->Get(names[i].c_str()));
       h->Scale(s[j].scale(data.lumi()));
       h->SetLineColor(s[j].color);
       h->SetFillColor(s[j].color);
       h->Rebin(options[names[i]].rebin);
       if(grouped.find(s[j].name)==grouped.end()) {
          grouped[s[j].name]=(TH1F *)h->Clone(("_"+names[i]).c_str());
          l->AddEntry(h,s[j].name.c_str(),"F");
       }
       else
       {
        grouped[s[j].name]->Add(h);
       }
       sta->Add(h);
//     h->Draw("same");
      }
   }
   sta->Draw("same");
   hd->Draw("E1same");
   hd->GetYaxis()->SetRangeUser(options[names[i]].min,options[names[i]].max);
   l->Draw();


   std::cout << names[i] << " d: " <<  hd->Integral() << " ";
   THStack * sta2 = new THStack("sta2",hd->GetTitle());
   float tot=0;
   float toterr2=0;

   for(std::map<std::string,TH1F *>::iterator it = grouped.begin(); it != grouped.end();it++)
   {
             std::cout << it->first << " " << it->second->Integral() << " | " ;
             if(it->second->GetEntries() > 0) {
             float er=1.*sqrt(it->second->GetEntries())/it->second->GetEntries()*it->second->Integral();
             toterr2+=er*er;
             }
	     tot+=it->second->Integral();
             sta2->Add(it->second);
   }   
    std::cout << " Tot: " << tot << "+-" << sqrt(toterr2) <<  " SF: " << hd->Integral()/tot << std::endl;
    c = new TCanvas();
    sta2->Draw();
    hd->Draw("E1,same");
    sta2->GetYaxis()->SetRangeUser(options[names[i]].min,options[names[i]].max);
    hd->GetYaxis()->SetRangeUser(options[names[i]].min,options[names[i]].max);
    l->Draw();

   

  }
//.........这里部分代码省略.........

void vs_PlotQCDcomp() {

  Bool_t saveC  = false;
  Bool_t diJets = true;
  Bool_t isMC   = false;

  TString vsSave;
  vsSave = "_T07w";

  TString jSave;
  if(diJets) jSave = "2j";
  else       jSave = "3j";

  TString sample;
  if(diJets) sample = "select_1ph_2jets";
  else       sample = "select_1ph_3jets";

  TString FOtag;
  if(isMC) FOtag = "_FO_CorrMC";
  //  else     FOtag = "_FO_Corr";
  else     FOtag = "_FO";

  TString sysu = "SYSTUP_";
  TString sysd = "SYSTDOWN_";

  TString outDir;
  outDir = "Plots_PhotonSusyAnalysis/QCDweights/";


  //  string inputFile1 = "/data/user/vsola/CMSSW_Releases/CMSSW_5_3_9/src/Plots_PhotonSusyAnalysis/Merged_QCD_PhotonJet_T07w_PAT/mergedHistos.root";
  //  string inputFile1 = "/data/user/vsola/CMSSW_Releases/CMSSW_5_3_9/src/Plots_PhotonSusyAnalysis/Merged_Data_V05w_PAT/mergedHistos.root";
  string inputFile1 = "/data/user/vsola/CMSSW_Releases/CMSSW_5_3_9/src/Plots_PhotonSusyAnalysis/PhotonHadReReco_22Jan2013_V05_PAT/mergedHistos.root";
  
  
  setMyTDRStyle();
  gROOT->SetStyle("mytdrStyle");
  
  //  gStyle->SetHistMinimumZero();
  //  gStyle->SetPaintTextFormat("4.2f");

  gStyle->SetHistLineWidth(2);
  gStyle->UseCurrentStyle();

  //  gStyle->SetPadTopMargin(1.0);
  //  gStyle->SetPadLeftMargin(3.2);
  //  gStyle->SetPadRightMargin(4.5);
  //  gStyle->SetPadBottomMargin(3.2);

  gROOT->ForceStyle(1);


  static const Int_t nHt  =  7;
  static const Int_t nPt  = 13;
  static const Int_t nMet = 16;
  static const Int_t nJet = 15;

