void graph() {
//Draw a simple graph
// To see the output of this macro, click begin_html <a href="gif/graph.gif">here</a>. end_html
//Author: Rene Brun
TCanvas *c1 = new TCanvas("c1","A Simple Graph Example",200,10,700,500);
c1->SetFillColor(42);
c1->SetGrid();
const Int_t n = 20;
Double_t x[n], y[n];
for (Int_t i=0;i<n;i++) {
x[i] = i*0.1;
y[i] = 10*sin(x[i]+0.2);
printf(" i %i %f %f \n",i,x[i],y[i]);
}
auto gr = new TGraph(n,x,y);
gr->SetLineColor(2);
gr->SetLineWidth(4);
gr->SetMarkerColor(4);
gr->SetMarkerStyle(21);
gr->SetTitle("a simple graph");
gr->GetXaxis()->SetTitle("X title");
gr->GetYaxis()->SetTitle("Y title");
gr->Draw("ACP");
// TCanvas::Update() draws the frame, after which one can change it
c1->Update();
c1->GetFrame()->SetFillColor(21);
c1->GetFrame()->SetBorderSize(12);
c1->Modified();
}
void MuReco( )
{
TCut CPdg = "_tracks_Pdg==13||_tracks_Pdg==211";
TFile *inFileMC;
//gStyle->SetOptStat(0);
inFileMC = new TFile("ERAnaOneToOneMuReco.root");
inFileMC->cd();
TTree* _algoMuMC_tree = (TTree*)(inFileMC->Get("_ana1to1_tree"));
TCanvas *C1 = new TCanvas("C1","C1",600,600);
C1->cd();
auto cut2 = new TH1D("cut2","Muon deposited Energy; E_{#mu} [MeV];Count",20,0,800);
_algoMuMC_tree->Draw("_tracks_DepEnFromLength>>cut2",CPdg,"");
cut2->SetLineWidth(3);
cut2->SetLineColor(kRed);
cut2->GetYaxis()->SetTitleOffset(1.5);
C1->SaveAs("MuRecoEn.png");
// TFile *inFileReco;
// inFileReco = new TFile("ERAnaOneToOneMuMC.root");
// inFileReco->cd();
// TTree* _algoMuReco_tree = (TTree*)(inFileReco->Get("_ProtonSel_tree"));
}
void CreateOutput(const std::vector<double>& x_list, const std::vector<double>& y_list,
const std::vector<double>& z_list, std::shared_ptr<TFile> output_file, const std::string& name,
const std::shared_ptr<TH2F> ref_hist, double excl_threshold = -std::numeric_limits<double>::infinity(),
double graph_factor = 1, double graph_max = std::numeric_limits<double>::infinity(),
bool interpolate = false)
{
std::ostringstream ss_name;
ss_name << name << "_hist";
auto hist = CreateTH2D(ss_name.str(), ref_hist);
ss_name << "_excl";
auto hist_excl = CreateTH2D(ss_name.str(), ref_hist);
if(interpolate) {
auto ref_graph = CreateTGraph2D("ref_tmp", x_list, y_list, z_list);
for(Int_t x_id = 1; x_id <= hist->GetXaxis()->GetNbins(); ++x_id) {
const double x = hist->GetXaxis()->GetBinCenter(x_id);
for(Int_t y_id = 1; y_id <= hist->GetYaxis()->GetNbins(); ++y_id) {
const double y = hist->GetYaxis()->GetBinCenter(y_id);
const double z = ref_graph->Interpolate(x, y);
hist->SetBinContent(x_id, y_id, z);
if(z < excl_threshold)
hist_excl->SetBinContent(x_id, y_id, 1.0);
}
}
} else {
for(size_t n = 0; n < z_list.size(); ++n) {
const Int_t bin_id = hist->FindBin(x_list.at(n), y_list.at(n));
const double z = z_list.at(n);
hist->SetBinContent(bin_id, z);
