RDataFrame_benchmark.ipynb

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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Welcome to JupyROOT 6.24/00\n"
     ]
    }
   ],
   "source": [
    "import ROOT"
   ]
  },
  {
   "cell_type": "code",
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   "metadata": {},
   "outputs": [],
   "source": [
    "#ROOT.ROOT.DisableImplicitMT()\n",
    "#ROOT.ROOT.EnableImplicitMT(4)"
   ]
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  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
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     "data": {
      "text/plain": [
       "True"
      ]
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     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "ROOT.gInterpreter.Declare('#include \"df103_NanoAODHiggsAnalysis_python.h\"')"
   ]
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   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def selection_4mu(df):\n",
    "    \"\"\"Select interesting events with four muons\"\"\"\n",
    "    df_ge4m = df.Filter(\"nMuon==4\", \"Exactly four muons\")\n",
    " \n",
    "    df_kin = df_ge4m.Filter(\"All(Muon_pt>5) && All(abs(Muon_eta)<2.4)\", \"Good muon kinematics\")\n",
    "    df_2p2n = df_kin.Filter(\"Sum(Muon_charge)==0\",\n",
    "                           \"Two positive and two negative muons\")\n",
    " \n",
    "    return df_2p2n\n",
    "\n",
    "def filter_z_candidates(df):\n",
    "    \"\"\"Apply selection on reconstructed Z candidates\"\"\"\n",
    "    df_z1_cut = df.Filter(\"Z_mass[0] > 40 && Z_mass[0] < 120\", \"Mass of first Z candidate in [40, 120]\")\n",
    "    df_z2_cut = df_z1_cut.Filter(\"Z_mass[1] > 12 && Z_mass[1] < 120\", \"Mass of second Z candidate in [12, 120]\")\n",
    "    return df_z2_cut\n",
    "\n",
    "def reco_higgs_to_4mu(df):\n",
    "    \"\"\"Reconstruct Higgs from four muons\"\"\"\n",
    "    # Filter interesting events\n",
    "    df_base = selection_4mu(df)\n",
    " \n",
    "    # Reconstruct Z systems\n",
    "    df_z_idx = df_base.Define(\"Z_idx\", \"reco_zz_to_4l(Muon_pt, Muon_eta, Muon_phi, Muon_mass, Muon_charge)\")\n",
    " \n",
    "    # Cut on distance between muons building Z systems\n",
    "    df_z_dr = df_z_idx.Filter(\"filter_z_dr(Z_idx, Muon_eta, Muon_phi)\", \"Delta R separation of muons building Z system\")\n",
    " \n",
    "    # Compute masses of Z systems\n",
    "    df_z_mass = df_z_dr.Define(\"Z_mass\", \"compute_z_masses_4l(Z_idx, Muon_pt, Muon_eta, Muon_phi, Muon_mass)\")\n",
    " \n",
    "    # Cut on mass of Z candidates\n",
    "    df_z_cut = filter_z_candidates(df_z_mass)\n",
    " \n",
    "    # Reconstruct H mass\n",
    "    df_h_mass = df_z_cut.Define(\"H_mass\", \"compute_higgs_mass_4l(Z_idx, Muon_pt, Muon_eta, Muon_phi, Muon_mass)\")\n",
    " \n",
    "    return df_h_mass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_bkg_4mu = ROOT.RDataFrame(\"Events\", \"./Run2012BC_DoubleMuParked_Muons.root\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_bkg_4mu_reco = reco_higgs_to_4mu(df_bkg_4mu)\n",
    "\n",
    "df_h_bkg_4mu = df_bkg_4mu_reco.Histo1D((\"h_bkg_4mu\", \"\", 36, 70, 180), \"H_mass\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 37.2 s, sys: 502 ms, total: 37.7 s\n",
      "Wall time: 37.2 s\n"
     ]
    },
    {
     "data": {
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     "execution_count": 7,
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   ],
   "source": [
    "%time df_h_bkg_4mu.GetValue()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
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