Proteomics Calculations Final.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import math\n",
    "import six\n",
    "%matplotlib inline\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note: You have to have the file and the correct path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Read the tsv file\n",
    "df=pd.read_csv(\"az20.txt\",delimiter = '\\t', index_col=False) # You have to have the file and the correct path\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\", 'This pattern has match groups') \n",
    "df=df.loc[df['Substrate'].str.contains('(None)|(M\\d+)')==False] # removing any with m residues or no residues (None)\n",
    "#print df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Separating columns into individual dataframes to use for later calculation and volcano plot\n",
    "df1=pd.DataFrame(data=df['Substrate'])\n",
    "df4=pd.DataFrame(data=df['AZ20_fold_change'])\n",
    "df5=pd.DataFrame(data=df['AZ20_p-value'])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Volcano Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Extracting significant values and removing zero values from fold change\n",
    "df4 = df4.replace([np.inf, -np.inf], np.nan)\n",
    "df4a = df4.dropna(axis=0, how='any')\n",
    "df4b = df4a[(df4a['AZ20_fold_change'] > 0.0000000)]#removing zero values from fold change\n",
    "sig = df5[(df5['AZ20_p-value'] < 0.05)] #Extracting significant values \n",
    "fcut = np.log2(df4b)\n",
    "\n",
    "\n",
    "#Creating the Volcano Plot\n",
    "df['log2'] = (np.log2(df4b))\n",
    "df.loc[(df['log2'] >= 0) & (df5['AZ20_p-value'] < 0.05), 'color'] = \"green\"  # upregulated substrates\n",
    "df.loc[(df['log2'] <= 0) & (df5['AZ20_p-value'] < 0.05), 'color'] = \"red\"  # downregulated substrates\n",
    "df['color'].fillna('grey', inplace=True) # substrates which aren't up and down regulated coloured grey\n",
    "df['logpv'] = -(np.log10(df5['AZ20_p-value'])) # -log10 p value\n",
    "plt.scatter(df['log2'], df['logpv'], c=df['color']) #Plotting the log2 (fold change) against log 10 (p value)\n",
    "plt.xlabel('log2 Fold Change', fontsize=15, fontname=\"sans-serif\", fontweight=\"bold\") # labelled x axis\n",
    "plt.ylabel('-log10(P-value)', fontsize=15, fontname=\"sans-serif\", fontweight=\"bold\") # labelled y axis\n",
    "plt.xlim(-5,5)  # set the x axis limit (-5,5)\n",