if(z < excl_threshold)
hist_excl->SetBinContent(bin_id, 1.0);
}
}
std::vector<double> z_list_graph(z_list.size());
for(size_t n = 0; n < z_list.size(); ++n)
z_list_graph.at(n) = std::min(graph_max, z_list.at(n) * graph_factor);
auto graph = CreateTGraph2D(name, x_list, y_list, z_list_graph);
output_file->WriteTObject(graph.get(), nullptr, "Overwrite");
output_file->WriteTObject(hist.get(), nullptr, "Overwrite");
output_file->WriteTObject(hist_excl.get(), nullptr, "Overwrite");
}
void macro6(){
auto sig_h=new TH1F("sig_h","Signal Histo",50,0,10);
auto gaus_h1=new TH1F("gaus_h1","Gauss Histo 1",30,0,10);
auto gaus_h2=new TH1F("gaus_h2","Gauss Histo 2",30,0,10);
auto bkg_h=new TH1F("exp_h","Exponential Histo",50,0,10);
// simulate the measurements
TRandom3 rndgen;
for (int imeas=0;imeas<4000;imeas++){
bkg_h->Fill(rndgen.Exp(4));
if (imeas%4==0) gaus_h1->Fill(rndgen.Gaus(5,2));
if (imeas%4==0) gaus_h2->Fill(rndgen.Gaus(5,2));
if (imeas%10==0)sig_h->Fill(rndgen.Gaus(5,.5));}
// Format Histograms
int i=0;
for (auto hist : {sig_h,bkg_h,gaus_h1,gaus_h2})
format_h(hist,1+i++);
// Sum
auto sum_h= new TH1F(*bkg_h);
sum_h->Add(sig_h,1.);
sum_h->SetTitle("Exponential + Gaussian;X variable;Y variable");
format_h(sum_h,kBlue);
auto c_sum= new TCanvas();
sum_h->Draw("hist");
bkg_h->Draw("SameHist");
sig_h->Draw("SameHist");
// Divide
auto dividend=new TH1F(*gaus_h1);
dividend->Divide(gaus_h2);
// Graphical Maquillage
dividend->SetTitle(";X axis;Gaus Histo 1 / Gaus Histo 2");
format_h(dividend,kOrange);
gaus_h1->SetTitle(";;Gaus Histo 1 and Gaus Histo 2");
gStyle->SetOptStat(0);
TCanvas* c_divide= new TCanvas();
c_divide->Divide(1,2,0,0);
c_divide->cd(1);
c_divide->GetPad(1)->SetRightMargin(.01);
gaus_h1->DrawNormalized("Hist");
gaus_h2->DrawNormalized("HistSame");
c_divide->cd(2);
dividend->GetYaxis()->SetRangeUser(0,2.49);
c_divide->GetPad(2)->SetGridy();
c_divide->GetPad(2)->SetRightMargin(.01);
dividend->Draw();
}
virtual Model::PointDescriptorCollection CollectAvailablePoints() const override
{
Model::PointDescriptorCollection points;
const auto ref_hist = *all_hists.begin();
for(Int_t x_id = 1; x_id <= ref_hist->GetXaxis()->GetNbins(); ++x_id) {
const double x = ref_hist->GetXaxis()->GetBinCenter(x_id);
for(Int_t y_id = 1; y_id <= ref_hist->GetYaxis()->GetNbins(); ++y_id) {
const double y = ref_hist->GetYaxis()->GetBinCenter(y_id);
Model::PointDescriptor desc;
desc.point = Model::Point({x, y});
for(const auto& entry : masses)
desc.masses[entry.first] = entry.second->GetBinContent(x_id, y_id);
for(const auto& entry : cross_sections)
desc.cross_sections[entry.first] = entry.second->GetBinContent(x_id, y_id);
for(const auto& entry : branching_ratios)
desc.branching_ratios[entry.first] = entry.second->GetBinContent(x_id, y_id);
points.push_back(desc);
