localtest.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "140fc5f4-c3e6-4c7a-b273-cf055fe39feb",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import awkward as ak\n",
    "from coffea.nanoevents import NanoEventsFactory, NanoAODSchema\n",
    "from coffea.analysis_tools import PackedSelection\n",
    "import hist\n",
    "import matplotlib.pyplot as plt\n",
    "import mplhep as hep\n",
    "import numpy as np\n",
    "import numba\n",
    "import uproot \n",
    "#plt.style.use(hep.style.CMS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ca987ef8-5b6d-4588-9208-1135ce33f055",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "redirector = {\"hdfs\":\"/hdfs\",\n",
    "              \"local\":\"\",\n",
    "              \"global\":\"root://cms-xrd-global.cern.ch//\",\n",
    "              \"infn\":\"root://xrootd-cms.infn.it//\",\n",
    "              \"fermilab\":\"root://cmsxrootd.fnal.gov//\",\n",
    "             }\n",
    "file = \"/store/mc/RunIIAutumn18NanoAODv7/MonoHTobb_ZpBaryonic_TuneCP2_13TeV_madgraph-pythia8/NANOAODSIM/Nano02Apr2020_rp_102X_upgrade2018_realistic_v21-v1/10000/0EE0D641-EDAE-D547-ABAD-56D54B768C5B.root\"\n",
    "local_file = \"/home/prayag/Coffea/data/3BF5BC57-5D24-1C4D-B277-7B0BAA5DF3C7.root\"\n",
    "filename= redirector[\"local\"] + local_file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4a3c6b18-cb8f-4adc-92f6-ccc8e8f67cf5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of events loaded :  297347\n"
     ]
    }
   ],
   "source": [
    "events = NanoEventsFactory.from_root(\n",
    "    filename,\n",
    "    schemaclass = NanoAODSchema.v7,\n",
    "    metadata = {\"Dataset\":\"HiggsTobbbarZprimeBaryonic\",\"isMC\":True},\n",
    "    #entry_stop=10e5 ,\n",
    ").events()\n",
    "print(\"Number of events loaded : \", len(events))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5ee5aff1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '2D Histogram')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Make a 2d histogram\n",
    "\n",
    "eta_hist = hist.axis.Regular(5,-3,3, name= \"eta\", label=\"$\\eta$\")\n",
    "pt_hist = hist.axis.Regular(5,5,40, name=\"pt\", label=\"$p_t$ (GeV)\")\n",
    "twoDhist= hist.Hist(pt_hist , eta_hist )\n",
    "twoDhist.fill(eta = ak.flatten(events.Jet.eta) , pt = ak.flatten(events.Jet.pt)) \n",
    "fig , ax = plt.subplots()\n",
    "hep.hist2dplot(twoDhist, labels=True, ax=ax)\n",
    "ax.set_title(\"2D Histogram\" , size = 18)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9942169",
   "metadata": {},
   "source": [
    "`ak.broadcast_arrays` : This function returns the input arrays with enough elements duplicated that they can be combined element-by-element."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c96d00f2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a=  [1, 2, [3, 4]]\n",
      "b=  [[5, 2], 6, 7]\n",
      "c=  [<Array [[1, 1], 2, [3, 4]] type='3 * union[var * int64, int64]'>, <Array [[5, 2], 6, [7, 7]] type='3 * union[var * int64, int64]'>]\n"
     ]
    }
   ],
   "source": [
    "a = ak.Array([1,2,[3 ,4 ]])\n",
    "print(\"a= \", a)\n",
    "b = ak.Array([[5,2,],6,7])\n",
    "print(\"b= \", b)\n",
    "c = ak.broadcast_arrays(a,b)\n",
    "print(\"c= \", c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "bf7a8994",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.axis.XTick at 0x7f31ccf5fd60>,\n",
       " <matplotlib.axis.XTick at 0x7f31ccc7a3e0>,\n",
       " <matplotlib.axis.XTick at 0x7f31ccc798d0>,\n",
       " <matplotlib.axis.XTick at 0x7f31ccca0520>,\n",
       " <matplotlib.axis.XTick at 0x7f31ccb04220>,\n",
       " <matplotlib.axis.XTick at 0x7f31ccb04cd0>]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fatjet_hist = (\n",
    "    hist.Hist.new\n",
    "    .StrCat([\"Jet\",\"FatJet\",\"FatJetCHS\",\"FatJetForJEC\"], name=\"jet\", label=\"Jets\")\n",