  Double_t binPt[nPt+1]   = {0.,75.,90.,120.,160.,210.,260.,320.,400.,500.,650.,800.,1000.,1500.};
  Double_t binHt[nHt+1]   = {0.,400.,450.,550.,700.,900.,1200.,1500.};
  Double_t binMet[nMet+1] = {0.,10.,20.,30.,40.,50.,60.,70.,80.,90.,100.,120.,160.,200.,270.,350.,500.};
  Double_t binJet[nJet+1] = {0.,1.,2.,3.,4.,5.,6.,7.,8.,9.,10.,11.,12.,13.,14.,15};


  TLatex *as = new TLatex();
  as->SetNDC(true);
  as->SetTextColor(12);
  as->SetTextFont(43);
  as->SetTextSize(19);

  TLegend *legend = new TLegend(0.60, 0.70, 0.75, 0.85, "");
  legend->SetFillColor(10);
  legend->SetFillStyle(1001);
  legend->SetTextSize(0.04);
  legend->SetBorderSize(0);
  legend->SetShadowColor(0);

  std::string outLumi  = "CMS Work in Progress - QCD MC #sqrt{s} = 8 TeV - #geq 1 #gamma, #geq 2 j";

  TFile* f1 = TFile::Open( inputFile1.c_str() );

  //photon Pt
  TCanvas * cPt = new TCanvas("cPt","cPt");

  TH1F* hpt   = (TH1F*) f1->Get( sample+"/PreselCut_photonPt" );
  TH1F* hptFO = (TH1F*) f1->Get( sample+FOtag+"/PreselCut_photonPt" );

  TH1F *hptR = (TH1F*) hpt->Rebin(nPt,hpt->GetTitle(),binPt);
  if (hptR->GetSumw2N() == 0)
    hptR->Sumw2();

  TH1F *hptFOR = (TH1F*) hptFO->Rebin(nPt,hptFO->GetTitle(),binPt);
  if (hptFOR->GetSumw2N() == 0)
    hptFOR->Sumw2();

  TH1F* hptSU = (TH1F*) f1->Get( sample+FOtag+"/PreselCut_"+sysu+"photonPt" );
  TH1F* hptSD = (TH1F*) f1->Get( sample+FOtag+"/PreselCut_"+sysd+"photonPt" );

  TH1F *hptSUR = (TH1F*) hptSU->Rebin(nPt,hptSU->GetTitle(),binPt);
  if (hptSUR->GetSumw2N() == 0)
    hptSUR->Sumw2();

//.........这里部分代码省略.........

//================================================
void make_histo_pt()
{
  const int nPtBins        = nPtBins_pt;
  const double* ptBinsLow  = ptBins_low_pt;
  const double* ptBinsHigh = ptBins_high_pt;
  const char** ptName      = pt_Name_pt;
  const int nCentBins      = nCentBins_pt; 
  const int* centBinsLow   = centBins_low_pt;
  const int* centBinsHigh  = centBins_high_pt;
  const char** centName    = cent_Name_pt;

  const char *hName[3] = {"hJpsiInfo","hBkgLSPos","hBkgLSNeg"};
  THnSparseF *hnInvMass[2][3] = {0x0};
  TH1F *hInvMass[2][5][nCentBins][nPtBins][3] = {0x0};
  
  // same event
  char name[512];
  for(int w=0; w<2; w++) // event weights
    { 
      for(Int_t j=0; j<3; j++) // pair type
	{ 
	  if(w==0) sprintf(name,"m%s_%s",hName[j],trigName[kTrigType]);
	  else     sprintf(name,"m%sWeight_%s",hName[j],trigName[kTrigType]);
	  hnInvMass[w][j] = (THnSparseF*)f->Get(name);
	  if(!hnInvMass[w][j]) continue; 
	  hnInvMass[w][j]->GetAxis(2)->SetRangeUser(pt1_cut+0.01,100);
	  hnInvMass[w][j]->GetAxis(3)->SetRangeUser(pt2_cut+0.01,100);
	  for(Int_t i=0; i<nPtBins; i++) // pt bins
	    {
	      hnInvMass[w][j]->GetAxis(1)->SetRangeUser(ptBinsLow[i]+0.01,ptBinsHigh[i]-0.01);
	      for(int k=0; k<nCentBins; k++) // centrality bins
		{
		  hnInvMass[w][j]->GetAxis(4)->SetRange(centBinsLow[k],centBinsHigh[k]);
		  for(int t=0; t<gNTrgSetup; t++) // trigger setup
		    {
		      if(t>0) hnInvMass[w][j]->GetAxis(5)->SetRange(t,t);
		      hInvMass[w][t][k][i][j] = (TH1F*)hnInvMass[w][j]->Projection(0);
		      hInvMass[w][t][k][i][j]->SetName(Form("%d_%s_%s_InvMass_jpsi_PtBin%d_CentBin%d_P%d",w,hName[j],trigName[kTrigType],i,k,t));
		      hInvMass[w][t][k][i][j]->Sumw2();
		      hnInvMass[w][j]->GetAxis(5)->SetRange(0,-1);
		    }
		  hnInvMass[w][j]->GetAxis(4)->SetRange(0,-1);
		}
	      hnInvMass[w][j]->GetAxis(1)->SetRange(0,-1);
	    }
	  hnInvMass[w][j]->GetAxis(2)->SetRange(0,-1);
	  hnInvMass[w][j]->GetAxis(3)->SetRange(0,-1);
	}
    }