    "plt.xticks(fontsize=10, fontname=\"sans-serif\")\n",
    "plt.yticks(fontsize=10, fontname=\"sans-serif\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Top 10 Up regulated and Top 10 Downregulated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xa108710>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x495 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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vTxSblJREenp6NGrUKKV+ClsoiYhGjx5NnTp1EpVVq1aNpk+f/vEd/h93d3elZCs7O5ukUint379fVF6zZs0i+x4yZAhVrFhRqTwhIYFsbGzozp07ZG9vr5RsERE1adLkk+bNWEm6efMmAaB79+6Jym1tbcnHx6fQdiNHjqRmzZrR1KlTqWzZsuTs7ExjxoyhzMxMIaZ169bUt29fGjZsGFlZWZGrqyv5+fnRu3fvVPb5ucnWH3/8QQDo2bNnonI3Nzdh3fqzpKQk8vLyoh49eghl8fHxpK2tTWvWrKH3799TRkYG+fj4UO3atT9pv//My8tLaW3duHEjaWhokJ2dHZUtW5batm1LN27cEMX4+fmRrq4u2djYkIODA/Xo0YMePHhQ6DhfyWflPPw1IvvXqFy5Mlq1aoU9e/b8pXYRERGIiorCxIkToaEhfgvZ2Nigd+/e2L59e/6nmWIKCwtDrVq1RGVyuRynT5/G06dPP2m+H3r//j3y8vKUTs3r6uri3LlzKttkZmZix44doq8XCvrq1asXZsyYAVdX10LH/Oabb3DmzJnPnjNjX1OlSpVgb2+PadOmIS0tDe/evcPChQvx+PFjJCcnF9ouLi4O586dQ2RkJPbs2YPVq1cjJCQEAwYMEMUEBwcjNzcXR44cwdy5c7FmzRpMnTr1i+5DSkoKpFIpzM3NReVWVlZISUkRlfXq1Qt6enooW7YsDA0NsXHjRqHOwcEBJ06cgJ+fH7S1tWFsbIxbt27h8OHDn7TfH4qJicGZM2eU1hMXFxds2LABBw4cwPbt26Gjo4P69euLrpXz9PTEpk2bcPToUQQEBCAlJQX16tXDixcvPvdQlRhOtti/ipubG+Li4v5Su4KLRQtLONzc3PDy5UukpqYWu/+HDx/C2tpaVLZs2TKkpaXB2toa7u7uGDJkCPbu3ftJSZyhoSHq1q2LefPmISkpCXl5ediyZQsuXrxY6B+S7du3IycnBz4+PqJyPz8/mJmZYeTIkUWOaWNjg4SEhGLPkbGvaevWrTAwMBC2S5cuYc+ePXjw4AHMzMygp6eH0NBQtG7dWrh+UhWFQgGJRIJt27bB09MTLVu2xOrVq7Fnzx7hA5JCoYClpSUCAgLg4eGBLl26YM6cOfj1118/6X38uYgIEolEVLZ8+XLcuHED+/fvR1xcHMaPHy/UpaSkYPDgwejfvz+uXr2K06dPC9daKRSKYu/3hwICAmBtbY22bduKyuvWrQsfHx9Ur14dDRs2xM6dO+Hk5IRVq1YJMa1bt0b37t1RtWpVeHt74/Dhw1AoFNi8efOXPExfhWZJT4Cxr0nV4vO57Qrrp2AR/ZRx3rx5o3T2yc3NDbdv38b169dx7tw5nD17Ft27d0eLFi1w+PBhpbNqhQkKCsKgQYNga2sLqVSKmjVrolevXrhx44bK+ICAAHz77bewsLAQys6cOYNNmzYhIiLio+Pp6urizZs3xZobY19bhw4d4OnpKbwuW7YsdHV1ERERgVevXuHdu3ewsLCAp6en0tnmD1lbW6Ns2bIwNjYWygo+gCUmJsLKygrW1taQyWSipM3V1RXZ2dl4/vy56D32V8jlcuTl5Sn1+ezZMzRq1EgpVi6Xo1KlSjAzM0PDhg0xY8YMlCtXDr/88gv09fWxaNEiIX7Lli0oV64cLly4gAYNGhRrvwu8e/cOmzdvxtChQ6GpWXS6IZVKUatWrSLvAjUwMIC7u3ux7hQtbfjMFvtXuXPnDsqXL/+X2lWsWBFA/p2Aqty9excmJiZKp/SLYm5urnQXI5B/B1Ht2rUxYcIE7Nu3Tzilfvbs2WL37eTkhDNnziArKwuPHj3ClStXkJubK7ojqkBERASuXbumdMo/NDQUycnJsLa2hqamJjQ1NfHw4UNMnjwZtra2oti0tLQv9keEsS/N0NAQzs7OwvbhHYDGxsawsLBAbGwsrl27ho4dOxbaT/369fHkyRNkZWUJZQVnve3t7YWY+/fvC2eFCmL09PQ+aX34GA8PD8hkMpw4cUIoe/z4Me7evYt69eoV2q5gXjk5OQCA7OxspbN5Ba8LYouz3wX27duH58+fY/DgwR/dByLCzZs3lc7wf+jt27e4d+9ekTGlFSdb7F/j9u3bCAkJQdeuXf9Su+rVq8PV1RXLli0TLaIA8OTJE2zduhW9evX6pDNbNWrUwJ07dz4a5+bmBgCiha649PX1YW1tjZcvX+LYsWMq/5CsW7cODg4O8Pb2FpWPGjUKN2/eREREhLDZ2NhgwoQJ+OOPP0Sxt2/fRs2aNT95foyVlODgYISGhiIuLg4HDhxA8+bN8e2336JFixZCTP/+/dG/f3/hde/evWFmZoaBAwciKioK58+fx7hx49C1a1dYWloCAEaOHIm0tDSMGzcO0dHROHbsGPz8/DBq1ChhfcjKyhLeUwqFAomJiYiIiEBiYqIwVlpaGiIiInD79m0AwP379xERESFcj2VsbIzBgwdj0qRJOHnyJMLDw9GvXz/h6zcAOHz4MDZv3ozbt28jISEBR44cwYgRI1CnTh04OzsDANq2bYsbN25g9uzZiI2NxY0bNzBw4ECUK1cOHh4exd7vAgEBAWjWrJnKD7izZ8/GsWPHEBcXh4iICAwePBg3b97EiBEjhBhfX1+cOXMG8fHxuHz5Mrp27YrXr18rXeLwt/C5V9Z/gY0xtfjwEQ5JSUkUERHxyY9+KKodEdHFixdJX1+f2rVrRxcuXKDExEQ6fPiw8OiHtLQ0IfbFixcUHh5OoaGhBIACAgIoPDyckpOThZiVK1dStWrVRPvRpUsXWrZsGV26dIkSEhIoNDSU6tSpQ5aWlvTixQsiIsrJyaHw8HAKDw8nJycnGj58OIWHh1NsbKzQT0hICP3+++8UFxdHx48fp2rVqtE333yjdEfU69evycjIiObNm1es41zY3Yj29vYUGBhYrD4YKw1WrFhBtra2JJPJyM7OjmbMmKH0uAYvLy/y8vISld27d4+aN28u3DE3atQoysjIEMVcvHiR6tatSzo6OuTg4EAzZ84U9V2wLvx5+/BOyI0bN6qM+fDu4zdv3tB3331HpqampKurS+3atRM9auHEiRNUp04dMjY2Jh0dHapQoQL98MMPorWKiGj79u1Uo0YN0tfXJ3Nzc2rXrh1FRUV98n4/ePCAJBIJ7dy5U+UxHz9+PNnZ2ZGWlhZZWFhQixYt6MKFC6KYHj16kLW1NclkMrKxsaHOnTsrzaUE8KMfGCPKT5oKFiOpVEpmZmbk5eVFK1euFC1yqpKt4rQrEBUVRT169CALCwuSyWRkb29PEyZMUFq8irNQpqWlka6uruj5VOvWraNmzZqRpaUlaWlpka2tLfXo0UMUEx8fr7LvD/8o7Ny5k8qXL09aWlokl8tp9OjRlJ6errQ/GzZsIKlUSklJScU6zqqSrQsXLlCZMmUoOzu7WH0wxtjfzGflPBL6CndEFKLEBmasNJoyZQpSU1Px22+/lfRUPlu3bt1Qo0YNTJs2raSnwhhj6vDpd1iBr9lirNSYNm0aypcv/7f+bcRq1aphwoQJJT0VxhgrVfjMFmOMMcZY8fCZLcYYY4yx0oaTLcYYY4wxNeJkizHGGGNMjTjZYowxxhhTI062GGOMMcbUiJMtxhhjjDE14mSLMcYYY0yNONlijDHGGFMjTrYYY4wxxtSoxJItIlKU1NiMsX+uEvxVDMbYP9hfyVtK9Od6MjIyS2psxtg/lJGRIXhtYYx9aUZGhgD/XA9jjDHGWOnDyRZjjDHGmBpxssUYY4wxpkacbDHGGGOMqREnW4wxxhhjasTJFmOMMcaYGnGyxRhjjDGmRpxsMcYYY4ypESdbjDHGGGNqxMkWY38zW7duRbt27Up6GiqFhBxFgwb1oVDwr3Gxv4+srCxMmuQLV9dKsLKyhIdHTfzyy+qPtgsIWIfatWsJbbZv31Zo7O7dwTA2NkL37t0KjVmyZAmMjY3g6ztRVG5sbKRymzjxeyFm5MgRSvXNmjUV9ZOTk4NJk3zh6OgAa2s5evbsgaSkJKH+1q1bGDRoINzcXIV9WrFihej9HBYWhl69eqJixQqQy61Qr15dBAUFKe3Lu3fvMH/+PFSpUgUWFuZwd3fDmjW/CvW5ublYuPAnVKtWFZaWFqhfvx5Onjyh1E9KSgpGjBiO8uUdYWlpgW++qY1z584VegxLK0622L/Ss2fPMHnyD6hWrSosLMxRqZILunTpjOPHjwEAqlSpLCxYlpYWcHNzRZ8+vXH06FFRPw8fPsTo0aNRtWpVWFlZomrVqvD398ebN29UjtuzZw+YmJTBqVOnlOoWLPhRGNPEpAzc3Fzx3Xff4fnz50LMu3fvMG/eXEyZMkVpnqq2tm3bIC0tDZMm+aJWLQ9YWVnCzc0VEyZMQFraC6FfhUKBnj17