Example analyzing data.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analyze the Kinematics!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import uproot\n",
    "import numpy as np\n",
    "from numpy import ndarray\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import textwrap\n",
    "import awkward as ak"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#open relevant files\n",
    "Graviton = \"mc.graviton.4lep.root\"\n",
    "graviton = uproot.open(Graviton)\n",
    "\n",
    "Higgs = \"mc_345060.ggH125_ZZ4lep.4lep.root\"\n",
    "higgs = uproot.open(Higgs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_fig(xTitle=\"xTitle\",yTitle=\"yTitle\"):\n",
    "    fig = plt.figure(figsize=(10,5))\n",
    "\n",
    "    ax = plt.gca()\n",
    "    ax.set_prop_cycle(color=['#002BFF','#A15FFF','#FF0061','#FF8913'])\n",
    "    ax.set_xlabel(xTitle,fontsize=18,labelpad=6)\n",
    "    ax.set_ylabel(yTitle,fontsize=18)\n",
    "    ax.tick_params(labelsize=10, direction='out', length=8, width=2)\n",
    "    ax.yaxis.offsetText.set_fontsize(10)\n",
    "    ax.xaxis.labelpad = 15\n",
    "    ax.yaxis.labelpad = 15\n",
    "    ax.tick_params(axis='both', which='major', labelsize=15)\n",
    "    \n",
    "    return fig, ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "titles = ['Complete Histogram']\n",
    "ytitle = \"Number of Leptons\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Generate Datasets\n",
    "\n",
    "Here I generate the datasets to make plots of them later - the only filter applied is that all events must be four lepton events."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Are all events in our dataset four lepton events?\n",
      "False\n"
     ]
    }
   ],
   "source": [
    "#DataFrame creation for graviton\n",
    "tree    = b'mini;1' \n",
    "lep_charge = ak.fromiter(graviton[tree].array(b'lep_charge'))\n",
    "\n",
    "#Confirmation that all events are four particle events\n",
    "print('Are all events in our dataset four lepton events?')\n",
    "print(len(lep_charge) == len(lep_charge[lep_charge.counts==4]))\n",
    "\n",
    "#make filters for only four lepton events\n",
    "#start with filtering the lep_charge dataset\n",
    "counts_filter = (lep_charge.counts==4)\n",
    "lep_charge = lep_charge[counts_filter]\n",
    "lep_charge_sum = lep_charge.sum()\n",
    "\n",
    "#Z_pl=sum(lep_pt*sinh(lep_eta))\n",
    "lep_pt = ak.fromiter(graviton[tree].array(b'lep_pt')*1e-3)\n",
    "lep_pt = lep_pt[counts_filter]\n",
    "sinh_lep_eta = ak.fromiter(np.sinh(graviton[tree].array(b'lep_eta')))\n",
    "sinh_lep_eta = sinh_lep_eta[counts_filter]\n",
    "prod =  lep_pt*sinh_lep_eta\n",
    "pl = prod.sum()\n",
    "\n",
    "#Sum lep types\n",
    "lep_type = ak.fromiter(graviton[tree].array(b'lep_type'))\n",
    "lep_type = lep_type[counts_filter]\n",
    "leptons = lep_type.sum()\n",
    "\n",
    "#Z_pt=sqrt((sum(lep_pt*cos(lep_phi)))^2+(sum(lep_pt*sin(lep_phi)))^2)\n",
    "cos_lep_phi = ak.fromiter(np.cos(graviton[tree].array(b'lep_phi')))\n",
    "cos_lep_phi = cos_lep_phi[counts_filter]\n",
    "sin_lep_phi = ak.fromiter(np.sin(graviton[tree].array(b'lep_phi')))\n",
    "sin_lep_phi = sin_lep_phi[counts_filter]\n",
    "prod1 = lep_pt * cos_lep_phi\n",
    "prod2 = lep_pt * sin_lep_phi\n",
    "pt = np.sqrt((prod1.sum())**2+(prod2.sum())**2)\n",
    "\n",
    "px = prod1\n",
    "phi = np.arccos(px/(np.sqrt((prod1)**2+(prod2)**2)))\n",
    "\n",
    "eta = np.arcsinh(prod/(np.sqrt((prod1)**2+(prod2)**2)))\n",
    "\n",
    "#Z_E=sum(lep_E)\n",
    "Ebit = ak.fromiter(graviton[tree].array(b'lep_E')*1e-3)\n",