}
}
return points;
}
h1.SetTitle("");
h1.SetXTitle("NJets");
h2.SetLineColor(kRed);
// h1.SetFillColor(kRed);
// h1.SetFillStyle(3005);
// h2.SetLineColor(kBlue);
// h2.SetFillColor(kBlue);
//h2.SetFillStyle(3005);
TAxis* xax = h1.GetXaxis();
TAxis* yax = h1.GetYaxis();
xax->SetTitleSize(0.045);
xax->SetTitleOffset(1.);
//6519.8
double scale1 = 6519.8/h1.Integral();
double scale2 = 6519.8/h2.Integral();
h1.Scale(scale1);
h2.Scale(scale2);
h1.Draw("HIST");
h2.Draw("HISTsame");
}
void findfunc()
{
//dijet case
// auto fmcppbjt = config.getfile_djt("mcppbfa");
// auto nt = (TTree *)fmcppbjt->Get("nt");
// seth(18,40,220);
// auto hd = geth("hd");
// auto hn = geth("hn");
// nt->Project("hd","jtpt2","weight*(pthat>80 && jtpt1>100 && abs(refparton_flavorForB1)==5 && abs(refparton_flavorForB2)!=5 && dphi21>2.1)");
// nt->Project("hn","jtpt2","weight*(pthat>80 && jtpt1>100 && abs(refparton_flavorForB1)==5 && abs(refparton_flavorForB2)!=5 && dphi21>2.1 && discr_csvV1_2>0.9)");
// hn->Divide(hn,hd,1,1,"B")
// hn->Fit(f)
auto fpp = new TF1("fpp","expo",40,200);
auto f1 = new TF1("fPb1","expo",40,200);
auto f2 = new TF1("fPb2","expo",40,200);
auto f3 = new TF1("fPb3","expo",40,200);
seth(18,40,200);
auto ntpp = (TTree *)config.getfile_inc("mcppqcd")->Get("nt");
auto hd = geth("hd");
auto hn = geth("hn",";p_{T} [GeV];mistag probability");
ntpp->Project("hd","jtpt","weight*(pthat>50 && refpt>20 && abs(refparton_flavorForB)!=5)");
ntpp->Project("hn","jtpt","weight*(pthat>50 && refpt>20 && abs(refparton_flavorForB)!=5 && discr_csvV1>0.9)");
hn->Divide(hn,hd,1,1,"B");
// hn->Scale(1/hn->Integral());
hn->Fit(fpp);
auto nt = (TTree *)config.getfile_inc("mcPbqcd")->Get("nt");
auto hd1 = geth("hd1");
auto hn1 = geth("hn1",";p_{T} [GeV];mistag probability");
nt->Project("hd1","jtpt","weight*(pthat>50 && refpt>20 && bin < 20 && abs(refparton_flavorForB)!=5)");
nt->Project("hn1","jtpt","weight*(pthat>50 && refpt>20 && bin < 20 && abs(refparton_flavorForB)!=5 && discr_csvV1>0.9)");
hn1->Divide(hn1,hd1,1,1,"B");
// hn1->Scale(1/hn1->Integral());
hn1->Fit(f1);
auto hd2 = geth("hd2");
auto hn2 = geth("hn2",";p_{T} [GeV];mistag probability");
nt->Project("hd2","jtpt","weight*(pthat>50 && refpt>20 && bin>=20 && bin<60 && abs(refparton_flavorForB)!=5)");
nt->Project("hn2","jtpt","weight*(pthat>50 && refpt>20 && bin>=20 && bin<60 && abs(refparton_flavorForB)!=5 && discr_csvV1>0.9)");
hn2->Divide(hn2,hd2,1,1,"B");
// hn2->Scale(1/hn2->Integral());
hn2->Fit(f2);
auto hd3 = geth("hd3");
auto hn3 = geth("hn3",";p_{T} [GeV];mistag probability");
nt->Project("hd3","jtpt","weight*(pthat>50 && refpt>20 && bin>=60 && abs(refparton_flavorForB)!=5)");
nt->Project("hn3","jtpt","weight*(pthat>50 && refpt>20 && bin>=60 && abs(refparton_flavorForB)!=5 && discr_csvV1>0.9)");