wN3dDZaWFqhYsQKGDh2CJ0+eKM1z584daNCgPiwtLeDo6IDhw4cJda1atYaGhhS7du0s9r8FYyVt2rRpOHbsONauXYcrV67C19cX/v7+2LFje6Ft1q9fDz8/P0yePBmXLl3G1KnT4Ovrq7RGAEB8fDxmzpyJevXqFdrf1atXsHnzZlSuXFmpLiYmVrTt3Jn//urUqbMornHjJqK44ODdovopU6bg4MGD+O23DTh6NASZmZno0aM78vLyAAAREREwNzfH2rXrhH1atGghli1bJvRx+fJluLm5ITAwCBcvXsKgQYMxbtxYBAfvEo01aNAgnDx5EitWrMC1a9exefNmuLv/f9/mzp2LDRs2YNGiRbh8+QoGDhyEPn36IDIyUohJT09HixYtQEQIDg7GlStXsWjRYlhYWBR6HEsrzZKeAGNf28OHD9GyZQsYGBjAz88fVapUgUKhwJkzpzFhwgRERd0BAEyePBmDBw/Bu3fvkJSUhAMH9qNPn94YPHgwFi9eAgCIjY2BQpGHZcuWwcnJCTEx0Rg3bhzS0tKwcuVK0bgpKSk4c+YMRo0ajcDAQDRt2lRpbhUqVMCRI78jLy8PN29G4rvvvkNy8hPs2bMXAHDgwH5oa2ujQYMGAIDQ0NPCQnnr1i106dIZp06FwtbWFgAgk8mQkpKCJ0+SMWfOXLi4uCA5ORkTJ36PQYMGYf/+A8LYjRo1wsSJE2FlJUdycjJmzJiOPn16IzT0tBCzZs2vWLZsGebOnYtatWrj7du3uH//vmgf+vbtgzVr1qBnz15/5Z+Jsa/mypXL6NmzBxo1agQAsLe3R1BQEK5du1bof8c7d+6Aj48PunbNP1Pl6OiI8PAb+Pnn5WjdurUQl5ubi8GDB2HmzJkICwvDixcvlPp69eoVhgwZgtWrV2PRooVK9VZWVqLXR478DmdnZ2EdKKCtraUU++EYQUGB+M9//iOsPWvXrkPlyu4IDQ2Ft7c3+vXrJ2rj6OiIyMhIHDx4EL6+vgAg/G+BIUOGICwsDAcOHES3bt0BAH/88QfOnDmNiIhImJmZAcg/pn8+fuPHj0fLlq2Efk6fPo3Vq1chIGA9AGDFihWQy62wdu06oZ2Dg4PK/Svt+MwW+9eZOPF7EBFOnz6Dzp07o0KFCnBxccGwYcNx7tx5Ic7AwBBWVlYoV64c6tSpgwULfsLSpcuwbt06nD17FgDg7d0cv/66Bt7e3nB0dETLlq0wcaIvDh48oDTu1q1b0ayZN0aMGIGjR38XnVkqoKmpCSsrK9jY2KBVq9YYPnwETp06JZwpCw4ORps2bYR4c3NzWFlZwcrKCqampirL3NzcsHXrVrRp0wZOTk5o0KAB5s6di9OnTyMjIwMAoKGhgVGjRqN27W9gZ2cHT09PTJjwPW7cuIG3b98CyP+UOXv2bKxZsxY9evSEk5MT3N3d0bFjR9E+tG7dBuHh4Xjw4MFf+Wdi7KupU6cujh4NwePHjwHkn725desWvL29C22Tk/MO2to6ojIdHR1cv34dubm5QtmcOXNgZ2eP3r37FNrXuHHj0LHjt/Dy8vroXDMzM7F37x74+AxQqrt06RKcnMqjZs0aGDNmDFJTU4W6iIgI5ObmomnTZkKZra0tXFxccOXK5SLHK1OmzEfmlCGKOXLkMGrUqInVq1fD1bUSatSojh9+mISsrCwhJicnR+n46eo+s4SUAAAgAElEQVTq4NKlS6J+atWqhQEDBsDJqTwaNKiPdevWgoiKnE9pxMkW+1dJS0vDyZMnMXToMBgYGCjVm5iYFNm+f//+KFOmjMpkqoCqxYmIsGVLEHr06IFy5cqhVq1a2LFjx0fnq6urC4VCgffv3wPIX0xr1Kjx0XYfk5GRCW1tbejp6amsT0tLw65du1CrVi3o6OQviKdOnUJeXh5SU5/hm29qo1IlF/Tp0xvx8fGituXKlYOlpSXOnz+vqmvGSp1FixahatUqcHd3g5mZKdq0aQ1//9lo1ap1oW2aNWuGLVuCcP36dRARbty4gcDAQOTm5gpnr/744w/s27cXy5cvL7SfTZs2IS4uDjNmzCjWXHfv3o2cnBz07t37T/Pxxpo1a3Hw4CHMn/8jbty4jvbt2yEnJwcA8OzZU0ilUuFMUwELC0s8ffpM5VgRERHYtm0rBg8eXOh8QkKO4syZMxg4cIBQlpCQgEuXLuL27VsICgrC4sVLcPLkSYwcOfKD+TbDr7/+B7GxsVAoFDh16hQOHTqElJQUUT/r16+Hg4MD9u7dhxEjRsLf3x8BAevwd8PJFvtXiY+PAxHBxcXls9pLpVI4OzsjISFBZf2jR4+watVKDBkyVFQeFhaGly9fomXLlgCAnj17qbyo9EMxMTH47bf18PDwgKGhIdLT0/Hq1StYWck/a+4F0tPTMX/+PPj