    "Ebit = Ebit[counts_filter]\n",
    "E = Ebit.sum()\n",
    "\n",
    "y = 0.5*np.log((Ebit+prod)/(Ebit-prod))\n",
    "\n",
    "#Missing transverse energy\n",
    "met_et = graviton[tree].array(b'met_et')*1e-3\n",
    "met_et = met_et[counts_filter]\n",
    "\n",
    "#Store isTight values to filter later leptons \n",
    "#that don't pass the strictest requirements\n",
    "lep_tight = ak.fromiter(graviton[tree].array(b'lep_isTightID'))\n",
    "lep_tight = lep_tight[counts_filter]\n",
    "lep_tight = lep_tight.sum()\n",
    "\n",
    "#Invariant mass of the four leptons\n",
    "#adds momentum component by component\n",
    "InvMass = np.sqrt(E**2-pt**2-pl**2)\n",
    "\n",
    "data = {'pl':pl,'pt':pt,'E':E,'InvMass':InvMass,'lep_type':leptons, 'MET':met_et, 'lep_tight':lep_tight, \n",
    "        'lep_charge':lep_charge_sum}\n",
    "\n",
    "#store data before summing over leptons for individual lepton analysis\n",
    "gravitonstoof = ak.fromiter(graviton[tree].array(b'lep_pt'))*1e-3\n",
    "gravitonstoof2 = prod\n",
    "gravitonstoof3 = Ebit\n",
    "gravitonstoof4 = eta\n",
    "gravitonstoof5 = px\n",
    "gravitonstoof6 = phi\n",
    "gravitonstoof7 = y\n",
    "df_graviton = pd.DataFrame(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Are all events in our dataset four lepton events?\n",
      "False\n"
     ]
    }
   ],
   "source": [
    "#DataFrame creation for higgs\n",
    "tree    = b'mini;1' \n",
    "lep_charge = ak.fromiter(higgs[tree].array(b'lep_charge'))\n",
    "\n",
    "#Confirmation that all events are four particle events\n",
    "print('Are all events in our dataset four lepton events?')\n",
    "print(len(lep_charge) == len(lep_charge[lep_charge.counts==4]))\n",
    "\n",
    "#make filters for only four lepton events\n",
    "#start with filtering the lep_charge dataset\n",
    "counts_filter = (lep_charge.counts==4)\n",
    "lep_charge = lep_charge[counts_filter]\n",
    "lep_charge_sum = lep_charge.sum()\n",
    "\n",
    "#Z_pl=sum(lep_pt*sinh(lep_eta))\n",
    "lep_pt = ak.fromiter(higgs[tree].array(b'lep_pt')*1e-3)\n",
    "lep_pt = lep_pt[counts_filter]\n",
    "sinh_lep_eta = ak.fromiter(np.sinh(higgs[tree].array(b'lep_eta')))\n",
    "sinh_lep_eta = sinh_lep_eta[counts_filter]\n",
    "prod =  lep_pt*sinh_lep_eta\n",
    "pl = prod.sum()\n",
    "\n",
    "#Sum lep types\n",
    "lep_type = ak.fromiter(higgs[tree].array(b'lep_type'))\n",
    "lep_type = lep_type[counts_filter]\n",
    "leptons = lep_type.sum()\n",
    "\n",
    "#Z_pt=sqrt((sum(lep_pt*cos(lep_phi)))^2+(sum(lep_pt*sin(lep_phi)))^2)\n",
    "cos_lep_phi = ak.fromiter(np.cos(higgs[tree].array(b'lep_phi')))\n",
    "cos_lep_phi = cos_lep_phi[counts_filter]\n",
    "sin_lep_phi = ak.fromiter(np.sin(higgs[tree].array(b'lep_phi')))\n",
    "sin_lep_phi = sin_lep_phi[counts_filter]\n",
    "prod1 = lep_pt * cos_lep_phi\n",
    "prod2 = lep_pt * sin_lep_phi\n",
    "pt = np.sqrt((prod1.sum())**2+(prod2.sum())**2)\n",
    "\n",
    "px = prod1\n",
    "phi = np.arccos(px/(np.sqrt((prod1)**2+(prod2)**2)))\n",
    "\n",
    "eta = np.arcsinh(prod/(np.sqrt((prod1)**2+(prod2)**2)))\n",
    "\n",
    "#Z_E=sum(lep_E)\n",
    "Ebit = ak.fromiter(higgs[tree].array(b'lep_E')*1e-3)\n",
    "Ebit = Ebit[counts_filter]\n",
    "E = Ebit.sum()\n",
    "\n",
    "y = 0.5*np.log((Ebit+prod)/(Ebit-prod))\n",
    "\n",
    "#Missing transverse energy\n",
    "met_et = higgs[tree].array(b'met_et')*1e-3\n",
    "met_et = met_et[counts_filter]\n",
    "\n",
    "#Store isTight values to filter later leptons \n",
