datavsmc_plotter.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "import uproot4\n",
    "#import coffea\n",
    "%pylab inline\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.colors import LogNorm\n",
    "import awkward1 as ak\n",
    "from coffea import hist, processor\n",
    "from coffea.nanoaod import NanoEvents\n",
    "\n",
    "from dask.distributed import Client, progress\n",
    "import distributed\n",
    "\n",
    "from condor_utils import make_htcondor_cluster\n",
    "import utils\n",
    "\n",
    "import mplhep\n",
    "plt.style.use(mplhep.style.ROOT)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Category is the loosest selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def getSumWeights(file):\n",
    "    import uproot4\n",
    "    tree = uproot4.open(file)[\"Runs\"]\n",
    "    return sum(tree[\"genEventSumw\"].array())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob\n",
    "background_filesets = {}\n",
    "signal_filesets = {}\n",
    "data_filesets = {}\n",
    "background_filesets[2016] = {\n",
    "    \"GJets40100\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/GJets_HT-40To100_TuneCUETP8M1_13TeV-madgraphMLM-pythia8_16_2____x3/*.root\"),\n",
    "    \"GJets100200\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/GJets_HT-100To200_TuneCUETP8M1_13TeV-madgraphMLM-pythia8_16_2____x3/*.root\"),\n",
    "    \"GJets200400\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/GJets_HT-200To400_TuneCUETP8M1_13TeV-madgraphMLM-pythia8_16_2____x3/*.root\"),\n",
    "    \"GJets400600\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/GJets_HT-400To600_TuneCUETP8M1_13TeV-madgraphMLM-pythia8_16_2____x3/*.root\"),\n",
    "    \"GJets600Inf\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/GJets_HT-600ToInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8_16_2____x3//*.root\"),\n",
    "    \"DYJets\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/DYJetsToLL_M-50_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8_16____x3/*.root\"),\n",
    "    \"ZGToLLG\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/ZGToLLG_01J_5f_TuneCP5_13TeV-amcatnloFXFX-pythia8_17____x3/*.root\"),\n",
    "    \"DiPhoton\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/DiPhotonJetsBox_MGG-80toInf_13TeV-Sherpa_17____x3/*.root\"),\n",
    "    \"ZZ\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/ZZ_TuneCUETP8M1_13TeV-pythia8_16_2____x3/*.root\"),\n",
    "    \"HZ\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/ggZH_HToGG_ZToLL_M125_13TeV_powheg_pythia8_17____x3/*.root\")\n",
    "}\n",
    "\n",
    "signal_filesets[2016] = {\n",
    "    \"signal\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/HHggtautau____x3/*.root\"),\n",
    "}\n",
    "\n",
    "data_filesets[2016] = {\n",
    "    \"DoubleEG\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/DoubleEG_Run2016*x3/*.root\"),\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "background_filesets[2017] = {\n",
    "        \"GJets40100\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/GJets_HT-40To100_TuneCP5_13TeV-madgraphMLM-pythia8_17____x3/*.root\"),\n",
    "    \"GJets100200\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/GJets_HT-100To200_TuneCP5_13TeV-madgraphMLM-pythia8_17____x3/*.root\"),\n",
    "    \"GJets200400\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/GJets_HT-200To400_TuneCP5_13TeV-madgraphMLM-pythia8_17____x3/*.root\"),\n",
    "    \"GJets400600\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/GJets_HT-400To600_TuneCP5_13TeV-madgraphMLM-pythia8_17____x3/*.root\"),\n",
    "    \"GJets600Inf\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/GJets_HT-600ToInf_TuneCP5_13TeV-madgraphMLM-pythia8_17____x3/*.root\"),\n",
    "    \"DYJets\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/DYJetsToLL_M-50_TuneCP5_13TeV-amcatnloFXFX-pythia8_17____x3/*.root\"),\n",
    "    \"ZGToLLG\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/ZGToLLG_01J_5f_TuneCP5_13TeV-amcatnloFXFX-pythia8_17____x3/*.root\"),\n",
    "    \"DiPhoton\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/DiPhotonJetsBox_MGG-80toInf_13TeV-Sherpa_17____x3/*.root\"),\n",
    "    \"ZZ\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/ZZ_TuneCP5_13TeV-pythia8_17____x3/*.root\"),\n",
    "    \"HZ\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/ggZH_HToGG_ZToLL_M125_13TeV_powheg_pythia8_17____x3/*.root\")\n",
    "}    \n",
    "    \n",
    "signal_filesets[2017] = {\n",
    "    \"signal\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/HHggtautau____x3/*.root\"),\n",
    "}\n",
    "\n",
    "data_filesets[2017] = {\n",
    "    \"DoubleEG\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/DoubleEG_Run2017*x3/*.root\"),\n",
    "}\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "background_filesets[2018] = {\n",
    "        \"GJets40100\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/GJets_HT-40To100_TuneCP5_13TeV-madgraphMLM-pythia8_18____x3/*.root\"),\n",
    "    \"GJets100200\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/GJets_HT-100To200_TuneCP5_13TeV-madgraphMLM-pythia8_18____x3/*.root\"),\n",
    "    \"GJets200400\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/GJets_HT-200To400_TuneCP5_13TeV-madgraphMLM-pythia8_18____x3/*.root\"),\n",
    "    \"GJets400600\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/GJets_HT-400To600_TuneCP5_13TeV-madgraphMLM-pythia8_18____x3/*.root\"),\n",
    "    \"GJets600Inf\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/GJets_HT-600ToInf_TuneCP5_13TeV-madgraphMLM-pythia8_18____x3/*.root\"),\n",
    "    \"DYJets\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/DYJetsToLL_M-50_TuneCP5_13TeV-amcatnloFXFX-pythia8_18____x3/*.root\"),\n",
    "    \"ZGToLLG\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/ZGToLLG_01J_5f_TuneCP5_13TeV-amcatnloFXFX-pythia8_18____x3/*.root\"),\n",
    "    \"DiPhoton\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/DiPhotonJetsBox_MGG-80toInf_13TeV-Sherpa_18____x3/*.root\"),\n",
    "    \"ZZ\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/ZZ_TuneCP5_13TeV-pythia8_18____x3/*.root\"),\n",
    "    \"HZ\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/ggZH_HToGG_ZToLL_M125_13TeV_powheg_pythia8_18____x3/*.root\")\n",
    "}    \n",
    "\n",
    "signal_filesets[2018] = {\n",
    "    \"signal\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/HHggtautau____x3/*.root\"),\n",
    "}\n",
    "\n",
    "\n",
    "data_filesets[2018] = {\n",
    "    \"DoubleEG\":glob.glob(\"/hadoop/cms/store/user/legianni/ProjectMetis/EGamma_Run2018*x3/*.root\"),\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "blacklist = [\n",
    "\"/hadoop/cms/store/user/legianni/ProjectMetis/DYJetsToLL_M-50_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8_16____x3/test_nanoaodSkim_33.root\"\n",
    "\"/hadoop/cms/store/user/legianni/ProjectMetis/DoubleEG_Run2016B-2____x3/test_nanoaodSkim_43.root\",\n",
    "\"/hadoop/cms/store/user/legianni/ProjectMetis/DoubleEG_Run2016D____x3/test_nanoaodSkim_10.root\",\n",
    "\"/hadoop/cms/store/user/legianni/ProjectMetis/DoubleEG_Run2016E____x3/test_nanoaodSkim_14.root\",\n",
    "\"/hadoop/cms/store/user/legianni/ProjectMetis/DoubleEG_Run2016D____x3/test_nanoaodSkim_17.root\",\n",
    "\"/hadoop/cms/store/user/legianni/ProjectMetis/DoubleEG_Run2016H____x3/test_nanoaodSkim_20.root\",\n",
    "\"/hadoop/cms/store/user/legianni/ProjectMetis/DoubleEG_Run2016H____x3/test_nanoaodSkim_32.root\"\n",
    "]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "for filesets in [background_filesets, data_filesets]:\n",
    "    for year in [2016]:\n",
    "        for dataset,fileList in filesets[year].items():\n",
    "            for blacklistFile in blacklist:\n",
    "                try:\n",
    "                    fileList.remove(blacklistFile)\n",
    "                except:\n",
    "                    continue\n",
    "            #for file in fileList:\n",
    "            #    try:\n",
    "                 #   uproot4.open(file)\n",
    "                \n",
    "                #except OSError:\n",
    "                #    print(\"{} is bad\".format(file))\n",
    "                #    fileList.remove(file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7321c5b04b024f23a11ce18beb382238",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HTML(value='<h2>UCSDHTCondorCluster</h2>'), HBox(children=(HTML(value='\\n<div>\\n  <style scoped…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Dask stuff\n",
    "cluster = make_htcondor_cluster(local=False, dashboard_address=13349)\n",
    "cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "cluster.scale(100)\n",
    "c = Client(cluster)\n",
    "c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import awkward\n",
    "class BaseProcessorClass(processor.ProcessorABC):\n",
    "    def __init__(self):\n",
    "        self._accumulator = processor.dict_accumulator({\n",
    "            \"sumw\": processor.defaultdict_accumulator(float),\n",
    "            \n",
    "            \"diphoton_mass\":hist.Hist(\n",
    "            \"Events\",\n",
    "            hist.Cat(\"dataset\",\"Dataset\"),\n",
    "            hist.Bin(\"diphoton_mass\",\"Diphoton mass\",500,0,500)),\n",
    "            \n",
    "            \"leading_gamma_pt_normalized\":hist.Hist(\n",
    "            \"Events\",\n",
    "            hist.Cat(\"dataset\",\"Dataset\"),\n",
    "            hist.Bin(\"category\",\"$\\tau$ category\",np.arange(-1,8,1)),\n",
    "            hist.Bin(\"leading_gamma_pt_normalized\",\"$\\gamma_1$~$P_T$/$m_{ \\gamma\\gamma}$\",100,0,10)),\n",
    "            \n",
    "            \"trailing_gamma_pt_normalized\":hist.Hist(\n",
    "            \"Events\",\n",
    "            hist.Cat(\"dataset\",\"Dataset\"),\n",
    "            hist.Bin(\"category\",\"$\\tau$ category\",np.arange(-1,8,1)),\n",
    "            hist.Bin(\"trailing_gamma_pt_normalized\",\"$\\gamma_2$~$P_T$/$m_{ \\gamma\\gamma}$\",100,0,10)), \n",
    "            \n",
    "            \"leading_gamma_eta\":hist.Hist(\n",
    "            \"Events\",\n",
    "            hist.Cat(\"dataset\",\"Dataset\"),\n",
    "            hist.Bin(\"leading_gamma_eta\",\"$\\gamma_1$~$\\eta$\",500,-5,5)),\n",
    "            \n",
    "            \"trailing_gamma_eta\":hist.Hist(\n",
    "            \"Events\",\n",
    "            hist.Cat(\"dataset\",\"Dataset\"),\n",
    "            hist.Bin(\"trailing_gamma_eta\",\"$\\gamma_2$~$\\eta$\",500,-5,5)),\n",
    "            \n",
    "            \"leading_pixel_seed_veto\":hist.Hist(\n",
    "            \"Events\",\n",
    "            hist.Cat(\"dataset\",\"Dataset\"),\n",
    "            hist.Bin(\"leading_pixel_seed_veto\",\"$\\gamma_1$~pixel seed veto\",2,0,2)),\n",
    "            \n",
    "            \"trailing_pixel_seed_veto\":hist.Hist(\n",
    "            \"Events\",\n",
    "            hist.Cat(\"dataset\",\"Dataset\"),\n",
    "            hist.Bin(\"trailing_pixel_seed_veto\",\"$\\gamma_2$~pixel seed veto\",2,0,2)),\n",
    "            \n",
    "            \"max_gamma_ID_MVA\":hist.Hist(\n",
    "            \"Events\",\n",
    "            hist.Cat(\"dataset\",\"Dataset\"),\n",
    "            hist.Bin(\"max_gamma_ID_MVA\",\"Max $\\gamma$ ID MVA\",200,-1,1)),\n",
    "            \n",
    "            \"min_gamma_ID_MVA\":hist.Hist(\n",
    "            \"Events\",\n",
    "            hist.Cat(\"dataset\",\"Dataset\"),\n",
    "            hist.Bin(\"min_gamma_ID_MVA\",\"Min $\\gamma$ ID MVA\",200,-1,1)),\n",
    "            \n",
    "            \"nJets\":hist.Hist(\n",
    "            \"Events\",\n",
    "            hist.Cat(\"dataset\",\"Dataset\"),\n",
    "            hist.Bin(\"nJets\",\"NJets\",12,0,12)),\n",
    "            \n",
    "            \"jet_1_pt\":hist.Hist(\n",
    "            \"Events\",\n",
    "            hist.Cat(\"dataset\",\"Dataset\"),\n",
    "            hist.Bin(\"jet_1_pt\",\"Jet 1 $P_T$\",1000,0,1000)),\n",
    "            \n",
    "            \"jet_1_eta\":hist.Hist(\n",
    "            \"Events\",\n",
    "            hist.Cat(\"dataset\",\"Dataset\"),\n",
    "            hist.Bin(\"jet_1_eta\",\"Jet 1 $\\eta$\",500,-2.5,2.5)),\n",
    "            \n",
    "            \"jet_2_pt\":hist.Hist(\n",
    "            \"Events\",\n",
    "            hist.Cat(\"dataset\",\"Dataset\"),\n",
    "            hist.Bin(\"jet_2_pt\",\"Jet 2 $P_T$\",1000,0,1000)),\n",
    "            \n",
    "            \"jet_2_eta\":hist.Hist(\n",
    "            \"Events\",\n",
    "            hist.Cat(\"dataset\",\"Dataset\"),\n",