  for(int w=0; w<2; w++) 
    {
      for(int t=0; t<gNTrgSetup; t++)
	{
	  for(int k=0; k<nCentBins; k++)
	    {
	      for(Int_t i=0; i<nPtBins; i++)
		{
		  if(hInvMass[w][t][k][i][1])
		    hInvMass[w][t][k][i][1]->Add(hInvMass[w][t][k][i][2]);
		}
	    }
	}
    }

  // mixed event
  TFile *fmix = 0;
  if(year==2014) 
    {
      char *mixName = Form("%s.Mix.pt%1.1f.pt%1.1f.%sroot",run_type.Data(),pt1_cut,pt2_cut,run_config);
      fmix = TFile::Open(Form("Output/%s",mixName),"read");

      cout << "Mix file: " << fmix->GetName() << endl;
      TH1F *hMixInvMass[nCentBins][nPtBins][3];
      printf("INFO: using Shuai's mixed events\n");
      TH3D *hMixMmumuvsPtCen[3];
      hMixMmumuvsPtCen[0] = (TH3D*)fmix->Get("hMixULMmumuvsPtCen");
      hMixMmumuvsPtCen[1] = (TH3D*)fmix->Get("hMixLPosMmumuvsPtCen");
      hMixMmumuvsPtCen[2] = (TH3D*)fmix->Get("hMixLNegMmumuvsPtCen");
      for(Int_t j=0; j<3; j++)
	{
	  for(int i=0; i<nPtBins; i++)
	    {
	      int ybin_min = hMixMmumuvsPtCen[j]->GetYaxis()->FindFixBin(ptBinsLow[i]+1e-4);
	      int ybin_max = hMixMmumuvsPtCen[j]->GetYaxis()->FindFixBin(ptBinsHigh[i]-1e-4);
	      for(int k=0; k<nCentBins; k++)
		{
		  TH1F *htmp = (TH1F*)hMixMmumuvsPtCen[j]->ProjectionZ(Form("mix_%s_%s_InvMass_jpsi_PtBin%d_CentBin%d_tmp",hName[j],trigName[kTrigType],i,k),centBinsLow[k],centBinsHigh[k],ybin_min,ybin_max);
		  hMixInvMass[k][i][j] = new TH1F(Form("mix_%s_%s_InvMass_jpsi_PtBin%d_CentBin%d",hName[j],trigName[kTrigType],i,k),htmp->GetTitle(),1400,0,14);
		  for(int bin=1; bin<=htmp->GetNbinsX(); bin++)
		    {
		      hMixInvMass[k][i][j]->SetBinContent(bin,htmp->GetBinContent(bin));
		      hMixInvMass[k][i][j]->SetBinError(bin,htmp->GetBinError(bin));
		    }
		}
	    }
	}
      for(int k=0; k<nCentBins; k++)
        {
//.........这里部分代码省略.........

void DrawMLPoutputMovie( TFile* file, const TString& methodType, const TString& methodTitle )
{
   gROOT->SetBatch( 1 );

   // define Canvas layout here!
   const Int_t width = 600;   // size of canvas

   // this defines how many canvases we need
   TCanvas* c = 0;

   Float_t nrms = 4;
   Float_t xmin = -1.2;
   Float_t xmax = 1.2;
   Float_t ymin = 0;
   Float_t ymax = 0;
   Float_t maxMult = 6.0;
   Int_t   countCanvas = 0;
   Bool_t  first = kTRUE;
            
