{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a8cef08d",
   "metadata": {},
   "source": [
    "# df102_NanoAODDimuonAnalysis\n",
    "Show how NanoAOD files can be processed with RDataFrame.\n",
    "\n",
    "This tutorial illustrates how NanoAOD files can be processed with ROOT\n",
    "dataframes. The NanoAOD-like input files are filled with 66 mio. events\n",
    "from CMS OpenData containing muon candidates part of 2012 dataset\n",
    "([DOI: 10.7483/OPENDATA.CMS.YLIC.86ZZ](http://opendata.cern.ch/record/6004)\n",
    "and [DOI: 10.7483/OPENDATA.CMS.M5AD.Y3V3](http://opendata.cern.ch/record/6030)).\n",
    "The macro matches muon pairs and produces an histogram of the dimuon mass\n",
    "spectrum showing resonances up to the Z mass.\n",
    "Note that the bump at 30 GeV is not a resonance but a trigger effect.\n",
    "\n",
    "More details about the dataset can be found on [the CERN Open Data portal](http://opendata.web.cern.ch/record/12341).\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "**Author:** Stefan Wunsch (KIT, CERN)  \n",
    "<i><small>This notebook tutorial was automatically generated with <a href= \"https://github.com/root-project/root/blob/master/documentation/doxygen/converttonotebook.py\">ROOTBOOK-izer</a> from the macro found in the ROOT repository  on Tuesday, May 19, 2026 at 08:10 PM.</small></i>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8037c613",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%%cpp -d\n",
    "#include \"ROOT/RDataFrame.hxx\"\n",
    "#include \"ROOT/RDFHelpers.hxx\"\n",
    "#include \"ROOT/RVec.hxx\"\n",
    "#include \"TCanvas.h\"\n",
    "#include \"TH1D.h\"\n",
    "#include \"TLatex.h\"\n",
    "#include \"TStyle.h\"\n",
    "\n",
    "using namespace ROOT::VecOps;"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d6236ea",
   "metadata": {},
   "source": [
    "Enable multi-threading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eee61895",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ROOT::EnableImplicitMT();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d032046d",
   "metadata": {},
   "source": [
    "Create dataframe from NanoAOD files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8ae5da34",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ROOT::RDataFrame df(\"Events\", \"root://eospublic.cern.ch//eos/opendata/cms/derived-data/AOD2NanoAODOutreachTool/\"\n",
    "                              \"Run2012BC_DoubleMuParked_Muons.root\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79576a68",
   "metadata": {},
   "source": [
    "Add ProgressBar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "14a968c9",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ROOT::RDF::Experimental::AddProgressBar(df);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9234cfeb",
   "metadata": {},
   "source": [
    "For simplicity, select only events with exactly two muons and require opposite charge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3163a00c",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "auto df_2mu = df.Filter(\"nMuon == 2\", \"Events with exactly two muons\");\n",
    "auto df_os = df_2mu.Filter(\"Muon_charge[0] != Muon_charge[1]\", \"Muons with opposite charge\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84a4aa74",
   "metadata": {},
   "source": [
    "Compute invariant mass of the dimuon system"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "884badb0",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "auto df_mass = df_os.Define(\"Dimuon_mass\", InvariantMass<float>, {\"Muon_pt\", \"Muon_eta\", \"Muon_phi\", \"Muon_mass\"});"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7adeef69",
   "metadata": {},
   "source": [
    "Make histogram of dimuon mass spectrum. Note how we can set title and axis labels in one go"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d8ab64e0",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "auto h = df_mass.Histo1D({\"Dimuon_mass\", \"Dimuon mass;m_{#mu#mu} (GeV);N_{Events}\", 30000, 0.25, 300}, \"Dimuon_mass\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ceb9688",
   "metadata": {},
   "source": [
    "Request cut-flow report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "afbe888c",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "auto report = df.Report();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26957e6e",
   "metadata": {},
   "source": [
    "Produce plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "201ffc36",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "gStyle->SetOptStat(0); gStyle->SetTextFont(42);\n",
    "auto c = new TCanvas(\"c\", \"\", 800, 700);\n",
    "c->SetLogx(); c->SetLogy();\n",
    "\n",
    "h->GetXaxis()->SetTitleSize(0.04);\n",
    "h->GetYaxis()->SetTitleSize(0.04);\n",
    "h->DrawClone();\n",
    "\n",
    "TLatex label; label.SetNDC(true);\n",
    "label.DrawLatex(0.175, 0.740, \"#eta\");\n",
    "label.DrawLatex(0.205, 0.775, \"#rho,#omega\");\n",
    "label.DrawLatex(0.270, 0.740, \"#phi\");\n",
    "label.DrawLatex(0.400, 0.800, \"J/#psi\");\n",
    "label.DrawLatex(0.415, 0.670, \"#psi'\");\n",
    "label.DrawLatex(0.485, 0.700, \"Y(1,2,3S)\");\n",
    "label.DrawLatex(0.755, 0.680, \"Z\");\n",
    "label.SetTextSize(0.040); label.DrawLatex(0.100, 0.920, \"#bf{CMS Open Data}\");\n",
    "label.SetTextSize(0.030); label.DrawLatex(0.630, 0.920, \"#sqrt{s} = 8 TeV, L_{int} = 11.6 fb^{-1}\");\n",
    "\n",
    "c->SaveAs(\"dimuon_spectrum.pdf\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "85ad2613",
   "metadata": {},
   "source": [
    "Print cut-flow report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1331d5e8",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "report->Print();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48336159",
   "metadata": {},
   "source": [
    "Draw all canvases "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "709d598a",
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%jsroot on\n",
    "gROOT->GetListOfCanvases()->Draw()"
   ]
  }
 ],
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