    "#that don't pass the strictest requirements\n",
    "lep_tight = ak.fromiter(higgs[tree].array(b'lep_isTightID'))\n",
    "lep_tight = lep_tight[counts_filter]\n",
    "lep_tight = lep_tight.sum()\n",
    "\n",
    "#Invariant mass of the four leptons\n",
    "#adds momentum component by component\n",
    "InvMass = np.sqrt(E**2-pt**2-pl**2)\n",
    "\n",
    "data = {'pl':pl,'pt':pt,'E':E,'InvMass':InvMass,'lep_type':leptons, 'MET':met_et, 'lep_tight':lep_tight, \n",
    "        'lep_charge':lep_charge_sum}\n",
    "\n",
    "#store data before summing over leptons for individual lepton analysis\n",
    "higgsstoof = ak.fromiter(higgs[tree].array(b'lep_pt'))*1e-3\n",
    "higgsstoof2 = prod\n",
    "higgsstoof3 = Ebit\n",
    "higgsstoof4 = eta\n",
    "higgsstoof5 = px\n",
    "higgsstoof6 = phi\n",
    "higgsstoof7 = y\n",
    "df_higgs = pd.DataFrame(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Invariant Mass Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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f+cxn2GOPPQDo168ft912GwA9evRg1apVvP766yxZsoR/+Zd/YdmyZVxxxRVceOGF633GjBkzmv0+3nvvPR5//HEuueQShg0bxqmnnsq5557LlltuycyZMxk6dCgAq1evpnfv3gAMGzaMd955h5UrV7J06VIGDRoEwHnnncdBBx1ESmmDz4mIdV+vXLmSsWPHcvHFF9O9e/dmv8dSmRBKkkpWOBdx0smtF4da15NPPsmSJUvYfPPN6datGwDz5s2jpqaGefPmsdtuu61Xt1+/fgBsskk2MPnrX/+aiRMnMm/ePObMmcPatWv51Kc+td5nDB8+fF1vYqHzzz+fkSNHVuQ++vTpQ58+fdb11B155JGce+65HHzwwRx33HH85Cc/2eCcRx55BMjmEF511VVcddVVG1xz0aJF696/+OKLbLPNNgCsWbOGsWPHMn78eMaMGVORe6gUh4wlSVLJlixZwvjx45k6dSqbbropf/rTn4AP5g9uu+226xZLPPfcc1xzzTV88YtfXHf+Jptswm233cYRRxxB9+7dOf/88znppJM2+JwZM2Ywa9asDV6VSgYBttpqK7bbbjueeeYZAO655x769evHAQccwM0338wrr7wCwNKlS3n++edLuubQoUN59tlnWbBgAe+++y5TpkzhsMMOI6XExIkTqamp4Vvf+lbF7qFSTAglSVJJVq1axZgxY7jggguoqanhjDPOYNKkScAHK4yPPfZYXnrpJXbbbTfGjRvHlVdeycc//vF11+jSpQuHHHIInTt3pnv37rz11lt87nOfa3RMxxxzDJ/+9Kd55pln6NOnD7/97W8BOPTQQ3nppZc2Wu+SSy5h/PjxDBw4kFmzZnHaaafRr18/zj77bA488EAGDhzIqFGjWLJkSUnxdO7cmUsvvZSDDjqImpoajj76aPr3788DDzzANddcw7333rtuPuTtt9/e6PuutCg21q3SDBkyJD322GOtHYYk1as5t5txyFhqXyJiZkppSLFjziGUpA7IfQcllcMhY0mSpCpnQihJklTlTAglSZKqnAmhJElSlTMhbISIGB0RVyxfvry1Q5Ekqc2YPn06xx577AblDz74ID/84Q+b/fMXLVrEiBEjqKmpoX///kyePLlovTvvvJNddtmFvn37cu6555Z8rLGKXbPUWFuK2840gdvOSGqrWmKVsdvOqK6LL76Y999/v9U2Xl6yZAlLlixh8ODBrFixgj333JNbb7113ZNSgHVPRbnrrrvo06cPQ4cO5YYbbqBfv34NHtuY+p5cUt81e/XqtdFYK62hbWfsIZQkSWU54ogjOP300xk+fDhbbbUVd999N5BtTr148WKGDRvGTjvtxPTp0wE46qijuP/++xs89+qrr2bPPfdk4MCBDB8+vFFxbb311gwePBiAbt26UVNTw+LFi9er8+ijj9K3b1922mknunTpwrhx45g6depGj1177bXstddeDBo0iBNPPJG1a9eWFFN91ywl1pZkQihJapRJl33wUnWZO3cuPXv2ZMaMGVx++eVcd911AMyaNYtu3brxyCOP8Mtf/pIzzjhjXf3a5xsXO3fFihWcd955PPTQQ8yZM4dp06at93nDhw9f93SPwldtMlnMwoULeeKJJ9Y9p7jW4sWL2W677da979Onz7pErL5j8+fP58Ybb+SBBx5g1qxZdOrUad09b0xDn7exWFuSG1NLkqSSrVq1iuXLl/PNb34TgPfee4+ePXvy3nvv8frrr3PaaacBMGjQIF577TXefvtt1qxZQ48ePeo9t1OnTqxevZpvf/vbHHfccQwZsv6o5owZM8qKceXKlYwdO5aLL76Y7t27r3es2FS5iGjw2D333MPMmTMZOnQoAKtXr6Z3794ADBs2jHfeeYeVK1eydOlSBg0aBMB5553HQQcd1ODnbSzWltTkhDAi9gQ+BsxIKb3d9JAkSVJb9dRTT7HnnnvSqVMnAObMmcOAAQOYN28effv2pUuXLgA8/vjj7L777jz11FPr5sXVd27Xrl2ZO3cu06ZN44QTTuD444/na1/72rrPHD58OCtWrNgglvPPP5+RI0euV7ZmzRrGjh3L+PHjGTNmzAbn9OnTh0WLFq17/+KLL7LNNts0eCylxHHHHcdPfvKTDa73yCOPAPXPIWzo8zYWa0sqOSGMiO8A+6WURheUXQ98Pn/7XER8JqX0fxWOUZJUAodu1RLmzp27rhcMsqTu8MMPZ/bs2SxYsIB33nmHNWvWcOaZZ3LRRRfx5JNPMnDgwAbPffbZZ9l5550ZN24c8+bN4+231+9fKrWHMKXExIkTqampqXdhy9ChQ3n22WdZsGAB2267LVOmTOH6669v8FhEcPjhh/PNb36T3r17s3TpUlasWMH222+/0Zjqu2YpsbakcuYQjgNeqH0TEfvnZVOA/wK2Br5X0egkSVKb8uSTT66X1M2dO5cBAwYwe/Zsxo8fzz777MNee+3FKaecwt57771eQljfueeccw677LILgwcPZsGCBev1DpbjgQce4JprruHee+9dN8/w9ttvB+DQQw/lpZdeonPnzlx66aUcdNBB1NTUcPTRR9O/f3+Aeo/169ePs88+mwMPPJCBAwcyatQolixZUlJM9V2zoVhbQ8nbzkTEa8CZKaVL8vc/B8YCfVJKKSLOBw5LKX2q2aJtY9x2RlJb0hZ6CN2KRmq7KrXtzKbAqoL3+wN3pw8yynnAto0LUZIkSa2lnIRwMTAQICK2B/oBfy043gt4p3KhSZIkqSWUs8p4GvC1iOgEDCNL/v5YcHwAsLByoUmSJKkllJMQnkXWQ/g1smTwG7UriiPio8ARwG8rHqEkSZKaVckJYUppGXBARHQHVqeU1tSpsh+waMMzJUmVVruAxEUckiqh7I2pU0pvFilbDcyuSESSJElqUWUnhBHxKaAv8HEg6h5PKf1vBeKSJJWgLWw1I6n9K+dJJVsCVwOjaouKVEuACaEkSVI7Uk4P4aVkyeAvgHuB15slIkmSJLWochLCUcAvU0pfb65gJEmS1PLK2Zh6E1w4IkmS1OGUkxDOAHZvrkAkSZLUOspJCL8FHBERY5srmJYSEdtFxD0RMT8inoqIn0ZEsUUykiRJHV45cwh/AawEboqIl4DngLV16qSU0gGVCq4ZvQd8P6X0WER0Ae4CxgD/r3XDkiRJannl9BDuBHwIeIEsofoEsGOd106VDrBQRPSNiF9FxOyIWBsR0+up1y/vAVwVES9FxFn5M5gBSCktSSk9ln/9LjAH2K45Y5ckSWqrynl03Q7NGEep+gOHAg8DXYpViIhewN3APOBw4JPABWTJ7+lF6n8c+DfgwGaJWJIkqY0r+0klrWxaSmkqQETcDGxepM5JwEeBMflj9u7Kn788KSJ+WvjovYj4MHAzcHFKaX7zhy9JktT2NObRdd2BkXwwPPwccFdKaUUlAysmpfR+CdUOAf5U55nLU4DzgP2AaQD5EPJ1wBMppQsqHaskVaNij9KbdHLLxyGpPOXMISQijgcWAb8Dfpq/fge8GBETKx9eo+wKPF1YkFJ6AViVH6v1K2AF8O36LhQRqaFXcwQvSZLU0kpOCCPiMOAK4FWyLWhG5a9vAq8AV0TE6OYIsky9gDeKlC/LjxER/wJMBIYAT0TErIg4pcUilCRJakPKGTL+HjAfGJZSWllQfk9E/A/ZQo/vkw/JtrJivXdRW55SeiB/3/BFUmqwzpAhQ+wllCRJ7V45Q8a7A1fVSQYByOcPXk3beJLJMqBnkfIeFO85lCRJqmplzSGk4V61ttJb9jTrzxUkIrYDNqXO3EJJkiSVlxDOBo6LiE3rHoiIzYAJeZ3WdgdwUER0Kyj7PLAa+GslPiAiRkfEFcuXL6/E5SRJklpVOQnh+UAN8HhEnBwRI/LX14GZZL1yP2uOIGtFRNeIODIijgS2BbaofR8RXfNqvwTeAW6JiJERcQIwCbiwzlY0jZZSmpZSOqFHjx6VuJwkSVKrKudJJbfmyd95wCV8MEQcwFvA12s3jW5Gvcm2uSlU+35HYGFKaVlEHABcSrbA5Q3gIrKkUJLarWJ7/ElSJZS1MXVK6fKIuJ5su5kdyZLBf5JtTN3s46cppYWUtjp4HrB/c8cjSZLUEZScEEbEJ4BXU0pvsGEvHRHxUWCLfBNoSZIktRPlzCFcABzRwPHD8jodnotKJElSR1JOQrixodpNaDtbzzQrF5VIkqSOpKw5hDSc8NXgxs+SVBGFC0gmndx6cUiqDg0mhBFxHHBcQdHpEfGVIlU/BgwAfl/B2CRJktQCNtZD2JNsNTFkvYNbAF3r1EnASuBK4L8qGZwkSZKaX4MJYUppMjAZICLeB76RUrq+JQJryyJiNDC6b9++rR2KJElSk5W8qCSltInJYMZFJZIkqSMpd1EJEfFh4LPATnnRc8BfU0pvVzAuSVKuIz2hpPZeXCgjtS1lJYQR8UXgQqAXH2xDk4A3IuLbKaWrKhueJEmSmls5Tyr5PHAV8AJwPjCPLCnsB5wE/DYiVqeUbmyGOCVJ7VRH6uGUOqpyeghPA54G9k4pvVlQPjUiLgceIVtlbEIoSZLUjpTzpJJdgP+pkwwCkFJaDvwPsHOlAmvLfHSdJEnqSMpJCF+m4cfXvQ/8X9PCaR9cZSxJkjqScoaMrwImRMTlKaWVhQciojvwZbJeQklSIznfTlJrKCchnAF8DngynzP4NNkK437AV4HXgBkRsW/hSSml+yoUqyRJkppBOQnhXQVfn0eWDMIHw8jb16kTeZ1OjY5OkiRJza6chPBLzRaFJEmSWk3JCWFK6ermDESSJEmto5xVxpIkSeqAykoII2K7iLgyIl6MiHcjYv+8fIu8fGjzhNm2uA+hJEnqSMp5dN2OwMPAR/I/t649llJ6NSKGAMcDf6t0kG1NSmkaMG3IkCFfae1YJKk9KtxeZ9LJrReHpEw5i0rOIdt8egCwGnilzvHbgdEVikuSJEktpJwh45HA5SmlRXyw5Uyh54E+FYlKkqrApMvciFpS21BOQtgdWNLA8S6U1+MoSZKkNqCchHAR0L+B43sD/2haOJIkSWpp5SSEtwBfjogBBWUJICLGAkcBN1UwNkmSJLWAchLCc4AXgUeAa8mSwR9ExENkieBs4IKKRyhJkqRmVXJCmFJ6E/g08BtgCNmzikcBuwCXAyNSSm83R5CSJElqPmVtTJ1SejOldGpKaQtgS2Ar4OMppf8A1kRE7+YIsq1xY2pJktSRNHpVcErp1TpF3wLOAjo1KaJ2wI2pJVWSW89Iam1uEyNJzaQ20St8EofJn6S2qKwhY0mSJHU8JoSSJElVziFjSWpmDhNLauvsIZQktSqf6Sy1vgZ7CCPitjKu1beJsUiSJKkVbGzI+HNlXi81NhBJkiS1jgYTwpSSQ8qSVIJiW8yoPIXDxraj1LJM+CRJkqqcCWEj+Og6SZLUkZgQNkJKaVpK6YQePXq0diiSJElNZkIoSZJU5dyYWpLUZtW3P6GLTqTKsodQkiSpytWbEEbEcxFxWMH7/46IAS0TliRJklpKQz2EnwC6FbyfBAxs1mgkSZLU4hpKCBcDu9Up80kkkiRJHUxDi0qmAt+LiIOBpXnZ6RHxlQbOSSmlAyoWnSRJkppdQwnh94FlwEhge7LewS2Ari0QlySpitW3uriheq48lhqv3oQwpbQa+GH+IiLeB76RUrq+hWKTJElSCyhn25kvAQ82VyCSJElqHSVvTJ1Surr264j4OLBj/nZBSun1SgcmSZKkllHWxtQRsXtE/BV4BXgkf70SEdMjwi1pJEmS2qGSewjzTanvBz4C3AbMzQ/1B0YDMyJin5TSUxWPUpIkSc2mnGcZnwWsAfZJKT1ZeCBPFu/L64ytXHiS1L6UujpWktqScoaM9wUuq5sMAqSU5gKXA/tVKrC2LCJGR8QVy5cvb+1QJJElYS2ZiLX050lScysnIdwUeLmB40vyOh1eSmlaSumEHj16tHYokiRJTVZOQvgc8LkGjn8uryNJkqR2pJw5hP8L/CQirgfOAZ7Oy2uA/wQOBH5Q2fAkqeUVe/qFQ8SSOrJyEsLzgcHAOODzwPt5+SZAADcBF1Q0OkmSJDW7cjamXgt8PiJ+A/wb2cbUAfwTuDWldHezRCipXfCZspLUfpXTQwhASuku4K5miEWSJEmtoOyEUFL7U9t711577krtfWzpXkrnFUrqKMp6