    "    .Regular(100,0,300,name=\"pt\")\n",
    "    .Double()\n",
    "    )\n",
    "fatjet_hist.fill(jet=\"Jet\", pt= ak.flatten(events.Jet.pt) )\n",
    "fatjet_hist.fill(jet=\"FatJet\", pt= ak.flatten(events.FatJet.pt) )\n",
    "fatjet_hist.fill(jet=\"FatJetCHS\", pt= ak.flatten(events.FatJetCHS.pt) )\n",
    "fatjet_hist.fill(jet=\"FatJetForJEC\", pt= ak.flatten(events.FatJetForJEC.pt) )\n",
    "hists= [ fatjet_hist[\"Jet\", :], fatjet_hist[\"FatJet\", :] ,fatjet_hist[\"FatJetCHS\", :], fatjet_hist[\"FatJetForJEC\", :] ]\n",
    "fig , ax = plt.subplots()\n",
    "fill_colors = [\"#317773\" , \"#B99095\", \"#FCB5AC\", \"#B5E5CF\"]\n",
    "labels =[\"Jet\",\"FatJet\",\"FatJetCHS\",\"FatJetForJEC\"]\n",
    "hep.histplot(\n",
    "    hists ,\n",
    "    histtype=\"fill\",\n",
    "    color = fill_colors,\n",
    "    edgecolor=\"black\",\n",
    "    label=labels,\n",
    "    stack=True ,\n",
    "    lw=1,\n",
    "    ax=ax\n",
    ")\n",
    "ax.set_title(\"FatJet $p_t$\")\n",
    "hep.cms.label(\"\", pad=0.05)\n",
    "fig.legend(loc = 10)\n",
    "ax.set_xlabel(\"$p_t$ (GeV)\")\n",
    "ax.set_ylabel(\"Events / 3 GeV\")\n",
    "ax.set_xticks(np.arange(0,300,50))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "91ea0430",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['SoftActivityJet',\n",
       " 'SV',\n",
       " 'FsrPhoton',\n",
       " 'JetCalo',\n",
       " 'SoftActivityJetHT5',\n",
       " 'L1',\n",
       " 'L1PreFiringWeight',\n",
       " 'IsoTrack',\n",
       " 'Jet',\n",
       " 'TrigObj',\n",
       " 'L1Reco',\n",
       " 'RawMET',\n",
       " 'Tau',\n",
       " 'SoftActivityJetHT',\n",
       " 'LowPtElectron',\n",
       " 'SoftActivityJetNjets2',\n",
       " 'luminosityBlock',\n",
       " 'CaloMET',\n",
       " 'DeepMETResponseTune',\n",
       " 'fixedGridRhoFastjetAll',\n",
       " 'fixedGridRhoFastjetCentralCalo',\n",
       " 'Flag',\n",
       " 'JetPuppi',\n",
       " 'fixedGridRhoFastjetCentralChargedPileUp',\n",
       " 'Muon',\n",
       " 'HLT',\n",
       " 'HLTriggerFirstPath',\n",
       " 'PuppiMET',\n",
       " 'fixedGridRhoFastjetCentralNeutral',\n",
       " 'Proton',\n",
       " 'fixedGridRhoFastjetCentral',\n",
       " 'SoftActivityJetNjets10',\n",
       " 'TkMET',\n",
       " 'SoftActivityJetHT10',\n",
       " 'PV',\n",
       " 'SoftActivityJetHT2',\n",
       " 'ChsMET',\n",
       " 'DeepMETResolutionTune',\n",
       " 'Electron',\n",
       " 'FatJet',\n",
       " 'SoftActivityJetNjets5',\n",
       " 'RawPuppiMET',\n",
       " 'Photon',\n",
       " 'boostedTau',\n",
       " 'PPSLocalTrack',\n",
       " 'SubJet',\n",
       " 'event',\n",
       " 'CorrT1METJet',\n",
       " 'run',\n",
       " 'FatJetForJEC',\n",
       " 'FatJetCHS',\n",
       " 'MET',\n",
       " 'OtherPV',\n",
       " 'HLTriggerFinalPath']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "events.fields"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1dbfb7f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['AK8PFJet360_TrimMass30',\n",
       " 'AK8PFJet380_TrimMass30',\n",
       " 'AK8PFJet400_TrimMass30',\n",
       " 'AK8PFJet420_TrimMass30',\n",
       " 'AK8PFHT750_TrimMass50',\n",
       " 'AK8PFHT800_TrimMass50',\n",
       " 'AK8PFHT850_TrimMass50',\n",
       " 'AK8PFHT900_TrimMass50',\n",
       " 'CaloJet500_NoJetID',\n",
       " 'CaloJet550_NoJetID',\n",
       " 'Trimuon5_3p5_2_Upsilon_Muon',\n",
       " 'DoubleEle25_CaloIdL_MW',\n",
       " 'DoubleEle27_CaloIdL_MW',\n",
       " 'DoubleEle33_CaloIdL_MW',\n",
       " 'DoubleEle24_eta2p1_WPTight_Gsf',\n",
       " 'DoubleEle8_CaloIdM_TrackIdM_Mass8_DZ_PFHT350',\n",
       " 'DoubleEle8_CaloIdM_TrackIdM_Mass8_PFHT350',\n",
       " 'Ele27_Ele37_CaloIdL_MW',\n",
       " 'Mu27_Ele37_CaloIdL_MW',\n",