   TString     dirname  = methodType + "/" + methodTitle + "/" + "EpochMonitoring";
   TDirectory *epochDir = (TDirectory*)file->Get( dirname );
   if (!epochDir) {
      cout << "Big troubles: could not find directory \"" << dirname << "\"" << endl;
      exit(1);
   }

   // now read all evolution histograms
   TIter keyItTit(epochDir->GetListOfKeys());
   TKey *titkeyTit;
   while ((titkeyTit = (TKey*)keyItTit())) {
      
      if (!gROOT->GetClass(titkeyTit->GetClassName())->InheritsFrom("TH1F")) continue;
      TString name = titkeyTit->GetName();
      
      if (!name.BeginsWith("convergencetest___")) continue;
      if (!name.Contains("_train_"))              continue; // only for training so far
      if (name.EndsWith( "_B"))                   continue;
      
      // must be signal histogram
      if (!name.EndsWith( "_S")) {
         cout << "Big troubles with histogram: " << name << " -> should end with _S" << endl;
         exit(1);
      }
      
      // create canvas
      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();
//.........这里部分代码省略.........

void plotTreeNorms(TTree *tree_, std::string selectString, bool do7TeV){

	// Create a map for plotting the pullsummaries:
	std::map < const char*, std::pair <double,double> > pullSummaryMap;
	int nPulls=0;

	TObjArray *l_branches = tree_->GetListOfBranches();
	int nBranches = l_branches->GetEntries();

	gStyle->SetPadTopMargin(0.01);

	TCanvas *c = new TCanvas("c","",960,800);

	std::string treename = tree_->GetName();
	c->SaveAs(Form("%s_normresiduals.pdf[",treename.c_str()));
	// File to store plots in 
	TFile *fOut = new TFile(Form("%s_normresiduals.root",treename.c_str()),"RECREATE");

        TH1F *bHd = new TH1F("bHd","",50,-1.0,1.0);
        TH1F *bHfd = new TH1F("bHfd","",50,-1.0,1.0);

	for (int iobj=0;iobj<nBranches;iobj++){

		TBranch *br =(TBranch*) l_branches->At(iobj);

		// Draw the normal histogram
		const char* name = br->GetName();

                // select only the normalizations
                string namestr(name);
                if(namestr.find("n_exp")==string::npos) continue;

                bool fitPull=true;
                bool fitPullf=true;

		double p_mean =0;

		int nToysInTree = tree_->GetEntries();
		// Find out if paramter is fitted value or constraint term.
                bool isFitted = true;
			
                p_mean = prenorms_[name].first;	// toy initial parameters from the datacards
                std::cout << "******* "<< name << " *******"<<std::endl;
                std::cout << p_mean << std::endl;
                std::cout << "******************************" <<std::endl;

                TH1F* bH = (TH1F*)bHd->Clone(Form("%s",name));
                TH1F* bHf = (TH1F*)bHfd->Clone(Form("%s_fail",name));
                
                const char* drawInput = Form("(%s-%f)/%f",name,p_mean,p_mean);
                tree_->Draw(Form("%s>>%s",drawInput,name),"");
                tree_->Draw(Form("%s>>%s_fail",drawInput,name),selectString.c_str(),"same");
                fitPull  = true;
                fitPullf = true;
                  
		bHf->SetLineColor(2);
		bH->GetXaxis()->SetTitle(bH->GetTitle());
		bH->GetYaxis()->SetTitle(Form("no toys (%d total)",nToysInTree));
		bH->GetYaxis()->SetTitleOffset(1.05);
		bH->GetXaxis()->SetTitleOffset(0.9);
		bH->GetYaxis()->SetTitleSize(0.05);
		bH->GetXaxis()->SetTitleSize(0.05);
		bH->GetXaxis()->SetTitle(Form("%s",name));
                
		
		bH->SetTitle("");	

		if ( bH->Integral() <=0 )  fitPull = false;
		if (fitPull) {bH->Fit("gaus"); bH->GetFunction("gaus")->SetLineColor(4);}
		
		if ( bHf->Integral() <=0 )  fitPullf = false;
		if (fitPullf) {bHf->Fit("gaus"); bHf->GetFunction("gaus")->SetLineColor(2);}

		c->Clear();
		
 		TPad pad1("t1","",0.01,0.01,0.66,0.95);
 		TPad pad2("t2","",0.70,0.20,0.98,0.80);

		pad1.SetNumber(1); pad2.SetNumber(2);

                if ( isFitted ) {pad2.Draw();}

		pad1.Draw();
		pad1.SetGrid(true);