hn3->Divide(hn3,hd3,1,1,"B");
// hn3->Scale(1/hn3->Integral());
hn3->Fit(f3);
// because of backward imcompatibility with root version on polui
cout<<"auto fpp = new TF1(\"fpp\",\"expo\","<<fpp->GetXmin()<<","<<fpp->GetXmax()<<");"<<endl;
cout<<"auto fPb1 = new TF1(\"fPb1\",\"expo\","<<f1->GetXmin()<<","<<f1->GetXmax()<<");"<<endl;
cout<<"auto fPb2 = new TF1(\"fPb2\",\"expo\","<<f2->GetXmin()<<","<<f2->GetXmax()<<");"<<endl;
cout<<"auto fPb3 = new TF1(\"fPb3\",\"expo\","<<f3->GetXmin()<<","<<f3->GetXmax()<<");"<<endl;
cout<<"fpp->SetParameters("<<fpp->GetParameter(0)<<","<<fpp->GetParameter(1)<<");"<<endl;
cout<<"fPb1->SetParameters("<<f1->GetParameter(0)<<","<<f1->GetParameter(1)<<");"<<endl;
cout<<"fPb2->SetParameters("<<f2->GetParameter(0)<<","<<f2->GetParameter(1)<<");"<<endl;
cout<<"fPb3->SetParameters("<<f3->GetParameter(0)<<","<<f3->GetParameter(1)<<");"<<endl;
// hn->SetMinimum(0);
// hn1->SetMinimum(0);
// hn2->SetMinimum(0);
// hn3->SetMinimum(0);
auto fout = new TFile("../correctionfiles/BXmistagfunc.root","recreate");
fout->cd();
fpp->Write();
f1->Write();
f2->Write();
f3->Write();
hn->Write();
hn1->Write();
hn2->Write();
hn3->Write();
auto c = getc();
f1->SetLineColor(kRed);
f2->SetLineColor(kGreen);
f3->SetLineColor(kOrange);
fpp->SetLineColor(kBlue);
auto l = getLegend();
l->AddEntry(fpp,"pp","L");
l->AddEntry(f1,"bin<20","L");
l->AddEntry(f2,"20<bin<60","L");
l->AddEntry(f3,"bin>60","L");
f1->GetXaxis()->SetTitle("p_{T} [GeV]");
f1->GetYaxis()->SetTitle("mistag probability");
f1->Draw();
f2->Draw("same");
f3->Draw("same");
fpp->Draw("same");
l->Draw();
SavePlot(c,"func");
float x = 0.55;
float y = 0.75;
auto t= new TLatex();
auto cpp = getc();
hn->Draw();
fpp->Draw("same");
t->DrawLatexNDC(x,y,"pp");
SavePlot(cpp,"pp");
auto c1 = getc();
hn1->Draw();
f1->Draw("same");
t->DrawLatexNDC(x,y,"PbPb 0-10%");
SavePlot(c1,"bin_0_20");
auto c2 = getc();
hn2->Draw();
f2->Draw("same");
t->DrawLatexNDC(x,y,"PbPb 10-30%");
SavePlot(c2,"bin_20_60");
auto c3 = getc();
hn3->Draw();
f3->Draw("same");
t->DrawLatexNDC(x,y,"PbPb 30-100%");
SavePlot(c3,"bin_60");
fout->Close();
}
void derivefromNS(bool data = false)
{
// float shift = mode == 2 ? -2 : mode*2; //mode = 0,1,2 shift = 0,2,-2
// cout<<"shift = "<<shift<<endl;
auto file = config.getfile_djt(data ? "dtPbjcl" : "mcPbqcd");
auto nt = (TTree *)file->Get("nt");
for (unsigned i=1;i<binbounds.size();i++) {
int b1 = binbounds[i-1];
int b2 = binbounds[i];
seth(71,38,180); //71,38
auto h = geth(Form("h%d%d",b1,b2)); //allowing one more bin for overflow
seth(b2-b1,b1,b2);
auto hb = geth(Form("hb%d%d",b1,b2));
TString mcappendix = data ? "" : "&& pthat>50";//"&& subid2!=0 && pthat>50"; //"&& pthat>50";//"&& !(subid2==0 && refpt2>20) && pthat>50"; //"&& pthat>80";//
//Form("jtpt2+%f",shift)