       " 'Mu37_Ele27_CaloIdL_MW',\n",
       " 'Mu37_TkMu27',\n",
       " 'DoubleMu4_3_Bs',\n",
       " 'DoubleMu4_3_Jpsi_Displaced',\n",
       " 'DoubleMu4_JpsiTrk_Displaced',\n",
       " 'DoubleMu4_LowMassNonResonantTrk_Displaced',\n",
       " 'DoubleMu3_Trk_Tau3mu',\n",
       " 'DoubleMu4_PsiPrimeTrk_Displaced',\n",
       " 'DoubleMu4_Mass8_DZ_PFHT350',\n",
       " 'DoubleMu8_Mass8_PFHT350',\n",
       " 'Mu3_PFJet40',\n",
       " 'Mu7p5_L2Mu2_Jpsi',\n",
       " 'Mu7p5_L2Mu2_Upsilon',\n",
       " 'Mu7p5_Track2_Jpsi',\n",
       " 'Mu7p5_Track3p5_Jpsi',\n",
       " 'Mu7p5_Track7_Jpsi',\n",
       " 'Mu7p5_Track2_Upsilon',\n",
       " 'Mu7p5_Track3p5_Upsilon',\n",
       " 'Mu7p5_Track7_Upsilon',\n",
       " 'DoublePhoton33_CaloIdL',\n",
       " 'DoublePhoton70',\n",
       " 'DoublePhoton85',\n",
       " 'Ele20_WPTight_Gsf',\n",
       " 'Ele20_WPLoose_Gsf',\n",
       " 'Ele20_eta2p1_WPLoose_Gsf',\n",
       " 'DiEle27_WPTightCaloOnly_L1DoubleEG',\n",
       " 'Ele27_WPTight_Gsf',\n",
       " 'Ele32_WPTight_Gsf',\n",
       " 'Ele35_WPTight_Gsf',\n",
       " 'Ele35_WPTight_Gsf_L1EGMT',\n",
       " 'Ele38_WPTight_Gsf',\n",
       " 'Ele40_WPTight_Gsf',\n",
       " 'Ele32_WPTight_Gsf_L1DoubleEG',\n",
       " 'HT450_Beamspot',\n",
       " 'HT300_Beamspot',\n",
       " 'IsoMu20_eta2p1_LooseChargedIsoPFTau27_eta2p1_CrossL1',\n",
       " 'IsoMu20_eta2p1_MediumChargedIsoPFTau27_eta2p1_CrossL1',\n",
       " 'IsoMu20_eta2p1_TightChargedIsoPFTau27_eta2p1_CrossL1',\n",
       " 'IsoMu20_eta2p1_LooseChargedIsoPFTau27_eta2p1_TightID_CrossL1',\n",
       " 'IsoMu20_eta2p1_MediumChargedIsoPFTau27_eta2p1_TightID_CrossL1',\n",
       " 'IsoMu20_eta2p1_TightChargedIsoPFTau27_eta2p1_TightID_CrossL1',\n",
       " 'IsoMu24_eta2p1_LooseChargedIsoPFTau20_SingleL1',\n",
       " 'IsoMu24_eta2p1_MediumChargedIsoPFTau20_SingleL1',\n",
       " 'IsoMu24_eta2p1_TightChargedIsoPFTau20_SingleL1',\n",
       " 'IsoMu24_eta2p1_LooseChargedIsoPFTau20_TightID_SingleL1',\n",
       " 'IsoMu24_eta2p1_MediumChargedIsoPFTau20_TightID_SingleL1',\n",
       " 'IsoMu24_eta2p1_TightChargedIsoPFTau20_TightID_SingleL1',\n",
       " 'IsoMu20',\n",
       " 'IsoMu24',\n",
       " 'IsoMu24_eta2p1',\n",
       " 'IsoMu27',\n",
       " 'IsoMu30',\n",
       " 'UncorrectedJetE30_NoBPTX',\n",
       " 'UncorrectedJetE30_NoBPTX3BX',\n",
       " 'UncorrectedJetE60_NoBPTX3BX',\n",
       " 'UncorrectedJetE70_NoBPTX3BX',\n",
       " 'L1SingleMu18',\n",
       " 'L1SingleMu25',\n",
       " 'L2Mu10',\n",
       " 'L2Mu10_NoVertex_NoBPTX3BX',\n",
       " 'L2Mu10_NoVertex_NoBPTX',\n",
       " 'L2Mu45_NoVertex_3Sta_NoBPTX3BX',\n",
       " 'L2Mu40_NoVertex_3Sta_NoBPTX3BX',\n",
       " 'L2Mu50',\n",
       " 'DoubleL2Mu50',\n",
       " 'Mu17_TrkIsoVVL_Mu8_TrkIsoVVL',\n",
       " 'Mu19_TrkIsoVVL_Mu9_TrkIsoVVL',\n",
       " 'Mu17_TrkIsoVVL_Mu8_TrkIsoVVL_DZ',\n",
       " 'Mu19_TrkIsoVVL_Mu9_TrkIsoVVL_DZ',\n",
       " 'Mu17_TrkIsoVVL_Mu8_TrkIsoVVL_DZ_Mass8',\n",
       " 'Mu19_TrkIsoVVL_Mu9_TrkIsoVVL_DZ_Mass8',\n",
       " 'Mu17_TrkIsoVVL_Mu8_TrkIsoVVL_DZ_Mass3p8',\n",
       " 'Mu19_TrkIsoVVL_Mu9_TrkIsoVVL_DZ_Mass3p8',\n",
       " 'Mu25_TkMu0_Onia',\n",
       " 'Mu30_TkMu0_Onia',\n",
       " 'Mu20_TkMu0_Phi',\n",
       " 'Mu25_TkMu0_Phi',\n",
       " 'Mu20',\n",
       " 'Mu27',\n",
       " 'Mu50',\n",
       " 'Mu55',\n",
       " 'OldMu100',\n",
       " 'TkMu100',\n",
       " 'DiPFJet15_NoCaloMatched',\n",
       " 'DiPFJet25_NoCaloMatched',\n",
       " 'DiPFJet15_FBEta3_NoCaloMatched',\n",
       " 'DiPFJet25_FBEta3_NoCaloMatched',\n",
       " 'DiPFJetAve40',\n",
       " 'DiPFJetAve60',\n",
       " 'DiPFJetAve80',\n",
       " 'DiPFJetAve140',\n",
       " 'DiPFJetAve200',\n",
       " 'DiPFJetAve260',\n",
       " 'DiPFJetAve320',\n",
       " 'DiPFJetAve400',\n",
       " 'DiPFJetAve500',\n",
       " 'DiPFJetAve15_HFJEC',\n",
       " 'DiPFJetAve25_HFJEC',\n",
       " 'DiPFJetAve35_HFJEC',\n",
       " 'DiPFJetAve60_HFJEC',\n",
       " 'DiPFJetAve80_HFJEC',\n",
       " 'DiPFJetAve100_HFJEC',\n",
       " 'DiPFJetAve160_HFJEC',\n",
       " 'DiPFJetAve220_HFJEC',\n",
       " 'DiPFJetAve300_HFJEC',\n",
       " 'AK8PFJet40',\n",
       " 'AK8PFJet60',\n",
       " 'AK8PFJet80',\n",
       " 'AK8PFJet140',\n",
       " 'AK8PFJet200',\n",
       " 'AK8PFJet260',\n",
       " 'AK8PFJet320',\n",
       " 'AK8PFJet400',\n",
       " 'AK8PFJet450',\n",
       " 'AK8PFJet500',\n",
       " 'AK8PFJet550',\n",
       " 'PFJet40',\n",
       " 'PFJet60',\n",
       " 'PFJet80',\n",
       " 'PFJet140',\n",
       " 'PFJet200',\n",
       " 'PFJet260',\n",
       " 'PFJet320',\n",
       " 'PFJet400',\n",
       " 'PFJet450',\n",
       " 'PFJet500',\n",
       " 'PFJet550',\n",
       " 'PFJetFwd40',\n",
       " 'PFJetFwd60',\n",
       " 'PFJetFwd80',\n",
       " 'PFJetFwd140',\n",
       " 'PFJetFwd200',\n",
       " 'PFJetFwd260',\n",
       " 'PFJetFwd320',\n",
       " 'PFJetFwd400',\n",
       " 'PFJetFwd450',\n",
       " 'PFJetFwd500',\n",
       " 'AK8PFJetFwd40',\n",
       " 'AK8PFJetFwd60',\n",
       " 'AK8PFJetFwd80',\n",
       " 'AK8PFJetFwd140',\n",
       " 'AK8PFJetFwd200',\n",
       " 'AK8PFJetFwd260',\n",
       " 'AK8PFJetFwd320',\n",
       " 'AK8PFJetFwd400',\n",
       " 'AK8PFJetFwd450',\n",
       " 'AK8PFJetFwd500',\n",
       " 'PFHT180',\n",
       " 'PFHT250',\n",
       " 'PFHT370',\n",
       " 'PFHT430',\n",
       " 'PFHT510',\n",
       " 'PFHT590',\n",
       " 'PFHT680',\n",
       " 'PFHT780',\n",
       " 'PFHT890',\n",
       " 'PFHT1050',\n",
       " 'PFHT500_PFMET100_PFMHT100_IDTight',\n",
       " 'PFHT500_PFMET110_PFMHT110_IDTight',\n",
       " 'PFHT700_PFMET85_PFMHT85_IDTight',\n",
       " 'PFHT700_PFMET95_PFMHT95_IDTight',\n",
       " 'PFHT800_PFMET75_PFMHT75_IDTight',\n",
       " 'PFHT800_PFMET85_PFMHT85_IDTight',\n",
       " 'PFMET110_PFMHT110_IDTight',\n",
       " 'PFMET120_PFMHT120_IDTight',\n",
       " 'PFMET130_PFMHT130_IDTight',\n",
       " 'PFMET140_PFMHT140_IDTight',\n",
       " 'PFMET100_PFMHT100_IDTight_CaloBTagCSV_3p1',\n",
       " 'PFMET110_PFMHT110_IDTight_CaloBTagCSV_3p1',\n",
       " 'PFMET120_PFMHT120_IDTight_CaloBTagCSV_3p1',\n",
       " 'PFMET130_PFMHT130_IDTight_CaloBTagCSV_3p1',\n",
       " 'PFMET140_PFMHT140_IDTight_CaloBTagCSV_3p1',\n",
       " 'PFMET120_PFMHT120_IDTight_PFHT60',\n",
       " 'PFMETNoMu120_PFMHTNoMu120_IDTight_PFHT60',\n",
       " 'PFMETTypeOne120_PFMHT120_IDTight_PFHT60',\n",
       " 'PFMETTypeOne110_PFMHT110_IDTight',\n",
       " 'PFMETTypeOne120_PFMHT120_IDTight',\n",
       " 'PFMETTypeOne130_PFMHT130_IDTight',\n",
       " 'PFMETTypeOne140_PFMHT140_IDTight',\n",
       " 'PFMETNoMu110_PFMHTNoMu110_IDTight',\n",
       " 'PFMETNoMu120_PFMHTNoMu120_IDTight',\n",
       " 'PFMETNoMu130_PFMHTNoMu130_IDTight',\n",
       " 'PFMETNoMu140_PFMHTNoMu140_IDTight',\n",
       " 'MonoCentralPFJet80_PFMETNoMu110_PFMHTNoMu110_IDTight',\n",
       " 'MonoCentralPFJet80_PFMETNoMu120_PFMHTNoMu120_IDTight',\n",
       " 'MonoCentralPFJet80_PFMETNoMu130_PFMHTNoMu130_IDTight',\n",
       " 'MonoCentralPFJet80_PFMETNoMu140_PFMHTNoMu140_IDTight',\n",
       " 'L1ETMHadSeeds',\n",
       " 'CaloMHT90',\n",
       " 'CaloMET80_NotCleaned',\n",
       " 'CaloMET90_NotCleaned',\n",
       " 'CaloMET100_NotCleaned',\n",
       " 'CaloMET110_NotCleaned',\n",
       " 'CaloMET250_NotCleaned',\n",
       " 'CaloMET70_HBHECleaned',\n",
       " 'CaloMET80_HBHECleaned',\n",
       " 'CaloMET90_HBHECleaned',\n",
       " 'CaloMET100_HBHECleaned',\n",
       " 'CaloMET250_HBHECleaned',\n",
       " 'CaloMET300_HBHECleaned',\n",
       " 'CaloMET350_HBHECleaned',\n",
       " 'PFMET200_NotCleaned',\n",
