{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import glob\n",
    "import os\n",
    "import numpy as np\n",
    "import numba as nb\n",
    "import awkward as ak\n",
    "import matplotlib.pyplot as plt\n",
    "import uproot\n",
    "from uproot_methods import TLorentzVectorArray\n",
    "from coffea import hist\n",
    "from coffea.analysis_objects import JaggedCandidateArray\n",
    "from cycler import cycler\n",
    "import coffea.processor as processor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
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   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from itertools import combinations\n",
    "\n",
    "# This is a helper function which adds muon (0) and electron (1) identifiers to a stacked lepton JaggedArray.\n",
    "def make_labeled_p4(x, indices, itype):\n",
    "    p4 = TLorentzVectorArray.from_ptetaphim(x.pt, x.eta, x.phi, x.mass)\n",
    "    return ak.JaggedArray.zip(p4=p4,\n",
    "                              ptype=itype*x.pt.ones_like().astype(np.int),\n",
    "                              pidx=indices,\n",
    "                              charge=x.charge)\n",
    "\n",
    "# This generates a stacked lepton JaggedArray, allowing combination of both muons and electrons for computations across flavor.\n",
    "def stack_leptons(muons, electrons):\n",
    "    # Construct new lepton indices within every event array.\n",
    "    muons_indices = ak.JaggedArray.fromoffsets(muons.pt.offsets, \n",
    "                                             np.arange(0, muons.pt.content.size)) - muons.pt.offsets[:-1]\n",
    "    electrons_indices = ak.JaggedArray.fromoffsets(electrons.pt.offsets, \n",
    "                                             np.arange(0, electrons.pt.content.size)) - electrons.pt.offsets[:-1]\n",
    "    # Assign 0/1 value depending on whether lepton is muon/electron.\n",
    "    muons_p4 = make_labeled_p4(muons, muons_indices, 0)\n",
    "    electrons_p4 = make_labeled_p4(electrons, electrons_indices, 1)\n",
    "    # Concatenate leptons.\n",
    "    stacked_p4 = ak.concatenate((muons_p4, electrons_p4), axis=1)\n",
    "    \n",
    "    return stacked_p4\n",
    "\n",
    "# Helper function which takes a pair, tells you if it is an OSSF with |m_ll - m_z| < 15. Reject these events.\n",
    "def ossf_zmass_check(dileptons):\n",
    "    return ((dileptons.i0.charge != dileptons.i1.charge) & \n",
    "            (np.abs(91.18 - (dileptons.i0 + dileptons.i1).mass) < 15.)).any()\n",
    "\n",
    "# This is a helper function which adds up the transverse momentum of two leptons from their x and y components.\n",
    "@nb.njit()\n",
    "def ptAddition(l1_px, l1_py, l2_px, l2_py):\n",
    "    return np.sqrt((l1_px + l2_px)**2 + (l1_py + l2_py)**2)\n",
    "\n",
    "# This takes as input values from the trilepton channel and outputs an array with del(phi) between the two highest sslps.\n",
    "def channel_dphi_ssp(e_starts, e_stops, mu_starts, mu_stops,\n",
    "                     e_px, e_py, e_phi, mu_px, mu_py, mu_phi, \n",
    "                     e_charge, mu_charge):\n",
    "    dphi = np.zeros(e_starts.size)\n",
    "    dphi.fill(-np.inf)\n",
    "    for e_start, e_stop, mu_start, mu_stop, i in zip(e_starts, e_stops, mu_starts, mu_stops, range(0, e_starts.size)):\n",
    "        event_px = np.concatenate((e_px[e_start:e_stop], mu_px[mu_start:mu_stop]))\n",
    "        event_py = np.concatenate((e_py[e_start:e_stop], mu_py[mu_start:mu_stop]))\n",
    "        event_phi = np.concatenate((e_phi[e_start:e_stop], mu_phi[mu_start:mu_stop]))\n",
    "        event_charge = np.concatenate((e_charge[e_start:e_stop], mu_charge[mu_start:mu_stop]))\n",
    "        maxpt = -np.inf\n",
    "        pair = (None, None)\n",
    "        for combination in np.array(list(combinations(np.argsort(event_px), 2))):\n",
    "            if (np.abs(event_charge[combination[0]] + event_charge[combination[1]]) == 2):\n",
    "                pair_pt = ptAddition(event_px[combination[0]], event_py[combination[0]], event_px[combination[1]], event_px[combination[1]])\n",
    "                if pair_pt > maxpt:\n",
    "                    maxpt = pair_pt\n",
    "                    pair = (combination[0], combination[1])\n",
    "        if pair != (None, None):\n",
    "            dphi[i] = np.abs(event_phi[pair[0]] - event_phi[pair[1]])\n",
    "    return dphi[np.invert(np.isinf(dphi))]\n",
    "\n",
    "# This take as input values from  a cross-lepton channel and outputs the eta difference of the closest leptons (in eta) to each event's most forward jet.\n",
    "def channel_fwdeta_jetlep(e_starts, e_stops, mu_starts, mu_stops,\n",
    "                          jet_maxeta, e_eta, mu_eta):\n",
    "    deta = np.zeros(e_starts.size)\n",
    "    deta.fill(-np.inf)\n",
    "    for e_start, e_stop, mu_start, mu_stop, i in zip(e_starts, e_stops, mu_starts, mu_stops, range(0, e_starts.size)):\n",
    "        jet = jet_maxeta[i]\n",
    "        event_eta = np.concatenate((e_eta[e_start:e_stop], mu_eta[mu_start:mu_stop]))\n",
    "        deta[i] = np.min(np.abs(jet - event_eta))\n",
    "    return deta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "class SignalProcessor(processor.ProcessorABC):\n",
    "    def __init__(self):\n",
    "        dataset_axis = hist.Cat(\"dataset\", \"\")\n",
    "        lll_3rdLepton_pT_axis = hist.Bin(\"lll_3rdLepton_pT\", \"3rd Lepton $p_T$ [GeV]\", 18, 0, 90)\n",
    "        lll_fwdJet_leadbJet_axis = hist.Bin(\"lll_fwdJet_leadbJet\", \"$\\Delta \\eta$ max fwd jet and leading bjet\", 18, 0, 6)\n",
    "        lll_fwdJet_subleadbJet_axis = hist.Bin(\"lll_fwdJet_subleadbJet\", \"$\\Delta \\eta$ max fwd jet and sub-leading bjet\", 18, 0, 6)\n",
    "        lll_fwdJet_closestLepton_axis = hist.Bin(\"lll_fwdJet_closestLepton\", \"$\\Delta \\eta$ max fwd jet and closest lepton\", 18, 0, 6)\n",
    "        lll_highpT_sslp_axis = hist.Bin(\"lll_highpT_sslp\", \"$\\Delta \\Phi$ highest $p_T$ same-sign lepton pair\", 18, 0, 3.5)\n",
    "        lll_jetMaxEta_axis = hist.Bin(\"lll_jetMaxEta\", \"max jet $|\\eta|$ ($p_T$ > 25)\", 18, 0, 5)\n",
    "        lll_minDelR_axis = hist.Bin(\"lll_minDelR\", \"Minimum $\\Delta$ R between any two leptons\", 18, 0, 4)\n",
    "        lll_NJetMedium_axis = hist.Bin(\"lll_NJetMED\", \"N(jet, $p_T$ > 25, $|\\eta|$ < 2.4)\", 6, 2, 8)\n",
    "        lll_NJetNonCSVMedium_axis = hist.Bin(\"lll_NJetNONMED\", \"N(jet, $|\\eta|$ > 1) non CSV medium\", 7, 1, 8)        \n",
    "        lll_TotalCharge_axis = hist.Bin(\"lll_TotalCharge\", \"Total Lepton Charge\", 5, -2, 3)\n",
    "        \n",
    "        mumu_subleadLepton_pT_axis = hist.Bin(\"mumu_subleadLepton_pT\", \"Sub-leading Lepton $p_T$ [GeV]\", 18, 0, 144)\n",
    "        mumu_fwdJet_leadbJet_axis = hist.Bin(\"mumu_fwdJet_leadbJet\", \"$\\Delta \\eta$ max fwd jet and leading bjet\", 18, 0, 6)\n",
    "        mumu_fwdJet_subleadbJet_axis = hist.Bin(\"mumu_fwdJet_subleadbJet\", \"$\\Delta \\eta$ max fwd jet and sub-leading bjet\", 18, 0, 6)\n",
    "        mumu_fwdJet_closestLepton_axis = hist.Bin(\"mumu_fwdJet_closestLepton\", \"$\\Delta \\eta$ max fwd jet and closest lepton\", 18, 0, 6)\n",
    "        mumu_highpT_sslp_axis = hist.Bin(\"mumu_highpT_sslp\", \"$\\Delta \\Phi$ highest $p_T$ same-sign lepton pair\", 18, 0, 3.5)\n",
    "        mumu_jetMaxEta_axis = hist.Bin(\"mumu_jetMaxEta\", \"max jet $|\\eta|$ ($p_T$ > 40)\", 18, 0, 5)\n",
    "        mumu_minDelR_axis = hist.Bin(\"mumu_minDelR\", \"Minimum $\\Delta$ R between any two leptons\", 18, 0, 4)\n",
    "        mumu_NJetMedium_axis = hist.Bin(\"mumu_NJetMED\", \"N(jet, $p_T$ > 25, $|\\eta|$ < 2.4)\", 6, 2, 8)\n",
    "        mumu_NJetNonCSVMedium_axis = hist.Bin(\"mumu_NJetNONMED\", \"N(jet, $|\\eta|$ > 1) non CSV medium\", 7, 1, 8)        \n",
    "        mumu_TotalCharge_axis = hist.Bin(\"mumu_TotalCharge\", \"Total Lepton Charge\", 5, -2, 3)\n",
    "        \n",
    "        emu_subleadLepton_pT_axis = hist.Bin(\"emu_subleadLepton_pT\", \"Sub-leading Lepton $p_T$ [GeV]\", 18, 0, 144)\n",
    "        emu_fwdJet_leadbJet_axis = hist.Bin(\"emu_fwdJet_leadbJet\", \"$\\Delta \\eta$ max fwd jet and leading bjet\", 18, 0, 6)\n",
    "        emu_fwdJet_subleadbJet_axis = hist.Bin(\"emu_fwdJet_subleadbJet\", \"$\\Delta \\eta$ max fwd jet and sub-leading bjet\", 18, 0, 6)\n",
    "        emu_fwdJet_closestLepton_axis = hist.Bin(\"emu_fwdJet_closestLepton\", \"$\\Delta \\eta$ max fwd jet and closest lepton\", 18, 0, 6)\n",
    "        emu_highpT_sslp_axis = hist.Bin(\"emu_highpT_sslp\", \"$\\Delta \\Phi$ highest $p_T$ same-sign lepton pair\", 18, 0, 3.5)\n",
    "        emu_jetMaxEta_axis = hist.Bin(\"emu_jetMaxEta\", \"max jet $|\\eta|$ ($p_T$ > 40)\", 18, 0, 5)\n",
    "        emu_minDelR_axis = hist.Bin(\"emu_minDelR\", \"Minimum $\\Delta$ R between any two leptons\", 18, 0, 4)\n",
    "        emu_NJetMedium_axis = hist.Bin(\"emu_NJetMED\", \"N(jet, $p_T$ > 25, $|\\eta|$ < 2.4)\", 6, 2, 8)\n",
    "        emu_NJetNonCSVMedium_axis = hist.Bin(\"emu_NJetNONMED\", \"N(jet, $|\\eta|$ > 1) non CSV medium\", 7, 1, 8)        \n",
    "        emu_TotalCharge_axis = hist.Bin(\"emu_TotalCharge\", \"Total Lepton Charge\", 5, -2, 3)\n",
    "        \n",
    "        ee_subleadLepton_pT_axis = hist.Bin(\"ee_subleadLepton_pT\", \"Sub-leading Lepton $p_T$ [GeV]\", 18, 0, 144)\n",
    "        ee_fwdJet_leadbJet_axis = hist.Bin(\"ee_fwdJet_leadbJet\", \"$\\Delta \\eta$ max fwd jet and leading bjet\", 18, 0, 6)\n",
    "        ee_fwdJet_subleadbJet_axis = hist.Bin(\"ee_fwdJet_subleadbJet\", \"$\\Delta \\eta$ max fwd jet and sub-leading bjet\", 18, 0, 6)\n",