		TLatex *titletext = new TLatex();titletext->SetNDC();

		
		c->cd(1); bH->Draw(); bHf->Draw("same");
		TLegend *legend = new TLegend(0.6,0.8,0.9,0.89);
		legend->SetFillColor(0);
		legend->AddEntry(bH,"All Toys","L");
		legend->AddEntry(bHf,selectString.c_str(),"L");
		legend->Draw();

		if (fitPull){
			c->cd(2);
			double gap;
			TLatex *tlatex = new TLatex(); tlatex->SetNDC(); 
//.........这里部分代码省略.........

void plotTree(TTree *tree_, std::string whichfit, std::string selectString){

	// Create a map for plotting the pullsummaries:
	std::map < const char*, std::pair <double,double> > pullSummaryMap;
	int nPulls=0;

	TObjArray *l_branches = tree_->GetListOfBranches();
	int nBranches = l_branches->GetEntries();

	gStyle->SetPadTopMargin(0.01);

	TCanvas *c = new TCanvas("c","",960,800);

	std::string treename = tree_->GetName();
	c->SaveAs(Form("%s.pdf[",treename.c_str()));
	// File to store plots in 
	TFile *fOut = new TFile(Form("%s.root",treename.c_str()),"RECREATE");

	for (int iobj=0;iobj<nBranches;iobj++){

		TBranch *br =(TBranch*) l_branches->At(iobj);

		// Draw the normal histogram
		const char* name = br->GetName();

                // names with - are not allowed
                string namestr(name);
                if(namestr.find("-")!=string::npos) {
                  std::cout << "Variable " << name << " contains a bad character: -. Skipping. " << std::endl;
                  continue;
                }
		bool fitPull=false;
		bool fitPullf=false;

		bool plotLH=false;

		TGraph *gr=NULL;
		double p_mean =0;
		double p_err  =0;

		int nToysInTree = tree_->GetEntries();
		// Find out if paramter is fitted value or constraint term
		bool isFitted = findNuisancePre(name);
		if (doPull && isFitted){
			
			p_mean = bfvals_[name].first;	// toy constrainits thrown about best fit to data
			if(namestr.find("n_exp")==string::npos) p_err  = prevals_[name].second; // uncertainties taken from card
			std::cout << "******* "<< name << " *******"<<std::endl;
			std::cout << p_mean <<  " " << p_err << std::endl;
			std::cout << "******************************" <<std::endl;

			const char* drawInput;
                        // if the parameter is a normalization, the error is not available. Do the residual instead of the pull
                        if(namestr.find("n_exp")!=string::npos) drawInput = Form("(%s-%f)/%f",name,p_mean,p_mean);
                        else drawInput = Form("(%s-%f)/%f",name,p_mean,p_err);
			tree_->Draw(Form("%s>>%s",drawInput,name),"");
			tree_->Draw(Form("%s>>%s_fail",drawInput,name),selectString.c_str(),"same");
			fitPull  = true;
			fitPullf = true;
			if (doLH) {
			  gr = graphLH(name,p_err,whichfit);
			  if (gr) plotLH=true;
			}
			
		}

		else{
			tree_->Draw(Form("%s>>%s",name,name),"");
			tree_->Draw(Form("%s>>%s_fail",name,name),selectString.c_str(),"same");
		}
		

		TH1F* bH  = (TH1F*) gROOT->FindObject(Form("%s",name))->Clone();
		TH1F* bHf = (TH1F*) gROOT->FindObject(Form("%s_fail",name))->Clone();
		bHf->SetLineColor(2);
		bH->GetXaxis()->SetTitle(bH->GetTitle());
		bH->GetYaxis()->SetTitle(Form("no toys (%d total)",nToysInTree));
		bH->GetYaxis()->SetTitleOffset(1.05);
		bH->GetXaxis()->SetTitleOffset(0.9);
		bH->GetYaxis()->SetTitleSize(0.05);
		bH->GetXaxis()->SetTitleSize(0.05);
		if (isFitted) {bH->GetXaxis()->SetTitle(Form("(%s-#theta_{B})/#sigma_{#theta}",name));}
		else {bH->GetXaxis()->SetTitle(Form("%s",name));}
		
		bH->SetTitle("");	