       " 'PFMET200_HBHECleaned',\n",
       " 'PFMET250_HBHECleaned',\n",
       " 'PFMET300_HBHECleaned',\n",
       " 'PFMET200_HBHE_BeamHaloCleaned',\n",
       " 'PFMETTypeOne200_HBHE_BeamHaloCleaned',\n",
       " 'MET105_IsoTrk50',\n",
       " 'MET120_IsoTrk50',\n",
       " 'SingleJet30_Mu12_SinglePFJet40',\n",
       " 'Mu12_DoublePFJets40_CaloBTagCSV_p33',\n",
       " 'Mu12_DoublePFJets100_CaloBTagCSV_p33',\n",
       " 'Mu12_DoublePFJets200_CaloBTagCSV_p33',\n",
       " 'Mu12_DoublePFJets350_CaloBTagCSV_p33',\n",
       " 'Mu12_DoublePFJets40MaxDeta1p6_DoubleCaloBTagCSV_p33',\n",
       " 'Mu12_DoublePFJets54MaxDeta1p6_DoubleCaloBTagCSV_p33',\n",
       " 'Mu12_DoublePFJets62MaxDeta1p6_DoubleCaloBTagCSV_p33',\n",
       " 'DoublePFJets40_CaloBTagCSV_p33',\n",
       " 'DoublePFJets100_CaloBTagCSV_p33',\n",
       " 'DoublePFJets200_CaloBTagCSV_p33',\n",
       " 'DoublePFJets350_CaloBTagCSV_p33',\n",
       " 'DoublePFJets100MaxDeta1p6_DoubleCaloBTagCSV_p33',\n",
       " 'DoublePFJets116MaxDeta1p6_DoubleCaloBTagCSV_p33',\n",
       " 'DoublePFJets128MaxDeta1p6_DoubleCaloBTagCSV_p33',\n",
       " 'Photon300_NoHE',\n",
       " 'Mu8_TrkIsoVVL',\n",
       " 'Mu8_DiEle12_CaloIdL_TrackIdL_DZ',\n",
       " 'Mu8_DiEle12_CaloIdL_TrackIdL',\n",
       " 'Mu8_Ele8_CaloIdM_TrackIdM_Mass8_PFHT350_DZ',\n",
       " 'Mu8_Ele8_CaloIdM_TrackIdM_Mass8_PFHT350',\n",
       " 'Mu8_TrkIsoVVL_Ele23_CaloIdL_TrackIdL_IsoVL_DZ',\n",
       " 'Mu8_TrkIsoVVL_Ele23_CaloIdL_TrackIdL_IsoVL',\n",
       " 'Mu17_TrkIsoVVL',\n",
       " 'Mu19_TrkIsoVVL',\n",
       " 'BTagMu_AK4DiJet20_Mu5',\n",
       " 'BTagMu_AK4DiJet40_Mu5',\n",
       " 'BTagMu_AK4DiJet70_Mu5',\n",
       " 'BTagMu_AK4DiJet110_Mu5',\n",
       " 'BTagMu_AK4DiJet170_Mu5',\n",
       " 'BTagMu_AK4Jet300_Mu5',\n",
       " 'BTagMu_AK8DiJet170_Mu5',\n",
       " 'BTagMu_AK8Jet300_Mu5',\n",
       " 'Ele23_Ele12_CaloIdL_TrackIdL_IsoVL_DZ',\n",
       " 'Mu23_TrkIsoVVL_Ele12_CaloIdL_TrackIdL_IsoVL_DZ',\n",
       " 'Mu23_TrkIsoVVL_Ele12_CaloIdL_TrackIdL_IsoVL',\n",
       " 'Mu12_TrkIsoVVL_Ele23_CaloIdL_TrackIdL_IsoVL',\n",
       " 'Mu12_TrkIsoVVL_Ele23_CaloIdL_TrackIdL_IsoVL_DZ',\n",
       " 'Mu12_DoublePhoton20',\n",
       " 'Ele23_Ele12_CaloIdL_TrackIdL_IsoVL',\n",
       " 'TriplePhoton_20_20_20_CaloIdLV2',\n",
       " 'TriplePhoton_20_20_20_CaloIdLV2_R9IdVL',\n",
       " 'TriplePhoton_30_30_10_CaloIdLV2',\n",
       " 'TriplePhoton_30_30_10_CaloIdLV2_R9IdVL',\n",
       " 'TriplePhoton_35_35_5_CaloIdLV2_R9IdVL',\n",
       " 'Photon25',\n",
       " 'Photon33',\n",
       " 'Photon50',\n",
       " 'Photon75',\n",
       " 'Photon90',\n",
       " 'Photon120',\n",
       " 'Photon150',\n",
       " 'Photon175',\n",
       " 'Photon200',\n",
       " 'Photon50_R9Id90_HE10_IsoM',\n",
       " 'Photon75_R9Id90_HE10_IsoM',\n",
       " 'Photon90_R9Id90_HE10_IsoM',\n",
       " 'Photon120_R9Id90_HE10_IsoM',\n",
       " 'Photon165_R9Id90_HE10_IsoM',\n",
       " 'Diphoton30_22_R9Id_OR_IsoCaloId_AND_HE_R9Id_Mass90',\n",
       " 'Diphoton30_22_R9Id_OR_IsoCaloId_AND_HE_R9Id_Mass95',\n",
       " 'Diphoton30PV_18PV_R9Id_AND_IsoCaloId_AND_HE_R9Id_PixelVeto_Mass55',\n",
       " 'Diphoton30PV_18PV_R9Id_AND_IsoCaloId_AND_HE_R9Id_NoPixelVeto_Mass55',\n",
       " 'Diphoton30EB_18EB_R9Id_OR_IsoCaloId_AND_HE_R9Id_NoPixelVeto_Mass55',\n",
       " 'Diphoton30EB_18EB_R9Id_OR_IsoCaloId_AND_HE_R9Id_PixelVeto_Mass55',\n",
       " 'Dimuon0_Jpsi_L1_NoOS',\n",
       " 'Dimuon0_Jpsi_NoVertexing_NoOS',\n",
       " 'Dimuon0_Jpsi',\n",
       " 'Dimuon0_Jpsi_NoVertexing',\n",
       " 'Dimuon0_Jpsi_L1_4R_0er1p5R',\n",
       " 'Dimuon0_Jpsi_NoVertexing_L1_4R_0er1p5R',\n",
       " 'Dimuon0_Jpsi3p5_Muon2',\n",
       " 'Dimuon0_Upsilon_L1_4p5',\n",
       " 'Dimuon0_Upsilon_L1_5',\n",
       " 'Dimuon0_Upsilon_L1_4p5NoOS',\n",