    "        ee_fwdJet_closestLepton_axis = hist.Bin(\"ee_fwdJet_closestLepton\", \"$\\Delta \\eta$ max fwd jet and closest lepton\", 18, 0, 6)\n",
    "        ee_highpT_sslp_axis = hist.Bin(\"ee_highpT_sslp\", \"$\\Delta \\Phi$ highest $p_T$ same-sign lepton pair\", 18, 0, 3.5)\n",
    "        ee_jetMaxEta_axis = hist.Bin(\"ee_jetMaxEta\", \"max jet $|\\eta|$ ($p_T$ > 40)\", 18, 0, 5)\n",
    "        ee_minDelR_axis = hist.Bin(\"ee_minDelR\", \"Minimum $\\Delta$ R between any two leptons\", 18, 0, 4)\n",
    "        ee_NJetMedium_axis = hist.Bin(\"ee_NJetMED\", \"N(jet, $p_T$ > 25, $|\\eta|$ < 2.4)\", 6, 2, 8)\n",
    "        ee_NJetNonCSVMedium_axis = hist.Bin(\"ee_NJetNONMED\", \"N(jet, $|\\eta|$ > 1) non CSV medium\", 7, 1, 8)        \n",
    "        ee_TotalCharge_axis = hist.Bin(\"ee_TotalCharge\", \"Total Lepton Charge\", 5, -2, 3)\n",
    "        \n",
    "        self._accumulator = processor.dict_accumulator({\n",
    "            'lll_3rdLepton_pT': hist.Hist(\"Events\", dataset_axis, lll_3rdLepton_pT_axis),\n",
    "            'lll_fwdJet_leadbJet': hist.Hist(\"Events\", dataset_axis, lll_fwdJet_leadbJet_axis),\n",
    "            'lll_fwdJet_subleadbJet': hist.Hist(\"Events\", dataset_axis, lll_fwdJet_subleadbJet_axis),\n",
    "            'lll_fwdJet_closestLepton': hist.Hist(\"Events\", dataset_axis, lll_fwdJet_closestLepton_axis),\n",
    "            'lll_highpT_sslp': hist.Hist(\"Events\", dataset_axis, lll_highpT_sslp_axis),\n",
    "            'lll_jetMaxEta': hist.Hist(\"Events\", dataset_axis, lll_jetMaxEta_axis),\n",
    "            'lll_minDelR': hist.Hist(\"Events\", dataset_axis, lll_minDelR_axis),\n",
    "            'lll_NJetMED': hist.Hist(\"Events\", dataset_axis, lll_NJetMedium_axis),\n",
    "            'lll_NJetNONMED': hist.Hist(\"Events\", dataset_axis, lll_NJetNonCSVMedium_axis),\n",
    "            'lll_TotalCharge': hist.Hist(\"Events\", dataset_axis, lll_TotalCharge_axis),\n",
    "            'mumu_subleadLepton_pT': hist.Hist(\"Events\", dataset_axis, mumu_subleadLepton_pT_axis),\n",
    "            'mumu_fwdJet_leadbJet': hist.Hist(\"Events\", dataset_axis, mumu_fwdJet_leadbJet_axis),\n",
    "            'mumu_fwdJet_subleadbJet': hist.Hist(\"Events\", dataset_axis, mumu_fwdJet_subleadbJet_axis),\n",
    "            'mumu_fwdJet_closestLepton': hist.Hist(\"Events\", dataset_axis, mumu_fwdJet_closestLepton_axis),\n",
    "            'mumu_highpT_sslp': hist.Hist(\"Events\", dataset_axis, mumu_highpT_sslp_axis),\n",
    "            'mumu_jetMaxEta': hist.Hist(\"Events\", dataset_axis, mumu_jetMaxEta_axis),\n",
    "            'mumu_minDelR': hist.Hist(\"Events\", dataset_axis, mumu_minDelR_axis),\n",
    "            'mumu_NJetMED': hist.Hist(\"Events\", dataset_axis, mumu_NJetMedium_axis),\n",
    "            'mumu_NJetNONMED': hist.Hist(\"Events\", dataset_axis, mumu_NJetNonCSVMedium_axis),\n",
    "            'mumu_TotalCharge': hist.Hist(\"Events\", dataset_axis, mumu_TotalCharge_axis),\n",
    "            'emu_subleadLepton_pT': hist.Hist(\"Events\", dataset_axis, emu_subleadLepton_pT_axis),\n",
    "            'emu_fwdJet_leadbJet': hist.Hist(\"Events\", dataset_axis, emu_fwdJet_leadbJet_axis),\n",
    "            'emu_fwdJet_subleadbJet': hist.Hist(\"Events\", dataset_axis, emu_fwdJet_subleadbJet_axis),\n",
    "            'emu_fwdJet_closestLepton': hist.Hist(\"Events\", dataset_axis, emu_fwdJet_closestLepton_axis),\n",
    "            'emu_highpT_sslp': hist.Hist(\"Events\", dataset_axis, emu_highpT_sslp_axis),\n",
    "            'emu_jetMaxEta': hist.Hist(\"Events\", dataset_axis, emu_jetMaxEta_axis),\n",
    "            'emu_minDelR': hist.Hist(\"Events\", dataset_axis, emu_minDelR_axis),\n",
    "            'emu_NJetMED': hist.Hist(\"Events\", dataset_axis, emu_NJetMedium_axis),\n",
    "            'emu_NJetNONMED': hist.Hist(\"Events\", dataset_axis, emu_NJetNonCSVMedium_axis),\n",
    "            'emu_TotalCharge': hist.Hist(\"Events\", dataset_axis, emu_TotalCharge_axis),\n",
    "            'ee_subleadLepton_pT': hist.Hist(\"Events\", dataset_axis, ee_subleadLepton_pT_axis),\n",
    "            'ee_fwdJet_leadbJet': hist.Hist(\"Events\", dataset_axis, ee_fwdJet_leadbJet_axis),\n",
    "            'ee_fwdJet_subleadbJet': hist.Hist(\"Events\", dataset_axis, ee_fwdJet_subleadbJet_axis),\n",
    "            'ee_fwdJet_closestLepton': hist.Hist(\"Events\", dataset_axis, ee_fwdJet_closestLepton_axis),\n",
    "            'ee_highpT_sslp': hist.Hist(\"Events\", dataset_axis, ee_highpT_sslp_axis),\n",
    "            'ee_jetMaxEta': hist.Hist(\"Events\", dataset_axis, ee_jetMaxEta_axis),\n",
    "            'ee_minDelR': hist.Hist(\"Events\", dataset_axis, ee_minDelR_axis),\n",
    "            'ee_NJetMED': hist.Hist(\"Events\", dataset_axis, ee_NJetMedium_axis),\n",
    "            'ee_NJetNONMED': hist.Hist(\"Events\", dataset_axis, ee_NJetNonCSVMedium_axis),\n",
    "            'ee_TotalCharge': hist.Hist(\"Events\", dataset_axis, ee_TotalCharge_axis),\n",
    "            'cutflow': processor.defaultdict_accumulator(int)\n",
    "        })\n",
    "    \n",
    "    @property\n",
    "    def accumulator(self):\n",
    "        return self._accumulator\n",
    "    \n",
    "    def process(self, events):\n",
    "        output = self.accumulator.identity()\n",
    "        \n",
    "        # btag working point numbers, for easy reference.\n",
    "        loose_wp = 0.5425\n",
    "        medium_wp = 0.8484\n",
    "\n",
    "        # Initialize relevant event columns.\n",
    "        dataset = events.metadata[\"dataset\"]\n",
    "        jets = events.Jet\n",
    "        muons = events.Muon\n",
    "        electrons = events.Electron\n",
    "\n",
    "        # This is bookkeeping that tracks how many total events there are.\n",
    "        output['cutflow']['all events'] += events.size\n",
    "        \n",
    "        \n",
    "        \n",
    "        # # # # # # # # # # #\n",
    "        # LEPTON SELECTIONS #\n",
    "        # # # # # # # # # # #\n",
    "        \n",
    "        # Don't want any jets below 25 pT. Remove them now instead of later.\n",
    "        jets = jets[(jets.pt > 25)]\n",
    "        \n",
    "        # Here we establish the loose muons array, based on provided cuts.\n",
    "        loose_muons = muons[(np.abs(muons.eta) < 2.4) &\n",
    "                      (np.abs(muons.dxy) < 0.05) & \n",
    "                      (np.abs(muons.dz) < 0.1) & \n",
    "                      (muons.sip3d < 8) &\n",
    "                      (muons.miniPFRelIso_all < 0.4) &\n",
    "                      (muons.looseId) &\n",
    "                      (muons.pt > 5)]\n",
    "        \n",
    "        # Tight is loose with additional cuts; build tight array and add cuts.\n",
    "        tight_muons = loose_muons[(loose_muons.tightCharge > 0) &\n",
    "                                  (loose_muons.mediumId) &\n",
    "                                  (loose_muons.mvaTTH > 0.9)]\n",
    "\n",
    "        # This ends up getting referenced a lot. Let's not generate it every time!\n",
    "        abs_eta = np.abs(electrons.eta)\n",
    "        \n",
    "        # Here we establish the loose electrons array, based on provided cuts.\n",
    "        loose_electrons = electrons[(abs_eta < 2.5) & \n",
    "                              (np.abs(electrons.dxy) < 0.05) & \n",
    "                              (np.abs(electrons.dz) < 0.1) & \n",
    "                              (electrons.lostHits < 2) &\n",
    "                              (electrons.miniPFRelIso_all < 0.4) &\n",
    "                              (electrons.pt > 7) &\n",
    "                              (((electrons.mvaFall17V2noIso > 0) & (abs_eta < 1.479)) | ((electrons.mvaFall17V2noIso > 0.7) & (abs_eta > 1.479) & (abs_eta < 2.5)))]\n",
    "            \n",
    "        # Now we build tight from loose, adding in tight's extra cuts.\n",
    "        # Redefine abs_eta since we're now using loose.\n",
    "        abs_eta = np.abs(loose_electrons.eta)\n",
    "        \n",
    "        tight_electrons = loose_electrons[(loose_electrons.pt > 15) &\n",
    "                                         (loose_electrons.lostHits == 0) &\n",
    "                                         (loose_electrons.tightCharge > 0) &\n",
    "                                         (loose_electrons.convVeto) &\n",
    "                                         (loose_electrons.mvaTTH > 0.90) &\n",
    "                                         # Two ranges for sigma_ieie.\n",
    "                                         (((abs_eta < 1.479) & (loose_electrons.sieie < 0.011)) | \n",
    "                                         ((abs_eta < 2.5) & (abs_eta > 1.479) & (loose_electrons.sieie < 0.03))) &\n",
    "                                         # Two ranges for H/E\n",
    "                                         (((abs_eta < 1.479) & (loose_electrons.hoe < 0.1)) | \n",
    "                                         ((abs_eta < 2.5) & (abs_eta > 1.479) & (loose_electrons.hoe < 0.07))) &\n",
    "                                         # Two ranges for 1/E - 1/p\n",
    "                                         (((abs_eta < 1.479) & (loose_electrons.eInvMinusPInv < 0.01) & (loose_electrons.eInvMinusPInv > -0.05)) |\n",
    "                                         ((abs_eta < 2.5) & (abs_eta > 1.479) & (loose_electrons.eInvMinusPInv < 0.005) & (loose_electrons.eInvMinusPInv > -0.05)))]        \n",
    "        \n",
    "        \n",
    "\n",
    "        # # # # # # # # # #\n",
    "        # EVENT SELECTION #\n",
    "        # # # # # # # # # #\n",
    "        \n",
    "        # Loose pre-selection. See definition of stack_leptons above to see how we construct arrays across leptons.\n",