		if ( bH->Integral() <=0 )  fitPull = false;
		if (fitPull) {bH->Fit("gaus"); bH->GetFunction("gaus")->SetLineColor(4);}
		
		if ( bHf->Integral() <=0 )  fitPullf = false;
		if (fitPullf) {bHf->Fit("gaus"); bHf->GetFunction("gaus")->SetLineColor(2);}

		c->Clear();
		//TPad pad1("t1","",0.01,0.02,0.59,0.98);
		// Pad 1 sizes depend on the parameter type ...
		double pad1_x1,pad1_x2,pad1_y1,pad1_y2;
		if ( !isFitted ) {
			 pad1_x1 = 0.01; 
			 pad1_x2 = 0.98; 
			 pad1_y1 = 0.045; 
//.........这里部分代码省略.........

int main(int argc, char* argv[])
{
        string htitle = "Events rate, cloud ";
        htitle = htitle+string(argv[1]);
	string drootpath;
    
        if (strcmp(argv[2],"ttreecache")==0)
	{
                htitle = htitle + ", TTreeCache enabled, protocol: WebDAV";
		drootpath = "../../../Histograms/TDavix/";
        }
	else if (strcmp(argv[2],"xrootd")==0)
        {
		htitle = htitle + ", TTreeCache enabled xrootd";
		drootpath = "../../../Histograms/xrootd/";
        }
	else
        {
	        htitle = htitle + ", TTreeCache disabled, protocol: WebDAV ";
		drootpath = "../../../Histograms/Davix/";
	}

	string cloudpath = argv[1] ;
	cloudpath = cloudpath + "/";
	DIR* dcloudrep = opendir(string2char(drootpath+cloudpath));
	struct dirent* dcloudfichier = NULL;
	string allgrid;
	allgrid = string(argv[3]);

	vector<ratioMatrixValue> th2array;
	
	while ((dcloudfichier = readdir(dcloudrep))!=0)
	{
		if (dcloudfichier->d_name[0]=='.')
			continue;
		string dcloudpath = cloudpath + dcloudfichier->d_name + "/";
		//DIR* drootfile = opendir(string2char(drootpath+dcloudpath));
		//struct dirent* drootfichier = NULL;

		string dfilepath = drootpath + dcloudpath + allgrid + "/" + dcloudfichier->d_name + ".root";
		ratioMatrixValue column;

		TFile *dfr = TFile::Open(string2char(dfilepath));
		if (dfr==NULL)
			continue;

		column.analy = dcloudfichier->d_name;

		for (int i=0;i<dfr->GetListOfKeys()->GetEntries();i++)
		{
			string dstrRead = string2char(dfr->GetListOfKeys()->At(i)->GetName());
			TH1F* dhist = (TH1F*)dfr->Get(string2char(dstrRead));
			if (dhist==NULL)
				continue;
			string otherTitle = string(dhist->GetName()) + "No Zero";
			TH1F* histSansZeros = new TH1F(string2char(otherTitle),dhist->GetTitle(),3000.,0,3000);
			for ( int l=2;l<3000;l++)
				for (int k=0;k<dhist->GetBinContent(l);k++)
					histSansZeros->Fill(l-1);
			column.datadisk.push_back(string2char(dstrRead));
			column.ratio.push_back(histSansZeros->GetMean());
			column.error.push_back(histSansZeros->GetRMSError());
		}
		th2array.push_back(column);
	}



        TCanvas * c = new TCanvas("c", "c");
        c->SetLeftMargin(0.20);
        c->SetBottomMargin(0.15);
        c->SetWindowSize(2100,1500);

	/*for (unsigned int i=0;i<th2array.size();i++)
	{
		cout << th2array[i].analy << "\t";
		for (unsigned int j=0;j<th2array[i].datadisk.size();j++)
			cout << th2array[i].datadisk[j] << "\t" ;
		cout << endl;
	}*/

	cout << "--------------------------" << endl;

	th2array = ordenate(th2array,string(argv[1]));

	cout << "--------------------------" << endl;

	/*for (unsigned int i=0;i<th2array.size();i++)
	{
		cout << th2array[i].analy << "\t";
		for (unsigned int j=0;j<th2array[i].datadisk.size();j++)
			cout << th2array[i].datadisk[j] << "\t" ;
		cout << endl;
	}*/

	unsigned int datadisk_number=0;
	unsigned int analy_number=0;
	for (unsigned int i=0;i<th2array.size();i++)
	{
		if (datadisk_number < th2array[i].datadisk.size())
//.........这里部分代码省略.........