       " 'Dimuon0_Upsilon_L1_4p5er2p0',\n",
       " 'Dimuon0_Upsilon_L1_4p5er2p0M',\n",
       " 'Dimuon0_Upsilon_NoVertexing',\n",
       " 'Dimuon0_Upsilon_L1_5M',\n",
       " 'Dimuon0_LowMass_L1_0er1p5R',\n",
       " 'Dimuon0_LowMass_L1_0er1p5',\n",
       " 'Dimuon0_LowMass',\n",
       " 'Dimuon0_LowMass_L1_4',\n",
       " 'Dimuon0_LowMass_L1_4R',\n",
       " 'Dimuon0_LowMass_L1_TM530',\n",
       " 'Dimuon0_Upsilon_Muon_L1_TM0',\n",
       " 'Dimuon0_Upsilon_Muon_NoL1Mass',\n",
       " 'TripleMu_10_5_5_DZ',\n",
       " 'TripleMu_12_10_5',\n",
       " 'Tau3Mu_Mu7_Mu1_TkMu1_Tau15',\n",
       " 'Tau3Mu_Mu7_Mu1_TkMu1_Tau15_Charge1',\n",
       " 'Tau3Mu_Mu7_Mu1_TkMu1_IsoTau15',\n",
       " 'Tau3Mu_Mu7_Mu1_TkMu1_IsoTau15_Charge1',\n",
       " 'DoubleMu3_DZ_PFMET50_PFMHT60',\n",
       " 'DoubleMu3_DZ_PFMET70_PFMHT70',\n",
       " 'DoubleMu3_DZ_PFMET90_PFMHT90',\n",
       " 'DoubleMu3_Trk_Tau3mu_NoL1Mass',\n",
       " 'DoubleMu4_Jpsi_Displaced',\n",
       " 'DoubleMu4_Jpsi_NoVertexing',\n",
       " 'DoubleMu4_JpsiTrkTrk_Displaced',\n",
       " 'DoubleMu43NoFiltersNoVtx',\n",
       " 'DoubleMu48NoFiltersNoVtx',\n",
       " 'Mu43NoFiltersNoVtx_Photon43_CaloIdL',\n",
       " 'Mu48NoFiltersNoVtx_Photon48_CaloIdL',\n",
       " 'DoubleMu20_7_Mass0to30_L1_DM4',\n",
       " 'DoubleMu20_7_Mass0to30_L1_DM4EG',\n",
       " 'HT425',\n",
       " 'HT430_DisplacedDijet40_DisplacedTrack',\n",
       " 'HT430_DisplacedDijet60_DisplacedTrack',\n",
       " 'HT430_DisplacedDijet80_DisplacedTrack',\n",
       " 'HT400_DisplacedDijet40_DisplacedTrack',\n",
       " 'HT650_DisplacedDijet60_Inclusive',\n",
       " 'HT550_DisplacedDijet80_Inclusive',\n",
       " 'HT550_DisplacedDijet60_Inclusive',\n",
       " 'HT650_DisplacedDijet80_Inclusive',\n",
       " 'HT750_DisplacedDijet80_Inclusive',\n",
       " 'DiJet110_35_Mjj650_PFMET110',\n",
       " 'DiJet110_35_Mjj650_PFMET120',\n",
       " 'DiJet110_35_Mjj650_PFMET130',\n",
       " 'TripleJet110_35_35_Mjj650_PFMET110',\n",
       " 'TripleJet110_35_35_Mjj650_PFMET120',\n",
       " 'TripleJet110_35_35_Mjj650_PFMET130',\n",
       " 'VBF_DoubleLooseChargedIsoPFTau20_Trk1_eta2p1_Reg',\n",
       " 'VBF_DoubleMediumChargedIsoPFTau20_Trk1_eta2p1_Reg',\n",
       " 'VBF_DoubleTightChargedIsoPFTau20_Trk1_eta2p1_Reg',\n",
       " 'Ele30_eta2p1_WPTight_Gsf_CentralPFJet35_EleCleaned',\n",
       " 'Ele28_eta2p1_WPTight_Gsf_HT150',\n",
       " 'Ele28_HighEta_SC20_Mass55',\n",
       " 'DoubleMu20_7_Mass0to30_Photon23',\n",
       " 'Ele15_IsoVVVL_PFHT450_CaloBTagCSV_4p5',\n",
       " 'Ele15_IsoVVVL_PFHT450_PFMET50',\n",
       " 'Ele15_IsoVVVL_PFHT450',\n",
       " 'Ele50_IsoVVVL_PFHT450',\n",
       " 'Ele15_IsoVVVL_PFHT600',\n",
       " 'Mu8_TrkIsoVVL_DiPFJet40_DEta3p5_MJJ750_HTT300_PFMETNoMu60',\n",
       " 'Mu10_TrkIsoVVL_DiPFJet40_DEta3p5_MJJ750_HTT350_PFMETNoMu60',\n",
       " 'Mu15_IsoVVVL_PFHT450_CaloBTagCSV_4p5',\n",
       " 'Mu15_IsoVVVL_PFHT450_PFMET50',\n",
       " 'Mu15_IsoVVVL_PFHT450',\n",
       " 'Mu50_IsoVVVL_PFHT450',\n",
       " 'Mu15_IsoVVVL_PFHT600',\n",
       " 'Dimuon10_PsiPrime_Barrel_Seagulls',\n",
       " 'Dimuon20_Jpsi_Barrel_Seagulls',\n",
       " 'Dimuon10_Upsilon_Barrel_Seagulls',\n",
       " 'Dimuon12_Upsilon_eta1p5',\n",
       " 'Dimuon14_Phi_Barrel_Seagulls',\n",
       " 'Dimuon18_PsiPrime',\n",
       " 'Dimuon25_Jpsi',\n",
       " 'Dimuon18_PsiPrime_noCorrL1',\n",
       " 'Dimuon24_Upsilon_noCorrL1',\n",
       " 'Dimuon24_Phi_noCorrL1',\n",
       " 'Dimuon25_Jpsi_noCorrL1',\n",
       " 'DiMu9_Ele9_CaloIdL_TrackIdL_DZ',\n",
       " 'DiMu9_Ele9_CaloIdL_TrackIdL',\n",
       " 'DoubleIsoMu20_eta2p1',\n",
       " 'DoubleIsoMu24_eta2p1',\n",
       " 'TrkMu12_DoubleTrkMu5NoFiltersNoVtx',\n",
       " 'TrkMu16_DoubleTrkMu6NoFiltersNoVtx',\n",
       " 'TrkMu17_DoubleTrkMu8NoFiltersNoVtx',\n",