dJ0kSZI6HnsIJbUpG+vNbOneTnsB24+Gvjec4yo1zB5CSZKkKmdCKEmSVOVKGjKOiI8CRwHPpJQead6QpI6jNYepOvpQZ6n351ChJG1cqT2E7wC/BvZoxlgkSZLUCkpKCFNK7wOLgO7NG44kSZJaWjmrjK8Gjo2IySmld5orIEkfaEv7B3akodeOdC/VqqEpA/79SuUrJyF8EBgDzIqIy4FngVV1K6WU7qtQbJIkSWoB5SSEhY+rmwykOscjL+vU1KAkSZLUcspJCL/UbFFI6lDKHeru6CuiJamtKzkhTCld3ZyBSJIkqXW4MbUkSVKVK+tZxhGxHXAmcCDQGzg4pXRvRGwBnAf8IqX0t8qHKaklNGZVc2M2iF5X1sDntMYwskPXkqpVyT2EEbEj8BgwFniKgsUjKaVXgSHA8ZUOsLlExC8iYnFE1F0cI0mSVFXKGTI+B3gfGACMJ1tVXOh24DMViqsl3AAMbu0gJEmSWls5CeFI4PKU0iI23HIG4HmgT0WiqkdE9I2IX0XE7IhYGxHT66nXLyLuiYhVEfFSRJwVEetth5NSui+l9H/NGa8kSVJ7UM4cwu7AkgaOdynzeo3RHzgUeDj/vA1ERC/gbmAecDjwSeACsuT39GaOT1WiMU9CqNTTE5ry9JKWfoJDa87Jcz6gKqktPTVIag7lJHCLyBKy+uwN/KNp4WzUtJTSVICIuBnYvEidk4CPAmNSSm8Cd0VEd2BSRPw0L5MkSVKunCHjW4AvR8SAgrIEEBFjgaOAmyoY2wZSSu+XUO0Q4E91Er8pZEnifuV8XkSkhl7lXEuSJKmtKqeH8Bzgc8AjwH1kyeAPIuLHwF7ALLKh2da2K3BvYUFK6YWIWJUfm9YqUanDqvRWLS01FNyU7WLaq450L2o8h3+lDZXcQ5j3uH0a+A3ZFjMBjAJ2AS4HRqSU3m6OIMvUC3ijSPmy/BgAEfGbiHgx//rFiPhN3RNSStHQq7luQJIkqSWVtQgkTwpPBU7NN6MO4NWUUlsbPi0WTxSWp5TazZ6JkiRJzanRq4LzzajbomVAzyLlPSjecyhJklTVyk4II+Jo4Ahgp7zoOeD3KaVmXVBShqfJ5gqukz9yb9P8mCRJkgqUnBBGRFdgKrA/2fDrG/mfQ4GjI+JE4LCU0lvNEGc57gC+GxHdUkor8rLPA6uBv1biAyJiNDC6b9++lbicWkBLTCJvKwsWKhHHxq5RqXttC23WFmJQ62vpPTqltqacbWd+DBwAXAJsk1L6WEqpF7BNXjaCbCVys4mIrhFxZEQcCWwLbFH7Pk9YAX4JvAPcEhEjI+IEYBJwYaX2IEwpTUspndCjR49KXE6SJKlVlTNk/HngdymlbxQWppReBr4REdvmdb6x4akV0xv4XZ2y2vc7AgtTSssi4gDgUrItZt4ALiJLCiVJklRHuY+u+0sDx+8le6xcs0kpLSQbpt5YvXlkQ9uSJEnaiHISwjnAzg0c3xl4smnhtA/OIex4Sp1j2BLzzZzTJlVOS/+brfb5h5WYr217to5y5hCeDnwlT4bWExGHA8cDp1UqsLbMOYSSJKkjqbeHMCKuLFK8ALg1Ip4B5pNt9NyP7GklTwLjqfPYOEmSJLVtDQ0ZT2jg2K7U2esPGAjsBkxsYkySJElqQfUmhCmlcoaTJUmS1E6Z9EmSJFW5Rj/LuJq5yrg6tMTTTUpVbKWkq5Glpqnv31Cp/7b8N1ialv5Z2pZ+drcnZfUQRsQ+EXFdRDwaEf+MiOfqvP7ZXIG2Ja4yliRJHUk5zzL+Ctlj4d4FngFeaK6gJEmS1HLKGTI+DZgFHJRSeq15wpEkSVJLK2fIeEvgtyaDkiRJHUs5CeF8oFdzBSJJkqTWUc6Q8TnAJRFxVUppcXMF1B64yrh5FF1JW+KzhRuzmswVgpIqzRWuaq9KTghTSrdERFdgXkTcCiwE1m5YLf2ocuG1TSmlacC0IUOGfKW1Y5EkSWqqclYZfwo4C+gGHFtPtQR0+IRQkiSpIylnyPhyoDdwKjADWNYsEUmSJKlFlZMQ7g2cn1K6pLmCkSRJUssrZ5Xxm8CrzRWIJEmSWkc5CeFNwJjmCkSSJEmto5wh418BV+crjH8OLGDDVcaklDr8I+3cdqbtqdQWMm5FI6mlNbTlVmO242qvWuLnb+FndNR2bKxyEsKnyFYRDwFGN1CvU5MiagfcdkaSJHUk5SSEZ5ElhJIkSepAytmYelIzxiFJkqRWUs6iEkmSJHVA5TypZN9S6qWU7mt8OJIkSWpp5cwhnE5pcwg7/KISSZKkjqSchPBL9Zz/SWACsJBsaxpJkiS1I+UsKrm6vmMR8TPg8YpEJEmSpBZVTg9hvVJKyyLiN8D3gHoTx47Cjakbp1Ibgrp5tKTWUurPn439vNvYdRo6XqnNqtvrJs3F4m5KeypTyVXGy4CdKni9NiulNC2ldEKPHj1aOxRJkqQmq0hCGBEfAY4FXq7E9SRJktRyytl25sp6Dn0M+DSwBfDdSgQlSZKkllPOHMIJ9ZQvBf4OfDOldH2TI5IkSVKLKmeVsU81kSRJ6oBM8iRJkqqcCaEkSVKVa3DIOCJuK/N6KaV0eBPikSRJUgvb2BzCz5V5vVKedSxJkqQ2pMEh45TSJht7AfsDf8tPWdLsEUuSJKmiGj2HMCIGRMQfgXuAXYAzgJ0rFZgkSZJaRtnPMo6I7YAfAeOBtcDPgbNTSq9XOLY2y2cZl6foczfzsnKen1mJZ1H6PEtJHVF9zyWuxHOPW/PZyU19JnQp166vvdrT850roeQewojoFRHnA8+QPabuRmDXlNI3qykZBJ9lLEmSOpaN9hBGxIeBbwDfB3oCdwHfTynNas7AJEmS1DIa7CGMiC8D/wB+DPwTGJlSOshkUJIkqePYWA/hb8i2knkMuAkYFBGDGqifUkoXVSg2SZIktYBSFpUEMDR/bUwCTAglSZLakY0lhCNaJApJkiS1mgYTwpTSX1sqEEmSJLWORm9MLUmSpI7BhFCSJKnKmRBKkiRVORNCSZKkKmdCKEmSVOVMCCVJkqqcCaEkSVKVMyGUJEmqcqU8uk51RMRoYHTfvn1bO5RmNemy/M+TS6tXSt2Gzm2r2kOMktq+lvpZ0pjPKXZOuT/PmxpDpTU1hmL/B5ZaVu5nNPb8SrKHsBFSStNSSif06NGjtUORJElqMhNCSZKkKmdCKEmSVOVMCCVJkqqcCaEkSVKVMyGUJEmqciaEkiRJVc6EUJIkqcqZEEqSJFU5E0JJkqQqZ0IoSZJU5UwIJUmSqpwJoSRJUpUzIZQkSapyJoSSJElVzoRQkiSpypkQSpIkVTkTQkmSpCpnQihJklTlTAglSZKqXFUmhBExICIej4hnI+K2iOjW2jFJkiS1lqpMCIFfAqenlHYGnga+18rxSJIktZp2kxBGRN+I+FVEzI6ItRExvZ56/SLinohYFREvRcRZEdGp4PiWwI4ppdvzot8CY5v/DiRJktqmzq0dQBn6A4cCDwNdilWIiF7A3cA84HDgk8AFZInv6Xm1PsCLBae9AGzXPCFLkiS1fe0pIZyWUpoKEBE3A5sXqXMS8FFgTErpTeCuiOgOTIqIn+ZlAaSWClqSJKmtazdDximl