    "            hist.Bin(\"jet_2_eta\",\"Jet 2 $\\eta$\",500,-2.5,2.5))\n",
    "        }\n",
    "            \n",
    "        )\n",
    "        self.sumw = sumw\n",
    "    \n",
    "    def fillHistograms(self, output, goodEvents, dataset, weightToFill):\n",
    "        ggMass = goodEvents.ggMass\n",
    "        \n",
    "        #JaggedCandidateArray - one array for each object\n",
    "        \n",
    "        gHidx = awkward.JaggedArray.fromregular(goodEvents.gHidx)\n",
    "        tauHidx = awkward.JaggedArray.fromregular(goodEvents.tauHidx)\n",
    "        \n",
    "        \n",
    "        photons = goodEvents.Photon[gHidx]\n",
    "        \n",
    "        #output[\"sumw\"][dataset] += events.genWeight.sum()\n",
    "        #weightToFill = goodEvents.genWeight * xsecs[dataset] * 1000 * lumi\n",
    "        \n",
    "        output[\"diphoton_mass\"].fill(\n",
    "        dataset = dataset,\n",
    "        diphoton_mass = ggMass,\n",
    "        weight = weightToFill)\n",
    "     \n",
    "\n",
    "        output[\"leading_gamma_pt_normalized\"].fill(\n",
    "        dataset = dataset,\n",
    "        category = goodEvents.Category.lveto,\n",
    "        leading_gamma_pt_normalized = photons.pt[:,0]/ggMass, \n",
    "        weight = weightToFill)\n",
    "        \n",
    "        output[\"trailing_gamma_pt_normalized\"].fill(\n",
    "        dataset = dataset,\n",
    "        category = goodEvents.Category.lveto,\n",
    "        trailing_gamma_pt_normalized = photons.pt[:,1]/ggMass,\n",
    "        weight = weightToFill)\n",
    "        \n",
    "        output[\"leading_gamma_eta\"].fill(\n",
    "        dataset = dataset,\n",
    "        leading_gamma_eta = photons.eta[:,0],\n",
    "        weight = weightToFill)\n",
    "        \n",
    "        output[\"trailing_gamma_eta\"].fill(\n",
    "        dataset = dataset,\n",
    "        trailing_gamma_eta = photons.eta[:,1],\n",
    "        weight = weightToFill)\n",
    "        \n",
    "        output[\"leading_pixel_seed_veto\"].fill(\n",
    "        dataset = dataset,\n",
    "        leading_pixel_seed_veto = photons.pixelSeed[:,0],\n",
    "        weight = weightToFill)\n",
    "        \n",
    "        output[\"trailing_pixel_seed_veto\"].fill(\n",
    "        dataset = dataset,\n",
    "        trailing_pixel_seed_veto = photons.pixelSeed[:,1],\n",
    "        weight = weightToFill)\n",
    "        \n",
    "        output[\"max_gamma_ID_MVA\"].fill(\n",
    "        dataset = dataset,\n",
    "        max_gamma_ID_MVA = photons.mvaID.max(),\n",
    "        weight = weightToFill)\n",
    "        \n",
    "        output[\"min_gamma_ID_MVA\"].fill(\n",
    "        dataset = dataset,\n",
    "        min_gamma_ID_MVA = photons.mvaID.min(),\n",
    "        weight = weightToFill)\n",
    "        \n",
    "        jets = goodEvents.Jet\n",
    "        \n",
    "        output[\"nJets\"].fill(\n",
    "        dataset = dataset,\n",
    "        nJets = jets.counts,\n",
    "        weight = weightToFill)\n",
    "        \n",
    "        output[\"jet_1_pt\"].fill(\n",
    "        dataset = dataset,\n",
    "        jet_1_pt = jets[jets.counts >= 1].pt[:,0],\n",
    "        weight = weightToFill[jets.counts >= 1] if weightToFill is not None else None)\n",
    "        \n",
    "        output[\"jet_1_eta\"].fill(\n",
    "        dataset = dataset,\n",
    "        jet_1_eta = jets[jets.counts >= 1].eta[:,0],\n",
    "        weight = weightToFill[jets.counts >= 1] if weightToFill is not None else None)\n",
    "        \n",
    "        output[\"jet_2_pt\"].fill(\n",
    "        dataset = dataset,\n",
    "        jet_2_pt = jets[jets.counts >= 2].pt[:,1],\n",
    "        weight = weightToFill[jets.counts >= 2] if weightToFill is not None else None)\n",
    "        \n",
    "        output[\"jet_2_eta\"].fill(\n",
    "        dataset = dataset,\n",
    "        jet_2_eta = jets[jets.counts >= 2].eta[:,1],\n",
    "        weight = weightToFill[jets.counts >= 2] if weightToFill is not None else None) \n",
    "        \n",
    "        return output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "class MyProcessor(BaseProcessorClass):\n",
    "    \n",
    "    def __init__(self, year, data = False, sumw = None):\n",
    "        super().__init__()\n",
    "        self.year = year\n",
    "        self.data = data\n",
    "        self.sumw = sumw\n",
    "    \n",
    "    \n",
    "    @property\n",
    "    def accumulator(self):\n",
    "        return self._accumulator\n",
    "\n",
    "    def process(self, events):\n",
    "        xsecs = {\n",
    "            \"GJets40100\":20790,\n",
    "            \"GJets100200\":9238,\n",
    "            \"GJets200400\":2305,\n",
    "            \"GJets400600\":274.4,\n",
    "            \"GJets600Inf\":93.46,\n",
    "            \"DYJets\":6104,\n",
    "            \"ZGToLLG\":117.864,\n",
    "            \"DiPhoton\":88.36,\n",
    "            \"HZ\":0.006185,\n",
    "            \"ZZ\":10.16,\n",
    "            \"signal\":0.029 * 0.0027 * 0.06 * 2,\n",
    "        }\n",
    "        lumis = {2016:35.9,2017:41.5,2018:59.8}\n",
    "        lumi = lumis[self.year]\n",
    "        output = self.accumulator.identity()\n",
    "        dataset = events.metadata[\"dataset\"]\n",
    "        \n",
    "        import os\n",
    "        import psutil\n",
    "        import time\n",
    "        \n",
    "        goodEvents = events[(events.ggMass >= 0)] #no tau selections!\n",
    "        ggMass = goodEvents.ggMass\n",
    "        \n",
    "        \n",
    "        gHidx = awkward.JaggedArray.fromregular(goodEvents.gHidx)\n",
    "        tauHidx = awkward.JaggedArray.fromregular(goodEvents.tauHidx)\n",
    "\n",
    "        if not self.data:\n",
    "            output[\"sumw\"][dataset] += events.genWeight.sum()\n",
    "            weightToFill = goodEvents.genWeight * xsecs[dataset] * 1000 * lumi/self.sumw[dataset]\n",
    "        else:\n",
    "            weightToFill = None\n",
    "        \n",
    "        if \"GJets\" in dataset:\n",
    "            dataset = \"GJets\"\n",
    "        output = super().fillHistograms(output, goodEvents, dataset, weightToFill)\n",
    "     \n",
    "        return output\n",
    "\n",
    "    def postprocess(self, accumulator):\n",
    "        return accumulator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "year = 2016, processClass = signal, process = signal\n",
      "year = 2017, processClass = signal, process = signal\n",
      "year = 2018, processClass = signal, process = signal\n",
      "year = 2016, processClass = background, process = GJets40100\n",
      "year = 2016, processClass = background, process = GJets100200\n",
      "year = 2016, processClass = background, process = GJets200400\n",
      "year = 2016, processClass = background, process = GJets400600\n",
      "year = 2016, processClass = background, process = GJets600Inf\n",
      "year = 2016, processClass = background, process = DYJets\n",
      "year = 2016, processClass = background, process = ZGToLLG\n",
      "year = 2016, processClass = background, process = DiPhoton\n",
      "year = 2016, processClass = background, process = ZZ\n",
      "year = 2016, processClass = background, process = HZ\n",
      "year = 2017, processClass = background, process = GJets40100\n",
      "year = 2017, processClass = background, process = GJets100200\n",
      "year = 2017, processClass = background, process = GJets200400\n",
      "year = 2017, processClass = background, process = GJets400600\n",
      "year = 2017, processClass = background, process = GJets600Inf\n",
      "year = 2017, processClass = background, process = DYJets\n",
      "year = 2017, processClass = background, process = ZGToLLG\n",
      "year = 2017, processClass = background, process = DiPhoton\n",
      "year = 2017, processClass = background, process = ZZ\n",
      "year = 2017, processClass = background, process = HZ\n",
      "year = 2018, processClass = background, process = GJets40100\n",
      "year = 2018, processClass = background, process = GJets100200\n",
      "year = 2018, processClass = background, process = GJets200400\n",
      "year = 2018, processClass = background, process = GJets400600\n",
      "year = 2018, processClass = background, process = GJets600Inf\n",
      "year = 2018, processClass = background, process = DYJets\n",
      "year = 2018, processClass = background, process = ZGToLLG\n",
      "year = 2018, processClass = background, process = DiPhoton\n",
      "year = 2018, processClass = background, process = ZZ\n",
      "year = 2018, processClass = background, process = HZ\n"
     ]
    }
   ],
   "source": [
    "#sumw\n",
    "from collections import defaultdict\n",
    "sumw = defaultdict(dict)\n",
    "for processClass,datasets in {\"signal\":signal_filesets, \"background\":background_filesets}.items():\n",
    "    for year in [2016,2017,2018]:\n",
    "        sumw[processClass][year] = {}\n",
    "        \n",
    "        for process,fileList in datasets[year].items():\n",
    "            print(\"year = {}, processClass = {}, process = {}\".format(year,processClass, process))\n",
    "            weight = 0\n",
    "            for file in fileList:\n",
    "                weight += getSumWeights(file)\n",
    "            sumw[processClass][year][process] = weight"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[####################################### ] | 99% Completed |  9min  9.6ss"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "distributed.utils - ERROR - '<' not supported between instances of 'NoneType' and 'tuple'\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/distributed/utils.py\", line 655, in log_errors\n",
      "    yield\n",
      "  File \"/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/distributed/dashboard/components/scheduler.py\", line 2077, in graph_doc\n",
      "    graph = TaskGraph(scheduler, sizing_mode=\"stretch_both\")\n",
      "  File \"/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/distributed/dashboard/components/scheduler.py\", line 1412, in __init__\n",
      "    self.layout = GraphLayout(scheduler)\n",
      "  File \"/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/distributed/diagnostics/graph_layout.py\", line 42, in __init__\n",
      "    priority=priority,\n",
      "  File \"/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/distributed/diagnostics/graph_layout.py\", line 48, in update_graph\n",
      "    stack = sorted(tasks, key=lambda k: priority.get(k, 0), reverse=True)\n",
      "TypeError: '<' not supported between instances of 'NoneType' and 'tuple'\n",
      "tornado.application - ERROR - Uncaught exception GET /graph (::1)\n",
      "HTTPServerRequest(protocol='http', host='localhost:13349', method='GET', uri='/graph', version='HTTP/1.1', remote_ip='::1')\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/tornado/web.py\", line 1704, in _execute\n",
      "    result = await result\n",
      "  File \"/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/bokeh/server/views/doc_handler.py\", line 52, in get\n",
      "    session = await self.get_session()\n",
      "  File \"/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/bokeh/server/views/session_handler.py\", line 120, in get_session\n",
      "    session = await self.application_context.create_session_if_needed(session_id, self.request, token)\n",
      "  File \"/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/bokeh/server/contexts.py\", line 218, in create_session_if_needed\n",
      "    self._application.initialize_document(doc)\n",
      "  File \"/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/bokeh/application/application.py\", line 171, in initialize_document\n",
      "    h.modify_document(doc)\n",
      "  File \"/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/bokeh/application/handlers/function.py\", line 132, in modify_document\n",
      "    self._func(doc)\n",
      "  File \"/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/distributed/dashboard/components/scheduler.py\", line 2077, in graph_doc\n",
      "    graph = TaskGraph(scheduler, sizing_mode=\"stretch_both\")\n",
      "  File \"/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/distributed/dashboard/components/scheduler.py\", line 1412, in __init__\n",
      "    self.layout = GraphLayout(scheduler)\n",
      "  File \"/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/distributed/diagnostics/graph_layout.py\", line 42, in __init__\n",
      "    priority=priority,\n",
      "  File \"/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/distributed/diagnostics/graph_layout.py\", line 48, in update_graph\n",