    "        loose_leptons = stack_leptons(loose_muons, loose_electrons)\n",
    "        loose_pairs = loose_leptons.argchoose(2)\n",
    "        loose_pairs_mass = (loose_leptons[loose_pairs.i0].p4 + loose_leptons[loose_pairs.i1].p4).mass\n",
    "        looseMask = ((loose_pairs_mass >= 12).all() & (loose_pairs_mass.counts > 0))\n",
    "        \n",
    "        # Dilepton selection.\n",
    "        tight_leptons = stack_leptons(tight_muons, tight_electrons)\n",
    "        tight_pairs = tight_leptons.argchoose(2)\n",
    "        # Add types to see what kind of pair we have. mu = 0, e = 1, so: mumu = 0, emu = 1, ee = 2.\n",
    "        tight_types = (tight_leptons[tight_pairs.i0].ptype + tight_leptons[tight_pairs.i1].ptype)\n",
    "        \n",
    "        # Respectively; each event should have exactly 1 pair (2 leptons) with same charge\n",
    "        #               one should have pT > 25 (pT > 15 is guaranteed by lepton selection)\n",
    "        #               for ee events, check that mass from Z is < 10 to veto possible Z bosons.\n",
    "        dileptonMask = ((tight_pairs.counts == 1) &\n",
    "                        (tight_leptons[tight_pairs.i0].charge == tight_leptons[tight_pairs.i1].charge).any() &\n",
    "                        ((tight_leptons[tight_pairs.i0].p4.pt > 25) | (tight_leptons[tight_pairs.i1].p4.pt > 25)).any() &\n",
    "                        ((tight_types < 2) | (np.abs((tight_leptons[tight_pairs.i0].p4 + tight_leptons[tight_pairs.i1].p4).mass - 91.18) > 10)).any())\n",
    "        \n",
    "        # Trilepton selection.\n",
    "        tight_triples = tight_leptons.argchoose(3)\n",
    "        tight_muon_pairs = tight_muons.choose(2)\n",
    "        tight_electron_pairs = tight_electrons.choose(2)\n",
    "        \n",
    "        # Respectively; we want events with exactly three tight leptons (one triple),\n",
    "        #               one should have pT > 25, discard if OSSF dileptons are close to the Z mass.\n",
    "        trileptonMask = ((tight_triples.counts == 1) &\n",
    "                        ((tight_leptons[tight_triples.i0].p4.pt > 25) | (tight_leptons[tight_triples.i1].p4.pt > 25) | (tight_leptons[tight_triples.i2].p4.pt > 25)).any() &\n",
    "                        (~ossf_zmass_check(tight_muon_pairs)) & (~ossf_zmass_check(tight_electron_pairs)))\n",
    "        \n",
    "        # Jet masks can be generated much more simply, since we're staying in one collection.\n",
    "        jetMask_medium = ((np.abs(jets.eta) < 2.4) & (jets.btagCSVV2 > medium_wp)).sum() >= 1\n",
    "        jetMask_loose = (((np.abs(jets.eta) < 2.4) | ((jets.pt > 40) & (np.abs(jets.eta) > 2.4))) & (jets.btagCSVV2 <= loose_wp)).sum() >= 1\n",
    "        \n",
    "        # May as well combine all of our masks into one (well, two) big one(s) for easier referencing.\n",
    "        # Split dileptons and trileptons into separate channels, because it's easier to work with later.\n",
    "        dilepton_eventMask = (looseMask) & (dileptonMask) & (jetMask_medium) & (jetMask_loose)\n",
    "        trilepton_eventMask = (looseMask) & (trileptonMask) & (jetMask_medium) & (jetMask_loose)\n",
    "        \n",
    "        # Dilepton masks.\n",
    "        tight_ll_e = tight_electrons[dilepton_eventMask].compact()\n",
    "        tight_ll_mu = tight_muons[dilepton_eventMask].compact()\n",
    "        \n",
    "        # Trilepton masks.\n",
    "        tight_lll_e = tight_electrons[trilepton_eventMask].compact()\n",
    "        tight_lll_mu = tight_muons[trilepton_eventMask].compact()\n",
    "        \n",
    "        # Split dileptons into further channels: ee, mumu, and emu (need two arrays for this one)\n",
    "        tights_2mu = tight_ll_mu[tight_ll_mu.counts == 2]\n",
    "        tights_2e = tight_ll_e[tight_ll_e.counts == 2]\n",
    "        tights_1e = tight_electrons[dilepton_eventMask & tight_electrons.counts == 1]\n",
    "        tights_1mu = tight_muons[dilepton_eventMask & tight_muons.counts == 1]\n",
    "        \n",
    "        # Can't forget to mask our jets after all of that lepton array-building! We want jets that meet either mask requirement.\n",
    "        jets_3lep = jets[trilepton_eventMask]\n",
    "        jets_2mu = jets[dilepton_eventMask & (tight_muons.counts == 2)]\n",
    "        jets_2e = jets[dilepton_eventMask & (tight_electrons.counts == 2)]\n",
    "        jets_emu = jets[dilepton_eventMask & (tight_muons.counts == 1) & (tight_electrons.counts == 1)]\n",
    "        \n",
    "        \n",
    "        \n",
    "        # # # # # #\n",
    "        # OUTPUTS #\n",
    "        # # # # # #\n",
    "        \n",
    "        # Selecting the data that we want.\n",
    "            # Three-lepton channel\n",
    "        lll_ee_pairs = tight_electrons[trilepton_eventMask].distincts()\n",
    "        lll_mumu_pairs = tight_muons[trilepton_eventMask].distincts()\n",
    "        lll_emu_pairs = tight_electrons[trilepton_eventMask].cross(tight_muons[trilepton_eventMask])  \n",
    "        lll_3rdLepton_pT = np.asarray([lll_ee_pairs.i0.pt.min(), lll_ee_pairs.i1.pt.min(),\n",
    "                                       lll_mumu_pairs.i0.pt.min(), lll_mumu_pairs.i1.pt.min(),\n",
    "                                       lll_emu_pairs.i0.pt.min(), lll_emu_pairs.i1.pt.min()]).min(0)\n",
    "        output['cutflow']['passing'] += lll_3rdLepton_pT.size\n",
    "        lll_lightjets = jets_3lep[jets_3lep.btagCSVV2 <= loose_wp]\n",
    "        lll_jetcross = jets_3lep[jets_3lep.btagCSVV2 > loose_wp].cross(lll_lightjets[lll_lightjets.eta == lll_lightjets.eta.max()])\n",
    "        lll_fwdJet_leadbJet = lll_jetcross[lll_jetcross.counts >= 1][:, 0]\n",
    "        lll_fwdJet_leadbJet = np.abs((lll_fwdJet_leadbJet.i0 - lll_fwdJet_leadbJet.i1).eta)\n",
    "        lll_fwdJet_subleadbJet = lll_jetcross[lll_jetcross.counts >= 2][:, 1]\n",
    "        lll_fwdJet_subleadbJet = np.abs((lll_fwdJet_subleadbJet.i0 - lll_fwdJet_subleadbJet.i1).eta)\n",
    "        lll_fwdJet_closestLepton = channel_fwdeta_jetlep(tight_lll_e.starts, tight_lll_e.stops, tight_lll_mu.starts, tight_lll_mu.stops,\n",
    "                                              lll_lightjets.eta.max(), tight_lll_e.eta.content, tight_lll_mu.eta.content)\n",
    "        lll_highpT_sslp = channel_dphi_ssp(tight_lll_e.starts, tight_lll_e.stops, tight_lll_mu.starts, tight_lll_mu.stops,\n",
    "                                        tight_lll_e.x.content, tight_lll_e.y.content, tight_lll_e.phi.content, tight_lll_mu.x.content, tight_lll_mu.y.content, tight_lll_mu.phi.content,\n",
    "                                        tight_lll_e.charge.content, tight_lll_mu.charge.content)\n",
    "        lll_jetMaxEta = np.abs(jets_3lep.eta[jets_3lep.btagCSVV2 <= loose_wp]).max()\n",
    "        lll_minDelR = np.asarray([lll_ee_pairs.i0.delta_r(lll_ee_pairs.i1).min(),\n",
    "                                 lll_mumu_pairs.i0.delta_r(lll_mumu_pairs.i1).min(),\n",
    "                                 lll_emu_pairs.i0.delta_r(lll_emu_pairs.i1).min()]).min(0)\n",
    "        lll_NJetMED = jets_3lep[(np.abs(jets_3lep.eta) < 2.4)].counts\n",
    "        lll_NJetNONMED = jets_3lep[(np.abs(jets_3lep.eta) > 1) & (jets_3lep.btagCSVV2 <= loose_wp)].counts\n",
    "        lll_TotalCharge = tight_lll_e.charge.sum() + tight_lll_mu.charge.sum()\n",
    "            # mu-mu channel\n",
    "        mumu_subleadLepton_pT = tights_2mu.pt[:, 1]\n",
    "        mumu_lightjets = jets_2mu[jets_2mu.btagCSVV2 <= loose_wp]\n",
    "        mumu_jetcross = jets_2mu[jets_2mu.btagCSVV2 > loose_wp].cross(mumu_lightjets[mumu_lightjets.eta == mumu_lightjets.eta.max()])\n",
    "        mumu_fwdJet_leadbJet = mumu_jetcross[mumu_jetcross.counts >= 1][:, 0]\n",
    "        mumu_fwdJet_leadbJet = np.abs((mumu_fwdJet_leadbJet.i0 - mumu_fwdJet_leadbJet.i1).eta)\n",
    "        mumu_fwdJet_subleadbJet = mumu_jetcross[mumu_jetcross.counts >= 2][:, 1]\n",
    "        mumu_fwdJet_subleadbJet = np.abs((mumu_fwdJet_subleadbJet.i0 - mumu_fwdJet_subleadbJet.i1).eta)\n",
    "        mumu_fwdJet_closestLepton = (mumu_lightjets.eta.max() - tights_2mu.eta).min()\n",
    "        mumu_fwdJet_closestLepton = mumu_fwdJet_closestLepton[np.invert(np.isinf(mumu_fwdJet_closestLepton))]\n",
    "        mumu_highpT_sslp = tights_2mu[np.abs(tights_2mu.charge[:, 0] + tights_2mu.charge[:, 1]) == 2]\n",
    "        mumu_highpT_sslp = np.abs(mumu_highpT_sslp.phi[:, 0] - mumu_highpT_sslp.phi[:, 1])\n",
    "        mumu_jetMaxEta = np.abs(jets_2mu.eta[(jets_2mu.btagCSVV2 <= loose_wp) & (jets_2mu.pt > 40)]).max()\n",
    "        mumu_minDelR = tights_2mu[:, 0].delta_r(tights_2mu[:, 1])\n",
    "        mumu_NJetMED = jets_2mu.counts\n",
    "        mumu_NJetNONMED = jets_2mu[(np.abs(jets_2mu.eta) > 1) & (jets_2mu.btagCSVV2 <= loose_wp)].counts\n",
    "        mumu_TotalCharge = tights_2mu.charge.sum()\n",
    "            # e-mu channel\n",
    "        emu_subleadLepton_pT = np.minimum(tights_1e.pt, tights_1mu.pt)\n",
    "        emu_lightjets = jets_emu[jets_emu.btagCSVV2 <= loose_wp]\n",
    "        emu_jetcross = jets_emu[jets_emu.btagCSVV2 > loose_wp].cross(emu_lightjets[emu_lightjets.eta == emu_lightjets.eta.max()])\n",
    "        emu_fwdJet_leadbJet = emu_jetcross[emu_jetcross.counts >= 1][:, 0]\n",
    "        emu_fwdJet_leadbJet = np.abs((emu_fwdJet_leadbJet.i0 - emu_fwdJet_leadbJet.i1).eta)\n",
    "        emu_fwdJet_subleadbJet = emu_jetcross[emu_jetcross.counts >= 2][:, 1]\n",
    "        emu_fwdJet_subleadbJet = np.abs((emu_fwdJet_subleadbJet.i0 - emu_fwdJet_subleadbJet.i1).eta)\n",
    "        mu_fwdJet_closestLepton = (emu_lightjets.eta.max() - tights_1mu.eta)\n",
    "        e_fwdJet_closestLepton = (emu_lightjets.eta.max() - tights_1e.eta)\n",
