ntpl004_dimuon.C

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/// \file
/// \ingroup tutorial_ntuple
/// \notebook
/// Mini-Analysis on CMS OpenData with RDataFrame.
/// This tutorial illustrates that analyzing data with RDataFrame works the same
/// for both TTree data and RNTuple data.  The RNTuple data are converted from the Events tree
/// in http://root.cern/files/NanoAOD_DoubleMuon_CMS2011OpenData.root
/// Based on RDataFrame's df102_NanoAODDimuonAnalysis.C
///
/// \macro_image
/// \macro_code
///
/// \date April 2019
/// \author The ROOT Team
 
// NOTE: The RNTuple classes are experimental at this point.
// Functionality, interface, and data format is still subject to changes.
// Do not use for real data!
 
#include <ROOT/RDataFrame.hxx>
#include <ROOT/RNTupleDS.hxx>
#include <ROOT/RVec.hxx>
 
#include <TCanvas.h>
#include <TH1D.h>
#include <TLatex.h>
#include <TStyle.h>
 
#include <cassert>
#include <cmath>
#include <iostream>
#include <memory>
#include <string>
#include <vector>
#include <utility>
 
// Import classes from experimental namespace for the time being
using RNTupleDS = ROOT::Experimental::RNTupleDS;
 
constexpr char const* kNTupleFileName = "http://root.cern/files/tutorials/ntpl004_dimuon_v1rc2.root";
 
using namespace ROOT::VecOps;
 
void ntpl004_dimuon() {
   // Use all available CPU cores
   ROOT::EnableImplicitMT();
 
   ROOT::RDataFrame df("Events", kNTupleFileName);
 
   // The tutorial is identical to df102_NanoAODDimuonAnalysis except the use of RNTuple.
 
   // For simplicity, select only events with exactly two muons and require opposite charge
   auto df_2mu = df.Filter("nMuon == 2", "Events with exactly two muons");
   auto df_os = df_2mu.Filter("Muon_charge[0] != Muon_charge[1]", "Muons with opposite charge");
 
   // Compute invariant mass of the dimuon system
   auto df_mass = df_os.Define("Dimuon_mass", InvariantMass<float>, {"Muon_pt", "Muon_eta", "Muon_phi", "Muon_mass"});
 
   // Make histogram of dimuon mass spectrum
   auto h = df_mass.Histo1D({"Dimuon_mass", "Dimuon_mass", 30000, 0.25, 300}, "Dimuon_mass");
 
   // Request cut-flow report
   auto report = df_mass.Report();
 
   // Produce plot
   gStyle->SetOptStat(0); gStyle->SetTextFont(42);
   auto c = new 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->DrawCopy();
 
   TLatex label; 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}");
 
   // Print cut-flow report
   report->Print();
}