      "    stack = sorted(tasks, key=lambda k: priority.get(k, 0), reverse=True)\n",
      "TypeError: '<' not supported between instances of 'NoneType' and 'tuple'\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[####################################### ] | 99% Completed |  9min  9.8s"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Exception ignored in: <function TaskGraph.__del__ at 0x7f4e8dfcb950>\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/distributed/dashboard/components/scheduler.py\", line 1582, in __del__\n",
      "    self.scheduler.remove_plugin(self.layout)\n",
      "AttributeError: 'TaskGraph' object has no attribute 'layout'\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################] | 100% Completed | 11min 53.5s\r"
     ]
    }
   ],
   "source": [
    "background_hists = {}\n",
    "signal_hists = {}\n",
    "data_hists = {}\n",
    "#c = None\n",
    "for year in background_filesets.keys():\n",
    "    background_hists[year] = processor.run_uproot_job(\n",
    "    background_filesets[year],\n",
    "    treename = \"Events\",\n",
    "    processor_instance = MyProcessor(year = year,sumw = sumw[\"background\"][year]),\n",
    "    #executor = processor.futures_executor,\n",
    "    executor = processor.dask_executor,\n",
    "    executor_args={\"nano\":True, \"client\":c,\"workers\":8},\n",
    "    )\n",
    "    \n",
    "    signal_hists[year] = processor.run_uproot_job(\n",
    "    signal_filesets[year],\n",
    "    treename = \"Events\",\n",
    "    processor_instance = MyProcessor(year = year, sumw = sumw[\"signal\"][year]),\n",
    "    #executor = processor.futures_executor,\n",
    "    executor = processor.dask_executor,\n",
    "    executor_args={\"nano\":True, \"client\":c,\"workers\":8},\n",
    "    )\n",
    "    \n",
    "    data_hists[year] = processor.run_uproot_job(\n",
    "    data_filesets[year],\n",
    "    treename = \"Events\",\n",
    "    processor_instance = MyProcessor(year = year, data = True),\n",
    "    #executor = processor.futures_executor,\n",
    "    executor = processor.dask_executor,\n",
    "    executor_args={\"nano\":True, \"client\":c, \"workers\":16},\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "background_hists_final = {}\n",
    "for histName, hist in background_hists[2016].items():\n",
    "    if histName == \"sumw\":\n",
    "        continue\n",
    "    background_hists_final[histName] = hist.copy()\n",
    "    background_hists_final[histName].add(background_hists[2017][histName])\n",
    "    background_hists_final[histName].add(background_hists[2018][histName])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "signal_hists_final = {}\n",
    "for histName, hist in signal_hists[2016].items():\n",
    "    if histName == \"sumw\":\n",
    "        continue\n",
    "    signal_hists_final[histName] = hist.copy()\n",
    "    signal_hists_final[histName].add(signal_hists[2017][histName])\n",
    "    signal_hists_final[histName].add(signal_hists[2018][histName])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_hists_final = {}\n",
    "for histName, hist in data_hists[2016].items():\n",
    "    if histName == \"sumw\":\n",
    "        continue\n",
    "    data_hists_final[histName] = hist.copy()\n",
    "    data_hists_final[histName].add(data_hists[2017][histName])\n",
    "    data_hists_final[histName].add(data_hists[2018][histName])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams.update({\n",
    "    'font.size': 14,\n",
    "    'axes.titlesize': 18,\n",
    "    'axes.labelsize': 18,\n",
    "    'xtick.labelsize': 12,\n",
    "    'ytick.labelsize': 12\n",
    "})\n",
    "\n",
    "fill_opts = {\n",
    "    'edgecolor': (0,0,0,0.3),\n",
    "    'alpha': 0.8\n",
    "}\n",
    "error_opts = {\n",
    "    'label': 'Stat. Unc.',\n",
    "    'hatch': '///',\n",
    "    'facecolor': 'none',\n",
    "    'edgecolor': (0,0,0,.5),\n",
    "    'linewidth': 0\n",
    "}\n",
    "data_err_opts = {\n",
    "    'linestyle': 'none',\n",
    "    'marker': '.',\n",
    "    'markersize': 10.,\n",
    "    'color': 'k',\n",
    "    'elinewidth': 1,}\n",
    "\n",
    "line_opts={'linewidth':3, \"color\":\"black\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['GJets', 'DYJets', 'DiPhoton', 'ZGToLLG', 'ZZ', 'HZ']"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "order"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:280: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  ax.set_ylim(0, None)\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:280: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  ax.set_ylim(0, None)\n",
      "'texgyreheros-regular.otf' can not be subsetted into a Type 3 font. The entire font will be embedded in the output.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import coffea.hist as hist\n",
    "\n",
    "order = [k[0] for k,v in sorted(background_hists_final[\"diphoton_mass\"].project(\"dataset\").values().items(), key = lambda x : x[1])]\n",
    "\n",
    "fig, (ax, rax) = plt.subplots(\n",
    "    nrows=2,\n",
    "    ncols=1,\n",
    "    figsize=(8,10),\n",
    "    gridspec_kw={\"height_ratios\": (3.5, 1)},\n",
    "    sharex=True\n",
    ")\n",
    "fig.subplots_adjust(hspace=.07)\n",
    "ax.set_yscale('log')\n",
    "ax.set_ylim([1e-5, 1e8])\n",
    "from cycler import cycler\n",
    "colors = ['#a6cee3','#1f78b4','#b2df8a','#33a02c','#fb9a99','#e31a1c']\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "\n",
    "rebin = hist.Bin(\"diphoton_mass\",\"$m_{\\gamma\\gamma}$\",100,0,500)\n",
    "new_hist = background_hists_final[\"diphoton_mass\"].rebin(\"diphoton_mass\",rebin)\n",
    "\n",
    "\n",
    "hist.plot1d(\n",
    "    new_hist,\n",
    "    overlay=\"dataset\",\n",
    "    ax=ax,\n",
    "    clear=False,\n",
    "    stack=True,\n",
    "    line_opts=None,\n",
    "    order = order,\n",
    "    fill_opts=fill_opts,\n",
    "    error_opts=error_opts\n",
    ")\n",
    "\n",
    "new_sig_hist = signal_hists_final[\"diphoton_mass\"].rebin(\"diphoton_mass\",rebin)\n",
    "hist.plot1d(\n",
    "    new_sig_hist, overlay = \"dataset\", \n",
    "    line_opts=line_opts, \n",
    "    clear = False,\n",
    "    ax = ax,\n",
    ")\n",
    "\n",
    "new_data_hist = data_hists_final[\"diphoton_mass\"].rebin(\"diphoton_mass\",rebin)\n",
    "hist.plot1d(\n",
    "    new_data_hist,\n",
    "    overlay=\"dataset\",\n",
    "    ax=ax,\n",
    "    clear=False,\n",
    "    error_opts=data_err_opts\n",
    ")\n",
    "\n",
    "hist.plotratio(\n",
    "    num= new_data_hist.integrate(\"dataset\"),\n",
    "    denom= new_hist.integrate(\"dataset\"),\n",
    "    ax=rax,\n",
    "    error_opts=data_err_opts,\n",
    "    denom_fill_opts={},\n",
    "    guide_opts={},\n",
    "    unc='num'\n",
    ")\n",
    "rax.set_ylabel('Ratio')\n",
    "rax.set_ylim(0,10)\n",
    "\n",
    "# add some labels\n",
    "coffee = plt.text(0., 1., r\"CMS Preliminary\",\n",
    "                  fontsize=28,\n",
    "                  horizontalalignment='left',\n",
    "                  verticalalignment='bottom',\n",
    "                  transform=ax.transAxes\n",
    "                 )\n",
    "lumi = plt.text(1., 1., r\"137.2 fb$^{-1}$ (13 TeV)\",\n",
    "                fontsize=16,\n",
    "                horizontalalignment='right',\n",
    "                verticalalignment='bottom',\n",
    "                transform=ax.transAxes\n",
    "               )\n",
    "plt.savefig(\"all_years_mgg.pdf\")\n",
    "plt.savefig(\"all_years_mgg.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:280: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  ax.set_ylim(0, None)\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:280: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  ax.set_ylim(0, None)\n",
      "'texgyreheros-regular.otf' can not be subsetted into a Type 3 font. The entire font will be embedded in the output.\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:280: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  ax.set_ylim(0, None)\n",
      "'texgyreheros-regular.otf' can not be subsetted into a Type 3 font. The entire font will be embedded in the output.\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:280: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  ax.set_ylim(0, None)\n",
      "'texgyreheros-regular.otf' can not be subsetted into a Type 3 font. The entire font will be embedded in the output.\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:280: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  ax.set_ylim(0, None)\n",
      "'texgyreheros-regular.otf' can not be subsetted into a Type 3 font. The entire font will be embedded in the output.\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:280: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  ax.set_ylim(0, None)\n",
      "'texgyreheros-regular.otf' can not be subsetted into a Type 3 font. The entire font will be embedded in the output.\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:280: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  ax.set_ylim(0, None)\n",
      "'texgyreheros-regular.otf' can not be subsetted into a Type 3 font. The entire font will be embedded in the output.\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:280: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  ax.set_ylim(0, None)\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:357: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  rsumw = sumw_num / sumw_denom\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:357: RuntimeWarning: invalid value encountered in true_divide\n",
      "  rsumw = sumw_num / sumw_denom\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:364: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  rsumw_err = np.abs(poisson_interval(rsumw, sumw2_num / sumw_denom**2) - rsumw)\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:364: RuntimeWarning: invalid value encountered in true_divide\n",
      "  rsumw_err = np.abs(poisson_interval(rsumw, sumw2_num / sumw_denom**2) - rsumw)\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:39: RuntimeWarning: invalid value encountered in true_divide\n",
      "  scale[sumw != 0] = sumw2[sumw != 0] / sumw[sumw != 0]\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:378: RuntimeWarning: invalid value encountered in true_divide\n",
      "  denom_unc = poisson_interval(unity, sumw2_denom / sumw_denom**2)\n",
      "'texgyreheros-regular.otf' can not be subsetted into a Type 3 font. The entire font will be embedded in the output.\n"
     ]
    },
    {
     "data": {
      "image/png": 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3tdU+fwLaUrmbvNaybUwBeB/SwSWQ/2Zmh0U72My64Y1yBi96rTFrVKBvN9jcOIzf1jp4KUyTbCSvB/7tY2aX13SwmXXGG2ENsQceUjsT8O5eHzKzg0N3BL6E/x9e983fA5v3wgvUfq5STnDMR7i/vwYAgWb8D4A/m1nrkPM0xvtivj/wYfxfvDuNq81bDjzoAgKtFQGL8fobRwRar4Ll9cRrjiyI/LIreS3wGv+BF3y+GePzYvEyXl/pXXh1f67K/reBM8xsz+AGMzO8/5dgRtFQodfyv8CfQscEBX7/E/CfkG6TcB7Au6OL9OPHmAq//RdvZsbL5k2JPc3MnsQLaKtm7jsO730a9nPDzHqFdGeCF/juGCj/ODMbWOUn4liZMLqaNy32TDN7EC93w12h41588hW/dSPFqjbXsFYCrWv3A4+b2U2Bsu/C+7v6Iczxn+C1VF4KzHIRpovidU0tjqdudR6hmM4/eM2eZXhNStuBGwkzRTFw3A+B48qAI6rsrzb7IGTf4YF9JXgfng44NMxxYWcf4A1GC567FHiYkJHTIcc1APIDbxiHF/D0SPY1ztQfYN/Atd6G13Q6Eq9v8bPA9X8i5NhmeM2Ea/AChpvwBmMtC7wnvgJOCBx7ReD5dwC/D2zri5cOewVeOuU78fq9S4ABIecZEXju/4Cb8Vb23Ig3S+GTkONODbyPv8S7u70Xr7Uh3JTEau/pkP3LA+d7Po7rGPYceF0iDq/PtOq+3QPXcg3e3ftteOOEHCEJpfBa5xzeHWh+YNsheF0iK/Hutv6GdwefsVMS8Zrmnw18jmwMvD9OiHDupTXUzYU8Pp3omRD3iFBOuNkH/fHGpPwaeF9elaDrOwxYUJvrV5trGMN7fUaY7YY3jfxzvM+DL4C/RilndOCajYhyzBuEzGqq07VKxH9AOvzgDfzbGvJGLsKb4vcy3sCOn0L2lRJ++ke0oMACH0DBMlYQJocA0TMa7o+XzSq0Ht8A7+LdGf0X70sndH9+Xa+JfmJ+77TCi/K/CXyprMTrMvpDmGMPxLsD2xQ4/lG8u+C/BN5jowPH7Rx4/23G624IPr8n3t34Krwv7/eA34U5zx/xmjjX4d3198cbnfxhleOOxBujsCbwnnwJ2L3KMTUFBQ8E3m+D4riGkYKCuwJlXxbhebvhjbdZhhcAf1S1Hnij1ycHrvm/Q7bvjzc76MfAz9vAvsl+PwXqFldQoJ8ar++Ogb+tXZJdlwS+xuC0917xlGOBwrKSmXXCuwP7A5Gnh00BrnHe1K2qz38Krx9ugXOuT5j99+A1hwHc45y7Nswx3+GNaH/AOXdlmP15eIOArsGblhLOVuCfeM1uyyMcIxko0G2xA97Yg61V9s0BvnLOnRP2yXU/57/wZgns6mKYSSOSCsxsIl5X0d9rPDgNmbdK603Oud/FVU42BwVBgTnKh+M1T+6Ad1e2BFjivLnMSRfop+uGF0DsiZficjneHdMS59zGSM+VzBUYzLgWr3XhmpDt++ONxj/bOedbn7eZtcV7373gnPtzyPY8vL+dWKxx0fvwRXxnZgfidSlVnU2QEczsTbxcHG/EVU4GXhuRrGJmj+PNpPkn3syCdnhTqYrxEif5cjdvZg/jDTI7AOjjnPs0ZN+fiG0mD8BfnHO1WvJWxA+Bv5W3nXOvJ7sufjKzPsAdzrmBNR5cU1kKCkTSm5k1wctqeQ5ea9cq4GO8ZWyrznyI5zzf4aVVvsk590SVfR2B/WIs6nPn3IqaDxOR+qagQERERIAsSF5klZfpFBERyRrOOav5qN9kY/IiERERCSNrgoJEzQ296KKLVG7g58ADD0yrOifyWiSq7HS7xun4/6drnL7XOB2vRaLKrausCQpEREQkOt/GFJjZAXhBxnwXw8qDIiIiklpq3VJgZg3M7GYzeydk2wS8hSMKgdmBVctEREQkjdSl+2Ak3gpRO4G3ghZwId7a2hcAXfEWZREREZE0Upeg4By8xV/6Bh7/AW9RmEudc0/jLURyoj/VS32DBw9WuQmWjtci3a5zOl4LXePEl51u1xjS71qk2jWudfIiMysG/uacGx94PA1vWc1jA49H4mU8a+53ZesimKcgntGYEpu+ffsyd+7cZFcjo+kaJ56uceLpGieemZeewNVDnoJVBNKZmlkr4HfA1JD9PfGWbxQREZE0Upeg4DVgiJndDbyDt1rfq2bW3MyuAE7GW+NcRERE0khdpiSOxVvC90rAAdc5574zs/2A+/CWHNZAQxERkTRT66DAeeug/8HMcoEy59zWwK7v8AYfLnTOlfhYRxEREakHdclT8KSZDXDOFYcEBDjnNjnn5gH9zOx+X2spaWH48OHJrkLG0zVOPF3jxIvnGg8YMAAzq/jZYYcdyM/P55NPPvGxhtkrptkHZtYIaAoYsB64Bng8zKENgBuAy5xzef5Vs+40+0BEJHMMGDCA/fbbjxEjRuCc4/vvv+eFF17gueee49133+Wwww6rsYxOnTpxxx13cOaZZya0rk8//TR33HEHixYtSuh5wqnr7INYuw9uBEaFPL478BO2LsDM2lRCREQkVm3btqVLly4A7LXXXhx55JGYGSNHjmTmzJnJrVyai7X7YCYwBrgt8Lgg8Djcz5VAYsMvERGREFdeeSUffPABK1asYPny5Zxwwgm0atWK1q1bc+KJJ/L9998DXivBsmXLGDp0KGPGjAFg+vTpHHjggTRv3pxddtmFv/71r2zfvh2AoqIiLrjgAnbeeWdat27N6aefzvr16yvO+95773HQQQeRm5tL7969ee+99wCvleC8887jq6++qrhrTwt1WI5xOnBSopa9TMDykc57mSIiku6OPPJIN3r06Grby8vLXaNGjdzMmTPd4MGD3SGHHOLef/99984777iuXbu68847zznn3LJly1yHDh3cAw884NauXeu2b9/uWrdu7S644AL38ccfu2effdY1atTI/etf/3LOOXfNNde4zp07u7ffftu9++67rnPnzu66665zzjk3f/5816JFCzdhwgS3YMECd/fdd7vWrVu7hQsXuo0bN7o777zTde7c2S1ZsqT+LlBAyHdfrb4z6zL74Cg/gxIREZF4BQcd/vjjjwwcOJAjjjiCXr16AXDqqafy8ccfA7DHHnvQqFEjdt11V9q0acPGjRu55pprGDFiBC1atKB///488sgjLFu2DIBFixZx+OGHc8IJJwDw8ssvs3nzZgDuu+8+Lr/8ci666CIA9t9/fz777DMefvhhHn30UXbZZRcaN25c0dWRDmodFAQGHd4EHANESmXsnHN9I+wTERHxlXOOtWvX0q5dO8444wzef/993n77bT777DMmT57MAQccEPZ5LVu25PLLL+edd97h888/Z+7cucyePZvjjz8egPPPP5+zzjqLL7/8kiFDhjB48OCKsr788ksmTZrEPffcU1FeaWkpAwcOTPwLTpC6JC+6A2/cwK/AIqDM1xqJiIjU0tdff01JSQmdO3dmyJAhLFmyhD/84Q+cdNJJtGvXLuKUxR9//JEjjjiC3XffnaOPPpq//vWvFBcXV+w/9dRT+eabb3j11VeZNm0at9xyC1dddRV33XUX27dvZ+TIkdVmMTRvnhJL/9RJXYKCM4CPgaOdc1t8ro+IiEit3X///QwYMICioiLefPNNVqxYQceOHQH46KPImfdff/11ysvLeffddysGBN54440V+++55x6OPPJIrrzySq688kqee+45Lr74Yu666y66d+/O999/z957711x/Lhx49h///0rzp1u6hIUNATeUEAgIiLJsHbtWr799lucc6xatYqJEyfy7LPP8t5779G8eXPMjOeff54BAwbwzjvv8OSTT9K+fXtWrFjB7rvvToMGDVi8eDEbNmwgNzeXH374gbfeeou8vDyeeeYZvvjiC7p3786GDRv4+OOPee2117jtttto0qQJzz77bMVYhREjRnDkkUeyzz77cNhhhzFlyhTGjx/PvHnzAGjQoAFr1qzh22+/TZ9xBbUdmQi8ADxT2+cl6wfNPhARyRhHHnlkxch6wLVp08YNHDjQffLJJxXHPPDAA26XXXZxO+20kzv//PPdZ5995rp06eKuueYa55xz48ePdy1btnR33XWXKy0tdeeee65r2bKl69Klixs/frx788033S677OJee+01t2zZMjdw4EDXsmVL17p1a3fiiSdWmk3w2muvuf3228/l5ua6Pn36uKlTp1bsW7VqlevZs6fLy8urvwsUQB1nH8SU0TCUmXXGm5b4APCwc267XwFKIiijoYiIZJu6ZjSsS1DwBrADcAiwFVgW+DeUcyky+0BBgYiIZJtEpzkO1QIoAT6ow3N9Z2ZXAicFHrYExjrnXk9ejURERNJTrVsKUpmZPQf81Tm3IWSbWgpERCSr1LWloNZLJ1c5aQczO8DMWsdTjh/M7DBgXmhAICIiIrGrU1BgZgPNbDGwApgDHGJmh5rZx2Z2uB8VM7M3zGyfkMcHmdl8M1tjZk8EMiuGugT4ux/nFhERyUa1DgrM7PfAW8Am4Ga8pZIBlgfKe9fMDq5rhcysn5ndCQwO2dYQeB0vm2J3oCNwdcj+3YBNzrmqAx5FREQkRnVpKbgFWAIcCjwT3Oic+wE4LLBvdBx1OhhvTYWikG1HASudcy86534BxgHDQvbn402TFBERkTqqy+yDg4AHnHMlVdeIDmybDFxY1wo55x4CMLNBIZu7AAtDHi8EOoc8zgf+Eq3cvn1jnyE5fPhwhg8fHvPxIiIiiTZhwgQmTJiQ0HPUJSjYCORE2b+d6nkL4tWGyi0Hm4A8M2vknCt1zp1SUwFz5871uUoiIpJO/t//+38UFhby3HPP+VruBx98wMiRI/nPf/7ja7lV1eaGtepNe6zq0n1QCJxtZs3CVKIVcA7g9zfwOrz8CEEtgc3OuVKfzyMiIhnqsssu8z0gyDR1CQquxbtznwtchJdf+SgzG4nXrL8DcINvNfQsBXqFPO4V2CYiIlLNhg0buOCCC9hnn33o168fzzzzDE8++STnn38+AJ988gkHHXQQe++9N5dccgm9e/dm+fLlfPDBB5x00kmMGDGCrl27csQRR7BgwQIAvvjiCw466CB22203dtttN+69994kvsLEqHVQ4JxbDvwO+BZv0KHhzQS4DW+Q4RHOua/8rCTeIMKOZnaGme2EN+vheZ/PISIiCWJmvv7U5Nlnn2XdunUsXLiQp59+mqeeeqpi3/bt2zn99NMZM2YMixcvpnfv3nz66acV+wsKChgyZAhff/013bt35+9//3tFmX/84x/5/vvv+d///sett96acYnx6pSnwDm3yDl3EpCLd9feG2jhnBvgnPvEx/oFz1cKDAFuAoL5ETIvRBMREV8ceeSRFBYWct1117Fs2TIKCgoq9i1evJgtW7aQn58PwLBhw2jY8Lchdh07duSoo47CzDj00EPZsmULAHfccQeHHHIITz31FHfccQebN2+mvLy8fl9YgtUlT8F9ZtYHwDm3zTn3pXPuM+dcsZ8Vc851cs59EfJ4tnOut3OurXPuIo0nEBGRSHr16sWCBQvYd999mTRpEvvssw9bt3pj4MvKyiq1NlRtfejQoUPYMi+88ELGjRtHkyZNuOSSSxL7ApKkLrMPLgcuN7Ov8PIUvOCcW+lvtUREJJPUdzP7yJEj+eWXX3jsscc47bTT6Nq1K9u3bwege/fu5OTkMHXqVI4//nhefPFFSktrvs985ZVXmDVrFt26deP5570e7Fiel07q0n3QEbgSWAOMB74zs+lmdr6ZtYj+VBERkcQbPnw4CxcupH379vTo0YMLLriAvLw8ABo3bszLL7/MDTfcQM+ePSvGDuy4445Ryxw/fjynnXYavXr1YsmSJZx00klcfPHF9fFy6k1cqySa2a7AqcBpwO/xllR+E3jGOTfFlxrGSaskiohIVddeey1XXXUV7dq149NPP+Wcc87hs88+S3a1fFPXVRLr0n1QwTn3I/AI8IiZ7QKMxctmeDrRExyJiIgkzT777MMf//hHfv31V8rLyytmGGS7eFsKcoAj8GYGnIzXtbAZeNs5d6YfFYyXWgpERCTb1LWloNZBgZnl4q01cDJwItCKQCAAvAxMcc5tqVWhCaSgQEREsk19dh+sARoBxcBkvECgQMsWi4iIpLe6BAWv8lsgsK3qTjNrCDRzzm2Kt3IiIiJSf2qckmhmr5rZ8cHHzrmzgfeA4Wa2R5inDAfW+1ZDERERqRextBT8AZhWZVsr4AG8tQ6W+1wnERHJQMefcCI/rFodVxkd2rfjnSlv+1QjqSqeKYl1W6xZRESy0g+rVnPPpIKaD4zimqH5MR1nZnTp0gUzo6SkhC5dunDffffRu3dvZs+ezVFHHcXcuXPp3r17xXPOOussmjRpUmnxpLKyMho2bFjjYPU33niD3XffnT59+tTthaWIuPIUiIiIpKrFixeTk+OlzJk2bRr5+fnMmzePfv36cfnll/PnP/+ZmTNnYmZMnz6dmTNn8sUXX9RQanivv/46hx12WNoHBXVaJVFERCSdHHPMMZx77rk8+uijAIwaNYr169fzxBNPUFJSwiWXXMLf//532rRpE7Wcv//973Tt2pUuXbowdOhQNm7cyJNPPsmrr77KjTfeyMsvv8yMGTM47rjj6NatGyeffDJLliypj5foCwUFIiKSFfr27cuXX34JeOsfPP3009x8881ce+219OnThyFDhkR9/owZM3jxxReZO3cuixcvpnv37lxwwQX86U9/4tRTT+X222/n9NNP59prr+WSSy7h66+/5ne/+x1vvvlmPbw6f6j7QEREslLv3r255JJLePjhh1m0aFGNx0+ZMoXFixdz8MEHA954g2bNmlU7Lj8/n9tuu43ly5dz/PHHs99++/le90SJtaVgLzP7ffAHODiwvVfo9sC+rompqoiISN3NmTOHnj17Vto2YMAAevTowU477VSx7ZprrmHOnDkAlJSUVGwvLy/nyiuvZNGiRSxatIgvv/ySDz/8sNp5xo4dyxNPPEFpaSkXXHABN9xwQ4Jekf9iDQquAGaG/Lwc2H5nle0zgct9qpuIiIgvpk2bxjPPPBPTUse//PILTz/9NGVlZUyZMoVu3boBcOyxx/L000+zZs0aysrKGDFiBGPGjKl43vbt2wHo1KkTRUVFXHPNNYwcOZKpU6cm5kUlQCzdB+cluhIiIiJ+23vvvSumJHbq1IkpU6bQrl27Gp83evRo/vjHP7Lrrruy66678uSTTwJw/PHH8/nnn9O/f39KSko4/PDDufvuuwE4/PDDue2222jfvj3jxo3jnHPOwTlH27ZteeCBBxL5Mn0V1yqJ6UALIomIpAYlL6o/9bZKYrpRUCAiItmmrkGBpiSKiIgIoKBAREREAhQUiIiICKCgQERERAIUFIiIiAigNMciIlJPjjj2eFZ+vyquMjru1p4P3nvHpxpJVQoKRESkXqz8fhX7/PXvcZXxxSOXxHxseXk5Dz74IC+88AJr1qyhpKSE4447jr/97W/suuuulY7t2LEj//3vf9ljjz0ilvfBBx9QXl7OgAED6lz/VKfuAxERyUgXXXQRhYWFvPPOOyxdupTPPvuMpk2bcuyxx1JeXl7r8mbOnMn06dMTUNPUoZYCERHJOJ9++ikffPABX375JY0bNwagbdu2PPLII6xatSpqQrtXX32VW265hS1bttCzZ08mTJjA559/zkMPPVSRuvjoo49m5MiRLF68mN13353x48fTr1+/+np5CaOWAhERyTgff/wxRx99dEVAMGXKFHr06EHPnj056KCD+Oijj8I+7+uvv+bWW29l5syZfPvtt5xyyimcfPLJHH/88YwYMYK//vWvXHnlldx2220cddRRLF68mHPPPZeXXnqpPl9ewqilQEREMk5paSk5OTkVj0844QROOOEEAA444ABKS0vDPu+9997jxx9/5IgjjgC8FPlr1qypWAEx6Pjjj+euu+5i69atDBgwgLPPPjtBr6R+qaVAREQyzgEHHMCMGTOqfZn/8ssvLFq0iLlz5zJ58uSK7SUlJZgZ5eXlnHHGGSxatKji5+uvv6Zhw8r30BdeeCFvvfUWubm53HTTTQwbNqxeXleiKSgQEZGMc+ihh9K9e3cuvPBC1q9fD3gBwbnnnkuTJk2YPHkyTzzxBNu2bWPOnDls2bKFdu3acdRRR/H666+zfPlynHPceeed/OlPf6ooNxhkHHHEEcyePZvLLruMe++9l6lTpybjZfpO3QciIpKRJk2axPjx4zn00EPZvn07u+yyC7feeitdunThyCOP5J///CcdO3akRYsWPP300zRq1Ih99tmHu+66i4EDB7J582b2228/nnzySQAOPvhghg8fzp577snIkSO59NJLufnmm2nevDkTJkxI8qv1h5ZOFhGReqHkRfWnrksnKygQERHJMHUNCjSmQERERACNKfBNWVkZBQUFzJ8/nz59+pCfn19pOoyIiEiqU1Dgg7KyMgYOHEhhYSHFxcXk5ubSv39/pk6dqsBARETShroPfFBQUEBhYSFFRUU45ygqKqKwsJCCgoJkV01ERCRmCgp8MH/+fIqLiyttKy4uZsGCBcmpkIiISB2o+8AHffr0ITc3l6Kiooptubm59O7dO3mVEhFJMcefeByrVv8QVxnt23Xgnbff9alGUpWCAh/k5+fTv3//amMK8vPzk101EZGUsWr1Dzw8+fq4yrh00J0xHTdjxgyGDx9eadvPP/9Mly5dmDdvHs8++yx///vf+eWXX9i8eTOHHXYY48aNo1u3btxxxx0VCYt++OEH2rRpQ/PmzQFv9cXg71WNGTOG7du3M3bs2Erbly9fzmGHHcbKlSvDPm/OnDnccsstfPfdd2zcuJFu3bpx0003MXDgwJheq58UFPggJyeHqVOnUlBQwIIFC+jdu7dmH4iIJNGAAQP45ptvKh4vW7aMfv36MWrUKMaOHcvMmTN58cUX2X333dm0aRMPPfQQv//97/n222+54YYbuOGGGyrKGTlyJEcffXRC6jljxgwuuuginn76aX73u99RWlrK1KlTOe2003jvvfc4+OCDE3LeSBQU+CQnJ4dBgwYxaNCgZFdFRERCFBcXc/LJJ3PppZdyyCGH8Oc//5kvvviCHXbYAYAWLVpw8803c/7551cstRzNlClTuP7669m8eTO77bYbjz32GN27d69T3a6++moee+wxfve73wHQqFEjBg0axLJly2Kqi9800FBERDLaeeedx1577cUtt9zC/Pnz2X///SsCgk8//ZQePXrQo0cP+vXrx0svvRS1rJ9//pmhQ4fy/PPP8+233zJs2LA6L5u8ZcsWFi9ezIABAyq27b///vTo0YO+ffty3XXX1anceKiloBYO6n8wW7eVVNteUrKNDevX06p1axo3blLj/tatWvGfD2bUR5VFRLLauHHj+Oqrr5g1axZmRmlpaaWu3f33359FixYBcMopp7Bt27ao5RUWFtKjRw/2228/AP7v//6Pyy+/nA0bNtS6btu3b8fMKlISgxekADz00EPMmTOn1mXGS0FBLWzdVsI9k+LPPXDNUA1AFBFJtLfeeosHH3yQwsJC8vLyAOjduzdz585l48aNtGzZsuLYbdu2UVhYyIknnlhjuaFf4sHH5eXlta5fixYtaN++Pf/73/8qug+CPvzwQ5o1a1brMuOl7gMREck4ixYt4txzz2XixIl07ty5Yvtuu+3G2WefzdChQ1m1yluxsaioiOHDh7Nly5Yay+3fvz9ffvkln3/+OQDPPvssPXv2pE2bNnWq51133cX5559f0SpQXl7OI488wowZyWlNVkuBiIhknHvuuYfNmzdz8cUXV9reuXNnCgoKeOihhzj++OPZvHkzO+64IyNGjKjoEohm5513ZtKkSZx11lls3ryZjh07MnHixIr9999/P0888UTF4wEDBnD77bezatUq2rVrV6mszz77jCFDhtC8eXOuvPJKvv/+e9q0acOJJ57I22+/zSOPPBLnVai9tF862cy6Ay8AG4Ai59zgKvt9Wzp5394H+NZ98PmCeXGXIyKSTpS8qP7UdenkTGgp6Ao85Jz7V7IrIiIikenLPPVlwpiCTsDpZvZfMzsn2ZURERFJVykbFJjZG2a2T8jjg8xsvpmtMbMnzKxRYNcSYBQwGLjCzNomo74iIiLpLuWCAjPrZ2Z34n3JB7c1BF4H7gC6Ax2BqwGcc1Occ3Odc+uAj4A967vOIiIimSDlggLgYKA5UBSy7ShgpXPuRefcL8A4YBiAmU0ws/5mlgPsByyt7wqLiIhkgpQbaOicewjAzEIXEegCLAx5vBAITjy9C/h/QDvgUefc+nDl9u3bN+Y6DB8+vNrqWiIiIsk0YcIEJkyYkNBzpFxQEEEbKrccbALyzKyRc24JUGOKwLlz5yaqbiIiEoMBA49k5Q/hlw+OVccOHZkxdaY/FUoztblhrZp1MVbpEhSsw2stCGoJbHbOldZnJZYuW8F5g46Ku5yNv/7kQ21ERNLLyh9WcsgdsbfahjPrhthu8MyMLl26YGaUlJTQpUsX7rvvPnr37g3AkUceyYgRIzjllFMqHbtp0yZ22WUXHnzwQY488kiefvpppk2bxrPPPhtzHZcvX8706dM5//zz6/ISkypdgoKlwHkhj3uRhLEDZRhd//Jw3OXMHneGD7UREZFoFi9eXLH40bRp08jPz2fevHm0a9eOmTNnhj22rKyM+++/n6FDh7J69eo6nXfZsmX885//TMugIBUHGoYzHehoZmeY2U7AzcDzSa6TiIikiWOOOYZzzz2XRx99FIDf//73fPDBB9WOy8nJ4f/+7//46aefWLNmDQAbN27kjDPOYM899yQ/P5/vv/8e8FZM7NevH126dOGggw5i1qxZrFu3jrPPPpu5c+cydOhQAG6//Xa6du1Kly5dOOecc9i4cSPgpUB+/PHH+f3vf88ee+zBjTfeWB+XIqq0CAoC3QRDgJuAxcAK4F4/yi4rK2Py5MmMHTuWyZMnU1ZW5kexIiKSYvr27cuXX34Z9ZitW7fyj3/8gz322IMdd9wRgClTpjB+/HiWLFnC9u3beeGFFygpKeG0007j1ltv5dtvv2Xs2LGceuqpNG/enOeff56+ffsyadIkpkyZwpNPPsmcOXNYsmQJZWVljBkzpuJ8r7zyCtOnT+eDDz7g3nvvrVikKVlStvvAOdepyuPZQG8/z1FWVsbAgQMpLCykuLiY3Nxc+vfvz9SpUyutty0iIpltn332wczYvHkze+yxB6+99lrFvsMPP5yuXbsCcPDBB7NlyxYWL15MaWlpxVLLxx9/PGbGV199Vanc999/n1NPPZXWrVsDcN5553H99ddX7D/77LNp1KgRe+65Jx06dIhppcZEStmgoD4UFBRQWFhIUZE3saGoqIjCwkIKCgoYNGhQDc8WEZF0MmfOHHr27Bl23xdffBHxZrB9+/Zht1cd4W9mlJeXRz2u6jEdOnSosd71KS26DxJl/vz5FBcXV9pWXFzMggULklMhERFJiGnTpvHMM89UW0q5rvbee28aNmzIlClTAO8ms7y8nB49egCwfft2AI4++mheffVVNmzYQHl5OU899RRHH320L3VIhKxuKejTpw+5ubkVLQUAubm5FVNWREQkfe29994VUxI7derElClTaNeunS9lN27cmFdeeYVLL72UESNG0LZtW1599VWaNm1Kjx49+OWXX7jwwgt54oknWLBgAX379qW8vJzf/e53jB492pc6JII555Jdh4QyMwcQ7nXWdkxB09Y70W/kS3HXafa4M9i6/pe4yxERSSdKXlR/gl0WzrlaZTHK6paCnJwcpk6dSkFBAQsWLKB3797k5+drkKGISALoyzz1ZXVQAF5gMGjQIA0sFBGRrJfVAw1FRETkN1nfUpBqysrKKCgoYP78+fTp00fdGSIiUm8UFKQQJVMSEZFkUvdBCglNpuScq5RMSUREJNHUUpBCoiVT0kBIEUl3gwcOZPUPP8RVRrsOHXhr6lSfaiRVKShIIUqmJCKZbPUPP/Dx2NviKuPgW26N6bgZM2YwfPjwStt+/vlnGjRoULHQUdC6desoLy9n7dq1cdUtEygoqIUct4WvHr0w7nLKt25g2bJl7LnnnpW25+fns99++zF37lxKS0srxhTk5+dXHLNs2TJeeumlimU8RUSkugEDBvDNN99UPF62bBn9+vXj8ccf5+STT67Yvm7dOvr168eIESOSUc2Uo6CgFho1asD4l6+Ku5yrj74+7Bf6ypUrGTx4MBdccAGrV6+ulkxJAYGISO0VFxdz8sknc+mll1YKCMrKyhg6dCiHHXYYl112WRJrmDqyJiio6Qs1lv1+aZDTgH17H1BpW0nJNjasX0+r1q1p3LgJAC++8ho3jry12v5nX5gEQOtWrfjPBzN8q5eISCY677zz2Guvvbjlllsqbb/++uvZuHEjb775ZpJqlnqyJiiINyB46aX41zwIapCTwz2T4p9RcM3Q/JoPEhHJYuPGjeOrr75i1qxZlZYwfu6555g4cSJz586lSZMmSaxhasmaoODJfz1dcYcdKtwdeKT9IiKSPt566y0efPBBCgsLycvLq9g+d+5cLrvsMt555x3fVk3MFFkTFDz02vS4yxh2RHcfaiIiIom2aNEizj33XF566SU6d+5csf2nn37iD3/4A/fffz/9+/dPYg1TU9YEBSIikj3uueceNm/ezMUXX1xp+9KlSzEzxo8fz/jx4yu2N27cmC+++KK+q5lysiYoOG/QUT6UUqtlqUVEJES7Dh1izjMQrYxYPPnkkzz55JNxnSsbZU1Q0PUvD8ddhh85CkREspUyEaY+rX0gIiIiQBa1FKQW86U7Y+OvP/lQFxEREY+CgiRomNfGl+6M2ePO8KE2IiIiHnUfiIiICKCgQERERALUfSAiIvXixCOOYPXKlXGV0a5jR97+4AOfaiRVKSjIUGVlZRQUFDB//nz69OlTabVFEZFkWL1yJQV7x5cZNn/xVzEdZ2Zs37690ufeLbfcQsOGDRk1ahT9+vVj3bp1Ffu2bt3K999/z6effsp+++0XVx3TmYKCWtiwZhUjh47xoZxNPtQmsrKyMgYOHEhhYSHFxcXk5ubSv39/pk6dqsBARASYPXt2xe/OOU4//XT69evHvvvum8RaJZ+Cgtpo4Ogzrlfcxcz4y/98qExkBQUFFBYWUlRUBEBRURGFhYUUFBQwaNCghJ5bRCTdjB8/nsWLF1dbSTEbKSjIQPPnz6e4uLjStuLiYhYsWKCgQESyxj777FPpS/6XX37hsssuq3TMm2++GXYlxWyloCAD9enTh9zc3IqWAoDc3Fx69+6dvEqJiNSzL774otqYglCLFi3ivPPO4+WXX660kmI205TEDJSfn0///v3Jy8vDzMjLy6N///7k5+cnu2oiIilh/fr1nHzyyYwaNYqjjz462dVJGWopyEA5OTlMnTqVgoICFixYQO/evTX7QEQkoLy8nKFDh3LooYdy+eWXJ7s6KUVBQYbKyclh0KBBGkMgIlLFRx99xNSpU9l9993p2rVrpX0vv/xyVne1KigQEZF60a5jx5jzDEQrIxbOuWrbxo4dG3W/KCjIOMuWLeOll17ijDPOYM8996z1fhGRRFEmwtSngYYZRAGBiIjEQ0FBhkhUQFBWVsbkyZMZO3YskydPpqyszL9Kh7Fs2bKI2++666467/ejXsk8v4hIfVD3QRI0MOOrRy+Mu5wct4V9ex9ASck2NqxfT6vWrXn2hUnVjqtpf+tWrfjPBzOqbU9GuuS6BDSJbgGJ9/zLli1Ty4yIpAUFBUnQcocWjJt0VdzlXJ9/Cz+u28TWoo00zWvJxhKgZFulY7aXltS4f/HixWG/uAoKCpg1axabN28GwqdLTvUv5GSfP7j/uuuu871uIiJ+U1CQxhrmtaH7xRPiLqfwtlPDfqFNnz69IiAICk2XnOpfyH7wIyA444wzElI3ERG/ZU1Q4EdzfYMMXSjDGlTvCli2bBnr1q2jefPmlQKDYLrkRH0h//6IAazfsCFhXSK15UdAoK4Dkcr095O6siYoGP9y/M31fiybnA6Cf5AjR45k5cqV1cYU9OjRI2F/sOs3bOCaex/jPwVv8vv8k9i1w+7VjvnxhxU17r/n6j/7Uh8FBCL+qq+/n2nTpnHzzTezevVqmjRpwsEHH8z999/PjjvuyKeffsrSpUv5wx/+ELWMN954g913350+ffpEPa5Tp05MmzaNLl26VGx78skn+e9//8tTTz1V59eQDJp9IJWE/kF26dKFqVOnMnHiRG677TYmTpzIY489xquvvpqwWQwlJdviDgj+U/BmzPWqLQUEInXnxxidWKxZs4azzz6bBx98kOXLl7No0SI6dOhQsULiggULeO2112os5/XXX2fevHkxnTNTKCiQCuH+IIPpkkeOHEmvXr2iBgSRpuUFZzGceeaZ3HrrrZx55pkMHDiwWmCwbNkyNqxfH3dA8Pv8k+p8DaJRQCASHz/G6MRizZo1NGzYkD59+mBmNGzYkOuvv56TTz6ZhQsXct111/H6669zzTXXUFZWxkUXXUT79u1p164dJ554Ihs2bODJJ5/k1Vdf5cYbb+Tll1+O63Wff/753HfffRxzzDHsvvvuXHTRRWzfvh2ASZMmsc8++9ChQwdOO+20asve17es6T6QyMyMvXvuE1cffknJNkq2bmXG9PdrnMWwefPmiLMYWrVuHXdAEG5/vBQQiMSvvgbtduvWjSFDhtC5c2cGDx7MYYcdxjHHHMPQoUMBuOuuu5g2bRr33HMPc+bMYcWKFSxfvpycnBxOOOEEJk+ezJ/+9Cf++9//cthhh3H66afH87IBePrpp/noo4/Yvn07Xbt25fzzz2eHHXZgxIgRfPrpp+y4446cffbZPPzww1x//fVxn6+uFBQIeS1b8fsTTon7Dr1w+lQGDzml2v7VP3xfbRZDUVERf7poODvvsmulgKNF6x3C1nHXDrtz+oWXRnwNNe2Ph/IUiPijPsfoPPLII9x66618+OGHzJgxg+uuu44RI0Zwww03VDruoIMO4l//+hdvvPEGixcv5osvvmDr1q21fGU1O/XUU8nLywOgV69ebNmyhWnTpjFgwADatWsHwLPPPktpaanv564NBQXC1qKNvjTZh/tS/vGHFTz/8L18OPVNtm3ZUrG9afPm/PXWO9mjW/eE3uHHS3kKRBInUQHBO++8w+rVqzn//PM5/fTTOf300xk9ejR77703f/3rXysd+95773HllVdy4YUXcthhh/HZZ5/V+nU0bdqULSGfbwBbtmyhWbNmFY87dOhQ7XllZWU0bNiw0uMtW7ZUBA/JkDVBgR8zB6ypDxVJQU1b78wNfz6v2vbQxEdvv159UE5N+4OcczgMzMA5MKPcwd/vuR0LTPMMPr9Vq5Y8+PzrYcspKytj7ofvs2TRQvbq0Yu+hx+dsMyKQcpTIJIYieyS23HHHbnooovo27cv++67LwBLliyhefPmNG/eHKCiT//tt9/mxBNP5IorrmDp0qXMmTOHAQMGVJQVPC6aY445hgcffJDx48ez88478+WXX/LUU09xyy23RH3egAEDGDt2LD/++CM77bQTl156Ke3bt2fcuHG1er1+SvugwMx2A14FmgH3Oef+Fe64PuN61We10kqPix+qtm3r2h/55dOZdNr/SJq23bXW+6ty5WWs/Wo2xauWkNt+L9p27xc2P8LXT17LeYOOqv5851i3ejklW7dUBBaNmzajTbs9KgKLUBt//anGOsVCeQpE/Jfov5++ffty//33c95557Fu3TqaNWvG7rvvzttvv01OTg4HHHAAo0aNYtSoUVx44YWMGDGCvfbai7333ps///nP3HHHHZxyyikcfvjh3HbbbbRv357S0lIeeughZs6cWe18d955JzfddBMHHXQQ27dvp3Xr1lxxxRUMGTIkaj333Xdf7rrrLo488kiKi4s5+OCDK7o3unbtyvPPP0+/fv1q/frjYem+prSZ3QbMA94Epjjnjq+y3wEMfHFAmGcnx/yRCxk3aVTc5dx8+n10v/gJH2pUWfALf6caAoJI+xNhzZez+Or5cZSX/NZE16BxU7qffQs79Dyk2vGzx53B1vW/JKQuCghEJNUFb5acc7XKupcJUxLfAqbhtXq0SnJd0l4qBgQAxT8sobyk8uCf8pJtFK9aUm91AAUEIpLZUrb7wMzeAG5yzn0ReHwQMAHYHfg3cLFzrtQ5N8fM9gI+BB5NWoVrwZr6M8Zhw5pNPtSmsqZtd6XjgKF13p8ouR32okHjplVaCpqQ236vequDAgIRyXQpFxSYWT/gVGAwcFNgW0PgdeAqYDrwHHA1cIeZtXHOLTGzTsAMM7vHObclbOEpovdIf8Y3zPjL/3wpJx207d6PFrt3Z9OKRZSXbKNB4ya02L0HbbvXT3+bAgIRyQYpFxQABwPNgaKQbUcBK51zLwKY2TjgYeAOYIKZ3Qp8BVjgRzKMNchh34vuimmwYk3KysooKChg/vz59OnTh/z8/KizGJSnQESyRcoFBc65hwDMbFDI5i7AwpDHC4HOgd/vB14BSoGnnHOVs+QEzLpxbsx12O3o9nQ8pn0tap0cDcx8Wf2RRnl0v/CB+MtJMGuQww49Dwk7sDBWwZTLVRd5mjp1atjAwK88BZrFICLxmjBhAhMmTEjoOVIuKIigDZVbDjYBeWbWyDn3P2Cfmgo45Pa+iapb0rTcoQXjJsW/+uPNp9/nQ21ST7gv1IKCAgoLCykq8t5ORUVFzJo1q1LK5WjPT6X9Iplm9OjRjB49OtnVSFnDhw9n+PDhMR0bbqp2LNJl9sE6oEXI45bAZudccvNBSspy5WVhv1Dnz59fbcGRLVu2sGDBgkrbkv2Fr4BAstGYMdmxPH0qS5eWgqXAeSGPewW2iYRVXlrCk/96utriTRs3bqh+sBmP//MpXnzFy6oYuhbDW28X8J8PZlQ6XAGBSOozM7p06YKZUVJSQpcuXbjvvvvo3bt3ncpbvnw5hx12GCtXrqy2b8yYMWzfvp2xY8dGfX6XLl3o1KlTpe3HHHMMjz7qTZz7+uuvueGGG1i0aBEbNmxgt9124/LLL+fss8+uU53rIl2CgunAU2Z2BjADuBl4PrlVklTWeud2PPTa9GrbV634jpsvGsban3+iZNtWmjRrRvf9DmT8E5PIycmpttbDNUPzKz0/9Au7Y8eOTJ48udKAxZUrV4b9Qv/9EQNYv2FDTKtNRtvfulWrakGKSLoLDv4FmDx5co2Df2O1ePHiinKmTZtGfn4+8+bNq1iAqL61a9eOb775Juy+xYsXVwQIJ554Is45Pv74Y04++WQaN27sy0qNsUiLoMA5V2pmQ/DyFPwDL63xvUmtlKS0nOatwqZLBnANm9Gs9Y40KtlKw8ZNWf3zr/zp5GMrHRNciyE0XXLVgKDqgMX99tuPwYMHM3To0Gp3+PM+/ZzmrdpUrBWxsQQo2VbpmNC1JCLtX7psRd0uiEiKCh38CzBs2LCog3/r6phjjuHcc8/l0Ucf5bbbbqOwsJDLLruMNWvW0LZtWx566CEOOeSQanf9559/fsXSy2VlZVx11VW8/fbbANx+++2cckrllWFXrFjBxRdfzBdffEHbtm254YYbYlr/5MYbb2T06NEVY5vMjEMPPZQlS5ZQXl7u23WoScoGBc65TlUezwZ6J6c2km66/eluX8qZPc77Y67apD958uRqAxbnzp3LBRdcELbJf3t5OXm9jqrzWhLB/Zs+irzwlEg6Cjf4t7CwMOzg33j17duXSZMmUVJSwmmnncajjz7KoEGDeOeddzj11FP57rvvoj5/9erV7LnnnixevJjZs2czYMAADj300ErH/PGPf+Tyyy/nD3/4AytWrODQQw+lW7dutGnThh9//JEePXpUOv4vf/kLl19+ObNmzeKRRx6p2H7CCSfw3XffUVpaSvfu3Zk8ebJ/FyKKlA0KRFJBg6Z5dOzSneJNG8ht0Yp/PPUcAOt+/aniQyyopKSEa264mfH3PFhpe2lJCeWOOqeODt2/WkGBZJhwg3+Li4tZsGCB70FB0OLFiyktLeXEE08E4Pjjj8fM+Oqrr6I+r2HDhpx77rkA9OvXj549e1a0cIAX0Hz00Uf89NNP3HTTTRXbv/jiCw477DB23XVXFi1aFLbs0tLSSi0jU6ZMAeDNN9/k7rv9ucmJhYICkSh2OOYi8opW0q3PUTTf4bd+yJ8WfsS8f42hbNtvyTNzmjSj66lXskuv31Vs27xmNavmT6dj+z4R14pI1dTSIvWhT58+5ObmVgqyc3Nz6zwgMJo5c+bQs2dPoPqUPTML20y/evXqSseEPq+8vJzGjRtXPHbO0bhxY7788suK4zZu3EizZs1YtWpV1LodcMABvPfee9UGFX744Ycxvjp/pMuURJGkKP72E9pXCQgAdu55MC3bd8FyGgJGTpNmtN6jJzv3PLjimGBA0L5P+LENQa68jDVfzmLFe8+y5stZuPKyRLwUkZSUn59P//79ycvLAyAvL4/+/fuTn59fwzNrZ9q0aTzzzDNcfPHF7L333jRs2LDibrygoIDy8nJ69OhB06ZN+eSTT3DO8f3331daKrm0tJSnn34agI8//pilS5dy8MG//c23aNGCfffdl3/84x+A1yLRpUsX1q1bV2P9br/9dq6//nreffddnHM453jllVd4/vn6HVOvlgIhr2XjrMqMWBu5XQ6sFhAAbFn3MzvveygdDz6RbRvX0HK3vdi558EVaZdDA4LmO7SDn8J/KLjyMj5//Do2rfiK8pKtNGjclBa7d2ffi+6qUwpnkXSTk5PD1KlTKSgoYPDgwUycONG32Qd77713xZTETp06MWXKlIqZB6+88gqXXnopI0aMoG3btrz66qs0bdqUs88+mw8++IAePXqw33778cc//rGivP3224+FCxey995706hRI15++WXatGlT6ZzPPfccf/7zn7nrrrto1qwZTz31FDvvvDPLly9n9erVdO3atdLxO+64I7NmzeLAAw/k9ddf58Ybb+Siiy6idevW/O53v2PWrFmcc845cV+LWJlzrt5Olgxm5gAGvjgg2VXx3fyRCxk3aVSyq1Hh5tPvo/vFTyS7Gr76fuk37BNobgyq9oVfRbj9X3z5Jbt17lrt2DVfzuKr58dVWf2xKd3PviVsOufZ485g6/pf4n1ZIinJzMj076T6Euy+cM7VKrWhug9EaqEuAUE0xT8sobxka6Vt5SXbKF61xLc6i6SLUaNS5yYnWykoEImR3wEBQG6HvWjQuGmlbQ0aNyG3/V6+1FkknWjdg+TTmALxjS9jE1J0XEIiAgKAtt370WL37mxasYjykm00aNyEFrv3oG33fmGPjzQIUamTRcQPCgrENzc+eWncZaTiio3xBgSb16yuti3IGuSw70V3sfar2RSvWkJu+71o271fxEGG4bZrLQYR8YuCAkkpqTYTonTjr6xaNT+ugGDV/OnQvk/Ec1iDHHboeUjYgYXVjjVj394HVDwOXSvhmecnsmnTRrZu2ULTZs1o0aIlpaUlYddSCK6hoIBAREIpKJCU4kdrA/jX4lD87Sd0O35oXAFB+z5H8V2EKYm11XqHnbhnUkG17WVlZdx84VB+XvIN27Zspkmz5rTdpQN3BRZ6qurmC05n7577xLU4U0nJNkq2bmXG9PfjaoG47rrrYnvxtaSAR6T2FBSIRBEpT0GtuxR8Cgpco2ZhF3raWryJ9T99D4HpXFs3F7Og8L+cfczBNM1tUe345k0bM+CEUypWg6yq6mqRkfb/Z8prcXdJJIICApG6UVAgEkWjljtW25aoQYexiLTQ04r3nmX9u/+qvNFBq/2PYfdjqic++frJa3n79dcqVoOMpKb9oatIBiX7CznZ5xdJZwoKRGohmQFBNMGpjZWTIEWe2hhtFUlXXuYNfPxhCbkdog98DK4iGVR1eenJkyczf/58+vTpQ35+PitXrkzpgGDZsmUpHSgo4JFEU0bDNJZqGQ1Tye1/epiijSVxl1O2vZRGjRp5v5eWsrWomKZ5ueQEtlU6Nsr+rWUN2e+v/4i7PpH8li658tTG2qZLrm3a5bn3/onyLZsqnltWuo2cRk3AGlBavBFXVlpxrOU0xBo2omHjppXKapzTgI1rqrc41NZB/Q9m5cqVtGrdmsaNm1TbHzpGItr+jh07Mqfw42r7k/2FnOzzS3qpa0ZDBQVpbMG4hbitNR9Xk7wWudzw+DXxF5SBSkq20axpU35dtYY5787joOMOYMf2O1Q7rqb91558B/tc9nRC61pxhx/D1MZIapt2Oajq8s/hyrGchuz1hyvYtf8JlZ7rV+rmxs1yabVzexo2alxt3/bSErYWbaRpXssa92/esI7i9b9W2p/sL+RMbwER/9U1KFD3QRrrPbKXL+XMH7nQl3IyVbwBwa+r1tRHNWs1tTGSaGmXI5VbNSCIVI4rK6NkU+KuhTVqQo/LJkSsX6eQ+kXbP2f8mRGnfdZmlkZw2me8/MozkahZHhJdsgPK2lJQIBLFmtVr+fyDL+IKCOa8O4+8Vk1SKv9CJLUdmxAuIKhNOVvX/uhb3cO1ikSqX7T9odM+Y52FEW7/NUPzk55YKtGzPCS6dAsIQEGBSFTz319An6N7k9s2ly1bK9/5rlm9lnnvL+CAGPYPGPp7GoXpx66tRGd8rG3a5UhfuG279yO3XWeKvl+MKysLW07wCzlR6hIQVLVrh905/cLIuTOi7S8p2ebLF/rLr75W5zwSofurtlwkO2BJF2VlZRQUFFQaMBvLss7pen0UFIhE0e/4fhFbAD6duZD+ddyfqmqbdrnjgKERy9n/kgeiltO07a50HDCU1R9Vn/boxwdqsPxIIu2PlAuittb8sMyXL9RnX5hULWFVXVowrhmaX6fzp2tAUNcv86plDBw4kMLCQoqLi8nNzaV///5MnTo1alnpcH0i0UBD0SyGWvp11RrmvjePvsdG7jKItj8efs2q8I0P3RlVBxpWndZY9YM90rTGpq13ot/Il+Kqi58KbzuNbp33qLY91lkQwf3LVnxPXtudKvbXZtBk6P6Nv/5E8fpfkx4Q1Megx7p+mVc1efJkhg0bRlFRUcW2vLw8Jk6cyKBBg8I+J9LrDwYp06dPZ926dYwcOZIuXbqEfb4f10cDDUXqQTIDAvAvDbRf/OjOCF3PoepaDsuWLmHz5s248nKsQQOaNm1Ki5ataN2mTbUm8+CHYDi1yb3gl7Y77+rLHf55g46i618eBmo/aDLUnPFn+pLaOtJ+5xzr1q6p9P9X9f8k+PyuXbv5MgizquAX8g477EBhYWHFl3lRURGFhYX861//Ys2aNTHfoc+fP5/i4uJK24qLi1mwYEHYoCBaQDBw4EBmzZrF5s2bad68OStXrqwWpKTCoFAFBSIxSnZAkKmCA/uqfiEWzniX26+5GFdeDoArL6e0tJSzLr2G4089u1o5kZr8K+de2EKDxs2i5l6IJt7gIjgGoaysjMIZ77Jk0UL26tGLvocfTU5OTtQxCvGOkchr2YrfR0htXVZWxnuvT+LDKW9ywtl/4tghQ6vdUUcLaMrKyrjmnCH8/NOPbC8tpay8nJ1325PxIWtvhD7/nqv/XK1+frZQPPvss2G/zF966SUee+yxmO/E+/TpQ25ubqWWgtzcXHr37h32+Ej1KygoqAgIADZv3kxhYSEFBQUVwUWsg0L96BaJRkGBSAwUECSOa9SM/xt4WEWTdzC1ctHaX9i6ufIH+/bSUp647w4mPfVkle0l5DRvFbb8tV/NrggIAMpLtrBpxSLWfjW7VtM3axtcRBqb4Jxj3erllGzd4q1VYUbjps1o026PsK0drlEzIPwYiKpBym5HnB4xSNlatDHqF/o3CxdQtn07Xy6Yy8zJr0f8Qg/XwvHe65P4ZuECtpd6yaq2bi7mq88+Ye6H79N/wHE1Pj/eTJhVA4ZwX+aNGjWqdR9+fn4+/fv3r9YNkZ+fH/b4SINCV//wfUVAEFRUVMSfLhrOzrvsWuOg0CC/ukWiUVAgUoN4A4JfV61RoBBFpJTLkRIp7X7yFbX6Mq9L7oVwahtcRHtdvzw/rmLxKpxje1k5Oxzxf3EEKTVnn8xrs2PYL+S5H77Pd4u/jPiFDpVnWVx+9hA2bNhYqYyitb9UPD9o6+bN3D3yavLa/DYeIjTg86PLqOrzg/udczjAGjTwWprMyGnYkPsfepgH/t8j1Z4fabXPnJwcHnvsMcaNG0fbtm0ZMGBAtTvz0IBk67aSsF1Gzz98Lx9OfZNtW357Lzdt3py/3none3TrHvOg0IULF1brFpk1axYXXngho0aN8mUsgoICkSj8CAjmvjeP4889tj6qm1FqOz0yktrmXojEr+AiWUFKpJaLcC0y4b7QQ8vpFhjjEFTbAO6bf1zqS5dRTV0a770+iQ8L3uTw/JOidolEW+3z1VdfjfiFW1OXRrD8YRdfwS8/ruKrzz5h25YtNGnWjO77HUjHLl1jbkHZc889w3aLbN68mbZt2/o2eFNBgUgUfgQEfY89oNq+TJHXsnH8SZkizGCo7fTISFItuEhWkJLIFpm6XONwX+hLFi1k25bKzexl27ez9uefY3p+qF9+/IFN69YxYszdNQ7qLJz2drX9dRnjsHTZiorAK3QWyNuvv4ZzjqYtd6Bh0600bNyUlT+sYsSwkyt1mQWt+/VnOnbpTvGmDeS2aMU/nnoOgM1FGwEDfps1aGY8/9Kr/HvKe9XqWBcKCmph4ZiF2Jb4p3C6ZkavUf6kKJbE8iMgyOSuAz9mQ0SbweBH6uZUCy5SLUipXJ9gN0Tt6lPba+waNeOGP58HVF6ee2vxJqp+wjrgzZde4N2336pWTqtWLSMOzIwn8VRdBz2WYXT9y8MxzxLpHGH/dwtmkVe0km5VVlt15WV8/MjVrF+2kLKSbeQ0bkLrPXvR96/3VrrWm9es5rvRdctiqaCgFmyL492RV8ddznHj7vWhNlIfFBBkhtoEF189cQWUFoXd18g58tq0YntJCQ0bN6ZR2XoWP1Z9JH1NalVOhJYUP77Mwb+gqTbXOFKrRaTVPntFGCfx9ZPX+pJoKtIYh9pOyzSzuGeJbF37I5uXzoPOB/DdT+vgp3WV9jc9cAhNrTE5TXJp1mFvmu3eiy+/Wlyxv3TjrxR/+0mdrgMoKBCpFQUEqSval3lt5LVszI0vXBV/hXwSqSXFry/zYFnxtsj4obavKVJwUVuRxjhUVdP+/xt4WNwBwS+fzqTLkadG3r/8E3qeclnU/XsNOI05H1fPFBoLBQUiMVJAkBi+jEsg9b7M60OqfJn7KVmvKd6A4McfVrC1aGONXQbxBgzxrOURCwUFgjWFkUPHxF1OXotcbnj8Gh9qlHoUECROqmVplOwUzxiE4P68NjtG/EKu61ocUH8BASgoEKD3SH8GPc4fudCXclKN8hRIMvnVkuLXstu+dNMkeAnwTFKfAQEoKBCJSnkKJNn8aknxbdnt0iLGvxxfN83tf3rYn0DHJ1s3rPNlwGIw+6Sf4mlhqAsFBSJRKE+BiP9Srcvo5tPvq1h0KhX4NWi2LhQUiEShPAWSKfwc0CkJ5kNrzPAD6xZ4KSgQiUIBgWSKVLs7l9SkoECkFhQQiGSeVBvMmUwKCkRipIBAJDP51Yri1wDKZHbRKChIgrZNmvPFDZ/HXY7WUKg/CghEpCaZ0EWjoCAJJl17sS/laA2F+qE8BSKSLRQUiG/8yIyYalkRladARLKJggLxjR+ZEVMtK6LyFIhINmmQ7AqIpDLlKRCRbKKgQCQKBQQikk0UFIjUggICEclkCgpEYqSAQEQynYICkRgoIBCRbKCgQKQGfkxLFBFJBwoKRKLwK0+BiEg6yKg8BWY20Tk3LNn1kLrzIwES+JcESXkKRCSbZERQYGYdgUnAzsmui8THjwRI4F8SJOUpEJFskindB98DRwHLk10RySwKCEQkm6R0UGBmb5jZPiGPDzKz+Wa2xsyeMLNGAM6zDXBJq6xkBQUEIpLJUrL7wMz6AacCg4GbAtsaAq8DVwHTgeeAq4E76qtexas2cMYNd8ddTm5eLk+NvMSHGkl9UkAgIpkuJYMC4GCgOVAUsu0oYKVz7kUAMxsHPEw9BgUNnWPyHnvEXc7QZct8CS6KN26KuwyJjQICEckGKRkUOOceAjCzQSGbuwCho8cWAp1jLXPWjXNjPv9uR7en4zHtYz6+tibtuacv5Rz02ee+lJOJ/JzFcOGY8+OehaBAQUTi9eFr/+U/r32U0HOkZFAQQRsqtxxsAvLMrJFzrhTAORdx0fpDbu+b4OrVvwYYX9wQf2Dgmhm9Rvkz6j9V+DWLYe71n/oyLfH4cyO+NUVEYnL4KYdx+CmHxXTs8AMvrdM50ikoWIfXWhDUEtgcDAiy0U6tWvDSyKvjLue4cff6UJvMtHXTNuUpEJGskdKzD6pYCoTe/vUKbBNJmKYtmmhaoohkjXRqKZgOPGVmZwAzgJuB52N9sh/N7A2wuMuQ9JLTKKfaNgUEIpKp0iYocM6VmtkQYALwD+BVIOZ273d9aGb3Y8aApDcFBCKSyVI6KHDOdaryeDbQOzm1kWyngEBEMl06jSkQSRoFBCKSDRQUiNTAj+WTRUTSgYICkSjKSst8yVMgIpIOFBSIRKE8BSKSTVJ6oKHUj7ZNmiszYgTKUyAi2URBQRrLc863VRv9mLKZiZkRG7bIqbaGQllpGVs3baNpiyb8t+B/1Z5T0/545LXI5YbHr/G1TBGRIAUFacyvhZUGLV/uSzmZqOoaClt+3sKPs35m10N2ptnOzaodX9P+eM0fubDmg0RE6khjCkRilOyAQEQk0RQUiMRAAYGIZAMFBSI1iDcg2PLzlvqopohI3DSmQCQKPwKCH2f9TKeT9/ClPtaUagMf60IDFkUkHAUFIlH4ERDsesjOvtWn6sDHutKARREJR90HIlH4ERBojIGIpAsFBSJRKCAQkWyi7gORWsiUgEBjE0QkHAUFIjHKlIAANDZBRMJT94FIDDIpIBARiURBgUgNlKdARLKFug8kpSwcsxDb4uIux68VG1MtT4GISCIpKJCUYltcSq3YmGp5CkREEklBgfi2BHPxxk0+1MYfbZs054sbPo+7nNKc8rB3+RpjICKZSEGB+LYE80Gfxf8l7JdJ117sSznhWhwUEIhIplJQIL5pgMV9d962SXOfapMYCghEJJMpKBDf7NSqBS/5MB4gVSkgEJFMpymJIjFQQCAi2UBBgUgNlKdARLKFggKRKLaXlvkyLVFEJB1oTIFIFFuKt9FNeQoi8mNhJS2qJJI6FBSIRNGuTWuW3rek2vbtpWVsKd5Gs9wmbJ61scb9fmVYTDV+LKyUaosq3XHRPRRtKo67HAU7ko4UFIhE8drNl1Xb9sOv63hnzmccf9B+dNixTUz7/cqwKIlXtKmYPuMyL9gRiYXGFIjUQl0CAhGRdKGWApEYKSBIbX41+1tTHyojkqYUFIhv/FhDITcvl6dGXuJTjfyjgCBx/BisGCzHj2Z/kWymoEB848caCoOWL4+/Ij6LNyD44dd1vtUl1ZaW9oMfgxVFxB8KCkSi8CMgeGfOZ77VJ9WWlpbE86tbxC+pNKtCM0X8lzVBgR9LA+e5+O/QJL34ERAcf9B+vPjJ3PqormQgv2ZD+CWVZlVopoj/siYomLzHHsmugqQhPwICjTEQkXSRNUGBSF1kakDQtknzuJe5htQamyAi8VNQIFILmRAQAEy69mJfytHYBJHMouRFIjHKlIBARCQStRSIxEABgaQ7v6azlq7d6kNtJFUpKBCpQSrlKRCpK7+msx559e0+1EZSlYICSSl+ZEUE/zIjplqeAhGRRFJQICnFj6yI4F9mROUpEJFsooGGIlEoT4GIZBO1FIhEoYBAkq305y2+5JRo26S5D7UBs/gXsMrUtMKZkHZZQYFILSggkPrWyBr4MkDQL41aN2afOFMLZ2pa4UxIu6zuA5EYKSAQkUynlgLJSH7PYlBAICLZQEGBZCQ/ZzEoT4GIZIuMCwrMbKJzbliy6yGZoaSsTHkKpE6safwD8sAb2CdSXzImKDCzjsAkYOdk10Uyx4ZtJcpTIHXSe6Q/q0f6MfNA0otfAWVdZExQAHwPHAW8neyKSOZo1aSxpiWKSL3yI6CceuaMOj0vpWYfmNkbZrZPyOODzGy+ma0xsyfMrFGk5zrPNiD+FT9EAhrn5FTbpoBARDJVSgQFZtbPzO4EBodsawi8DtwBdAc6AlcH9h1nZm+F/BydhGpLFlJAICKZLFW6Dw4GmgNFIduOAlY6514EMLNxwMPAHc65d4F3672WktUUEIhIpkuJoMA59xCAmQ0K2dwFCE3rtBDoXNdzDP7yq5iPHbbTjpy10451PZVkIAUEIpJsK6et4vv3VyX0HCkRFETQhsotB5uAPDNr5JwrjfQk59yx4ba/1bO7z9WTbJDnHEOuvYMN20po1aQxUz+YXe2YkrKyGvcXF2+uj+qKSAbreEx7Oh7TPqZj6zrQMJWDgnV4rQVBLYHN0QICEb/d3a4db69dz4kdOtCxSZNq+1du2xbT/ieL4l8kRUQk0VJioGEES4HQeRm9AttE6s3ba9dzYtvW0QOCGPaLiKSDVA4KpgMdzewMM9sJuBl4Psl1kizjR0AQbr+ISCpK2aAg0E0wBLgJWAysAO5NZp0k+yggEJFsklJjCpxznao8ng30Tk5tRKpTQCAimSylggKRVBZPQNDWcph3zn/ir0SYDIsiIn5RUCASg3hbCKbu29OXegxavtyXckREwknZMQUiqSLegGDltm31UU0RkbgpKBCJwo+A4O216+uhpiIi8VNQIBKF8hSISDZRUCAShfIUiEg20UDDGD3+4088sOpHisvLk12VCrkNGnBF+125aNddkl2VjKWAQESyiVoKYpRqAQFAcXk5D6z6MdnVyCoKCEQkk6mlIEapFhAEpWq9MpECApHMZE1h5NAxvpST7hQU1MGyvn2SXQX2nDs/2VXIKgoIRDJX75G9aj4oSygoEKmBH9MSFSiI/EZ35qlLQYFIFH7lKfhLOw0GFQnSnXnq0kBDkSiUp0BEsolaCkSiyNQ8BeeP+zvFRcVxl1O8cZMPtRGRVKGgQCSKTAwIAIqLipm8xx5xl3PQZ5/7UBsRSRXqPhCphUwICEREIlFQIBIjBQQikunUfZAB4s1ZoHTJNVNAICLZQC0FaSq3gX//dUqXHJ0f0xJFRNKBWgrS1BXtd/V1PQalSw4v1fIU5DnHGTfc7Us5IiJVKShIUxftuosvzf1KlxxdquUpmLTnnr6VJSJSlboPRKLI1DwFIiLhKCgQiUIBgYhkEwUFIrWggEBEMpmCApEYKSAQkUynoEAkBgoIRCQbKCgQqYHyFIhIttCURJEoUi1PgSRe4Xn/pVFZ/HkcSnOM/v86zIcaidQfBQUiUaRangJJvEZljjn77Rt3OVpBUtKRug9EolCeAhHJJmopkApaWKk6BQTRtbUc5p3zn7jKUDO7SOpQUJDlchs08HX9hAdW/ZhRQUFVCggqm7pvz7jLUDO7SOpQ90GWu6L9rr6vuJipFBCISKZTS0GW08JKsVFAICLZQEGBSA38mJaoQCEyP8YlQOaOTShetcGX5bJz83J5auQlPtRIMpmCApEolKcg8fwYlwCZOzahoXNM3mOPuMsZtHy5D7WRTKcxBSJRKE+BiGQTBQUiUShPgYhkEwUFIlEoIBCRbKKgQKQWFBCISCbTQEORGCkgSG1+zWJoazk+1Cb16uOXbT9uUhbLDKagQCQGCghSn1+zGPySavXxyy55uXHPhsjUmSKZQEGB+C6eREapuH6C8hSISLbQmALxhV+pkoPrJ6QKv/IUiIikAwUF4gs/11BIpfUTlKdARLKJug/EF36soZCK6ycoT4GIZBO1FIhEoYBARLKJggKRWlBAICKZTEGBSIwUEIhIpkv7MQVmthvwKtAMuM8596/k1kgykQICSXd5zvmyBHOecz7URlJV2gcFwHDgduBNYArwr3AHpeIgNkkPylMgmWDSnnsmuwqSBjKh++AtYBpegNMq0Sfza9qdpAflKRCRbJISLQVm9gZwk3Pui8Djg4AJwO7Av4GLnXOl4Z7rnJtjZnsBHwKPJrKewWx7knjxtuz4lRlReQpEJJskNSgws37AqcBg4KbAtobA68BVwHTgOeBq4A4zOw64LKSIB4B5zrklZtYJmGFm9zjntoQ737K+fRL0SsQPuQ0a+Ja4KJgZMd6gQHkKRCSbJLst/GCgOVAUsu0oYKVz7kXn3C/AOGAYgHPuXefc4JCf94EJZtYDKAEs8CNpyM+siOBPZkQFBCKSTZLaUuCcewjAzAaFbO4CLAx5vBDoHKWY+4FXgFLgKefcZr/rKfXDj6yIkNhBpQoIRCSTpcSYgiraULnlYBOQZ2aNwo0rcM79D9gnloIHf/lVTBUYttOOnLXTjjEdK9lDAYGIJNPKaav4/v1VCT1HKgYF6/BaC4JaApsjDTSsjbd6do+3CMlSCghEJNk6HtOejse0j+nYqWfOqNM5kj2mIJylQK+Qx70C20SSwo9piSIi6SAVg4LpQEczO8PMdgJuBp5Pcp0kSylPgYhkk5QLCgLdBEPwpiguBlYA9yazTpK9lKdARLJJSowpcM51qvJ4NtA7ObUR+Y3yFIhINkmJoEAkURKRGVEBgYhkqpTrPhCJl98JkB5Y9WPFYwUEIpLJFBRIxklUZkQFBCKS6dR9IBknEZkRFRCISDZQS4FIDJSnQESygYICkRgoT4GIZAMFBSIxUJ4CEckGCgpE6kBjDEQkEykoEKklBQQikqk0+0AkBuGSIN3xQ/QlTEP3h0uCJCKSatRSIBJBIpMgiYikIgUFIhEkKgmSiEiqUveBSATBJEjxjiGId/0FEZH6opYCkSjiDQiUuEhE0olaCkSiiDcgqJq4KBGrNoqI+EUtBSJRxBsQnNi2tQYsikjaUFAgEkW8AUHHJk00YFFE0oa6D0RqoS5jDBKxaqOISCKopUAkRspkKCKZTkGBSAwUEIhINlBQIFIDTUsUkWyhoEAkCj8CgqrTEkVEUpUGGopE4UdAcGLb1r7XS/kORCQR1FIgEoUfAYFfYwyU70BEEk1BgUgUqRIQgBZoEpHEU/eBSC0kcxaC8h2ISKKppUAkRpqWKCKZTkGBSAwUEIhINlBQIFID5SkQkWyhMQUiUfiVp+Av7VJz6p+mNopIKLUUiESRqnkK4qGpjSISiYICkShSKU+BXzS1UUQiUfeBSBSZFhCApjaKSGRqKRCphXQPCEREolFQIBIjBQQikukUFIjEQAGBiGQDjSkQqYEf0xIzPVCIZ3yBpjWKpA61FIhE4Veegkzk1wwGTWsUSR0KCkSiyMQ8BX7xc2qjpjWKpAZ1H4hEkYl5Cvzix9RGTWsUSS1qKRCJQgGBiGQTBQUitaCAQEQymYICkRgpIBCRTKcxBSIxUECQeKkyvkBTJCWbqaVApAZ+TEuU8PxcmMkvmiIp2Sz1/iIlbb3wy6/JroLvUi1PQaZdY79XbPSLpkgm1pYyXd9Upe4D8c3EX37lrJ12THY1fJVqeQoy7Rr7tWKjX1KlCyPTbVXQlbIUFIhEoTwF2SveAEFjEyQdpV67nUgKUUCQXfzsytDYBElHCgpEakEBQWa7ov2uvn4oamyCpJu07z4ws+7AC8AGoMg5NzjJVZIMpYAg81206y68uXYdb/XsHlc5Gpsg6SoTWgq6Ag855wYkIyCYtn6Dyk2wVLgWtQ0I0u06J7K+qfD/lwp0jevHz58kZoZOupVbV5kQFHQCTjez/5rZOfV98vcT9EeTbuUmUrKvRV1aCELLToc8BYl8XyT7/y9V6BrXj18S9CWbbuXWVUp0H5jZG8BNzrkvAo8PAiYAuwP/Bi52zpVGePoS4H/At8A0M3vbObe2HqotWcCvPAV/aacR6FJ7j//4Ew+s+jGmsQkTf10Tdb9mQ0gsktpSYGb9zOxOYHDItobA68AdQHegI3B1YN9xZvZWyM/Rzrkpzrm5zrl1wEfAnvX9OiRzpVqeAskusQYEsdBsCIlFslsKDgaaA0Uh244CVjrnXgQws3HAw8Adzrl3gXdDCzCzCcCTwFxgP2BpPdRbskRdA4KisjINOpS4+T17QbMhpCbmnEt2HTCz74BBzrkvzOxi4EDn3IWBfW2AFc65FhGeuxfw/4B2wKPOuceq7E/+CxQREUkC55zV5vhktxSE04bKLQebgDwzaxRuXIFzbgmQX1+VExERyVSpGBSsA7qEPG4JbI4y0DCq2kZJIiIi2SoVpyQuBXqFPO6FxgmIiIgkXCoGBdOBjmZ2hpntBNwMPJ/kOomIiGS8lAsKAt0EQ4CbgMXACuDeZNZJREQkG6TE7AMREZFYmNm5wL/C7FoLfA6Mdc69X6+VqsLMWuAl1uvgnNuezLrUVioONBQREanJg8A3gd8b4CWuOx8vs+1Jzrm3klUx4HhgWroFBKCgQERE0tO/nXMfhG4ws8eAz4DxQDKDgpOAN5N4/jpLuTEFIiIideGc+xr4EOhpZo2TUQczywGOBd5JxvnjpaBAREQySRGQA+Ql6fyHAZ875zYAmNkMM/u3mR1uZu+a2Toz+8jMDjGznczsaTP73sx+NrPHkhXMBCkoEBGRjGBmzfHW1Pkpiavlhus62Bt4GZiPtwJwH+ANYBqwK/AIsBwYDlxcbzUNQ2MKREQkHe1kZh0CvxveQMOReOvg3JSsSuEFBcdW2dYDOMo5NwPAzHKBvwKznHMnB7a9jDdwsn891rUaBQUiIpKOXo6w/WHgnvqsSJCZ9cBLy7+syq6VwYAgYCZeUPBMcINzbomZ/QA0S3Q9o1FQICIi6ehGvLwEQVuBz5xzvwQ3mNkM4MgIzx/tnBvjc50izTpYU+VxcC2fXyNsT5qUHlNgZsea2edmVmRmH5pZrzDHnGhmi8zsJzP7WzLqKSIi9W6Wc+7tkJ/3QwMCAOfcAOecBRbGmwkMDT5OQEAAaTwVMShlg4JAn8sLwK1AJ2AW8LqZWcgxOwDPApcABwInmtnQJFRXREQygJk1N7P1ZtY5ZFsbM9tkZrtEed5OwB7A3PqoR13rWZOUDQqAfYAfnXP/DkR/t+KN0uwQcsypwLvOuRnOue/x+pGG1X9VRUQkEzjnNgMvAeeFbD4LmO6c+ynKUwcBbzuf1g6oqR5x1DOqlF37INBSsINzbkXgcS+8FRR3dc6VB7bdCWxyzo0LPO4DPOOc2zeknNR8gSIiIgkW6DqJWcq2FDjnikMCguOBqcBNwYAgoA1eooqgTUDb+quliIhI5kjZoAAq+kcmAY8Df3bOPVHlkHVAi5DHLQPbqnHOJeTnoosuUrmBnwMPPDCt6hxLuW+++Wadfo477rhKj7P1Gif7/0/XODXLTdQ1Tsdrkahy6yplpySaWUO83NHLge7OueIwhy0Fjgp53Av4rh6qJyIiknFSuaXgeGAH4MwIAQHAq8BxZnaEme0GXAU8X18VFBERySQJCQrMLNfMRprZrED+gLVmVmhmowIDCGPRA+gClJuZC/k518y+A3DO/QqcAzwGfII38nNSIl6TiIhIpvO9+8DM2uB9Qe+JN1+zACgHegKjgHPN7ADn3Ppo5Tjn7gbujrD76ZDjJgOT4664iIhIlkvEmIK78PIJHOOcmx66w8yOAd4KHDM8AeeOaPjw6qcbPHgwgwcPjqvceJ+fqHLLysooKChg/vz59OnTh/z8fHJychJW30RK1WscTb9+/RJWdiIk8lqk4/9fIuga1490uxZ+lPvWW2/x1ltv+VCbBOQpMLPFwHvOuUsj7P87XsDQzdcTR66PA+IajZluysrKGDhwIIWFhRQXF5Obm0v//v2ZOnUqOTk5CTtv3759mTvXl2ReKcOvPzS/PlAy8RqnGl3jxNM1Trxg8l+XAnkKdgFWR9n/A7BTAs4rAQUFBRQWFlJUVIRzjqKiIgoLCykoKEh21UREJIUlIij4DDjJzKrdkga2DQYWJuC8EjB//nyKiytP2CguLmbBggXJqZCIiKSFRAQFDwEHAVPN7Dgz62hmu5nZcXh5Bw4CHkjAeSWgT58+5OZWnuSRm5tL7969k1MhERFJC74HBc65V4ArgQPwZh4sw0tA9A7QF7jaOfeq3+eV3+Tn59O/f3/y8vIAyMvLo3///uTn5ye5ZiIiksoSktHQOfegmT0NHIa37LEB3wL/c86FTUOcaImafZCKcnJymDp1KgUFBSxYsIDevXtXzD5IpHDXWPyla5x4usaJp2vsr5SefZBqsnH2gfgn1WYfiEhyjB49mtGjRye7GjGr6+yDuIMCM/sWGOWcey7wOJauAeecOy2uE8dIQYHEQ0GBiID3JZtO3yN1DQr86D7oROWVCg8A0ufKiYiICOBDUOCca1Dlcad4yxQREZH6l4i1D24BpjjnPomwvzcwwDl3v9/njiabBhqKiEj2SOmBhmZWDlzinPtHhP1XAbc55/J8PXHk+mhMgdSZxhSICGhMQW1Pfh1wfcime8xsfJhDGwAtgdl+nFdERCSRgovLAUyePDnq9O5MuInwq/vgK+CNwO/nAZ8DiyIcuwGY4NN5RUREEiJ0cTmAYcOG1cvicsnkS1DgnHsTeBPAzI4EHglOURQREUlHoYvLAZUWlxs0aFCSa5cYiUhz3DlaQGBmB5vZBX6fN9nKysqYPHkyY8eOZfLkyZSVlSW7SiIiEodsXFwuIWmOzWw34BCgaZVdDYC/4OU2+Gcizh1JImcfhDYxFRcXk5ubm/FNTCIimS64uFywpQBSc3G5VJ99cCQwGWiGt+aBC/xL4HcHjHfOjfL1xJHrk/DZB5MnT2bYsGGV3jh5eXlMnDgxY5uYskUmDBwSkboJveErKiqqWFwu0g1fKn1eJHX2QRW3AEXAaXgzDZ4FzgG+B4YD/YBwMxMiMrM3gJucc1+E2fcpsF/IpieccxfVrep1E62JKR2Cgmhv5LKyMubNm8e3335Lly5dOOCAAyK2fuiLT0QySejicoMHD2bixIn1srhcMiUiKNgX+Ldz7h0AM7scaO2cewn4n5l9DIwCbq6pIDPrB5wKDAZuinBYJ6CZc26rH5Wvi3RpYqqtsrIyRo0axddff83WrVtp2rQp3bp1Y8yYMRn9RyEiEpSTk1Nxc5cON3nx8n2gIdAc+Drk8dfA3iGPJ+N9ycfi4EB5ReF2mtlOQFEyAwKA/Px8+vfvT15eHmZW0cSUn5+fzGrFbd68eRUBAcDWrVv5+uuvmTdvXpJrJiIiiZCIloIVwO+AewOPvwFOCNnfEtgzloKccw8BmFmk8Kwz0CDQhdAJmAn8xTm3qta1jkNoE9OCBQvo3bt3RjQxffvtt2zbtq3Stm3btrF06VIOOuigJNVKREQSJRFBwbPA+MAX9aHAe8A4M7sE+AUYSuTERrXVClgIjABWA/cBjxGmJaJv374xFzp8+PCwsxWiCTYxZVLzUpcuXWjSpElFSwFAkyZN6Ny5cxJrJSKSnSZMmMCECYnN/ZeIoOBOoDEwBGjqnJtjZvcDDwf2bwbO9+NEzrl3gXeDj83semC5mTVwzpWHHjt37lw/TplVDjjgALp168bXX3/Ntm3baNKkCd26deOAAw5IdtVERLJObW5Yg7MPasv3oCDwZTwm8BPcdrWZTQB64K17EHaMQG2Z2bFAqXNuZmDTDkBJ1YBA6iYnJ4cxY8Ywb948li5dSufOnaPOPhARyVSjRtXLLPqk82tBpMbAMKAX3hf+/4CZzrlSM2uE143QDi93wYXA5Xhf4PHKBf5uZicBS4AbgNd8KFcCcnJyOOiggzSGQESy2ujRo5NdhXoRd1BgZrsAHwJ7UTlJUaGZnQa8D3QL2QdQGsf5zgVGO+c6OedeN7P9gbeBRnjrL1xR17JFRESymR8tBX8Dugb+/TewBTgIuB2Yhze+4FLgE2Ar3piClbU5gXOuU8jvTwNPhzyu1FWR7oLLdM6fP58+ffpkxCwGEam7VMqSJ6lj9OjRCWm98CMoOBJ42Tk3MmTbl2ZWAjwPXO+ce9SH88QlkWsf+EVrKOgDMN348f/l1/+V3juSTcaMGVMRFPi59oEfQcEewN/DbJ8d+Nev6YdxSfQ0Dj9k4zKdIiJSWaxf8KHHVQ1mH3/88Tqd24+goAFel0BVWwL/ag3hGKX7GgoSme5iRSQdJCLNsdRRcA2FUJmwhoKIiKQHBQUpJFPXUBAREX+UlZUxZ84cAObMmUNZmb+N8X4lL9rLzH5fZdtOgX97mVm1ZEXOuf/4dO6MkalrKIiISPxCV64FuPvuu31fudavoOAKIucHuBMvb0GQBR7X6zddOsw+gMxcQ0FEJJX5NeYn0SKtXDtp0iTWrVvnyzn8CArO86GMhEuH2QciIiKRRFq5tmHDhlx66aWVtr/77rvURdxBgXPumXjLEBERkejqY+XaRKySKCKS9dKlSTqdZds1Dl25duvWrTRt2tT3lWsVFIhIUmXbB3u60/9X8oSuXDt27FiuvfZa31euVVAgIpIF9GWeGYIr1wIJWb02a4KCdJl9UBv6IxcRie6FF17grLPOSnY1Emr27NnMnj275gNjkDVBgWYfZBcFTFJXeu9klkmTJmV8UNCvXz/69etXaVvSZh+IBOnDVEQkvSkoEEkjCrxEYlNWVsa8efMALx2w3wPy6sqv7oyhQ4f6UJvqzDlX81FpzMwcQCa+Tn1BiIhUF5oOOHTqnp/pgOvqpJNO4s0336yX8wA456w2z8ualoJUGmioL/PkCt5BfPvtt3Tp0iVl7iBExB+R0gHPmzcvISP2k00DDesg0pd/bb6g03mmgnhS+Q5CRPwRKR3w0qVLkxYUJLI7w8+BhmmxdLKZvWFm+0TYd6KZLTKzn8zsb/VdN4lNcLnPSZMmJWS5z1hFu4MQkcwQTAccyu90wLURvBm5++67AW91w1GjRiXtczCalG4pMLN+wKnAYOCmMPt3AJ4NHPMN8LaZfeacm1SvFZWoQu/Ot23bRpMmTZJ2d56KdxAi4q/6SAdcG+nUnZHSQQFwMNAcKIqw/1TgXefcDAAzuwcYBiQkKNBYgLpJpT+I+lhQRESSqz7SAddGOt2MpHT3gXPuIefcZcCaCId0ARaGPF4I6NM9xUT7g6hvwTuIpk2bAiT9DkJEwnvhhRfien7VdMDJHDOUat0Z0aR6S0FN2gCrQx5vAtqGO/Dcc8+t+L1Vq1YAbNiwoWJbs2bNaN68OevWraNTp07stddetG3bluOPP57Zs2ezZMmSimOHDBnC2rVr+fDDDyu29evXj7322qvSG7lDhw4cccQRfPDBB/zwww8V28866yyWLFlSabTo4YcfTtu2bXn99dcrtu21117069ePd955h7Vr11bU8w9/+AOff/45n3/+ecWxAwcOBGDq1KkV2/bdd1/23Xdf/v3vf7NlyxaApLymlStXkpOTw/bt2yv2NWzYkBUrVvDCCy/U+2saM2YM9913H+vXr6d169b07duXnJycrP9/0mvSa0ql1zRp0m8NvvG+pnfeeSepr6lz585069aNRYsWUVpaSsOGDWnTpg0HHHBArV7THXfcwaJFiwDvM7RVq1YUFxdXavls06ZNpc/a2kqLPAVm9h0wyDn3RZXtdwJFzrmxgccHAM8453qFHOOAepkXKuFpxL/EKxvy10tlfs3nT5X3TnD2wdixY7nlllsS3p2RrXkKlgJHhTzuBXyXqJP5NSUx28YmhPbvLV26lM6dOys3gNRKNuSvF4/fU/dS5X2T6NUN/ZLuQcGrwB1mdgTwLXAVcEdyqyThBP8gUvmPQUSSK7RVEbype2pVrF8pPdAwHDM7N9CdgHPuV+Ac4DHgE+BtTUcUyRzB/BZAUvNbSP3IhjwiiVqzwC9pMaYgHqm49kG2dR9Idqtrn67GomSfSZMmMXHixEqf12bGWWedxZlnnpnEmqWfbB1TELNUWvtAYxMkGwT7hidNmkTXrl1r3TecSvktJHbxDOxTHpG60doHdTBhwoRkV0EkbukSUPrRN5xOCV/kN/EMCk21TITpws+1D7ImKBCR3yQ6uPDjLl93jenFj1kDqZaJMBspKBDf+PFF49cdbLrcUWcqP+7yk3XXqPdO7fk5ayBdpu5lKgUFaUwfXhKqrKyMgoIC7r33Xq6++mry8/OTdoflx12+7hrrX13HA2j8R+ZQUCCSAcrKyhg4cCCFhYUUFRUxd+5c+vfvz9SpU5PyJVqbu/yagtshQ4bQoEEDRo8eHfU4BbfRxXITcdJJJzFx4sRal71gwYKwLUONGzeu883LqFGjanyu/s/9lzVBQSrNPhDxW0FBQUVAAFBUVERhYSEFBQUMGjSo3usTepf/+uuvM2TIkLju8msKCFJROrXkBVuZACZPnlzrVqY+ffqQm5tb8f4DyM3NpXfv3nWuUyz/5+l0jRNJsw/qQLMPJJPNnz+f4uLiStuKi4tZsGBBUoICUBbLdBHaygQwbNiwWrcy5efn079//4rANC8vj/79+5Ofn5/IqkuAZh+ISCWJuFOTxBs9enTSW0H8aGXKyclh6tSpFBQUMHjwYCZOnJjUMS21pRaH36RdmmMRqS54p5aXlwegO7UUV1ZWxuTJkxkzZgyTJ09OavrmaK1MtZGTk1MRRAwaNChtAgKpTC0FIvUg0WNXQu/U7rvvPq666qq0ulPLJn401/vJ71amUaNG+VQzSQYFBZJSNPCz7oJ3askaQyCxSbVBoX6PB0h2d0gmSObnYNYEBZp9IBKb2uQ7SKW/n1SqSzS1HRRan61M6TgeQLyxDH6NZ8iaoECzD0Rqlmr5DjJRKg4KrToeQNJLuBvcxx9/vE5laaChiFSI1rQt/kjlQaEaDyAKCkSkgl8j0SWyYHN9MHPgxIkTU6YlRuMBREGBiFQINm2HSnbTdiYKNtePGjVK0/ckpWTNmAKJLF0GaEniKTNd/dKduaSarAkKNPtAUlVwtP/8+fPp06dPUkd+K99BbFIhE2GoVKuP1C8/Zx+Yc86XghLBzA4CJgC7A/8GLnbOlVY55lNgv5BNTzjnLgrZ7wBS+XVK6vLrDy1S8Fl1tH/wzjxV+pilsmAAN3jwYN56662kB0ypVh9JHWYGgHPOavO8lB1TYGYNgdeBO4DuQEfg6jCHdgKaOecs8HNRmGMkAwRTw44dOzbpqWH9otH+9SP43hkwYECd3zvBAG7YsGGAl4lw4MCBSXsfplp9JDOkbFAAHAWsdM696Jz7BRgHDAs9wMx2Aoqcc1uTUUGpP6EfgKNGjcqYD0CN9k+80PfOzJkz6/zeSbUALtXqI5khlYOCLsDCkMcLgc5VjukMNDCzT81so5m9aWbt662GUm9CPwCdcxnzAajR/onn15dnqgVwqVYfyQypPNCwDVAU8ngTkGdmjULGFbTCCxZGAKuB+4DHgGoduH379o35xMOHDw87MFGSp7apYdNF6Gj/4uJicnNzNdrfZ369d1ItE2Gq1UcSb8KECQnPzpvKQcE6vNaCoJbA5tCBhs65d4F3g4/N7HpguZk1cM6VhxY2d+7cBFdXEilTPwBDR/svWLCA3r17a7CYz/x676TadM1Uq48kXm1uWIMDDWsrZWcfmNlA4DbnXP/A48OBR5xz+4YccyxQ6pybGXjcA/jYOdcq5BjNPsgAoaP0Q++oEz1KP9GzDyTx/JzhERztnyrTNVOtPpI66jr7IJWDgkbAcuAKYAbwHDDDOXdHyDFDgL8DJwFLgAeBcufc+SHHKCjIEMEPwPq8o1ZQkBn05SnZJuOCAgAz68dveQpeBS4BzgJGO+c6BY4ZFdjeCHgTuNw5tyGkDAUFUmcKCkQkHWVkUOAHBQUSDwUFIpKO6hoUpPJAQ18pzbGIiGSirElz7Ae1FEg81FIgIuko49Ici4iISP1SUCAiIiKAggIREREJUFAgIiIigGYfaACYiIikNc0+qAXNPpB4aPaBiKQjzT4QERGRuCgoEBEREUBBgYiIiAQoKBARERFAsw80AMxHEyZMCHudxT+6xomna5x4usb+0uyDWtDsg/rTt29f5s6dm+xq+CrVZh9k4jVONbrGiadrnHiafSAiIiJxUVAgIiIigIICERERCVBQICIiIkAWBQXDhw+v9uPHIDK/BqKle7mJlI7XYvbs2QkrOxESeS3S8f8vEXSN60e6XQu/voeqfr/VVUoHBWZ2kJnNN7M1ZvaEmTUKc8yJZrbIzH4ys79FKmvChAnVfvwYEZ7Kb5T6LDeR0vFaKChIfNnp9l7WNa4f6XYt/Ch38ODB1b7f6iplgwIzawi8DtwBdAc6AldXOWYH4FngEuBA4EQzG1q/NRUREckMKRsUAEcBK51zLzrnfgHGAcOqHHMq8K5zboZz7nvgnjDHiIiISAxSOSjoAiwMebwQ6FyHY0RERCQGKZvR0MxuAnZ2zl0ReNwQKAUaO+dKA9smAF865x4IPN4L+MA51yGknNR8gSIiIgmWSRkN1wEtQh63BDYHA4Iox6yrh7qJiIhknFReEGkpcF7I416BbVWPOarKMd+FHlDbKElERCRbpXJLwXSgo5mdYWY7ATcDz1c55lXgODM7wsx2A64Kc4yIiIjEIGWDgkA3wRDgJmAxsAK418zONbPvAsf8CpwDPAZ8ArztnJuUnBqLiIikt5QdaCgiIiL1K2VbCkRERKR+ZXRQEEuaZImfmR1rZp+bWZGZfWhmvZJdp0xlZn3MbHWy65GJzKyDmU01sw1m9j8z2yPZdcpEZjbMzL42s2Iz+4+Z7ZPsOmUKM3sj9Hqa2c1mtsrMvjGzM2IpI2ODgljSJEv8zCwXeAG4FegEzAJeNzPN+vBZIKh9itSeNZTO3gBexHsf/wcYk9zqZB4za4v3Hr4M7zP5Q+DvSa1UBjCzfmZ2JzA4ZNsgvDF3hwB/BP4RGJAfVcYGBcSWJlnitw/wo3Pu34HrfCuwK9Ah+tOkDm6icgZP8YmZHQBsc8790zm3Fm+20+jk1iojbQO2BH53gAHrk1abzHEw0BwoCtl2FvCAc265c24W8G/g9JoKyuQ7DqVArh9fACeGPO4KbAZWJac6mcnM9gP+AJwJDExydTLRfsBPZlYAHArMBy5MbpUyj3Ou2Mz+ArwT2LQJ6JbEKmUE59xDUNE6ENSFyq0wMX0HZnJLQRsqR02bgDyNK/CXc67YObcCwMyOB6YCNznnypNbs8wR6Ap7ErgY2Jrk6mSqXfCmQD8C7IbXDfZcMiuUiQLN1w8BRwOtgEeBp5NaqcwV7juwbU1PyuSgIJY0yeIDM2tjZpOAx4E/O+eeSHadMsw1wH8DTYCSGFuBj5xzk51zm4D7gb5m1jLJ9co0xwOfOOemO+c24o35OiIw1kD8VadlADI5KFiKl/Y4KFyaZIlT4C72Hbz3Unfn3OQkVykT9QeuCCzutQzY0cycme2f3GpllBVA05DHDfH6vHUT4a8cvOsaqgHe2ALxV7jvwO8iHFshk4OCWNIkS/yOB3YAznTOFSe7MpnIOfcH55wF1vHYE/g18PjTJFctk0wF9jKzUwKtAzcC05xzW2p4ntTOu8DvzexIM2uBd51nO+fWJLlemegF4HIz293MDsHrHnuxpidlbFAQKU1yMuuUoXrgDWgpD9y9Bn80x1vShnNuM3AyMAr4HtgDuCCplcpAzrnv8GaBPQL8gHf3elZSK5WhnHNv4d0IFwLPAsOdc9/X9DylORYREREgg1sKREREpHYUFIiIiAigoEBEREQCFBSIiIgIoKBAREREAhQUiIiICKCgQERERAIUFIiISNows3OrJEoL/qwxs5lmdnQK1LGFmf0USAOfVtKuwiIiIsCDwDeB3xvgpQA/H5hmZicFMvoly/F4abK3J7EOdaKgQERE0tG/nXMfhG4ws8eAz4DxQDKDgpOAN5N4/jpT94GIiGQE59zXwIdATzNrnIw6mFkOcCze6rFpR0GBiIhkkiK8JZrzknT+w4DPnXMbAMxshpn928wON7N3zWydmX1kZoeY2U5m9rSZfW9mP5vZY8kKZoIUFIiISEYws+bAwcBPzrm1SapGuK6DvYGXgfnABKAP8AYwDdgVb9XI5cBw4OJ6q2kYGlMgIiLpaCcz6xD43fAGGo4E2gE3JatSeEHBsVW29QCOcs7NADCzXOCvwCzn3MmBbS/jDZzsX491rUZBgYiIpKOXI2x/GLinPisSZGY9gM3OuWVVdq0MBgQBM/GCgmeCG5xzS8zsB6BZousZjYICERFJRzcCn4c83gp85pz7JbjBzGYAR0Z4/mjn3Bif6xRp1sGaKo9LA//+GmF70igoEBGRdDSr6pTEqpxzA4K/BwKEfzjnXkxgnU4Crkhg+QmngYYiIiIBZtbczNabWeeQbW3MbJOZ7RLleTsBewBz66Meda1nTRQUiIiIBDjnNgMvAeeFbD4LmO6c+ynKUwcBbzvnXH3UI456RqWgQEREpLKngPPMLPgd+afAtgpm9kogUVFQIrIY1lSPGutZWxpTICIiEsI5N8vMNgPHmtlPwG7A2wBmtjPezIfDg8ebWVPgd3h36vVSj1j214X51NIhIiKSsmo70NDMrgcOBH4CSp1zV4XsywHeB452zpUlor6x1COW/bWllgIREZHqngFuBUoIaRUAcM6VmVl93VFHrEeM+2tFYwpERCQrmdl3ZjYq3D7n3Gq8JEPfOuc+D3dMfaipHn7XUy0FIiKS8UJzFoQ4H6/pPZI5eGsTJFtN9fCtnmopEBGRbHUTMDnKfhf4Sbaa6uFbPdVSICIiWck5d1wczw3X8pD2NPtAREREAHUfiIiISICCAhEREQEUFIiIiEiAggIREREBFBSIiIhIgIICERERARQUiIiISICCAhEREQEUFIiIiEjA/wcXEcMN5AXhwQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rebin = hist.Bin(\"leading_gamma_pt_normalized\",\"$P_{T,\\gamma_1}/m_{\\gamma\\gamma}$\",25,0,10)\n",