//.........这里部分代码省略.........
    //    if(isEB){
    //	  cb3.setRange(-1,1.);
    //	  cb4.setRange(-0.3,0.3);
    //	  cbpars.add( cb4 );
    //    }
    RooChebychev bkg("bkg","bkg model", x, cbpars );
    RooRealVar Nbkg("Nbkg","background yield",1.e3,0.,1.e8);
    Nbkg.setVal( h->GetSum()*0.8 );

    RooAbsPdf* model=0;

    RooAddPdf model1("model","sig+bkg",RooArgList(gaus,bkg),RooArgList(Nsig,Nbkg));
    RooAddPdf model2("model","sig+bkg",RooArgList(signal,bkg),RooArgList(Nsig,Nbkg));

    if(ngaus==1)      model = &model1;
    else if(ngaus==2) model = &model2;

    RooNLLVar nll("nll","log likelihood var",*model,dh,RooFit::Extended(true));//RooFit::Extended(true) fundamental for right ormalization
    //RooAbsReal * nll = model->createNLL(dh); Suggested way
    RooMinuit m(nll);
    m.setVerbose(kFALSE);
    m.migrad();
    //RooFitResult* res = m.save() ;

    x.setRange("sobRange",mean.getVal()-2.*sigma.getVal(), mean.getVal()+2.*sigma.getVal());
    RooAbsReal* integralSig = gaus.createIntegral(x,NormSet(x),Range("sobRange"));
    RooAbsReal* integralBkg = bkg.createIntegral(x,NormSet(x),Range("sobRange"));

    RooChi2Var chi2("chi2","chi2 var",*model,dh, true);
    //int ndof = h->GetNbinsX() - res->floatParsFinal().getSize();
    x.setRange("sobRange",mean.getVal()-2.*sigma.getVal(), mean.getVal()+2.*sigma.getVal());

    RooPlot*  xframe = x.frame(h->GetNbinsX());
    xframe->SetTitle(h->GetTitle());
    dh.plotOn(xframe);
    model->plotOn(xframe,Components(RooArgSet(bkg,gaus)),LineStyle(kDashed), LineColor(kRed));
    model->plotOn(xframe);

    //xframe->GetYaxis()->SetTitle("# Events");
    if(Are_pi0_) xframe->GetYaxis()->SetTitleOffset(2.05);
    else         xframe->GetYaxis()->SetTitleOffset(1.3);
    xframe->Draw();
    TLatex lat;
    char line[300];
    lat.SetNDC();
    lat.SetTextSize(0.040);
    lat.SetTextColor(1);

    sprintf(line,"CMS Preliminary");
    lat.DrawLatex(0.2, 0.93, line);
    float xmin(0.5), yhi(0.80), ypass(0.05);
    if(!Are_pi0_) xmin=0.30;
    sprintf(line,"m_{#gamma#gamma} = %.2f #pm %.2f", mean.getVal()*1000., mean.getError()*1000. );
    lat.DrawLatex(xmin,yhi, line);
    sprintf(line,"#sigma = %.2f #pm %.2f", sigma.getVal()*1000., sigma.getError()*1000. );
    lat.DrawLatex(xmin,yhi-ypass, line);
    //sprintf(line,"N = %.0f #pm %.0f", Nsig.getVal(), Nsig.getError() );
    //lat.DrawLatex(xmin,yhi-2*ypass, line);
    //sprintf(line,"Yield: %.0f #pm %.0f", Nsig.getVal(), Nsig.getError() );
    //lat.DrawLatex(xmin,yhi, line);
    //sprintf(line,"m_{#gamma#gamma}: %.2f #pm %.2f", mean.getVal()*1000., mean.getError()*1000. );
    //lat.DrawLatex(xmin,yhi-ypass, line);
    //sprintf(line,"#sigma: %.2f #pm %.2f (%.2f%s)", sigma.getVal()*1000., sigma.getError()*1000., sigma.getVal()*100./mean.getVal(), "%" );
    //lat.DrawLatex(xmin,yhi-2.*ypass, line);
    sprintf(line,"S/B (2#sigma): %.2f", (integralSig->getVal()*Nsig.getVal())/(integralBkg->getVal()*Nbkg.getVal()) );
    lat.DrawLatex(xmin,yhi-2.*ypass, line);