    "        emu_fwdJet_closestLepton = np.minimum(mu_fwdJet_closestLepton, e_fwdJet_closestLepton)\n",
    "        emu_fwdJet_closestLepton = emu_fwdJet_closestLepton[np.invert(np.isinf(emu_fwdJet_closestLepton))]\n",
    "        mu_highpT_sslp = tights_1mu[np.abs(tights_1mu.charge + tights_1e.charge) == 2]\n",
    "        e_highpT_sslp = tights_1e[np.abs(tights_1mu.charge + tights_1e.charge) == 2]\n",
    "        emu_highpT_sslp = np.abs(mu_highpT_sslp.phi - e_highpT_sslp.phi)\n",
    "        emu_jetMaxEta = np.abs(jets_emu.eta[(jets_emu.btagCSVV2 <= loose_wp) & (jets_emu.pt > 40)]).max()\n",
    "        emu_minDelR = tights_1e.delta_r(tights_1mu)\n",
    "        emu_NJetMED = jets_emu[(np.abs(jets_emu.eta) < 2.4)].counts\n",
    "        emu_NJetNONMED = jets_emu[(np.abs(jets_emu.eta) > 1) & (jets_emu.btagCSVV2 <= loose_wp)].counts\n",
    "        emu_TotalCharge = tights_1mu.charge + tights_1e.charge\n",
    "        # e-e channel\n",
    "        ee_subleadLepton_pT = tights_2e.pt[:, 1]\n",
    "        ee_lightjets = jets_2e[jets_2e.btagCSVV2 <= loose_wp]\n",
    "        ee_jetcross = jets_2e[jets_2e.btagCSVV2 > loose_wp].cross(ee_lightjets[ee_lightjets.eta == ee_lightjets.eta.max()])\n",
    "        ee_fwdJet_leadbJet = ee_jetcross[ee_jetcross.counts >= 1][:, 0]\n",
    "        ee_fwdJet_leadbJet = np.abs((ee_fwdJet_leadbJet.i0 - ee_fwdJet_leadbJet.i1).eta)\n",
    "        ee_fwdJet_subleadbJet = ee_jetcross[ee_jetcross.counts >= 2][:, 1]\n",
    "        ee_fwdJet_subleadbJet = np.abs((ee_fwdJet_subleadbJet.i0 - ee_fwdJet_subleadbJet.i1).eta)\n",
    "        ee_fwdJet_closestLepton = (ee_lightjets.eta.max() - tights_2e.eta).min()\n",
    "        ee_fwdJet_closestLepton = ee_fwdJet_closestLepton[np.invert(np.isinf(ee_fwdJet_closestLepton))]\n",
    "        ee_highpT_sslp = tights_2e[np.abs(tights_2e.charge[:, 0] + tights_2e.charge[:, 1]) == 2]\n",
    "        ee_highpT_sslp = np.abs(ee_highpT_sslp.phi[:, 0] - ee_highpT_sslp.phi[:, 1])\n",
    "        ee_jetMaxEta = np.abs(jets_2e.eta[(jets_2e.btagCSVV2 <= loose_wp) & (jets_2e.pt > 40)]).max()\n",
    "        ee_minDelR = tights_2e[:, 0].delta_r(tights_2e[:, 1])\n",
    "        ee_NJetMed = jets_2e[(np.abs(jets_2e.eta) < 2.4)].counts\n",
    "        ee_NJetNONMED = jets_2e[(np.abs(jets_2e.eta) > 1) & (jets_2e.btagCSVV2 <= loose_wp)].counts\n",
    "        ee_TotalCharge = tights_2e.charge.sum()\n",
    "        \n",
    "        # Actually graphing all of the selected data.\n",
    "        output['lll_3rdLepton_pT'].fill(dataset=dataset, lll_3rdLepton_pT=lll_3rdLepton_pT)\n",
    "        output['lll_fwdJet_leadbJet'].fill(dataset=dataset, lll_fwdJet_leadbJet=lll_fwdJet_leadbJet)\n",
    "        output['lll_fwdJet_subleadbJet'].fill(dataset=dataset, lll_fwdJet_subleadbJet=lll_fwdJet_subleadbJet)\n",
    "        output['lll_fwdJet_closestLepton'].fill(dataset=dataset, lll_fwdJet_closestLepton=lll_fwdJet_closestLepton)\n",
    "        output['lll_highpT_sslp'].fill(dataset=dataset, lll_highpT_sslp=lll_highpT_sslp)\n",
    "        output['lll_jetMaxEta'].fill(dataset=dataset, lll_jetMaxEta=lll_jetMaxEta.flatten())\n",
    "        output['lll_minDelR'].fill(dataset=dataset, lll_minDelR=lll_minDelR)\n",
    "        output['lll_NJetMED'].fill(dataset=dataset, lll_NJetMED=lll_NJetMED.flatten())\n",
    "        output['lll_NJetNONMED'].fill(dataset=dataset, lll_NJetNONMED=lll_NJetNONMED.flatten())\n",
    "        output['lll_TotalCharge'].fill(dataset=dataset, lll_TotalCharge=lll_TotalCharge)\n",
    "        \n",
    "        output['mumu_subleadLepton_pT'].fill(dataset=dataset, mumu_subleadLepton_pT=mumu_subleadLepton_pT)\n",
    "        output['mumu_fwdJet_leadbJet'].fill(dataset=dataset, mumu_fwdJet_leadbJet=mumu_fwdJet_leadbJet)\n",
    "        output['mumu_fwdJet_subleadbJet'].fill(dataset=dataset, mumu_fwdJet_subleadbJet=mumu_fwdJet_subleadbJet)\n",
    "        output['mumu_fwdJet_closestLepton'].fill(dataset=dataset, mumu_fwdJet_closestLepton=mumu_fwdJet_closestLepton)\n",
    "        output['mumu_highpT_sslp'].fill(dataset=dataset, mumu_highpT_sslp=mumu_highpT_sslp)\n",
    "        output['mumu_jetMaxEta'].fill(dataset=dataset, mumu_jetMaxEta=mumu_jetMaxEta.flatten())\n",
    "        output['mumu_minDelR'].fill(dataset=dataset, mumu_minDelR=mumu_minDelR)\n",
    "        output['mumu_NJetMED'].fill(dataset=dataset, mumu_NJetMED=mumu_NJetMED.flatten())\n",
    "        output['mumu_NJetNONMED'].fill(dataset=dataset, mumu_NJetNONMED=mumu_NJetNONMED.flatten())\n",
    "        output['mumu_TotalCharge'].fill(dataset=dataset, mumu_TotalCharge=mumu_TotalCharge.flatten())\n",
    "        \n",
    "        output['emu_subleadLepton_pT'].fill(dataset=dataset, emu_subleadLepton_pT=emu_subleadLepton_pT.flatten())\n",
    "        output['emu_fwdJet_leadbJet'].fill(dataset=dataset, emu_fwdJet_leadbJet=emu_fwdJet_leadbJet)\n",
    "        output['emu_fwdJet_subleadbJet'].fill(dataset=dataset, emu_fwdJet_subleadbJet=emu_fwdJet_subleadbJet)\n",
    "        output['emu_fwdJet_closestLepton'].fill(dataset=dataset, emu_fwdJet_closestLepton=emu_fwdJet_closestLepton.flatten())\n",
    "        output['emu_highpT_sslp'].fill(dataset=dataset, emu_highpT_sslp=emu_highpT_sslp.flatten())\n",
    "        output['emu_jetMaxEta'].fill(dataset=dataset, emu_jetMaxEta=emu_jetMaxEta.flatten())\n",
    "        output['emu_minDelR'].fill(dataset=dataset, emu_minDelR=emu_minDelR.flatten())\n",
    "        output['emu_NJetMED'].fill(dataset=dataset, emu_NJetMED=emu_NJetMED.flatten())\n",
    "        output['emu_NJetNONMED'].fill(dataset=dataset, emu_NJetNONMED=emu_NJetNONMED.flatten())\n",
    "        output['emu_TotalCharge'].fill(dataset=dataset, emu_TotalCharge=emu_TotalCharge.flatten())\n",
    "        \n",
    "        output['ee_subleadLepton_pT'].fill(dataset=dataset, ee_subleadLepton_pT=ee_subleadLepton_pT)\n",
    "        output['ee_fwdJet_leadbJet'].fill(dataset=dataset, ee_fwdJet_leadbJet=ee_fwdJet_leadbJet)\n",
    "        output['ee_fwdJet_subleadbJet'].fill(dataset=dataset, ee_fwdJet_subleadbJet=ee_fwdJet_subleadbJet)\n",
    "        output['ee_fwdJet_closestLepton'].fill(dataset=dataset, ee_fwdJet_closestLepton=ee_fwdJet_closestLepton)\n",
    "        output['ee_highpT_sslp'].fill(dataset=dataset, ee_highpT_sslp=ee_highpT_sslp)\n",
    "        output['ee_jetMaxEta'].fill(dataset=dataset, ee_jetMaxEta=ee_jetMaxEta.flatten())\n",
    "        output['ee_minDelR'].fill(dataset=dataset, ee_minDelR=ee_minDelR)\n",
    "        output['ee_NJetMED'].fill(dataset=dataset, ee_NJetMED=ee_NJetMed.flatten())\n",
    "        output['ee_NJetNONMED'].fill(dataset=dataset, ee_NJetNONMED=ee_NJetNONMED.flatten())\n",
    "        output['ee_TotalCharge'].fill(dataset=dataset, ee_TotalCharge=ee_TotalCharge.flatten())        \n",
    "        \n",
    "        return output\n",
    "\n",
    "    def postprocess(self, accumulator):\n",
    "        lum = 35900\n",
    "        \n",
    "        # Calculates the number of events in every file we process.\n",
    "        eventries = {}\n",
    "        sumcheck = 0\n",
    "        for key in fileset:\n",
    "            eventries[key] = uproot.numentries(fileset[key], 'Events')\n",
    "            sumcheck += uproot.numentries(fileset[key], 'Events')\n",
    "        \n",
    "        # Cross-sections are found in the draft note. Weights follow the formula of [cross-section * integrate luminosity]/[events]\n",
    "        weights = {'tHq': (lum*0.7927)/eventries['tHq'],\n",
    "                      'tHW': (lum*0.1472)/eventries['tHW'],\n",
    "                      'ttW': (lum*0.6105)/eventries['ttW'],\n",
    "                      'ttWJets': (lum*0.2043)/eventries['ttWJets'],\n",
    "                      'ttZ': (lum*0.2529)/eventries['ttZ'],\n",
    "                      'ttZJets': (lum*0.5297)/eventries['ttZJets'], # cross-section is labaled as 0.5297 / 0.692 ?\n",
    "                      'ttH': (lum*0.2151)/eventries['ttH'],\n",
    "                      'WZ': (lum*4.4296)/eventries['WZ'],\n",
    "                      'ZZ': (lum*1.256)/eventries['ZZ'],\n",
    "                      'ZZZ': (lum*0.01398)/eventries['ZZZ'],\n",
    "                      'WWZ': (lum*0.1651)/eventries['WWZ'],\n",
    "                      'WZZ': (lum*0.05565)/eventries['WZZ'],\n",
    "                      'tttt': (lum*0.009103)/eventries['tttt'],\n",
    "                      'WpWp': (lum*0.03711)/eventries['WpWp'],\n",
    "                   }\n",
    "        scaled = hist.Cat('scaled', 'scaled')\n",
    "        for key in accumulator:\n",
    "            if accumulator[key] != accumulator['cutflow']:\n",
    "                # Scales each dataset along the dataset axis according to weights above.\n",
    "                accumulator[key].scale(weights, axis='dataset')\n",
    "                # Combines keys after scaling.\n",
    "                accumulator[key] = accumulator[key].group('dataset', scaled, {'tHq': ['tHq'], \n",
    "                                                                               'tHW': ['tHW'],\n",
    "                                                                               'ttW': ['ttW', 'ttWJets'],\n",
    "                                                                               'ttZ': ['ttZ', 'ttZJets'],\n",
    "                                                                               'ttH': ['ttH'],\n",
    "                                                                               'WZ': ['WZ'],\n",
    "                                                                               'ZZ': ['ZZ'],\n",
    "                                                                               'VVV': ['ZZZ', 'WWZ', 'WZZ'],\n",