nt->Project(h->GetName(),"jtpt2", Form("weight*(jtpt1>100&&bin>=%d && bin<%d && dphi21<1.05 %s)",b1,b2,mcappendix.Data()));
nt->Project(hb->GetName(),"bin", Form("weight*(jtpt1>100&&bin>=%d && bin<%d && dphi21<1.05 %s)",b1,b2,mcappendix.Data()));
ScaleVisibleBins(h,NSfrac[i-1]);
h->SetBinContent(1,h->GetBinContent(0)+h->GetBinContent(1));
// auto p = new TProfile(Form("p%d%d",b1,b2),Form("prof"),71,38,180);
// nt->Project(p->GetName(),"(subid2 == 0 && refpt2 > 20):jtptSignal2",Form("weight*(jtpt1>100&&bin>=%d && bin<%d && dphiSignal21<1.05 && !(subid2==0 && refpt2>20) && pthat>80)",b1,b2));
auto g = getCDFgraph(h);
g->GetXaxis()->SetTitle("p_{T,2} threshold [GeV]");
g->GetYaxis()->SetTitle("found fraction");
auto gtemp = getCDFgraph(h);
meanb.push_back(hb->GetMean());
prob.push_back(gtemp->Eval(pt));
float c0=g->Eval(50);
cout<<"prob at 50: "<<c0<<endl;
auto gf = new TFile("graph.root","recreate");
gtemp->Write();
gf->Close();
// auto f = new TF1(Form("f%d%d",b1,b2),"1-[0]*exp(-[1]*(x-40))",40,180);
// f->SetParameters(0.1,0.1);
// // f->FixParameter(1,0.08);
// auto f = new TF1(Form("f%d%d",b1,b2),"TMath::Erf((x-[0])/[1])",40,180);
// f->SetParameters(40,10);
// f->FixParameter(1,25);
auto f = new TF1(Form("f%d%d",b1,b2),"exp(-[0]*exp(-[1]*x))",40,180);
f->SetParameters(100,0.1);
// f->FixParameter(1,0.11); //!!!!!!!!!!
f->SetLineColor(kRed);
f->SetLineWidth(2);
g->Fit(f,"RM");
fs.push_back(f);
binmean.push_back(hb->GetMean());
float median = -1/f->GetParameter(1)*log(-1/f->GetParameter(0)*log(0.5));
Draw({h});
// h->Rebin(2);
auto gcoarse = getCDFgraph(h);
auto c = getc();
TLatex *Tl = new TLatex();
gcoarse->SetMinimum(0);g->SetMaximum(1);
gcoarse->Draw("AP");
f->Draw("same");
Tl->DrawLatexNDC(0.6,0.55,"y=e^{-a e^{-b x} }");
Tl->DrawLatexNDC(0.6,0.50,Form("a = %.1f",f->GetParameter(0)));
Tl->DrawLatexNDC(0.6,0.45,Form("b = %.2f",f->GetParameter(1)));
Tl->DrawLatexNDC(0.6,0.4,Form("PbPb bin %d-%d",b1,b2));
Tl->DrawLatexNDC(0.6,0.35,Form("median = %.2f",median));
TLine *l1 = new TLine(median,0,median, f->Eval(median));
l1->Draw();
TLine *l2 = new TLine(0,0.5,median, f->Eval(median));
l2->Draw();
// p->SetMarkerColor(kRed);
// p->SetMarkerSize(1);
// p->Draw("same");
SavePlot(c,Form("fit%d%d",b1,b2));//return;
}
}
gStyle->SetOptStat(0);
gStyle->SetOptFit(1111);
gStyle->SetOptTitle(0);
int i;
// overlay of cocktail
file_exodus_new->cd();
TH1D *ratio;
ratio = (TH1D*)pte->Clone();
ratio->Scale(0.75);
file_exodus_old->cd();
ratio->Divide(pte);
TAxis *yaxis=ratio->GetYaxis();
yaxis->SetTitle("ratio of trigger biased cocktail: new/old");
TAxis *xaxis=ratio->GetXaxis();
xaxis->SetTitle("p_{T} [GeV/c]");
ratio->SetTitleOffset(1.5,"Y");
ratio->SetMinimum(0.0);
ratio->SetMaximum(1.2);
ratio->Draw("");
ratio->Fit("pol0","R","",0.4,5.);
return;
}