4+EBTU3wlwaxZs2BtLYejowMeP36EXbuChbqEhAQoFAosXrwYP/74I7Zu3Yrc3Fy0b98O2dnZon7kcmskJj78S/NkTB127doJGxtrYbtw4QLWrl2LS5cuYceOnThz5iwWLFiAmTNnqLxgu8APP/yAli1bokWL5jAzM0Xv3r3Qq1d+AiSVSvHixQuMGjUSv/66ptAPcbGxsZgzZzbWr18PLS2tYs1/8+ZNaNu2HczNzUXlXbt2RZs2beDu7o7WrVtj9+49iI2NxbFjxz7SI0EikaicW/fu3TBy5Cils9cFLl26hCFDhmDhwkXw8KgllCsUCkgkEqxf/xtq1aoNb29vLF68BAcPHsCzZ/mJ3cKFi1ChQgV8801tmJubYdIkX/Tp0wdSqVTUT7Vq1eDv749q1aqhb9++GD58BAICAop1rEoTTrbYv8qXOP1MpHpxevbsGTp37oQmTZpg9OjRorqgoEB06tRZWFA7duyI+Ph4XLt2VRQXHR0NGxtrWFlZ4ptvaqNsWVvh+oWCr/N0dLQ/e+6vX79Gz549YGNjgzlz5irVjxs3DmFhYdi3bz+kUimGDh0iHDOFQvG/O4gWwdu7OTw8aiEgYD1SU1OVLgrW1dXBmzdvP3uejKlL69ZtEBZ2Tthq1KiB2bP9MWfOXLRu3RqVK1fGsGHD0blzF6xcuarQfnR1dfHLL/9BSspT3Lp1G1FRd2BnZwdDQ0OYmZnhzp07SElJQceOHWBqagJTUxNs374dx48fh6mpCWJjY3HlyhW8ePECdep4CjHnzp3D+vXrYWpqIpyVKnDz5k2Eh4fDx8fno/tpbW0NG5uywtf5lpZWyMvLU7pmLDU1FZaW4gvOY2Ji0LZtG3Tp0gWzZ89W2f/FixfRtWsXTJs2DUOGDBHVyeVyWFtbw9jYWCgr+ID76NEjAPmXO2zbth3JySm4fTsK165dh76+gejaLrlcDheXSqK+XVwqCl/3/p3wBfLsX6V8eSdIJBJER0ejffv2n9w+Ly8P9+8/gIeHh6j86dOnaN++HVxd3bBuXYAoGUtPT8fBgwfx7t07bN68SdTX5s2BqFWrtlDm6OiI4ODdkEqlsLa2hrb2/xMrU1NTSCQSpKenf/K8gfzb27t16woA2Llzl/D14IfMzMxgZmYGZ+f869jc3Fxx8eJF1KtXD3J5/hm1SpX+v/gZGxtDLpcrLX4vX75U+uTNWGlgaGgIQ0ND4XVGRgZyc3MhlYrPPUil0mI9wkQmk6Fs2bIAgL1796Bly5bQ0NBAzZo1cfHiJVHsvHlzkZ6ejiVLlsLe3h4WFhZKMaNGjYSTkxMmTvRVOtu1adNG2NnZo0mTJh+d14sXL5Cc/ARyef4F89WrV4dMJkNo6CnhQvakpCRER0fjm288hXb37t1D+/bt0KlTJyxY8JPKvs+fP4/u3bthypSpGDVqtFK9p2cd7N+/H1lZWcLlGgU30tjZ2YlidXR0YGNjg9zcXBw8eEB0h6Wnpyfu348Vxd+/fx/lypX76P6XNpxssX8VU1NTNGvWDAEB6zBixAil67bS09OLvBh08+bNePUqHR07fiuUpaSkoF27tqhUyRUbNmxQ+mouOHgXzM3NlW7DvnLlCmbMmI6ffvoJ+vr6AAAtLS04OTmpHFtLSwuVKlXCvXvRaNGi5Sftd2ZmJrp27QIiwp49e1Ver/ZnBX9oCj5d16mTvyDHxsYKf1yysrLw9OlT0eL39u1bxMfHo1q1ap80R8ZKgpGRERo0aAB/f3/o6xugXLlyOH/+PHbs2I45c+YIcQWPOCm4M+7+/Vhcu3YNtWvXRnp6OlavXo07d+7g11/XAAD09fXh5uYmGsvY2Bjv378XyrW0tJTWG319fZiYmCi1zc7ORnBwMMaOHad0Zj0rKwsLFixAx44dYGUlR2JiImbP9oeFhQXatWsvjN2vX3/MnDkT5uYWMDU1xfTp01C5cmUhebt79y7at2+Hhg0bYuJEXzx9+lQYo+Aux7CwMHTv3g2DBw9B9+7dhRipVCp8wOrWrRsWL16EUaNGYerUqXj16hWmTJmMjh2/FR7bcO3aVTx5kowqVaogOTkZCxYsgEJBGDdunDDmqFGj0aJFcyxevBidO3fGzZs3sXbtWsyaNasY/7KlCydb7F9n6dJlaNGiORo39sL06TNQuXJlEBHOnj2L5cuXCY9+yMrKxNOnT5Gbm4ukpCTs378Pa9euxbBhw4RbrpOTk9G2bRtYW1vjp59+Ep2iNzc3h1QqRWBgEDp27Ki0eDo7O2PWrJnYu3ev0i3XhWnWrBkuXbqIsWPHFnt/MzMz0anTt8jMzMS2bduQnZ0tXGNlYmICLS0tXLlyGZGRkahTpy6MjY0RHx+P+fPnwc7OHnXr1v3ffCugbdu2mDJlMn7+eQXKlCmDH3/8ERYWFmjVqpUw3tWrV6GtrY06deoUe46MlaQNGzZi9mx/DB06BC9fvkS5cuUwffoMDBs2XIj589nbvDwFVq/+Bffvx0Imk6Fhw4Y4ceKk0iMOvpS9e/fi9evX6Nu3r1KdVCrFnTtR2LFjO169egW5XI6GDRti06bNorN4CxYsgKamFAMHDsDbt2/h5eWFNWvWCtdJ7d+/D6mpqdi7dy/27t0rGuPVq/w7l7dt24rs7GysWrUSq1b9//E2dnZ2uHXrNgDAwMAABw4cxKRJvmjSpDHKlCmDtm3bwt///19Jvn2bg3nz5iIhIQH6+vpo0aIF1q1bJ0o+PTw8sG3bNsyZMweLFy+Cra0tpk+frnRN7N+BpARvoaSMjMySGpv9y6WkpGDp0iU4duw4kpOfwNTUFJUrV8aIESPQvHkLVKlSGYmJiQDyP32am5ujRo0a6Nu3n+jRC1u3bsWoUSNVjnHz5i28fPkSXl6NcPz4CXh6eirFDB8+DHFxcThx4iQWLPgRBw4cwKVLhd+GHRMTgwYN6uPevWjhUQ8Fbty4gSZNGuPmzVuiBT8sLAzt2rVV2d/hw0fQsGFD3Lx5E9OmTcXt27fx+vVryOXW8Pb2hq+vr3AWC8hP3KZOnYpDhw6CCKhbN/+RGOXLlxdixo3L/+T9888/F7of6mRkZAheWxhjX5qRkSEAKF+wWwycbDH2NzNw4AC4urrihx8ml/RUlDx//hy1anng9OkzJfbwQU62GGPq8FeSLb4bkbG/mTlz5oq+GihNHj5MwNKly/62T3lmjDF14DNbjLF/FD6zxRhTBz6zxRhjjDFWSnGyxRhjjDGmRpxsMcYYY4ypESdbjDHGGGNqxMkWY4wxxpgacbLFGGOMMaZGnGwxxhhjjKkRJ1uMMcYYY2rEyRZjjDHGmBqV2BPkiShPIpFwsscY+6KICBLJZz3kmTHGCkVEColEIv2ctiX6cz0lNTBjjDHG2Gfgn+thjDHGGCttONlijDHGGFMjTrYYY4wxxtSIky3GGGOMMTXiZIsxxhhjTI042WKMMcYYUyNOthhjjDHG1IiTLcYYY4wxNeJkizHGGGNMjTjZYuxvpkmTJggMDCzpaai0evVqdOjQoaSnwdgnycrKwpgxY2BrawtdXV24uLhg+fLlH2337t07zJo1C46OjtDW1oadnR1Wrlwp1EdFRaFr164oX748JBIJ/P39lfpYsGABateuDSMjI1hYWKB9+/a4ffu2KIaI4O/vDxsbG+jq6qJx48aIiooS6hUKBTp06AA7Ozvo6OjA2toaffv2RVJSkhATGRmJXr16oVy5csI+Ll68GAqFQuW+xcbGwtDQEAYGBkp127ZtQ/Xq1aGnpwe5XI6+ffsiJSVFqA8ODkatWrVQpkwZ6Ovro3r16ti8ebOoD39/f0gkEtEml8tFMQMGDFCKqVOnjsr5lnacbLF/nQ/fwJqamrCzs8PIkSPx8uVLpdhly5ZBKpVi+vTpSnWnT58WLQIWFhZo3bo1IiMjhZjGjRvju+++U2q7e/du0e/3vX37FgMGDEDVqlUhk8nQuHFjlXM/cuQIHj16hD59+ghlkZGR6NixI+RyOXR0dGBnZ4cuXbrg4cOHQsyNGzfQvHlzlClTBmZmZhg2bBiysrKU+t+yZQuqV68OHR0dmJubo3///kJdQkKC0sInkUgQEhIixAwdOhTXrl1DWFiYyvkzVhp9//33OHLkCIKCgnD37l1Mnz4dU6ZMQVBQUJHtevXqhZCQEKxbtw7R0dEIDg5G1apVhfrs7Gw4ODhg3rx5cHR0VNnH6dOnMWrUKFy4cAGnTp2CpqYmvL29kZaWJsQsWrQIS5cuxapVq3D16lVYWlqiefPmyMzMFGKaNm2KXbt2ITo6Gnv27EFcXBw6deok1F+/fh0WFhYICgpCVFQUZs+ejTlz5uCnn35SmtO7d+/Qs2dPNGrUSKnu/Pnz6NevH3x8fBAVFYX9+/fjzp07ojXJzMwMM2bMwKVLl3Dz5k0MHDgQgwcPxu+//y7qy8XFBcnJycJ269YtpfG8vb1FMX/u42+DiEpqY6xE+Pj4kLe3NyUnJ9OjR4/o2LFjVLZsWerZs6dSrJubG02bNo1sbGzo/fv3orrQ0FACQFFRUZScnEyXL18mT09PksvllJ6eTkREXl5eNHr0aKV+g4ODKf/tly8rK4uGDx9Oa9eupY4dO5KXl5fKuTdv3pzmzp0rvH727BmZmZlR79696dq1axQfH0+nT5+mSZMm0c2bN4mIKCkpiUxMTGjYsGF07949unLlCtWrV4+6dOki6nvFihUkl8spKCiIYmNj6ebNm7R7926hPj4+ngBQSEgIJScnC1tOTo6on4kTJ1LXrl1Vzp+x0sjd3Z1mzZolKmvUqJHK926BY8eOkZGREaWmphZ7DD8/v