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df102_NanoAODDimuonAnalysis.py File Reference

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namespace  df102_NanoAODDimuonAnalysis
 

Detailed Description

View in nbviewer Open in SWAN This tutorial illustrates how NanoAOD files can be processed with ROOT dataframes.

The NanoAOD-like input files are filled with 66 mio. events from CMS OpenData containing muon candidates part of 2012 dataset (DOI: 10.7483/OPENDATA.CMS.YLIC.86ZZ and DOI: 10.7483/OPENDATA.CMS.M5AD.Y3V3). The macro matches muon pairs and produces an histogram of the dimuon mass spectrum showing resonances up to the Z mass. Note that the bump at 30 GeV is not a resonance but a trigger effect.

Some more details about the dataset:

  • It contains about 66 millions events (muon and electron collections, plus some other information, e.g. about primary vertices)
  • It spans two compressed ROOT files located on EOS for about a total size of 7.5 GB.
import ROOT
# Enable multi-threading
ROOT.ROOT.EnableImplicitMT()
# Create dataframe from NanoAOD files
files = ROOT.std.vector("string")(2)
files[0] = "root://eospublic.cern.ch//eos/root-eos/cms_opendata_2012_nanoaod/Run2012B_DoubleMuParked.root"
files[1] = "root://eospublic.cern.ch//eos/root-eos/cms_opendata_2012_nanoaod/Run2012C_DoubleMuParked.root"
df = ROOT.RDataFrame("Events", files)
# For simplicity, select only events with exactly two muons and require opposite charge
df_2mu = df.Filter("nMuon == 2", "Events with exactly two muons")
df_os = df_2mu.Filter("Muon_charge[0] != Muon_charge[1]", "Muons with opposite charge")
# Compute invariant mass of the dimuon system
df_mass = df_os.Define("Dimuon_mass", "InvariantMass(Muon_pt, Muon_eta, Muon_phi, Muon_mass)")
# Make histogram of dimuon mass spectrum
h = df_mass.Histo1D(("Dimuon_mass", "Dimuon_mass", 30000, 0.25, 300), "Dimuon_mass")
# Request cut-flow report
report = df_mass.Report()
# Produce plot
ROOT.gStyle.SetOptStat(0); ROOT.gStyle.SetTextFont(42)
c = ROOT.TCanvas("c", "", 800, 700)
c.SetLogx(); c.SetLogy()
h.SetTitle("")
h.GetXaxis().SetTitle("m_{#mu#mu} (GeV)"); h.GetXaxis().SetTitleSize(0.04)
h.GetYaxis().SetTitle("N_{Events}"); h.GetYaxis().SetTitleSize(0.04)
h.Draw()
label = ROOT.TLatex(); label.SetNDC(True)
label.DrawLatex(0.175, 0.740, "#eta")
label.DrawLatex(0.205, 0.775, "#rho,#omega")
label.DrawLatex(0.270, 0.740, "#phi")
label.DrawLatex(0.400, 0.800, "J/#psi")
label.DrawLatex(0.415, 0.670, "#psi'")
label.DrawLatex(0.485, 0.700, "Y(1,2,3S)")
label.DrawLatex(0.755, 0.680, "Z")
label.SetTextSize(0.040); label.DrawLatex(0.100, 0.920, "#bf{CMS Open Data}")
label.SetTextSize(0.030); label.DrawLatex(0.630, 0.920, "#sqrt{s} = 8 TeV, L_{int} = 11.6 fb^{-1}")
c.SaveAs("dimuon_spectrum.pdf")
# Print cut-flow report
report.Print()
ROOT's RDataFrame offers a high level interface for analyses of data stored in TTrees,...
Definition: RDataFrame.hxx:42
Events with exactly two muons: pass=33370298 all=66128870 -- eff=50.46 % cumulative eff=50.46 %
Muons with opposite charge: pass=25794885 all=33370298 -- eff=77.30 % cumulative eff=39.01 %
Date
April 2019
Author
Stefan Wunsch (KIT, CERN)

Definition in file df102_NanoAODDimuonAnalysis.py.