    "                                                                               'tttt': ['tttt'],\n",
    "                                                                               'WpWp': ['WpWp'],\n",
    "                                                                              })\n",
    "        return accumulator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "class SignalProcessor(processor.ProcessorABC):\n",
    "    def __init__(self):\n",
    "        dataset_axis = hist.Cat(\"dataset\", \"\")\n",
    "        lll_3rdLepton_pT_axis = hist.Bin(\"lll_3rdLepton_pT\", \"3rd Lepton $p_T$ [GeV]\", 18, 0, 90)\n",
    "        lll_fwdJet_leadbJet_axis = hist.Bin(\"lll_fwdJet_leadbJet\", \"$\\Delta \\eta$ max fwd jet and leading bjet\", 18, 0, 6)\n",
    "        lll_fwdJet_subleadbJet_axis = hist.Bin(\"lll_fwdJet_subleadbJet\", \"$\\Delta \\eta$ max fwd jet and sub-leading bjet\", 18, 0, 6)\n",
    "        lll_fwdJet_closestLepton_axis = hist.Bin(\"lll_fwdJet_closestLepton\", \"$\\Delta \\eta$ max fwd jet and closest lepton\", 18, 0, 6)\n",
    "        lll_highpT_sslp_axis = hist.Bin(\"lll_highpT_sslp\", \"$\\Delta \\Phi$ highest $p_T$ same-sign lepton pair\", 18, 0, 3.5)\n",
    "        lll_jetMaxEta_axis = hist.Bin(\"lll_jetMaxEta\", \"max jet $|\\eta|$ ($p_T$ > 25)\", 18, 0, 5)\n",
    "        lll_minDelR_axis = hist.Bin(\"lll_minDelR\", \"Minimum $\\Delta$ R between any two leptons\", 18, 0, 4)\n",
    "        lll_NJetMedium_axis = hist.Bin(\"lll_NJetMED\", \"N(jet, $p_T$ > 25, $|\\eta|$ < 2.4)\", 6, 2, 8)\n",
    "        lll_NJetNonCSVMedium_axis = hist.Bin(\"lll_NJetNONMED\", \"N(jet, $|\\eta|$ > 1) non CSV medium\", 7, 1, 8)        \n",
    "        lll_TotalCharge_axis = hist.Bin(\"lll_TotalCharge\", \"Total Lepton Charge\", 5, -2, 3)\n",
    "        \n",
    "        mumu_subleadLepton_pT_axis = hist.Bin(\"mumu_subleadLepton_pT\", \"Sub-leading Lepton $p_T$ [GeV]\", 18, 0, 144)\n",
    "        mumu_fwdJet_leadbJet_axis = hist.Bin(\"mumu_fwdJet_leadbJet\", \"$\\Delta \\eta$ max fwd jet and leading bjet\", 18, 0, 6)\n",
    "        mumu_fwdJet_subleadbJet_axis = hist.Bin(\"mumu_fwdJet_subleadbJet\", \"$\\Delta \\eta$ max fwd jet and sub-leading bjet\", 18, 0, 6)\n",
    "        mumu_fwdJet_closestLepton_axis = hist.Bin(\"mumu_fwdJet_closestLepton\", \"$\\Delta \\eta$ max fwd jet and closest lepton\", 18, 0, 6)\n",
    "        mumu_highpT_sslp_axis = hist.Bin(\"mumu_highpT_sslp\", \"$\\Delta \\Phi$ highest $p_T$ same-sign lepton pair\", 18, 0, 3.5)\n",
    "        mumu_jetMaxEta_axis = hist.Bin(\"mumu_jetMaxEta\", \"max jet $|\\eta|$ ($p_T$ > 40)\", 18, 0, 5)\n",
    "        mumu_minDelR_axis = hist.Bin(\"mumu_minDelR\", \"Minimum $\\Delta$ R between any two leptons\", 18, 0, 4)\n",
    "        mumu_NJetMedium_axis = hist.Bin(\"mumu_NJetMED\", \"N(jet, $p_T$ > 25, $|\\eta|$ < 2.4)\", 6, 2, 8)\n",
    "        mumu_NJetNonCSVMedium_axis = hist.Bin(\"mumu_NJetNONMED\", \"N(jet, $|\\eta|$ > 1) non CSV medium\", 7, 1, 8)        \n",
    "        mumu_TotalCharge_axis = hist.Bin(\"mumu_TotalCharge\", \"Total Lepton Charge\", 5, -2, 3)\n",
    "        \n",
    "        emu_subleadLepton_pT_axis = hist.Bin(\"emu_subleadLepton_pT\", \"Sub-leading Lepton $p_T$ [GeV]\", 18, 0, 144)\n",
    "        emu_fwdJet_leadbJet_axis = hist.Bin(\"emu_fwdJet_leadbJet\", \"$\\Delta \\eta$ max fwd jet and leading bjet\", 18, 0, 6)\n",
    "        emu_fwdJet_subleadbJet_axis = hist.Bin(\"emu_fwdJet_subleadbJet\", \"$\\Delta \\eta$ max fwd jet and sub-leading bjet\", 18, 0, 6)\n",
    "        emu_fwdJet_closestLepton_axis = hist.Bin(\"emu_fwdJet_closestLepton\", \"$\\Delta \\eta$ max fwd jet and closest lepton\", 18, 0, 6)\n",
    "        emu_highpT_sslp_axis = hist.Bin(\"emu_highpT_sslp\", \"$\\Delta \\Phi$ highest $p_T$ same-sign lepton pair\", 18, 0, 3.5)\n",
    "        emu_jetMaxEta_axis = hist.Bin(\"emu_jetMaxEta\", \"max jet $|\\eta|$ ($p_T$ > 40)\", 18, 0, 5)\n",
    "        emu_minDelR_axis = hist.Bin(\"emu_minDelR\", \"Minimum $\\Delta$ R between any two leptons\", 18, 0, 4)\n",
    "        emu_NJetMedium_axis = hist.Bin(\"emu_NJetMED\", \"N(jet, $p_T$ > 25, $|\\eta|$ < 2.4)\", 6, 2, 8)\n",
    "        emu_NJetNonCSVMedium_axis = hist.Bin(\"emu_NJetNONMED\", \"N(jet, $|\\eta|$ > 1) non CSV medium\", 7, 1, 8)        \n",
    "        emu_TotalCharge_axis = hist.Bin(\"emu_TotalCharge\", \"Total Lepton Charge\", 5, -2, 3)\n",
    "        \n",
    "        ee_subleadLepton_pT_axis = hist.Bin(\"ee_subleadLepton_pT\", \"Sub-leading Lepton $p_T$ [GeV]\", 18, 0, 144)\n",
    "        ee_fwdJet_leadbJet_axis = hist.Bin(\"ee_fwdJet_leadbJet\", \"$\\Delta \\eta$ max fwd jet and leading bjet\", 18, 0, 6)\n",
    "        ee_fwdJet_subleadbJet_axis = hist.Bin(\"ee_fwdJet_subleadbJet\", \"$\\Delta \\eta$ max fwd jet and sub-leading bjet\", 18, 0, 6)\n",
    "        ee_fwdJet_closestLepton_axis = hist.Bin(\"ee_fwdJet_closestLepton\", \"$\\Delta \\eta$ max fwd jet and closest lepton\", 18, 0, 6)\n",
    "        ee_highpT_sslp_axis = hist.Bin(\"ee_highpT_sslp\", \"$\\Delta \\Phi$ highest $p_T$ same-sign lepton pair\", 18, 0, 3.5)\n",
    "        ee_jetMaxEta_axis = hist.Bin(\"ee_jetMaxEta\", \"max jet $|\\eta|$ ($p_T$ > 40)\", 18, 0, 5)\n",
    "        ee_minDelR_axis = hist.Bin(\"ee_minDelR\", \"Minimum $\\Delta$ R between any two leptons\", 18, 0, 4)\n",
    "        ee_NJetMedium_axis = hist.Bin(\"ee_NJetMED\", \"N(jet, $p_T$ > 25, $|\\eta|$ < 2.4)\", 6, 2, 8)\n",
    "        ee_NJetNonCSVMedium_axis = hist.Bin(\"ee_NJetNONMED\", \"N(jet, $|\\eta|$ > 1) non CSV medium\", 7, 1, 8)        \n",
    "        ee_TotalCharge_axis = hist.Bin(\"ee_TotalCharge\", \"Total Lepton Charge\", 5, -2, 3)\n",
    "        \n",
    "        self._accumulator = processor.dict_accumulator({\n",
    "            'lll_3rdLepton_pT': hist.Hist(\"Events\", dataset_axis, lll_3rdLepton_pT_axis),\n",
    "            'lll_fwdJet_leadbJet': hist.Hist(\"Events\", dataset_axis, lll_fwdJet_leadbJet_axis),\n",
    "            'lll_fwdJet_subleadbJet': hist.Hist(\"Events\", dataset_axis, lll_fwdJet_subleadbJet_axis),\n",
    "            'lll_fwdJet_closestLepton': hist.Hist(\"Events\", dataset_axis, lll_fwdJet_closestLepton_axis),\n",
    "            'lll_highpT_sslp': hist.Hist(\"Events\", dataset_axis, lll_highpT_sslp_axis),\n",
    "            'lll_jetMaxEta': hist.Hist(\"Events\", dataset_axis, lll_jetMaxEta_axis),\n",
    "            'lll_minDelR': hist.Hist(\"Events\", dataset_axis, lll_minDelR_axis),\n",
    "            'lll_NJetMED': hist.Hist(\"Events\", dataset_axis, lll_NJetMedium_axis),\n",
    "            'lll_NJetNONMED': hist.Hist(\"Events\", dataset_axis, lll_NJetNonCSVMedium_axis),\n",
    "            'lll_TotalCharge': hist.Hist(\"Events\", dataset_axis, lll_TotalCharge_axis),\n",
    "            'mumu_subleadLepton_pT': hist.Hist(\"Events\", dataset_axis, mumu_subleadLepton_pT_axis),\n",
    "            'mumu_fwdJet_leadbJet': hist.Hist(\"Events\", dataset_axis, mumu_fwdJet_leadbJet_axis),\n",
    "            'mumu_fwdJet_subleadbJet': hist.Hist(\"Events\", dataset_axis, mumu_fwdJet_subleadbJet_axis),\n",
    "            'mumu_fwdJet_closestLepton': hist.Hist(\"Events\", dataset_axis, mumu_fwdJet_closestLepton_axis),\n",
    "            'mumu_highpT_sslp': hist.Hist(\"Events\", dataset_axis, mumu_highpT_sslp_axis),\n",
    "            'mumu_jetMaxEta': hist.Hist(\"Events\", dataset_axis, mumu_jetMaxEta_axis),\n",
    "            'mumu_minDelR': hist.Hist(\"Events\", dataset_axis, mumu_minDelR_axis),\n",
    "            'mumu_NJetMED': hist.Hist(\"Events\", dataset_axis, mumu_NJetMedium_axis),\n",
    "            'mumu_NJetNONMED': hist.Hist(\"Events\", dataset_axis, mumu_NJetNonCSVMedium_axis),\n",
    "            'mumu_TotalCharge': hist.Hist(\"Events\", dataset_axis, mumu_TotalCharge_axis),\n",
    "            'emu_subleadLepton_pT': hist.Hist(\"Events\", dataset_axis, emu_subleadLepton_pT_axis),\n",
    "            'emu_fwdJet_leadbJet': hist.Hist(\"Events\", dataset_axis, emu_fwdJet_leadbJet_axis),\n",
    "            'emu_fwdJet_subleadbJet': hist.Hist(\"Events\", dataset_axis, emu_fwdJet_subleadbJet_axis),\n",
    "            'emu_fwdJet_closestLepton': hist.Hist(\"Events\", dataset_axis, emu_fwdJet_closestLepton_axis),\n",
    "            'emu_highpT_sslp': hist.Hist(\"Events\", dataset_axis, emu_highpT_sslp_axis),\n",
    "            'emu_jetMaxEta': hist.Hist(\"Events\", dataset_axis, emu_jetMaxEta_axis),\n",
    "            'emu_minDelR': hist.Hist(\"Events\", dataset_axis, emu_minDelR_axis),\n",
    "            'emu_NJetMED': hist.Hist(\"Events\", dataset_axis, emu_NJetMedium_axis),\n",
    "            'emu_NJetNONMED': hist.Hist(\"Events\", dataset_axis, emu_NJetNonCSVMedium_axis),\n",
    "            'emu_TotalCharge': hist.Hist(\"Events\", dataset_axis, emu_TotalCharge_axis),\n",
    "            'ee_subleadLepton_pT': hist.Hist(\"Events\", dataset_axis, ee_subleadLepton_pT_axis),\n",
    "            'ee_fwdJet_leadbJet': hist.Hist(\"Events\", dataset_axis, ee_fwdJet_leadbJet_axis),\n",
    "            'ee_fwdJet_subleadbJet': hist.Hist(\"Events\", dataset_axis, ee_fwdJet_subleadbJet_axis),\n",
    "            'ee_fwdJet_closestLepton': hist.Hist(\"Events\", dataset_axis, ee_fwdJet_closestLepton_axis),\n",
    "            'ee_highpT_sslp': hist.Hist(\"Events\", dataset_axis, ee_highpT_sslp_axis),\n",
    "            'ee_jetMaxEta': hist.Hist(\"Events\", dataset_axis, ee_jetMaxEta_axis),\n",
    "            'ee_minDelR': hist.Hist(\"Events\", dataset_axis, ee_minDelR_axis),\n",
    "            'ee_NJetMED': hist.Hist(\"Events\", dataset_axis, ee_NJetMedium_axis),\n",
    "            'ee_NJetNONMED': hist.Hist(\"Events\", dataset_axis, ee_NJetNonCSVMedium_axis),\n",