       " 'Mu8',\n",
       " 'Mu17',\n",
       " 'Mu19',\n",
       " 'Mu17_Photon30_IsoCaloId',\n",
       " 'Ele8_CaloIdL_TrackIdL_IsoVL_PFJet30',\n",
       " 'Ele12_CaloIdL_TrackIdL_IsoVL_PFJet30',\n",
       " 'Ele23_CaloIdL_TrackIdL_IsoVL_PFJet30',\n",
       " 'Ele8_CaloIdM_TrackIdM_PFJet30',\n",
       " 'Ele17_CaloIdM_TrackIdM_PFJet30',\n",
       " 'Ele23_CaloIdM_TrackIdM_PFJet30',\n",
       " 'Ele50_CaloIdVT_GsfTrkIdT_PFJet165',\n",
       " 'Ele115_CaloIdVT_GsfTrkIdT',\n",
       " 'Ele135_CaloIdVT_GsfTrkIdT',\n",
       " 'Ele145_CaloIdVT_GsfTrkIdT',\n",
       " 'Ele200_CaloIdVT_GsfTrkIdT',\n",
       " 'Ele250_CaloIdVT_GsfTrkIdT',\n",
       " 'Ele300_CaloIdVT_GsfTrkIdT',\n",
       " 'PFHT300PT30_QuadPFJet_75_60_45_40',\n",
       " 'PFHT300PT30_QuadPFJet_75_60_45_40_TriplePFBTagCSV_3p0',\n",
       " 'PFHT380_SixPFJet32_DoublePFBTagCSV_2p2',\n",
       " 'PFHT380_SixPFJet32_DoublePFBTagDeepCSV_2p2',\n",
       " 'PFHT380_SixPFJet32',\n",
       " 'PFHT430_SixPFJet40_PFBTagCSV_1p5',\n",
       " 'PFHT430_SixPFJet40',\n",
       " 'PFHT350',\n",
       " 'PFHT350MinPFJet15',\n",
       " 'Photon60_R9Id90_CaloIdL_IsoL',\n",
       " 'Photon60_R9Id90_CaloIdL_IsoL_DisplacedIdL',\n",
       " 'Photon60_R9Id90_CaloIdL_IsoL_DisplacedIdL_PFHT350MinPFJet15',\n",
       " 'FullTrack_Multiplicity85',\n",
       " 'FullTrack_Multiplicity100',\n",
       " 'FullTrack_Multiplicity130',\n",
       " 'FullTrack_Multiplicity155',\n",
       " 'ECALHT800',\n",
       " 'DiSC30_18_EIso_AND_HE_Mass70',\n",
       " 'Physics',\n",
       " 'Physics_part0',\n",
       " 'Physics_part1',\n",
       " 'Physics_part2',\n",
       " 'Physics_part3',\n",
       " 'Physics_part4',\n",
       " 'Physics_part5',\n",
       " 'Physics_part6',\n",
       " 'Physics_part7',\n",
       " 'Random',\n",
       " 'ZeroBias',\n",
       " 'ZeroBias_part0',\n",
       " 'ZeroBias_part1',\n",
       " 'ZeroBias_part2',\n",
       " 'ZeroBias_part3',\n",
       " 'ZeroBias_part4',\n",
       " 'ZeroBias_part5',\n",
       " 'ZeroBias_part6',\n",
       " 'ZeroBias_part7',\n",
       " 'AK4CaloJet30',\n",
       " 'AK4CaloJet40',\n",
       " 'AK4CaloJet50',\n",
       " 'AK4CaloJet80',\n",
       " 'AK4CaloJet100',\n",
       " 'AK4CaloJet120',\n",
       " 'AK4PFJet30',\n",
       " 'AK4PFJet50',\n",
       " 'AK4PFJet80',\n",
       " 'AK4PFJet100',\n",
       " 'AK4PFJet120',\n",
       " 'HISinglePhoton10_Eta3p1ForPPRef',\n",
       " 'HISinglePhoton20_Eta3p1ForPPRef',\n",
       " 'HISinglePhoton30_Eta3p1ForPPRef',\n",
       " 'HISinglePhoton40_Eta3p1ForPPRef',\n",
       " 'HISinglePhoton50_Eta3p1ForPPRef',\n",
       " 'HISinglePhoton60_Eta3p1ForPPRef',\n",
       " 'Photon20_HoverELoose',\n",
       " 'Photon30_HoverELoose',\n",
       " 'Photon40_HoverELoose',\n",
       " 'Photon50_HoverELoose',\n",
       " 'Photon60_HoverELoose',\n",
       " 'EcalCalibration',\n",
       " 'HcalCalibration',\n",
       " 'L1UnpairedBunchBptxMinus',\n",
       " 'L1UnpairedBunchBptxPlus',\n",
       " 'L1NotBptxOR',\n",
       " 'L1MinimumBiasHF_OR',\n",
       " 'L1MinimumBiasHF0OR',\n",
       " 'L1_CDC_SingleMu_3_er1p2_TOP120_DPHI2p618_3p142',\n",
       " 'HcalNZS',\n",
       " 'HcalPhiSym',\n",
       " 'HcalIsolatedbunch',\n",
       " 'IsoTrackHB',\n",
       " 'IsoTrackHE',\n",
       " 'ZeroBias_FirstCollisionAfterAbortGap',\n",
       " 'ZeroBias_IsolatedBunches',\n",
       " 'ZeroBias_FirstCollisionInTrain',\n",
       " 'ZeroBias_LastCollisionInTrain',\n",
       " 'ZeroBias_FirstBXAfterTrain',\n",
       " 'Ele24_eta2p1_WPTight_Gsf_LooseChargedIsoPFTau30_eta2p1_CrossL1',\n",
       " 'Ele24_eta2p1_WPTight_Gsf_MediumChargedIsoPFTau30_eta2p1_CrossL1',\n",
       " 'Ele24_eta2p1_WPTight_Gsf_TightChargedIsoPFTau30_eta2p1_CrossL1',\n",
       " 'Ele24_eta2p1_WPTight_Gsf_LooseChargedIsoPFTau30_eta2p1_TightID_CrossL1',\n",