    "new_hist = background_hists_final[\"leading_gamma_pt_normalized\"].rebin(\"leading_gamma_pt_normalized\",rebin)\n",
    "new_sig_hist = signal_hists_final[\"leading_gamma_pt_normalized\"].rebin(\"leading_gamma_pt_normalized\",rebin)\n",
    "new_data_hist = data_hists_final[\"leading_gamma_pt_normalized\"].rebin(\"leading_gamma_pt_normalized\",rebin)\n",
    "\n",
    "\n",
    "for category in [-1,1,2,3,4,5,6]:\n",
    "\n",
    "    #ax = None, rax = None\n",
    "    fig, (ax, rax) = plt.subplots(\n",
    "    nrows=2,\n",
    "    ncols=1,\n",
    "    figsize=(8,10),\n",
    "    gridspec_kw={\"height_ratios\": (3.5, 1)},\n",
    "    sharex=True\n",
    ")\n",
    "    fig.subplots_adjust(hspace=.07)\n",
    "    ax.set_yscale(\"log\")\n",
    "    ax.set_ylim([1e-5, 1e8])\n",
    "    \n",
    "    from cycler import cycler\n",
    "    colors = ['#a6cee3','#1f78b4','#b2df8a','#33a02c','#fb9a99','#e31a1c']\n",
    "    ax.set_prop_cycle(cycler(color=colors))\n",
    "\n",
    "    order = [k[0] for k,v in sorted(new_hist[:,category:category+1,:].project(\"dataset\").values().items(), key = lambda x : x[1])]\n",
    "    hist.plot1d(\n",
    "        new_hist[:,category:category+1,:].integrate(\"category\"),\n",
    "        overlay=\"dataset\",\n",
    "        clear = False,\n",
    "        stack=True,\n",
    "        ax = ax,\n",
    "        line_opts=None,\n",
    "        fill_opts=fill_opts,\n",
    "        order = order,\n",
    "        error_opts=error_opts\n",
    "    )\n",
    "\n",
    "    \n",
    "    hist.plot1d(\n",
    "        new_sig_hist[:,category:category+1,:].integrate(\"category\"), \n",
    "        overlay = \"dataset\", \n",
    "        line_opts=line_opts, \n",
    "        clear = False,\n",
    "        ax = ax,\n",
    "        )\n",
    "    \n",
    "    hist.plot1d(\n",
    "    new_data_hist[:,category:category+1,:].integrate(\"category\"),\n",
    "    overlay=\"dataset\",\n",
    "    ax=ax,\n",
    "    clear=False,\n",
    "    error_opts=data_err_opts\n",
    "    )\n",
    "\n",
    "    hist.plotratio(\n",
    "        num= (new_data_hist[:,category:category+1,:].integrate(\"category\")).integrate(\"dataset\"),\n",
    "        denom= (new_hist[:,category:category+1,:].integrate(\"category\")).integrate(\"dataset\"),\n",
    "        ax=rax,\n",
    "        error_opts=data_err_opts,\n",
    "        denom_fill_opts={},\n",
    "        guide_opts={},\n",
    "        unc='num'\n",
    "    )\n",
    "    rax.set_ylabel('Ratio')\n",
    "    rax.set_ylim(0,2)\n",
    "\n",
    "    # add some labels\n",
    "    coffee = plt.text(0., 1., r\"CMS\",\n",
    "                  fontsize=28,\n",
    "                  horizontalalignment='left',\n",
    "                  verticalalignment='bottom',\n",
    "                  transform=ax.transAxes\n",
    "                 )\n",
    "    lumi = plt.text(1., 1., r\"137.2 fb$^{-1}$ (13 TeV)\",\n",
    "                fontsize=16,\n",
    "                horizontalalignment='right',\n",
    "                verticalalignment='bottom',\n",
    "                transform=ax.transAxes\n",
    "               )\n",
    "    ax.set_title(\"Category_lveto = {}\".format(category))\n",
    "    plt.savefig(\"all_years_leading_gamma_pt_normalized_category_{}.pdf\".format(category))\n",
    "    plt.savefig(\"all_years_leading_gamma_pt_normalized_category_{}.png\".format(category))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:280: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  ax.set_ylim(0, None)\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:280: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  ax.set_ylim(0, None)\n",
      "'texgyreheros-regular.otf' can not be subsetted into a Type 3 font. The entire font will be embedded in the output.\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:280: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  ax.set_ylim(0, None)\n",
      "'texgyreheros-regular.otf' can not be subsetted into a Type 3 font. The entire font will be embedded in the output.\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:280: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  ax.set_ylim(0, None)\n",
      "'texgyreheros-regular.otf' can not be subsetted into a Type 3 font. The entire font will be embedded in the output.\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:280: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  ax.set_ylim(0, None)\n",
      "'texgyreheros-regular.otf' can not be subsetted into a Type 3 font. The entire font will be embedded in the output.\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:280: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  ax.set_ylim(0, None)\n",
      "'texgyreheros-regular.otf' can not be subsetted into a Type 3 font. The entire font will be embedded in the output.\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:280: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  ax.set_ylim(0, None)\n",
      "'texgyreheros-regular.otf' can not be subsetted into a Type 3 font. The entire font will be embedded in the output.\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:280: UserWarning: Attempted to set non-positive bottom ylim on a log-scaled axis.\n",
      "Invalid limit will be ignored.\n",
      "  ax.set_ylim(0, None)\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:357: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  rsumw = sumw_num / sumw_denom\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:357: RuntimeWarning: invalid value encountered in true_divide\n",
      "  rsumw = sumw_num / sumw_denom\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:364: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  rsumw_err = np.abs(poisson_interval(rsumw, sumw2_num / sumw_denom**2) - rsumw)\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:364: RuntimeWarning: invalid value encountered in true_divide\n",
      "  rsumw_err = np.abs(poisson_interval(rsumw, sumw2_num / sumw_denom**2) - rsumw)\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:39: RuntimeWarning: invalid value encountered in true_divide\n",
      "  scale[sumw != 0] = sumw2[sumw != 0] / sumw[sumw != 0]\n",
      "/home/users/bsathian/miniconda3/envs/analysisenv/lib/python3.7/site-packages/coffea/hist/plot.py:378: RuntimeWarning: invalid value encountered in true_divide\n",
      "  denom_unc = poisson_interval(unity, sumw2_denom / sumw_denom**2)\n",
      "'texgyreheros-regular.otf' can not be subsetted into a Type 3 font. The entire font will be embedded in the output.\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 576x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rebin = hist.Bin(\"trailing_gamma_pt_normalized\",\"$P_{T,\\gamma_2}/m_{\\gamma\\gamma}$\",25,0,10)\n",
    "new_hist = background_hists_final[\"trailing_gamma_pt_normalized\"].rebin(\"trailing_gamma_pt_normalized\",rebin)\n",
    "new_sig_hist = signal_hists_final[\"trailing_gamma_pt_normalized\"].rebin(\"trailing_gamma_pt_normalized\",rebin)\n",
    "new_data_hist = data_hists_final[\"trailing_gamma_pt_normalized\"].rebin(\"trailing_gamma_pt_normalized\",rebin)\n",
    "\n",
    "for category in [-1,1,2,3,4,5,6]:\n",
    "\n",
    "    #ax = None, rax = None\n",
    "    fig, (ax, rax) = plt.subplots(\n",
    "    nrows=2,\n",
    "    ncols=1,\n",
    "    figsize=(8,10),\n",
    "    gridspec_kw={\"height_ratios\": (3.5, 1)},\n",
    "    sharex=True\n",
    ")\n",
    "    fig.subplots_adjust(hspace=.07)\n",
    "    ax.set_yscale(\"log\")\n",
    "    ax.set_ylim([1e-5, 1e8])\n",
    "    \n",
    "    from cycler import cycler\n",
    "    colors = ['#a6cee3','#1f78b4','#b2df8a','#33a02c','#fb9a99','#e31a1c']\n",
    "    ax.set_prop_cycle(cycler(color=colors))\n",
    "\n",
    "    order = [k[0] for k,v in sorted(new_hist[:,category:category+1,:].project(\"dataset\").values().items(), key = lambda x : x[1])]\n",
    "    hist.plot1d(\n",
    "        new_hist[:,category:category+1,:].integrate(\"category\"),\n",
    "        overlay=\"dataset\",\n",
    "        clear = False,\n",
    "        stack=True,\n",
    "        ax = ax,\n",
    "        line_opts=None,\n",
    "        fill_opts=fill_opts,\n",
    "        error_opts=error_opts\n",
    "    )\n",
    "\n",
    "    \n",
    "    hist.plot1d(\n",
    "        new_sig_hist[:,category:category+1,:].integrate(\"category\"), \n",
    "        overlay = \"dataset\", \n",
    "        line_opts=line_opts, \n",
    "        clear = False,\n",
    "        ax = ax,\n",
    "        )\n",
    "    \n",
    "    hist.plot1d(\n",
    "    new_data_hist[:,category:category+1,:].integrate(\"category\"),\n",
    "    overlay=\"dataset\",\n",
    "    ax=ax,\n",
    "    clear=False,\n",
    "    error_opts=data_err_opts\n",
    "    )\n",
    "\n",
    "    hist.plotratio(\n",
    "        num= (new_data_hist[:,category:category+1,:].integrate(\"category\")).integrate(\"dataset\"),\n",
    "        denom= (new_hist[:,category:category+1,:].integrate(\"category\")).integrate(\"dataset\"),\n",
    "        ax=rax,\n",
    "        error_opts=data_err_opts,\n",
    "        denom_fill_opts={},\n",
    "        guide_opts={},\n",
    "        unc='num'\n",
    "    )\n",
    "    rax.set_ylabel('Ratio')\n",
    "    rax.set_ylim(0,10)\n",
    "\n",
    "    # add some labels\n",
    "    coffee = plt.text(0., 1., r\"CMS\",\n",
    "                  fontsize=28,\n",
    "                  horizontalalignment='left',\n",
    "                  verticalalignment='bottom',\n",
    "                  transform=ax.transAxes\n",
    "                 )\n",
    "    lumi = plt.text(1., 1., r\"137.2 fb$^{-1}$ (13 TeV)\",\n",
    "                fontsize=16,\n",
    "                horizontalalignment='right',\n",
    "                verticalalignment='bottom',\n",
    "                transform=ax.transAxes\n",
    "               )\n",
    "    ax.set_title(\"Category_lveto = {}\".format(category))\n",
    "    plt.savefig(\"all_years_trailing_gamma_pt_normalized_category_{}.pdf\".format(category))\n",
    "    plt.savefig(\"all_years_trailing_gamma_pt_normalized_category_{}.png\".format(category))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Redundant stuff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "class TauProcessor(BaseProcessorClass):\n",
    "    \n",
    "    def __init__(self, year, data = False, sumw = None):\n",
    "        super().__init__()\n",
    "        self.year = year\n",
    "        self.data = data\n",
    "        self.sumw = sumw\n",
    "    \n",
    "    \n",
    "    @property\n",
    "    def accumulator(self):\n",
    "        return self._accumulator\n",
    "\n",
    "    def process(self, events):\n",
    "        xsecs = {\n",
    "            \"GJets40100\":20790,\n",
    "            \"GJets100200\":9238,\n",
    "            \"GJets200400\":2305,\n",
    "            \"GJets400600\":274.4,\n",
    "            \"GJets600Inf\":93.46,\n",
    "            \"DYJets\":6104,\n",
    "            \"ZGToLLG\":117.864,\n",
    "            \"DiPhoton\":88.36,\n",
    "            \"signal\":0.029 * 0.0027 * 0.06 * 2,\n",
    "        }\n",
    "        lumis = {2016:35.9,2017:41.5,2018:59.8}\n",
    "        lumi = lumis[self.year]\n",
    "        output = self.accumulator.identity()\n",
    "        dataset = events.metadata[\"dataset\"]\n",
    "        \n",
    "        import os\n",
    "        import psutil\n",
    "        import time\n",
    "        \n",
    "        goodEvents = events[(events.ggMass >= 0) & (events.Category >= 1)] #all tau selections!\n",
    "        ggMass = goodEvents.ggMass\n",
    "        \n",
    "        \n",