    "            'ee_TotalCharge': hist.Hist(\"Events\", dataset_axis, ee_TotalCharge_axis),\n",
    "            'cutflow': processor.defaultdict_accumulator(int)\n",
    "        })\n",
    "    \n",
    "    @property\n",
    "    def accumulator(self):\n",
    "        return self._accumulator\n",
    "    \n",
    "    def process(self, events):\n",
    "        output = self.accumulator.identity()\n",
    "        \n",
    "        # btag working point numbers, for easy reference.\n",
    "        loose_wp = 0.5425\n",
    "        medium_wp = 0.8484\n",
    "\n",
    "        # Initialize relevant event columns.\n",
    "        dataset = events.metadata[\"dataset\"]\n",
    "        jets = events.Jet\n",
    "        muons = events.Muon\n",
    "        electrons = events.Electron\n",
    "\n",
    "        # This is bookkeeping that tracks how many total events there are.\n",
    "        output['cutflow']['all events'] += events.size\n",
    "        \n",
    "        \n",
    "        \n",
    "        # # # # # # # # # # #\n",
    "        # LEPTON SELECTIONS #\n",
    "        # # # # # # # # # # #\n",
    "        \n",
    "        # Don't want any jets below 25 pT. Remove them now instead of later.\n",
    "        jets = jets[(jets.pt > 25)]\n",
    "        \n",
    "        # Here we establish the loose muons array, based on provided cuts.\n",
    "        loose_muons = muons[(np.abs(muons.eta) < 2.4) &\n",
    "                      (np.abs(muons.dxy) < 0.05) & \n",
    "                      (np.abs(muons.dz) < 0.1) & \n",
    "                      (muons.sip3d < 8) &\n",
    "                      (muons.miniPFRelIso_all < 0.4) &\n",
    "                      (muons.looseId) &\n",
    "                      (muons.pt > 5)]\n",
    "        \n",
    "        # Tight is loose with additional cuts; build tight array and add cuts.\n",
    "        tight_muons = loose_muons[(loose_muons.tightCharge > 0) &\n",
    "                                  (loose_muons.mediumId) &\n",
    "                                  (loose_muons.mvaTTH > 0.9)]\n",
    "\n",
    "        # This ends up getting referenced a lot. Let's not generate it every time!\n",
    "        abs_eta = np.abs(electrons.eta)\n",
    "        \n",
    "        # Here we establish the loose electrons array, based on provided cuts.\n",
    "        loose_electrons = electrons[(abs_eta < 2.5) & \n",
    "                              (np.abs(electrons.dxy) < 0.05) & \n",
    "                              (np.abs(electrons.dz) < 0.1) & \n",
    "                              (electrons.lostHits < 2) &\n",
    "                              (electrons.miniPFRelIso_all < 0.4) &\n",
    "                              (electrons.pt > 7) &\n",
    "                              (((electrons.mvaFall17V2noIso > 0) & (abs_eta < 1.479)) | ((electrons.mvaFall17V2noIso > 0.7) & (abs_eta > 1.479) & (abs_eta < 2.5)))]\n",
    "            \n",
    "        # Now we build tight from loose, adding in tight's extra cuts.\n",
    "        # Redefine abs_eta since we're now using loose.\n",
    "        abs_eta = np.abs(loose_electrons.eta)\n",
    "        \n",
    "        tight_electrons = loose_electrons[(loose_electrons.pt > 15) &\n",
    "                                         (loose_electrons.lostHits == 0) &\n",
    "                                         (loose_electrons.tightCharge > 0) &\n",
    "                                         (loose_electrons.convVeto) &\n",
    "                                         (loose_electrons.mvaTTH > 0.90) &\n",
    "                                         # Two ranges for sigma_ieie.\n",
    "                                         (((abs_eta < 1.479) & (loose_electrons.sieie < 0.011)) | \n",
    "                                         ((abs_eta < 2.5) & (abs_eta > 1.479) & (loose_electrons.sieie < 0.03))) &\n",
    "                                         # Two ranges for H/E\n",
    "                                         (((abs_eta < 1.479) & (loose_electrons.hoe < 0.1)) | \n",
    "                                         ((abs_eta < 2.5) & (abs_eta > 1.479) & (loose_electrons.hoe < 0.07))) &\n",
    "                                         # Two ranges for 1/E - 1/p\n",
    "                                         (((abs_eta < 1.479) & (loose_electrons.eInvMinusPInv < 0.01) & (loose_electrons.eInvMinusPInv > -0.05)) |\n",
    "                                         ((abs_eta < 2.5) & (abs_eta > 1.479) & (loose_electrons.eInvMinusPInv < 0.005) & (loose_electrons.eInvMinusPInv > -0.05)))]        \n",
    "        \n",
    "        \n",
    "\n",
    "        # # # # # # # # # #\n",
    "        # EVENT SELECTION #\n",
    "        # # # # # # # # # #\n",
    "        \n",
    "        # Loose pre-selection. See definition of stack_leptons above to see how we construct arrays across leptons.\n",
    "        loose_leptons = stack_leptons(loose_muons, loose_electrons)\n",
    "        loose_pairs = loose_leptons.argchoose(2)\n",
    "        loose_pairs_mass = (loose_leptons[loose_pairs.i0].p4 + loose_leptons[loose_pairs.i1].p4).mass\n",
    "        looseMask = ((loose_pairs_mass >= 12).all() & (loose_pairs_mass.counts > 0))\n",
    "        \n",
    "        # Dilepton selection.\n",
    "        tight_leptons = stack_leptons(tight_muons, tight_electrons)\n",
    "        tight_pairs = tight_leptons.argchoose(2)\n",
    "        # Add types to see what kind of pair we have. mu = 0, e = 1, so: mumu = 0, emu = 1, ee = 2.\n",
    "        tight_types = (tight_leptons[tight_pairs.i0].ptype + tight_leptons[tight_pairs.i1].ptype)\n",
    "        \n",
    "        # Respectively; each event should have exactly 1 pair (2 leptons) with same charge\n",
    "        #               one should have pT > 25 (pT > 15 is guaranteed by lepton selection)\n",
    "        #               for ee events, check that mass from Z is < 10 to veto possible Z bosons.\n",
    "        dileptonMask = ((tight_pairs.counts == 1) & (tight_leptons[tight_pairs.i0].charge == tight_leptons[tight_pairs.i1].charge).any()) & ((tight_leptons[tight_pairs.i0].p4.pt > 25) | (tight_leptons[tight_pairs.i1].p4.pt > 25)).any() & ((tight_types < 2) | (np.abs((tight_leptons[tight_pairs.i0].p4 + tight_leptons[tight_pairs.i1].p4).mass - 91.18) > 10)).any()\n",
    "        \n",
    "        # Trilepton selection.\n",
    "        tight_triples = tight_leptons.argchoose(3)\n",
    "        tight_muon_pairs = tight_muons.choose(2)\n",
    "        tight_electron_pairs = tight_electrons.choose(2)\n",
    "        \n",
    "        # Respectively; we want events with exactly three tight leptons (one triple),\n",
    "        #               one should have pT > 25, discard if OSSF dileptons are close to the Z mass.\n",
    "        trileptonMask = (tight_triples.counts == 1) & ((tight_leptons[tight_triples.i0].p4.pt > 25) | (tight_leptons[tight_triples.i1].p4.pt > 25) | (tight_leptons[tight_triples.i2].p4.pt > 25)).any() & (~ossf_zmass_check(tight_muon_pairs)) & (~ossf_zmass_check(tight_electron_pairs))\n",
    "        \n",
    "        # Jet masks can be generated much more simply, since we're staying in one collection.\n",
    "        jetMask_medium = ((np.abs(jets.eta) < 2.4) & (jets.btagCSVV2 > medium_wp)).sum() >= 1\n",
    "        jetMask_loose = (((np.abs(jets.eta) < 2.4) | ((jets.pt > 40) & (np.abs(jets.eta) > 2.4))) & (jets.btagCSVV2 <= loose_wp)).sum() >= 1\n",
    "        \n",
    "        # May as well combine all of our masks into one (well, two) big one(s) for easier referencing.\n",
    "        # Split dileptons and trileptons into separate channels, because it's easier to work with later.\n",
    "        dilepton_eventMask = (looseMask) & (dileptonMask) & (jetMask_medium) & (jetMask_loose)\n",
    "        trilepton_eventMask = (looseMask) & (trileptonMask) & (jetMask_medium) & (jetMask_loose)\n",
    "        \n",
    "        # Dilepton masks.\n",
    "        tight_ll_e = tight_electrons[dilepton_eventMask].compact()\n",
    "        tight_ll_mu = tight_muons[dilepton_eventMask].compact()\n",
    "        \n",
    "        # Trilepton masks.\n",
    "        tight_lll_e = tight_electrons[trilepton_eventMask].compact()\n",
    "        tight_lll_mu = tight_muons[trilepton_eventMask].compact()\n",
    "        \n",
    "        # Split dileptons into further channels: ee, mumu, and emu (need two arrays for this one)\n",
    "        tights_2mu = tight_ll_mu[tight_ll_mu.counts == 2]\n",
    "        tights_2e = tight_ll_e[tight_ll_e.counts == 2]\n",
    "        tights_1e = tight_electrons[dilepton_eventMask & tight_electrons.counts == 1]\n",
    "        tights_1mu = tight_muons[dilepton_eventMask & tight_muons.counts == 1]\n",
    "        \n",
    "        # Can't forget to mask our jets after all of that lepton array-building! We want jets that meet either mask requirement.\n",
    "        jets_3lep = jets[trilepton_eventMask]\n",
    "        jets_2mu = jets[dilepton_eventMask & (tight_muons.counts == 2)]\n",
    "        jets_2e = jets[dilepton_eventMask & (tight_electrons.counts == 2)]\n",
    "        jets_emu = jets[dilepton_eventMask & (tight_muons.counts == 1) & (tight_electrons.counts == 1)]\n",
    "        \n",
    "        \n",
    "        \n",
    "        # # # # # #\n",
    "        # OUTPUTS #\n",
    "        # # # # # #\n",
    "        \n",
    "        # Selecting the data that we want.\n",
    "            # Three-lepton channel\n",
    "        lll_ee_pairs = tight_electrons[trilepton_eventMask].distincts()\n",
    "        lll_mumu_pairs = tight_muons[trilepton_eventMask].distincts()\n",
    "        lll_emu_pairs = tight_electrons[trilepton_eventMask].cross(tight_muons[trilepton_eventMask])  \n",