90uodgjwpzzxqzWFLEncL3//Iuv3CH6C9XsMJUmSqkq7SQhLtCvZIpF1UkovAKvyY6SUXgYWRsSheZWJwC3FLhYRqaFX892GJElSy2lPQ8al6AW8UaR8WX6s1leBqyNiMvAMML75Q2ucSZcVfH1y449v7NzGxNDQ+aVeW5I6uo7483Bj//c05jqVrNtcMXRkHS0hhOLzA9ebN5hSmgPssdELpRQNHR8yZIi9hJIkqd3raEPGy4CeRcp7ULznUJIkqep1tITwafK5grUiYjtgU+rMLZQkSVKmoyWEdwAH1XkU3eeB1cBfK/UhETE6Iq5Yvnx5pS4pSZLUatpNQhgRXSPiyIg4EtgW2KL2fUR0zav9EngHuCUiRkbECcAk4MI6W9E0SUppWkrphB49elTqkpIkSa2mPS0q6Q38rk5Z7fsdgYUppWURcQBwKTCNbN7gRWRJoSRJkopoNwlhSmkh2WrhjdWbB+zf7AFJkiR1EO1myFiSJEnNw4SwEVxUIkmSOhITwkZwUYkkSepITAglSZKqXKTk09caKyJeBZ4v87Q98z9nVjicjsZ2Ko3tVDrbqjS2U2lsp9LZVqVpiXbaPqW0RbEDJoQtLCISbPw5ydXOdiqN7VQ626o0tlNpbKfS2Valae12cshYkiSpypkQSpIkVTkTQkmSpCpnQihJklTlTAglSZKqnAmhJElSlXPbGUmSpCpnD6EkSVKVMyGUJEmqciaEkiRJVc6EsIkiom9E/CoiZkfE2oiYXqRORMRpEbEoIlZHxH0RMahIvX4RcU9ErIqIlyLirIjo1BL30dwi4qiIuC0iFkfEyoiYGRHH1KljO0UcGREPRsTrEfF2RDwTEadHRJeCOlXfTnVFxLb591WKiM0Kyqu+rSJiQt4udV8nFdSp+nYCiIjOEfGDiHg2It6JiBcj4qI6daq+rSJiej3fUykiPp3Xqfp2AoiIcRHxeP7zaXFE/G9EbFOnTttoq5SSrya8gMOBRcDvgPnA9CJ1/hNYDXwdGAncDrwGbFVQpxfwEnA3MAo4CXgLOLu177FC7fQQcD1wNLA/cD6QgP+wndZrpxOBc4AjgBHA9/M2udR2arDdrgdezr+nNrOt1mubCXm7jAD2Lnj1tp02aKtr8ns8EdgP+Hfgx3XqVH1bAf3qfC/tDfwZeBXobDutu7/D8n97lwIH5N9PC4HHgU3a2vdUqzdYe3/V+Uu9mToJIfARYDnw3wVlm+b/cM4uKPtPYBnQvaDse8CqwrL2+gI2L1J2PbDAdtpo250DvAGE7VS0fYYDS4HvUJAQ2lbr7mUCdRLlOsdtp+xeDgbWAP0aqGNbFW+XLvm/wV/YTuu1yxRgZp2y2iSxpq21lUPGTZRSen8jVfYBugM3FZzzFjANOKSg3iHAn1JKbxaUTQE+SvabaruWUnqtSPETQO/8a9upfq+T/cAF22k9+XDJJcBZZL9RF7KtSmM7Zb4M3JtSmtdAHduquIPJerBuyN/bTpkPkSV7hd7I/4z8zzbTViaEzW9XYC3wbJ3y+fmxwnpPF1ZIKb1Alv0X1utI9gFqf/jaTgUiolNEdI2IzwCnkP3mnbCd6jqJ7Dfsy4ocs63W98+IeC+yeaknFpTbTplhwN8j4tKIeDOfp3VLnfletlVx44DFwIz8ve2UuRIYHhFfjIjuEfEp4GzgLwW/eLSZtjIhbH69gJUppbV1ypcBXeODxQK9+OA3h7r1ejVfeK0jIg4gm39Z+x+57bS+t/LXDOCvwHfzctspFxEfB34EfCultKZIFdsqswQ4AzgWGA08AvwyIr6ZH7edMluRDa8PIktwvgTsCfw+Imp7c2yrOiKiK9n31Y35L61gOwGQUvoj2ffUFWQ9hc8AnYAxBdXaTFt1rsRFtFHFHgcTRY7VV69DPU4mInYgmz84NaV0VcEh2+kD+wBdgb2A/yablPy1/JjtlDkHeCSldHsDdaq+rVJKfwL+VFB0R0R8GDg9IibXVityalW1E9l9BHB4Sul1gIhYQvYL2f7APXk922p9o4HN+GC4uFbVt1NEjAB+CUwG7gC2BCaR/ZIxsiAJbBNtZULY/JYB3SKiU53fAHoCqwp6NpblZXX1oPhvBe1SRHyM7B/GC2QrrmrZTgVSSo/nX94fEa8BV0fEBdhOAEREf7I5X/tGRM+8uGv+Z4+IWItt1ZCbyVb874DtVGsZ8FxtMpi7H3iXbFXtPdhWxYwD/pFSeqygzHbKXADcllL6fm1BRMwiG/o9HLiFNtRWDhk3v6fJuoj71imvOx/gaerMA4iI7chWG603b6C9yocW/kC2QOJf84mztWyn+tUmhztiO9XamWzC9kNkPyiX8cH0gxfJFprYVhuXsJ1qza+nPIDaxYO2VYGI6EG22KFu76DtlNkVmFVYkFJ6hmyLmU/mRW2mrUwIm9+DwJvAUbUFBXMu7iiodwdwUER0Kyj7PNk3zl9bIM5mFRGdyfZq3Bk4JKX0Sp0qtlP9/iX/cwG2U637yfbVK3ydlx87FPgZtlVDxpKtyn4e26nWH4CBEbF5Qdm+ZL94zM7f21brOwL4MBsmhLZT5nlgcGFBRNSQrQxemBe1nbZqjb15OtKLbJjqyPz1EPBUwfuu6YP9g1YBJ5NtTvlHsh/GWxZcpxfZ5O+7yDamPAFYScfZoPMKst6IU9hwQ9MP207r7u9Osv30DgEOBM7M729KQZ2qb6d62m4CxTemruq2Av4f2QbnhwCfI9t8ObHhpvDV3k7dyaayPET2n/EXyB46cFedelXfVgX3eScwq55jVd9OwKlkvcsX5Pc3nmxhyQJg07bWVq3eYO39RTYHJ9Xz2iGvE8B/kQ1lrSZbObpHkWv1A+7N6ywhW0HZqbXvsULttNB2KqmdfgTMzf+hv0E2XPwfwIcK6lR9O9XTdhPYMCGs+rYCfpz/J7Qqv7+ZwLF16lR9O+X315fsKRFvkU1DuAroZVsVbavNyTby/kE9x6u+nfI2+CowJ/+eWgzcCOzUFtsq8g+RJElSlXIOoSRJUpUzIZQkSapyJoSSJElVzoRQkiSpypkQSpIkVTkTQkmSpCpnQihJklTlTAglSZKqnAmhJElSlTMhlCRJqnImhJIkSVXOhFCSJKnKmRBKkiRVORNCSZKkKmdCKEmSVOVMCCVJkqqcCaEkSVKVMyGUJEmqciaEkjqkiJgQESkiPtvasXR0EbFD3ta1r9+0dkwbExE/qBPzZ1s7Jqk1mRBKalBEfDb/D/M7rR1LWxYR34iICWWeU5uMPNlAndm19ZocZPP7PXAsUDQhjIjhEXFdRCyIiNURsSoi/hER10fEv0VElPuBEfGveftcvJF6Z+b1vpAXTctjvaLcz5Q6IhNCSR3VNcBHgfta6PO+AUxoxHlvAwMiYmjdAxGxJzAwr9MezEkpXZtSeriwMCI2iYjLyf4u9gVuIWuvU4GbgF3JkskfNOIz7wQWA+Mj4kPFKuSJ5nHAG/lnk1J6KqV0LfBQIz5T6nBMCCV1KBHRDSCltDal9HZK6f3WjmkjZgCvA18qcuzLwGt5nfbsv4GvAtcDfVNK304p/Sql9OuU0mkppcHA/sAL5V44pbQWuBrYHBhdT7X9ge2B61NK7SW5llqUCaGkshXMGZsUEZ+LiL9FxNsRsSQifhYRnQvq3hgR70bE5kWus0vd4b6I+FpE/DkiFufnLYmIayNihyLnp4i4KiIOiIj7I2Il2VBg0TmEEdEtIs6OiEci4rWIeCcfsjw3IrrWuXbtUPmEiPhSRDyV138+Ir5XNw6yhGO/OvPSNoi5iHeB64BjIuIjBdf8MHBMfuzdIve+a0Rcnse1Ih9+nRkRXylS92MRcVFE/DP/e3o9r/vdOvW+GBGPRsQbEfFWRDyXD/FuUcJ9FBURvYHvAwuAL6eU3ilWL6X0l5TSdUXO/3z+d1t7j49ExJF1ql0JJLIEupgvF9STVIQJoaSmOJTsP9k7gG8Cs4HvAIUJ09XAh4BxRc7/YkGdWt8h6xX7OXAy2ZDiEcCDEfHxItcYAtwKPJrHsEFSUWBb4HjgMeBHwLeAx/N4f1/POSeR9XDdAHwbWAKcVzAXDbK5aK8BT+df175ebSCWQr8FepLdZ60jgF7Un8R8lmz49Q/Ad4EzgDXAFRHxn3Xq/g74Otnf038AZ5G112drK0TEv5P9Pbyd3+83yNpyF6B3ifdRzL8CHwGuqS8ZrE9EnA1MAVaQ3d8PgFXA7yLi5Np6KaV/kg1HHxwRW9e5Rg+ytpydUprZhPuQOraUki9fvnzV+yJLGhLwnYKyHfKyt4AdCsoDmAssKSjrRJZEPVrnugE8TzbvrLB80yIxHJB/3vfqlKf8NbLIORPyY58tKOsCfKhI3R/ldfcqct8vAT0LyruSJXoP1bnGQmB6mW2bgD/kX88E/lxw7M/AY/nXf8h+XG+0nTYBpgPLa+8T6JF/zuUbieUW4E2gcyO+R2q/HyYVOXZBfuyIIsd6kA311r4K23lwft6Pi5x3ax5rt4KyY+v5HjkxLz+lntg3+D7x5asaX/YQSmqKW1NKC2vfpJQS8Bdgq4jYLC9bS9bTNDQidi0497PAJ1i/d5CU0luwbiFCj3yoeTZZkjOsSAyzU0p3lxJsSundlNKa/PqdI6JXfv3a84td/39SSm8UXGMV8DCwcymfWYYrgQMiYruI2I4sCa53iLO2nQAi4iN57+nHyBLJ7mQLNQBWA+8AwzYyhL2cLNn918as9m1A9/zPN4scu4csua593V9wbDxZonZ1RGxe+AJuA7oBny6of3N+D3XnYn6J7P4b6jmWqp4JoaSmeK5I2ev5n4XDu7VJ3xcLyr4I1CaL60TE/hExnaz38Q0+SBZ6kA2h1vX3cgLO5yjOIUsSlubXnp4fLnb9+u6x2PB1U1xPNuR7HFmv1btkw9RFRcRmEXF+RLxAlvS9RnYv5+RVekGWBJMN/w4AFuRzDi+JiAPqXPLHZD22twKvRsT/i4jjaxfpNEFtIti9yLGvAaPy1//VOVZD1ov8NOsnja+SDbEDbFlbOaW0mqy9do2ITwNERD+yJH9qSul1JNWr88arSFK91jZwbF0vU0rpyYiYBfx7RPwX2XYwY8mGSF9ed0K29cqfgX+QzRdbQJbsJLK5ZMV+iV1VarAR8S2yIcw/k81RfIks8doWuKqe6zd0jxWTUloWEbeSJYNB1vu6rIFTrgc+R7aP3n1kye17ZPM6v0nBvaSUfhkRU8nm8+0HHAl8PSJuTCmNy+s8mydQB+Sv/YBfA2dGxL4pm6fXGHPzPwdRZ55mSunR2q8jou7q3yD7ez+E+v8Onqrz/kqyOZ9fIttOpra38LdIapAJoaSWcjVwETAC2JpsyO/qOnW+QDbn8JCU0oLawojYlOK9d+U6lmyu3yGpYDuaiDi4AteuxMbRVwKfz78+qb5KEdGTLBm8JqV0Up1jI4sGl9ISsg2jfxMRncj2aTwmIi5IKf0tr/MOcHv+IiIOBf5Itvjm5GLXLcEfyRaqHBsRP06lLyx5FjgYeCGlNL+UE1JKf8t7fz8f2Ubq/w4s4oMpAZLq4ZCxpJZyPVkP1hfz13Jgap06tT1BdeewnUZlfl6tJUvc1l0/si1yGrMhcl0ryebwNcXdZKtpzyCbX1efou2Ur7A9vk5Z17pb6uTzOufkbz+W19tgWyCyFdjr6jRGSukV4KfAjsCV+XY6xdT9O78m//PHeQK7fuVsO5tiriQbnv4NsBXZHNC2vhel1OrsIZTUIlJKr0TEHWTDlR8Bfps23CT492TDnbdHxBVkw7mjyJ7W8VoFwrgZ+AlwR0TcQpY4fIFs7l5TPQxMjIgfAfOB94FphYs/NiZPXM4uod6KiPgz2RD8auBvZPsgnkg2zF44v/FTwF8j4vdkw7fLyObnfTWvW7vp9Z8jYjnZ8PMism1wJpAl0NfQNGeSbV1zErBvRNwEPJMf6wMcRrbA6A8F9/i3iPhhfu6siPgd2RD/1sCeZEPjXYp81rVkCehReez/08TYpapgQiipJV3NB0+T+N+6B1NKD0TEWLIesh+RzR+8m2w+WyUeQfczsp6oicBk4GXgRrKkYV4Tr/1fZD1pJ5MlU0HWK1ZyQlimfwfOJWvP48iGWP+LLLktTIIWkfWajQD+Dfgw2aPefg2cl6+aBvgFcDRZUvkxsoUzTwD/kVL6S1MCzRPdr0bEFOAEsvmjW/HBtj6PAj8kWz1ceN5ZETETOIVsYcymwCtkie2p9XzW6/lczKOBvxSugpdUv8h2iZAkqXHy7WwWkCXcPwXeTimtbNWgNiIiPkqWYI4DLgFGpJSmt2pQUityDqEkqVK+S7YtzMWtHEcpTiWL9ZLWDkRqC+whlCQ1Sf4M5s8UFC0udWVwa4mI7Vl/c/GZG9nmR+rQTAglSZKqnEPGkiRJVc6EUJIkqcqZEEqSJFU5E0JJkqQqZ0IoSZJU5UwIJUmSqtz/B0oxOsKR2t8VAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plot full distributions (semi-filtered data)\n",
    "#Plotted on LOG SCALE PLOTS\n",
    "#INVARIANT MASS\n",
    "\n",
    "dataframes = [df_graviton,df_higgs]\n",
    "titles = [\"Graviton LOG\",\"Higgs LOG\"]\n",
    "adj_titles = [\"Zoomed-In Graviton\",\"Zoomed-In Higgs\"]\n",
    "minlims = [100,75]\n",
    "maxlims = [800,150]\n",
    "binning=[200,200]\n",
    "\n",
    "i=0\n",
    "for df in dataframes:\n",
    "        xtitle  = \"Invariant Mass [GeV]\"\n",
    "        param = 'InvMass'\n",
    "        fig,ax = make_fig(xTitle=xtitle,yTitle=ytitle)\n",
    "        xlow = (df[param].min()-1)\n",
    "        xhigh= (df[param].max()+1)\n",
    "        nbins = 200\n",
    "        bins  = np.linspace(xlow, xhigh, nbins)\n",