    "        gHidx = awkward.JaggedArray.fromregular(goodEvents.gHidx)\n",
    "        tauHidx = awkward.JaggedArray.fromregular(goodEvents.tauHidx)\n",
    "\n",
    "        if not self.data:\n",
    "            output[\"sumw\"][dataset] += events.genWeight.sum()\n",
    "            weightToFill = goodEvents.genWeight * xsecs[dataset] * 1000 * lumi/self.sumw[dataset]\n",
    "        else:\n",
    "            weightToFill = None\n",
    "        \n",
    "        if \"GJets\" in dataset:\n",
    "            dataset = \"GJets\"\n",
    "        output = super().fillHistograms(output, goodEvents, dataset, weightToFill)\n",
    "        #output = super().fillTauHistograms(output, goodEvents, dataset,weightToFill)\n",
    "        return output\n",
    "\n",
    "    def postprocess(self, accumulator):\n",
    "        return accumulator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "alltau_background_hists = {}\n",
    "alltau_signal_hists = {}\n",
    "alltau_data_hists = {}\n",
    "\n",
    "for year in background_filesets.keys():\n",
    "    alltau_background_hists[year] = processor.run_uproot_job(\n",
    "    background_filesets[year],\n",
    "    treename = \"Events\",\n",
    "    processor_instance = TauProcessor(year = year,sumw = sumw[\"background\"][year]),\n",
    "    #executor = processor.futures_executor,\n",
    "    executor = processor.dask_executor,\n",
    "    executor_args={\"nano\":True, \"client\":c,\"workers\":8},)\n",
    "    \n",
    "    alltau_signal_hists[year] = processor.run_uproot_job(\n",
    "    signal_filesets[year],\n",
    "    treename = \"Events\",\n",
    "    processor_instance = TauProcessor(year = year, sumw = sumw[\"signal\"][year]),\n",
    "    #executor = processor.futures_executor,\n",
    "    executor = processor.dask_executor,\n",
    "    executor_args={\"nano\":True, \"client\":c,\"workers\":8},)\n",
    "    \n",
    "    alltau_data_hists[year] = processor.run_uproot_job(\n",
    "    data_filesets[year],\n",
    "    treename = \"Events\",\n",
    "    processor_instance = TauProcessor(year = year, data = True),\n",
    "    #executor = process.futures_executor\n",
    "    executor = processor.dask_executor,\n",
    "    executor_args={\"nano\":True, \"client\":c, \"workers\":16},)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "alltau_background_hists_final = {}\n",
    "for histName, hist in alltau_background_hists[2016].items():\n",
    "    if histName == \"sumw\":\n",
    "        continue\n",
    "    alltau_background_hists_final[histName] = hist.copy()\n",
    "    alltau_background_hists_final[histName].add(alltau_background_hists[2017][histName])\n",
    "    alltau_background_hists_final[histName].add(alltau_background_hists[2018][histName])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "alltau_signal_hists_final = {}\n",
    "for histName, hist in alltau_signal_hists[2016].items():\n",
    "    if histName == \"sumw\":\n",
    "        continue\n",
    "    alltau_signal_hists_final[histName] = hist.copy()\n",
    "    alltau_signal_hists_final[histName].add(alltau_signal_hists[2017][histName])\n",
    "    alltau_signal_hists_final[histName].add(alltau_signal_hists[2018][histName])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "alltau_data_hists_final = {}\n",
    "for histName, hist in alltau_data_hists[2016].items():\n",
    "    if histName == \"sumw\":\n",
    "        continue\n",
    "    alltau_data_hists_final[histName] = hist.copy()\n",
    "    alltau_data_hists_final[histName].add(alltau_data_hists[2017][histName])\n",
    "    alltau_data_hists_final[histName].add(alltau_data_hists[2018][histName])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams.update({\n",
    "    'font.size': 14,\n",
    "    'axes.titlesize': 18,\n",
    "    'axes.labelsize': 18,\n",
    "    'xtick.labelsize': 12,\n",
    "    'ytick.labelsize': 12\n",
    "})\n",
    "\n",
    "fill_opts = {\n",
    "    'edgecolor': (0,0,0,0.3),\n",
    "    'alpha': 0.8\n",
    "}\n",
    "error_opts = {\n",
    "    'label': 'Stat. Unc.',\n",
    "    'hatch': '///',\n",
    "    'facecolor': 'none',\n",
    "    'edgecolor': (0,0,0,.5),\n",
    "    'linewidth': 0\n",
    "}\n",
    "data_err_opts = {\n",
    "    'linestyle': 'none',\n",
    "    'marker': '.',\n",
    "    'markersize': 10.,\n",
    "    'color': 'k',\n",
    "    'elinewidth': 1,}\n",
    "\n",
    "line_opts={'linewidth':3, \"color\":\"black\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import coffea.hist as hist\n",
    "\n",
    "fig, (ax, rax) = plt.subplots(\n",
    "    nrows=2,\n",
    "    ncols=1,\n",
    "    figsize=(8,10),\n",
    "    gridspec_kw={\"height_ratios\": (3.5, 1)},\n",
    "    sharex=True\n",
    ")\n",
    "fig.subplots_adjust(hspace=.07)\n",
    "ax.set_yscale('log')\n",
    "ax.set_ylim([1e-5, 1e8])\n",
    "from cycler import cycler\n",
    "colors = ['#a6cee3','#1f78b4','#b2df8a','#33a02c','#fb9a99','#e31a1c']\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "\n",
    "rebin = hist.Bin(\"diphoton_mass\",\"$m_{\\gamma\\gamma}$\",100,0,500)\n",
    "new_hist = alltau_background_hists_final[\"diphoton_mass\"].rebin(\"diphoton_mass\",rebin)\n",
    "\n",
    "\n",
    "hist.plot1d(\n",
    "    new_hist,\n",
    "    overlay=\"dataset\",\n",
    "    ax=ax,\n",
    "    clear=False,\n",
    "    stack=True,\n",
    "    line_opts=None,\n",
    "    fill_opts=fill_opts,\n",
    "    error_opts=error_opts\n",
    ")\n",
    "\n",
    "new_sig_hist = alltau_signal_hists_final[\"diphoton_mass\"].rebin(\"diphoton_mass\",rebin)\n",
    "hist.plot1d(\n",
    "    new_sig_hist, overlay = \"dataset\", \n",
    "    line_opts=line_opts, \n",
    "    clear = False,\n",
    "    ax = ax,\n",
    ")\n",
    "\n",
    "new_data_hist = alltau_data_hists_final[\"diphoton_mass\"].rebin(\"diphoton_mass\",rebin)\n",
    "hist.plot1d(\n",
    "    new_data_hist,\n",
    "    overlay=\"dataset\",\n",
    "    ax=ax,\n",
    "    clear=False,\n",
    "    error_opts=data_err_opts\n",
    ")\n",
    "\n",
    "hist.plotratio(\n",
    "    num= new_data_hist.integrate(\"dataset\"),\n",
    "    denom= new_hist.integrate(\"dataset\"),\n",
    "    ax=rax,\n",
    "    error_opts=data_err_opts,\n",
    "    denom_fill_opts={},\n",
    "    guide_opts={},\n",
    "    unc='num'\n",
    ")\n",
    "rax.set_ylabel('Ratio')\n",
    "rax.set_ylim(0,2)\n",
    "\n",
    "# add some labels\n",
    "coffee = plt.text(0., 1., r\"CMS Preliminary\",\n",
    "                  fontsize=28,\n",
    "                  horizontalalignment='left',\n",
    "                  verticalalignment='bottom',\n",
    "                  transform=ax.transAxes\n",
    "                 )\n",
    "lumi = plt.text(1., 1., r\"137.2 fb$^{-1}$ (13 TeV)\",\n",
    "                fontsize=16,\n",
    "                horizontalalignment='right',\n",
    "                verticalalignment='bottom',\n",
    "                transform=ax.transAxes\n",
    "               )\n",
    "plt.savefig(\"all_years_alltau_mgg.pdf\")\n",
    "plt.savefig(\"all_years_alltau_mgg.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, (ax, rax) = plt.subplots(\n",
    "    nrows=2,\n",
    "    ncols=1,\n",
    "    figsize=(8,10),\n",
    "    gridspec_kw={\"height_ratios\": (3.5, 1)},\n",
    "    sharex=True\n",
    ")\n",
    "fig.subplots_adjust(hspace=.07)\n",
    "ax.set_yscale('log')\n",
    "ax.set_ylim([1e-7, 1e8])\n",
    "from cycler import cycler\n",
    "colors = ['#a6cee3','#1f78b4','#b2df8a','#33a02c','#fb9a99','#e31a1c']\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "\n",
    "rebin = hist.Bin(\"diphoton_mass\",\"$P_{T,\\gamma_1}/m_{\\gamma\\gamma}$\",25,0,10)\n",
    "new_hist = alltau_background_hists_final[\"leading_gamma_pt_normalized\"].rebin(\"leading_gamma_pt_normalized\",rebin)\n",
    "\n",
    "\n",
    "hist.plot1d(\n",
    "    new_hist,\n",
    "    overlay=\"dataset\",\n",
    "    ax=ax,\n",
    "    clear=False,\n",
    "    stack=True,\n",
    "    line_opts=None,\n",
    "    fill_opts=fill_opts,\n",
    "    error_opts=error_opts\n",
    ")\n",
    "\n",
    "new_sig_hist = alltau_signal_hists_final[\"leading_gamma_pt_normalized\"].rebin(\"leading_gamma_pt_normalized\",rebin)\n",
    "hist.plot1d(\n",
    "    new_sig_hist, overlay = \"dataset\", \n",
    "    line_opts=line_opts, \n",
    "    clear = False,\n",
    "    ax = ax,\n",
    ")\n",
    "\n",
    "new_data_hist = alltau_data_hists_final[\"leading_gamma_pt_normalized\"].rebin(\"leading_gamma_pt_normalized\",rebin)\n",
    "hist.plot1d(\n",
    "    new_data_hist,\n",
    "    overlay=\"dataset\",\n",
    "    ax=ax,\n",
    "    clear=False,\n",
    "    error_opts=data_err_opts\n",
    ")\n",
    "\n",
    "hist.plotratio(\n",
    "    num= new_data_hist.integrate(\"dataset\"),\n",
    "    denom= new_hist.integrate(\"dataset\"),\n",
    "    ax=rax,\n",
    "    error_opts=data_err_opts,\n",
    "    denom_fill_opts={},\n",
    "    guide_opts={},\n",
    "    unc='num'\n",
    ")\n",
    "rax.set_ylabel('Ratio')\n",
    "rax.set_ylim(0,2)\n",
    "\n",
    "# add some labels\n",
    "coffee = plt.text(0., 1., r\"CMS Preliminary\",\n",
    "                  fontsize=28,\n",
    "                  horizontalalignment='left',\n",
    "                  verticalalignment='bottom',\n",
    "                  transform=ax.transAxes\n",
    "                 )\n",
    "lumi = plt.text(1., 1., r\"137.2 fb$^{-1}$ (13 TeV)\",\n",
    "                fontsize=16,\n",
    "                horizontalalignment='right',\n",
    "                verticalalignment='bottom',\n",
    "                transform=ax.transAxes\n",
    "               )\n",
    "plt.savefig(\"all_years_alltau_leading_gamma_pt_normalized.pdf\")\n",
    "plt.savefig(\"all_years_alltau_leading_gamma_pt_normalized.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, (ax, rax) = plt.subplots(\n",
    "    nrows=2,\n",
    "    ncols=1,\n",
    "    figsize=(8,10),\n",
    "    gridspec_kw={\"height_ratios\": (3.5, 1)},\n",
    "    sharex=True\n",
    ")\n",
    "fig.subplots_adjust(hspace=.07)\n",
    "ax.set_yscale('log')\n",
    "ax.set_ylim([1e-7, 1e8])\n",
    "from cycler import cycler\n",
    "colors = ['#a6cee3','#1f78b4','#b2df8a','#33a02c','#fb9a99','#e31a1c']\n",
    "ax.set_prop_cycle(cycler(color=colors))\n",
    "\n",
    "rebin = hist.Bin(\"diphoton_mass\",\"$P_{T,\\gamma_2}/m_{\\gamma\\gamma}$\",25,0,10)\n",
    "new_hist = alltau_background_hists_final[\"trailing_gamma_pt_normalized\"].rebin(\"trailing_gamma_pt_normalized\",rebin)\n",
    "\n",
    "\n",
    "hist.plot1d(\n",
    "    new_hist,\n",
    "    overlay=\"dataset\",\n",
    "    ax=ax,\n",
    "    clear=False,\n",
    "    stack=True,\n",
    "    line_opts=None,\n",
    "    fill_opts=fill_opts,\n",
    "    error_opts=error_opts\n",
    ")\n",
    "\n",
    "new_sig_hist = alltau_signal_hists_final[\"trailing_gamma_pt_normalized\"].rebin(\"trailing_gamma_pt_normalized\",rebin)\n",
    "hist.plot1d(\n",
    "    new_sig_hist, overlay = \"dataset\", \n",
    "    line_opts=line_opts, \n",
    "    clear = False,\n",
    "    ax = ax,\n",
    ")\n",
    "\n",
    "new_data_hist = alltau_data_hists_final[\"trailing_gamma_pt_normalized\"].rebin(\"trailing_gamma_pt_normalized\",rebin)\n",
    "hist.plot1d(\n",
    "    new_data_hist,\n",
    "    overlay=\"dataset\",\n",
    "    ax=ax,\n",
    "    clear=False,\n",
    "    error_opts=data_err_opts\n",
    ")\n",
    "\n",
    "hist.plotratio(\n",
    "    num= new_data_hist.integrate(\"dataset\"),\n",
    "    denom= new_hist.integrate(\"dataset\"),\n",
    "    ax=rax,\n",
    "    error_opts=data_err_opts,\n",
    "    denom_fill_opts={},\n",
    "    guide_opts={},\n",
    "    unc='num'\n",
    ")\n",
    "rax.set_ylabel('Ratio')\n",
    "rax.set_ylim(0,2)\n",
    "\n",
    "# add some labels\n",
    "coffee = plt.text(0., 1., r\"CMS Preliminary\",\n",
    "                  fontsize=28,\n",
    "                  horizontalalignment='left',\n",
    "                  verticalalignment='bottom',\n",
    "                  transform=ax.transAxes\n",
    "                 )\n",
    "lumi = plt.text(1., 1., r\"137.2 fb$^{-1}$ (13 TeV)\",\n",
    "                fontsize=16,\n",
    "                horizontalalignment='right',\n",
    "                verticalalignment='bottom',\n",
    "                transform=ax.transAxes\n",
    "               )\n",
    "plt.savefig(\"all_years_alltau_trailing_gamma_pt_normalized.pdf\")\n",
    "plt.savefig(\"all_years_alltau_trailing_gamma_pt_normalized.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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