4/GZWZmkoaGBh08eJCIiBQKBcnlcpo3b54Qk52dTQYGBrRmzZpC+zlw4AABoDdv3hQaM2nSJKpZs6ZS+fjx42nAgAG0ceNG0tfXF9UtXryY7OzsRGUbNmxQivuzGjVq0JQpU4TXfn5+5O7uXmQbHx8fatu2bZExJeCzch5Otti/jqo38Pfff0+mpqaisgsXLpClpSW9e/eOnJyc6NChQ6L6gmTrw8X23LlzQkJCVPxk60OjR49WmWw9e/aMJBIJRUZGCmX79u0jDQ0NpYTnQ2vXriUzMzNRsnjz5k0CQLGxsURE9PLlS9LT06Pjx48X2k9BsnX16tVCY4iIzpw5Q1paWvT69esi4xgrLYYPH041atSgxMREIiI6f/48GRkZKb3nPzRy5Ehq1qwZTZ06lcqWLUvOzs40ZswYyszMVBlf3GTryZMnBIDCwsKIiOjBgwcEgK5cuSKKa9OmDfXv319lHy9evKDu3buTp6dnkWMNHz6cmjVrJio7fPgwOTs7U0ZGhspk68KFCySTyejgwYOkUCgoNTWVWrRoQd26dVM5hkKhoJMnT5Kenh79/vvvQrmfnx/p6uqSjY0NOTg4UI8ePejBgweitj4+PmRsbEwWFhZUoUIFGjJkCD19+rTIffoKPivn4a8R2b9eXFwcQkJCIJPJROXr169Hz549IZPJ0LdvX6xfv/6jfenq6gIAcnNzv/g8z507B21tbbi7uwtlcrkcCoUCu3fvzv/0pEJOTg5kMhmkUqnSPM+dOwcAOH78OPLy8vD06VO4ubmhbNmy6NSpE+Li4pT669y5MywtLVG/fn3s3r1bqb5WrVp4//49Ll68+Jf2l7GvZeXKlahevTrs7Owgk8ng5eWFhQsXol27doW2iYuLw7lz5xAZGYk9e/Zg9erVCAkJwYABA/7SXMaNG4fq1aujbt26ACBcC2VlZSWKs7KyEl0nBQCTJ0+Gvr4+zMzMkJiYiMOHDxc6zo0bN7Bp0yaMHDlSKEtOTsbQoUMRFBQEQ0NDle3q1q2L7du3o0+fPtDS0oKFhQWISOmarFevXsHAwABaWlpo27YtVq5cidatWwv1np6e2LRpE44ePYqAgACkpKSgXr16ePHihRDTqlUrBAYG4o8//sDSpUtx5coVNG3aFDk5OUUdwtLpc7O0L7AxViJ8fHxIKpWSvr4+6ejoEAACQMuWLRNiMjMzycDAQDiL8+DBA5LJZJScnCzE/PnM1vPnz6lDhw5kaGgofPry8vIimUxG+vr6oq1gXFUKO7O1fPlypdP3RETTpk0jTU1NKlOmDDVv3pzmz59PCQkJQv3t27dJU1OTFixYQDk5OZSWlkZdunQhAPTjjz8SEdGCBQtIJpORi4sLHT16lC5fvkxt27YlOzs74QxVamoqLVmyhC5evEhXr16lmTNnkoaGBgUFBSnNycTEhNavX1/kvwNjJWHLli2i9+LZs2dpyZIlVLFiRTp48CBFRkbSqlWrSF9fn44ePVpoP82bNycdHR3hkgGi/K8WAVBKSopSfHHObE2YMIGsra1FZ3jOnz9PAISzbgUGDBhALVu2FJWlpqZSdHQ0HT9+nOrXr08tW7YkhUKhNM69e/dILpfT5MmTReVNmzalOXPmCK9VndmKiooiGxsbWrRoEUVGRlJISAhVqVKF+vXrJ4rLy8uj2NhYCg8PpyVLlpCRkRGdPHmy0H3PzMwkCwsLWrp0aaExSUlJpKmpSXv27Ck05ivgrxEZKw4fHx9q0qSJcF3SmDFjqE2bNqKv2QICAqhSpUqidvXq1aOffvpJeF2QbBUs2gCoQoUKwleIRPnJVt++fSk2Nla0rVq16pOTrR9//JEqVqyoss3z589p165d9P3331P58uVJT09PtLBt3bqVrKysSCqVkpaWFvn6+pKVlRUtXLiQiIjmz59PAOjYsWNCm/T0dNLR0aEdO3YUeixHjhxJVapUUSq3sbGhVatWFdqOsZKSkZEhei9mZ2eTTCaj/fv3i+IGDx6s9BXbh/r3709OTk6issTERJVf+RF9PNkaP348yeVyunv3rqj8c75GJCJ69OgRAaCzZ8+Kyu/evUtyuZzGjx+v1AYASaVSYdPQ0BDK1q5dS0REffv2pW+//VbULiwsTGVC+KHBgwdT06ZNC60nImrcuDGNGDGiyBgHBwfROlwC+GtExopLT08Pzs7OqFKlClauXIns7GzMnTtXqF+/fj2io6OhqakpbBcvXsRvv/2m1FdoaCgiIyPx6tUrxMTEoGXLlqJ6Y2NjODs7i7Y/3+JcHObm5irvmATy7/7p1q0bli5dirt378LBwUG0P71790ZKSgqSkpLw4sUL+Pv7IzU1VbhDytraGgDg5uYmmreNjQ0SExMLnZOnpydiY2OVytPS0mBhYfHJ+8iYuhkaGorei