    "        n, bins, patches = ax.hist(df[param], bins, alpha=0.5)\n",
    "        textstr = '\\n'.join((\n",
    "        r'$xhigh=%.2f$'+\"{:.2e}\".format(xhigh),\n",
    "        r'$xlow=%.2f$'+\"{:.2e}\".format(xlow),\n",
    "        r'$nbins=%.2f$'+\"{:.2e}\".format(nbins)))\n",
    "        ax.text(0.80, 0.95, textstr, transform=ax.transAxes, fontsize=10,\n",
    "            verticalalignment='top')\n",
    "        ax.set_title(titles[i])\n",
    "        plt.yscale('log')\n",
    "        \n",
    "        fig,ax = make_fig(xTitle=xtitle,yTitle=ytitle)\n",
    "        xlow = minlims[i]\n",
    "        xhigh= maxlims[i]\n",
    "        nbins = binning[i]\n",
    "        bins  = np.linspace(xlow, xhigh, nbins)\n",
    "        n, bins, patches = ax.hist(df[param], bins, alpha=0.5)\n",
    "        textstr = '\\n'.join((\n",
    "        r'$xhigh=%.2f$'+\"{:.2e}\".format(xhigh),\n",
    "        r'$xlow=%.2f$'+\"{:.2e}\".format(xlow),\n",
    "        r'$nbins=%.2f$'+\"{:.2e}\".format(nbins)))\n",
    "        ax.text(0.80, 0.95, textstr, transform=ax.transAxes, fontsize=10,\n",
    "            verticalalignment='top')\n",
    "        ax.set_title(adj_titles[i])\n",
    "\n",
    "        i+=1\n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Comments on InvMass Plots:\n",
    "\n",
    "From the invariant mass plots, we see that we'd expect the invariant mass of the graviton to be around 500 GeV, whereas all other invariant mass peaks are at much lower values."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Lepton pTs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[51.90546  41.430645 33.646713 ... 63.284214 52.538807 58.730095]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "stuff = [higgsstoof,gravitonstoof]\n",
    "labels = ['Higgs','Graviton']\n",
    "titles = [\"Lepton 1\",\"Lepton 2\",\"Lepton 3\",\"Lepton 4\"]\n",
    "print(higgsstoof[:,0])\n",
    "for i in range(4):\n",
    "    xtitle  = \"pT [1]\"\n",
    "    fig, ax = make_fig(xTitle=xtitle,yTitle=ytitle)\n",
    "    j=0\n",
    "    for thing in stuff:\n",
    "        \n",
    "        xlow = (thing[:,i].min()-1)\n",
    "        xhigh= (thing[:,i].max()+1)\n",
    "        nbins = 200\n",
    "        bins  = np.linspace(xlow, xhigh, nbins)\n",
    "        if j==4:\n",
    "            n, bins, patches = ax.hist(thing[:,i], bins, alpha=0.7,color='k',label=labels[j])\n",
    "        else:\n",
    "            n, bins, patches = ax.hist(thing[:,i], bins, alpha=0.3,label=labels[j])\n",
    "        textstr = '\\n'.join((\n",
    "        r'$xhigh=%.2f$'+\"{:.2e}\".format(xhigh),\n",
    "        r'$xlow=%.2f$'+\"{:.2e}\".format(xlow),\n",
    "        r'$nbins=%.2f$'+\"{:.2e}\".format(nbins)))\n",
    "        if j==2:\n",
    "            ax.text(0.01, 0.95, textstr, transform=ax.transAxes, fontsize=10,\n",
    "                verticalalignment='top')\n",
    "        ax.set_title(titles[i])\n",
    "        plt.yscale('log')\n",
    "        j+=1\n",
    "    plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Comments on Lepton pT plots:\n",
    "From these plots we see that we can make the following cuts:\n",
    "\n",
    "\\begin{itemize}\n",
    "  \\item The pT of the first lepton should be between (39,1000) GeV\n",
    "  \\item The pT of the second lepton should be between (18,400) GeV\n",
    "  \\item The pT of the third lepton should be between (0,250) GeV\n",
    "  \\item The pT of the fourth lepton should be between (0,150) GeV\n",
    "\\end{itemize}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}