    "        lll_3rdLepton_pT = np.asarray([lll_ee_pairs.i0.pt.min(), lll_ee_pairs.i1.pt.min(),\n",
    "                                       lll_mumu_pairs.i0.pt.min(), lll_mumu_pairs.i1.pt.min(),\n",
    "                                       lll_emu_pairs.i0.pt.min(), lll_emu_pairs.i1.pt.min()]).min(0)\n",
    "        output['cutflow']['passing'] += lll_3rdLepton_pT.size\n",
    "        lll_lightjets = jets_3lep[jets_3lep.btagCSVV2 <= loose_wp]\n",
    "        lll_jetcross = jets_3lep[jets_3lep.btagCSVV2 > loose_wp].cross(lll_lightjets[lll_lightjets.eta == lll_lightjets.eta.max()])\n",
    "        lll_fwdJet_leadbJet = lll_jetcross[lll_jetcross.counts >= 1][:, 0]\n",
    "        lll_fwdJet_leadbJet = np.abs((lll_fwdJet_leadbJet.i0 - lll_fwdJet_leadbJet.i1).eta)\n",
    "        lll_fwdJet_subleadbJet = lll_jetcross[lll_jetcross.counts >= 2][:, 1]\n",
    "        lll_fwdJet_subleadbJet = np.abs((lll_fwdJet_subleadbJet.i0 - lll_fwdJet_subleadbJet.i1).eta)\n",
    "        lll_fwdJet_closestLepton = channel_fwdeta_jetlep(tight_lll_e.starts, tight_lll_e.stops, tight_lll_mu.starts, tight_lll_mu.stops,\n",
    "                                              lll_lightjets.eta.max(), tight_lll_e.eta.content, tight_lll_mu.eta.content)\n",
    "        lll_highpT_sslp = channel_dphi_ssp(tight_lll_e.starts, tight_lll_e.stops, tight_lll_mu.starts, tight_lll_mu.stops,\n",
    "                                        tight_lll_e.x.content, tight_lll_e.y.content, tight_lll_e.phi.content, tight_lll_mu.x.content, tight_lll_mu.y.content, tight_lll_mu.phi.content,\n",
    "                                        tight_lll_e.charge.content, tight_lll_mu.charge.content)\n",
    "        lll_jetMaxEta = np.abs(jets_3lep.eta[jets_3lep.btagCSVV2 <= loose_wp]).max()\n",
    "        lll_minDelR = np.asarray([lll_ee_pairs.i0.delta_r(lll_ee_pairs.i1).min(),\n",
    "                                 lll_mumu_pairs.i0.delta_r(lll_mumu_pairs.i1).min(),\n",
    "                                 lll_emu_pairs.i0.delta_r(lll_emu_pairs.i1).min()]).min(0)\n",
    "        lll_NJetMED = jets_3lep[(np.abs(jets_3lep.eta) < 2.4)].counts\n",
    "        lll_NJetNONMED = jets_3lep[(np.abs(jets_3lep.eta) > 1) & (jets_3lep.btagCSVV2 <= loose_wp)].counts\n",
    "        lll_TotalCharge = tight_lll_e.charge.sum() + tight_lll_mu.charge.sum()\n",
    "            # mu-mu channel\n",
    "        mumu_subleadLepton_pT = tights_2mu.pt[:, 1]\n",
    "        mumu_lightjets = jets_2mu[jets_2mu.btagCSVV2 <= loose_wp]\n",
    "        mumu_jetcross = jets_2mu[jets_2mu.btagCSVV2 > loose_wp].cross(mumu_lightjets[mumu_lightjets.eta == mumu_lightjets.eta.max()])\n",
    "        mumu_fwdJet_leadbJet = mumu_jetcross[mumu_jetcross.counts >= 1][:, 0]\n",
    "        mumu_fwdJet_leadbJet = np.abs((mumu_fwdJet_leadbJet.i0 - mumu_fwdJet_leadbJet.i1).eta)\n",
    "        mumu_fwdJet_subleadbJet = mumu_jetcross[mumu_jetcross.counts >= 2][:, 1]\n",
    "        mumu_fwdJet_subleadbJet = np.abs((mumu_fwdJet_subleadbJet.i0 - mumu_fwdJet_subleadbJet.i1).eta)\n",
    "        mumu_fwdJet_closestLepton = (mumu_lightjets.eta.max() - tights_2mu.eta).min()\n",
    "        mumu_fwdJet_closestLepton = mumu_fwdJet_closestLepton[np.invert(np.isinf(mumu_fwdJet_closestLepton))]\n",
    "        mumu_highpT_sslp = tights_2mu[np.abs(tights_2mu.charge[:, 0] + tights_2mu.charge[:, 1]) == 2]\n",
    "        mumu_highpT_sslp = np.abs(mumu_highpT_sslp.phi[:, 0] - mumu_highpT_sslp.phi[:, 1])\n",
    "        mumu_jetMaxEta = np.abs(jets_2mu.eta[(jets_2mu.btagCSVV2 <= loose_wp) & (jets_2mu.pt > 40)]).max()\n",
    "        mumu_minDelR = tights_2mu[:, 0].delta_r(tights_2mu[:, 1])\n",
    "        mumu_NJetMED = jets_2mu.counts\n",
    "        mumu_NJetNONMED = jets_2mu[(np.abs(jets_2mu.eta) > 1) & (jets_2mu.btagCSVV2 <= loose_wp)].counts\n",
    "        mumu_TotalCharge = tights_2mu.charge.sum()\n",
    "            # e-mu channel\n",
    "        emu_subleadLepton_pT = np.minimum(tights_1e.pt, tights_1mu.pt)\n",
    "        emu_lightjets = jets_emu[jets_emu.btagCSVV2 <= loose_wp]\n",
    "        emu_jetcross = jets_emu[jets_emu.btagCSVV2 > loose_wp].cross(emu_lightjets[emu_lightjets.eta == emu_lightjets.eta.max()])\n",
    "        emu_fwdJet_leadbJet = emu_jetcross[emu_jetcross.counts >= 1][:, 0]\n",
    "        emu_fwdJet_leadbJet = np.abs((emu_fwdJet_leadbJet.i0 - emu_fwdJet_leadbJet.i1).eta)\n",
    "        emu_fwdJet_subleadbJet = emu_jetcross[emu_jetcross.counts >= 2][:, 1]\n",
    "        emu_fwdJet_subleadbJet = np.abs((emu_fwdJet_subleadbJet.i0 - emu_fwdJet_subleadbJet.i1).eta)\n",
    "        mu_fwdJet_closestLepton = (emu_lightjets.eta.max() - tights_1mu.eta)\n",
    "        e_fwdJet_closestLepton = (emu_lightjets.eta.max() - tights_1e.eta)\n",
    "        emu_fwdJet_closestLepton = np.minimum(mu_fwdJet_closestLepton, e_fwdJet_closestLepton)\n",
    "        emu_fwdJet_closestLepton = emu_fwdJet_closestLepton[np.invert(np.isinf(emu_fwdJet_closestLepton))]\n",
    "        mu_highpT_sslp = tights_1mu[np.abs(tights_1mu.charge + tights_1e.charge) == 2]\n",
    "        e_highpT_sslp = tights_1e[np.abs(tights_1mu.charge + tights_1e.charge) == 2]\n",
    "        emu_highpT_sslp = np.abs(mu_highpT_sslp.phi - e_highpT_sslp.phi)\n",
    "        emu_jetMaxEta = np.abs(jets_emu.eta[(jets_emu.btagCSVV2 <= loose_wp) & (jets_emu.pt > 40)]).max()\n",
    "        emu_minDelR = tights_1e.delta_r(tights_1mu)\n",
    "        emu_NJetMED = jets_emu[(np.abs(jets_emu.eta) < 2.4)].counts\n",
    "        emu_NJetNONMED = jets_emu[(np.abs(jets_emu.eta) > 1) & (jets_emu.btagCSVV2 <= loose_wp)].counts\n",
    "        emu_TotalCharge = tights_1mu.charge + tights_1e.charge\n",
    "        # e-e channel\n",
    "        ee_subleadLepton_pT = tights_2e.pt[:, 1]\n",
    "        ee_lightjets = jets_2e[jets_2e.btagCSVV2 <= loose_wp]\n",
    "        ee_jetcross = jets_2e[jets_2e.btagCSVV2 > loose_wp].cross(ee_lightjets[ee_lightjets.eta == ee_lightjets.eta.max()])\n",
    "        ee_fwdJet_leadbJet = ee_jetcross[ee_jetcross.counts >= 1][:, 0]\n",
    "        ee_fwdJet_leadbJet = np.abs((ee_fwdJet_leadbJet.i0 - ee_fwdJet_leadbJet.i1).eta)\n",
    "        ee_fwdJet_subleadbJet = ee_jetcross[ee_jetcross.counts >= 2][:, 1]\n",
    "        ee_fwdJet_subleadbJet = np.abs((ee_fwdJet_subleadbJet.i0 - ee_fwdJet_subleadbJet.i1).eta)\n",
    "        ee_fwdJet_closestLepton = (ee_lightjets.eta.max() - tights_2e.eta).min()\n",
    "        ee_fwdJet_closestLepton = ee_fwdJet_closestLepton[np.invert(np.isinf(ee_fwdJet_closestLepton))]\n",
    "        ee_highpT_sslp = tights_2e[np.abs(tights_2e.charge[:, 0] + tights_2e.charge[:, 1]) == 2]\n",
    "        ee_highpT_sslp = np.abs(ee_highpT_sslp.phi[:, 0] - ee_highpT_sslp.phi[:, 1])\n",
    "        ee_jetMaxEta = np.abs(jets_2e.eta[(jets_2e.btagCSVV2 <= loose_wp) & (jets_2e.pt > 40)]).max()\n",
    "        ee_minDelR = tights_2e[:, 0].delta_r(tights_2e[:, 1])\n",
    "        ee_NJetMed = jets_2e[(np.abs(jets_2e.eta) < 2.4)].counts\n",
    "        ee_NJetNONMED = jets_2e[(np.abs(jets_2e.eta) > 1) & (jets_2e.btagCSVV2 <= loose_wp)].counts\n",
    "        ee_TotalCharge = tights_2e.charge.sum()\n",
    "        \n",
    "        # Actually graphing all of the selected data.\n",
    "        output['lll_3rdLepton_pT'].fill(dataset=dataset, lll_3rdLepton_pT=lll_3rdLepton_pT)\n",
    "        output['lll_fwdJet_leadbJet'].fill(dataset=dataset, lll_fwdJet_leadbJet=lll_fwdJet_leadbJet)\n",
    "        output['lll_fwdJet_subleadbJet'].fill(dataset=dataset, lll_fwdJet_subleadbJet=lll_fwdJet_subleadbJet)\n",
    "        output['lll_fwdJet_closestLepton'].fill(dataset=dataset, lll_fwdJet_closestLepton=lll_fwdJet_closestLepton)\n",
    "        output['lll_highpT_sslp'].fill(dataset=dataset, lll_highpT_sslp=lll_highpT_sslp)\n",
    "        output['lll_jetMaxEta'].fill(dataset=dataset, lll_jetMaxEta=lll_jetMaxEta.flatten())\n",
    "        output['lll_minDelR'].fill(dataset=dataset, lll_minDelR=lll_minDelR)\n",
    "        output['lll_NJetMED'].fill(dataset=dataset, lll_NJetMED=lll_NJetMED.flatten())\n",
    "        output['lll_NJetNONMED'].fill(dataset=dataset, lll_NJetNONMED=lll_NJetNONMED.flatten())\n",
    "        output['lll_TotalCharge'].fill(dataset=dataset, lll_TotalCharge=lll_TotalCharge)\n",
    "        \n",
    "        output['mumu_subleadLepton_pT'].fill(dataset=dataset, mumu_subleadLepton_pT=mumu_subleadLepton_pT)\n",
    "        output['mumu_fwdJet_leadbJet'].fill(dataset=dataset, mumu_fwdJet_leadbJet=mumu_fwdJet_leadbJet)\n",
    "        output['mumu_fwdJet_subleadbJet'].fill(dataset=dataset, mumu_fwdJet_subleadbJet=mumu_fwdJet_subleadbJet)\n",
    "        output['mumu_fwdJet_closestLepton'].fill(dataset=dataset, mumu_fwdJet_closestLepton=mumu_fwdJet_closestLepton)\n",
    "        output['mumu_highpT_sslp'].fill(dataset=dataset, mumu_highpT_sslp=mumu_highpT_sslp)\n",
    "        output['mumu_jetMaxEta'].fill(dataset=dataset, mumu_jetMaxEta=mumu_jetMaxEta.flatten())\n",
    "        output['mumu_minDelR'].fill(dataset=dataset, mumu_minDelR=mumu_minDelR)\n",
    "        output['mumu_NJetMED'].fill(dataset=dataset, mumu_NJetMED=mumu_NJetMED.flatten())\n",
    "        output['mumu_NJetNONMED'].fill(dataset=dataset, mumu_NJetNONMED=mumu_NJetNONMED.flatten())\n",
    "        output['mumu_TotalCharge'].fill(dataset=dataset, mumu_TotalCharge=mumu_TotalCharge.flatten())\n",
    "        \n",
    "        output['emu_subleadLepton_pT'].fill(dataset=dataset, emu_subleadLepton_pT=emu_subleadLepton_pT.flatten())\n",
    "        output['emu_fwdJet_leadbJet'].fill(dataset=dataset, emu_fwdJet_leadbJet=emu_fwdJet_leadbJet)\n",
    "        output['emu_fwdJet_subleadbJet'].fill(dataset=dataset, emu_fwdJet_subleadbJet=emu_fwdJet_subleadbJet)\n",