       " 'Ele24_eta2p1_WPTight_Gsf_MediumChargedIsoPFTau30_eta2p1_TightID_CrossL1',\n",
       " 'Ele24_eta2p1_WPTight_Gsf_TightChargedIsoPFTau30_eta2p1_TightID_CrossL1',\n",
       " 'DoubleLooseChargedIsoPFTau35_Trk1_eta2p1_Reg',\n",
       " 'DoubleLooseChargedIsoPFTau40_Trk1_eta2p1_Reg',\n",
       " 'DoubleMediumChargedIsoPFTau35_Trk1_eta2p1_Reg',\n",
       " 'DoubleMediumChargedIsoPFTau40_Trk1_eta2p1_Reg',\n",
       " 'DoubleTightChargedIsoPFTau35_Trk1_eta2p1_Reg',\n",
       " 'DoubleTightChargedIsoPFTau40_Trk1_eta2p1_Reg',\n",
       " 'DoubleLooseChargedIsoPFTau35_Trk1_TightID_eta2p1_Reg',\n",
       " 'DoubleLooseChargedIsoPFTau40_Trk1_TightID_eta2p1_Reg',\n",
       " 'DoubleMediumChargedIsoPFTau35_Trk1_TightID_eta2p1_Reg',\n",
       " 'DoubleMediumChargedIsoPFTau40_Trk1_TightID_eta2p1_Reg',\n",
       " 'DoubleTightChargedIsoPFTau35_Trk1_TightID_eta2p1_Reg',\n",
       " 'DoubleTightChargedIsoPFTau40_Trk1_TightID_eta2p1_Reg',\n",
       " 'IsoMu24_eta2p1_MediumChargedIsoPFTau50_Trk30_eta2p1_1pr',\n",
       " 'MediumChargedIsoPFTau50_Trk30_eta2p1_1pr_MET90',\n",
       " 'MediumChargedIsoPFTau50_Trk30_eta2p1_1pr_MET100',\n",
       " 'MediumChargedIsoPFTau50_Trk30_eta2p1_1pr_MET110',\n",
       " 'MediumChargedIsoPFTau50_Trk30_eta2p1_1pr_MET120',\n",
       " 'MediumChargedIsoPFTau50_Trk30_eta2p1_1pr_MET130',\n",
       " 'MediumChargedIsoPFTau50_Trk30_eta2p1_1pr',\n",
       " 'MediumChargedIsoPFTau180HighPtRelaxedIso_Trk50_eta2p1_1pr',\n",
       " 'MediumChargedIsoPFTau180HighPtRelaxedIso_Trk50_eta2p1',\n",
       " 'IsoMu24_eta2p1_LooseChargedIsoPFTau35_Trk1_eta2p1_Reg_CrossL1',\n",
       " 'IsoMu24_eta2p1_LooseChargedIsoPFTau35_Trk1_TightID_eta2p1_Reg_CrossL1',\n",
       " 'IsoMu24_eta2p1_MediumChargedIsoPFTau35_Trk1_eta2p1_Reg_CrossL1',\n",
       " 'IsoMu24_eta2p1_MediumChargedIsoPFTau35_Trk1_TightID_eta2p1_Reg_CrossL1',\n",
       " 'IsoMu24_eta2p1_TightChargedIsoPFTau35_Trk1_eta2p1_Reg_CrossL1',\n",
       " 'IsoMu24_eta2p1_TightChargedIsoPFTau35_Trk1_TightID_eta2p1_Reg_CrossL1',\n",
       " 'IsoMu24_eta2p1_MediumChargedIsoPFTau40_Trk1_eta2p1_Reg_CrossL1',\n",
       " 'IsoMu24_eta2p1_MediumChargedIsoPFTau40_Trk1_TightID_eta2p1_Reg_CrossL1',\n",
       " 'IsoMu24_eta2p1_TightChargedIsoPFTau40_Trk1_eta2p1_Reg_CrossL1',\n",
       " 'IsoMu24_eta2p1_TightChargedIsoPFTau40_Trk1_TightID_eta2p1_Reg_CrossL1',\n",
       " 'Ele16_Ele12_Ele8_CaloIdL_TrackIdL',\n",
       " 'Rsq0p35',\n",
       " 'Rsq0p40',\n",
       " 'RsqMR300_Rsq0p09_MR200',\n",
       " 'RsqMR320_Rsq0p09_MR200',\n",
       " 'RsqMR300_Rsq0p09_MR200_4jet',\n",
       " 'RsqMR320_Rsq0p09_MR200_4jet']"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "events.HLT.fields"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c52a4360",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ele32_WPTight_Gsf\n",
      "Ele32_WPTight_Gsf_L1DoubleEG\n"
     ]
    }
   ],
   "source": [
    "for field in events.HLT.fields :\n",
    "    if field.startswith(\"Ele32\") :\n",
    "        print(field)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a8393f74",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total events :  297347\n",
      "No. of events after PFMETNoMu120_PFMHTNoMu120_IDTight :  549\n",
      "No. of events after  Ele32_WPTight_Gsf:  98961\n"
     ]
    }
   ],
   "source": [
    "print(\"Total events : \", len(events))\n",
    "print(\"No. of events after PFMETNoMu120_PFMHTNoMu120_IDTight : \" , len(events[events.HLT.PFMETNoMu120_PFMHTNoMu120_IDTight]))\n",
    "print(\"No. of events after  Ele32_WPTight_Gsf: \" , len(events[~events.HLT.Ele32_WPTight_Gsf]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e2bb92d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "from monoHbbtools.Utilities import condor"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}