    "        output['emu_fwdJet_closestLepton'].fill(dataset=dataset, emu_fwdJet_closestLepton=emu_fwdJet_closestLepton.flatten())\n",
    "        output['emu_highpT_sslp'].fill(dataset=dataset, emu_highpT_sslp=emu_highpT_sslp.flatten())\n",
    "        output['emu_jetMaxEta'].fill(dataset=dataset, emu_jetMaxEta=emu_jetMaxEta.flatten())\n",
    "        output['emu_minDelR'].fill(dataset=dataset, emu_minDelR=emu_minDelR.flatten())\n",
    "        output['emu_NJetMED'].fill(dataset=dataset, emu_NJetMED=emu_NJetMED.flatten())\n",
    "        output['emu_NJetNONMED'].fill(dataset=dataset, emu_NJetNONMED=emu_NJetNONMED.flatten())\n",
    "        output['emu_TotalCharge'].fill(dataset=dataset, emu_TotalCharge=emu_TotalCharge.flatten())\n",
    "        \n",
    "        output['ee_subleadLepton_pT'].fill(dataset=dataset, ee_subleadLepton_pT=ee_subleadLepton_pT)\n",
    "        output['ee_fwdJet_leadbJet'].fill(dataset=dataset, ee_fwdJet_leadbJet=ee_fwdJet_leadbJet)\n",
    "        output['ee_fwdJet_subleadbJet'].fill(dataset=dataset, ee_fwdJet_subleadbJet=ee_fwdJet_subleadbJet)\n",
    "        output['ee_fwdJet_closestLepton'].fill(dataset=dataset, ee_fwdJet_closestLepton=ee_fwdJet_closestLepton)\n",
    "        output['ee_highpT_sslp'].fill(dataset=dataset, ee_highpT_sslp=ee_highpT_sslp)\n",
    "        output['ee_jetMaxEta'].fill(dataset=dataset, ee_jetMaxEta=ee_jetMaxEta.flatten())\n",
    "        output['ee_minDelR'].fill(dataset=dataset, ee_minDelR=ee_minDelR)\n",
    "        output['ee_NJetMED'].fill(dataset=dataset, ee_NJetMED=ee_NJetMed.flatten())\n",
    "        output['ee_NJetNONMED'].fill(dataset=dataset, ee_NJetNONMED=ee_NJetNONMED.flatten())\n",
    "        output['ee_TotalCharge'].fill(dataset=dataset, ee_TotalCharge=ee_TotalCharge.flatten())        \n",
    "        \n",
    "        return output\n",
    "\n",
    "    def postprocess(self, accumulator):\n",
    "        lum = 35900\n",
    "        \n",
    "        # Calculates the number of events in every file we process.\n",
    "        eventries = {}\n",
    "        sumcheck = 0\n",
    "        for key in fileset:\n",
    "            eventries[key] = uproot.numentries(fileset[key], 'Events')\n",
    "            sumcheck += uproot.numentries(fileset[key], 'Events')\n",
    "            \n",
    "        print(eventries)\n",
    "        print(sumcheck)\n",
    "        \n",
    "        # Cross-sections are found in the draft note. Weights follow the formula of [cross-section * integrate luminosity]/[events]\n",
    "        weights = {'tHq': (lum*0.7927)/eventries['tHq'],\n",
    "                      'tHW': (lum*0.1472)/eventries['tHW'],\n",
    "                      'ttW': (lum*0.6105)/eventries['ttW'],\n",
    "                      'ttWJets': (lum*0.2043)/eventries['ttWJets'],\n",
    "                      'ttZ': (lum*0.2529)/eventries['ttZ'],\n",
    "                      'ttZJets': (lum*0.5297)/eventries['ttZJets'], # cross-section is labaled as 0.5297 / 0.692 ?\n",
    "                      'ttH': (lum*0.2151)/eventries['ttH'],\n",
    "                      'WZ': (lum*4.4296)/eventries['WZ'],\n",
    "                      'ZZ': (lum*1.256)/eventries['ZZ'],\n",
    "                      'ZZZ': (lum*0.01398)/eventries['ZZZ'],\n",
    "                      'WWZ': (lum*0.1651)/eventries['WWZ'],\n",
    "                      'WZZ': (lum*0.05565)/eventries['WZZ'],\n",
    "                      'tttt': (lum*0.009103)/eventries['tttt'],\n",
    "                      'WpWp': (lum*0.03711)/eventries['WpWp'],\n",
    "                   }\n",
    "        scaled = hist.Cat('scaled', 'scaled')\n",
    "        for key in accumulator:\n",
    "            if accumulator[key] != accumulator['cutflow']:\n",
    "                # Scales each dataset along the dataset axis according to weights above.\n",
    "                accumulator[key].scale(weights, axis='dataset')\n",
    "                # Combines keys after scaling.\n",
    "                accumulator[key] = accumulator[key].group('dataset', scaled, {'tHq': ['tHq'], \n",
    "                                                                               'tHW': ['tHW'],\n",
    "                                                                               'ttW': ['ttW', 'ttWJets'],\n",
    "                                                                               'ttZ': ['ttZ', 'ttZJets'],\n",
    "                                                                               'ttH': ['ttH'],\n",
    "                                                                               'WZ': ['WZ'],\n",
    "                                                                               'ZZ': ['ZZ'],\n",
    "                                                                               'VVV': ['ZZZ', 'WWZ', 'WZZ'],\n",
    "                                                                               'tttt': ['tttt'],\n",
    "                                                                               'WpWp': ['WpWp'],\n",
    "                                                                              })\n",
    "        return accumulator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8e5713694fbe40d5bd358d58978ffa66",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, description='Preprocessing', max=119.0, style=ProgressStyle(descriptio…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "output = processor.run_uproot_job(fileset=fileset, \n",
    "                       treename=\"Events\", \n",
    "                       processor_instance=SignalProcessor(),\n",
    "                       executor=processor.futures_executor,\n",
    "                       executor_args={'workers': 4, 'nano': True},\n",
    "                       chunksize=250000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "colors = ['#99CC66', '#669966', '#CC6600', '#FF3300', '#FF9966', '#CC66FF', '#FFCC00', '#000000']\n",
    "\n",
    "\n",
    "stack = True\n",
    "clear = False\n",
    "fill_opts = None\n",
    "overlay = 'scaled'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print('Three Lepton Channel')\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['lll_3rdLepton_pT'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['lll_fwdJet_leadbJet'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['lll_fwdJet_subleadbJet'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['lll_fwdJet_closestLepton'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['lll_highpT_sslp'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['lll_jetMaxEta'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['lll_minDelR'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['lll_NJetMED'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['lll_NJetNONMED'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['lll_TotalCharge'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print('mu-mu Channel')\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['mumu_subleadLepton_pT'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['mumu_fwdJet_leadbJet'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['mumu_fwdJet_subleadbJet'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['mumu_fwdJet_closestLepton'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['mumu_highpT_sslp'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['mumu_jetMaxEta'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['mumu_minDelR'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['mumu_NJetMED'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['mumu_NJetNONMED'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['mumu_TotalCharge'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print('e-mu Channel')\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['emu_subleadLepton_pT'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['emu_fwdJet_leadbJet'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['emu_fwdJet_subleadbJet'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['emu_fwdJet_closestLepton'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['emu_highpT_sslp'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['emu_jetMaxEta'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['emu_minDelR'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['emu_NJetMED'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['emu_NJetNONMED'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['emu_TotalCharge'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print('e-e Channel')\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['ee_subleadLepton_pT'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['ee_fwdJet_leadbJet'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['ee_fwdJet_subleadbJet'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['ee_fwdJet_closestLepton'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['ee_highpT_sslp'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['ee_jetMaxEta'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['ee_minDelR'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['ee_NJetMED'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['ee_NJetNONMED'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()\n",
    "fig, ax = plt.subplots(1)\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "hist.plot1d(output['ee_TotalCharge'], overlay=overlay, stack=stack, ax=ax, clear=clear, fill_opts=fill_opts)\n",
    "ax.set_ylim(0, None)\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for key, value in output['cutflow'].items():\n",
    "    print(key, value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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