7m5ucjNzRV9zQ4AUqm00MciAED9+vXx5MkT0V29MTExAAB7e/tPmtO4ceOwbds2nDp1CpUqVRLVOTo6Qi6X48SJE0LZ27dvERYWhnr16hXaZ8HcP/zK7c6dO2jcuDG6deum8tEWt27dQkREhLDNmTMHurq6iIiIQLdu3QDk32Gp6lgBKPRShoL5FPX139u3b3Hv3j1hLVLl+fPnSEpKKjKmtNIs6QkwVhr4+fmhdevWGDZsGF6+fInLly/jxIkToqTozZs3qF+/Ps6ePSu6JdrR0RHm5uZqn2ONGjWQmpqK58+fFzmelpYWnJyc8OTJE6W6gus+NmzYAB0dHTRv3hxA/h8OAIiOjoatrS2A/GcPJScnF/mHIyIiQmnhe/DgAd6+fYuaNWt+2g4yVgKMjIzg5eWFKVOmwMDAAPb29jhz5gwCAwOxaNEiIa7gMSgFz7jr3bs35s6di4EDB8Lf3x/p6ekYN24cunbtCktLSwD5j1C4c+cOgPxkIiUlBRERETAwMICzszMAYPTo0QgKCsL+/fthYmIiXIdlYGAAAwMDSCQSjB8/HvPnz0elSpVQsWJFzJs3DwYGBujduzcA4OLFi7hx4wYaNGiAMmXK4MGDB5g5cyYcHBzQoEEDAPnP/GratCmaNGmCadOmia73KljnKleuLDo2165dg4aGhqi8ffv2GDp0KH799Ve0bNkSycnJGD9+PGrWrAk7OzsAwPz58+Hp6Yny5csjJycHv//+O4KCgrBq1SqhH19fX7Rv3x52dnZ49uwZ5s6di9evX8PHxwdA/vrj7++PLl26wNraGgkJCZg6dSosLS1Fj7T42/jcU2JfYGOsRBR2O7GHhweNHDmSxo8fTzVq1FDZtlWrVsK1CaruRvyzT7kbMSoqisLDw6lHjx7k4eFB4eHhFB4eLtS/f/+eLC0tad++fULZoUOHqE+fPnTo0CGKjo6me/fu0eLFi0kqlYpuFV+1ahVdv36doqOjafXq1aSrq0srVqwQjd+xY0dyd3enc+fOUVRUFHXt2pXs7e2Fa7Y2bdpEW7dupTt37gjjyGQy0bVuRPnXeZQvX77QY8JYaZOcnEwDBgwgGxsb0tHRIRcXF1q8eLHoeicvLy+lr/fv3btHzZs3F+6qGzVqFGVkZAj1BXfw/nn7sB9V9QBEXzkqFAry8/MjuVxO2tra1KhRI7p165ZQHx4eTo0bNyZTU1PS0tIiBwcHGjFiBD169EiI8fPzK3Sswqi6ZouIaOXKleTm5ka6urokl8upV69eorGmTJlCzs7OpKOjQyYmJlS3bl3atm2bqI8ePXqQtbU1yWQysrGxoc6dO1NUVJRQn52dTS1atCALCwuSyWRkZ2dHPj4+RX5V+ZXwNVuMFUdhydbWrVuFxWf+/Pkq2/7222+kq6tL6enpXzzZsre3/+hCOGXKFNEzrB48eEDDhw8nFxcX0tPTIyMjI6pWrRotX75c9IeiX79+wkJctWpVCgwMVJpTRkYGDR48mExMTKhMmTLUrl07un//vlC/adMmcnV1JT09PTI0NCQPDw+VF8e3aNGCFixYUOgxYYyxv7HPynkkVMR3rGpWYgMz9nf17NkzuLm54cqVKyhfvnxJT0fJ7du30axZM8TExMDY2Likp8MYY1+a5OMhyvgCecb+RiwtLbFhwwY8evSopKei0pMnTxAYGMiJFmOMfYDPbDHGGGOMFQ+f2WKMMcYYK2042WKMMcYYUyNOthhjjDHG1IiTLcYYY4wxNeJkizHGGGNMjTjZYowxxhhTI062GGOMMcbUiJMtxhhjjDE14mSLMcYYY0yNSizZIiJFSY3NGPvnKsFfxWCM/YP9lbylRH+uJyMjs6TGZoz9QxkZGYLXFsbYl2ZkZAjwz/UwxhhjjJU+nGwxxhhjjKkRJ1uMMcYYY2rEyRZjjDHGmBpxssUYY4wxpkacbDHGGGOMqREnW4wxxhhjasTJFmOMMcaYGnGyxRhjjDGmRpxsMfYPs2DBjxg9etRXHzcnJwfu7m64cePGVx+bsb8iKysLkyb5wtW1EqysLOHhURO//LK6yDZhYWEwNjZS2mJiYoSYu3fvol+/fqhatSqMjY2wYMGPSv0sWPCjUh8VKjgL9bm5uZg1axbq1asLa2s5KlasgMGDB+HRo0eifjZu3Ih27drCzq4cjI2N8PDhQ6WxFi9ejBYtmsPaWg5jYyOl+q1bt6rcJ2NjI1y/fh0AcOvWLQwaNBBubq7CsVqxYgUUiv//ko2qfSrYUlNThePXq1dPVKxYAXK5FerVq4ugoCClOQUErEPt2rWEsbZv31bkv0tpxckWYx8xcuQIlYtGs2ZNAQBVqlRWWe/n5wcAePjwocr63r17ASje4lWwsL948UIoe/78ORo1aoSGDRsKC1hqaip++eUX+PpOEsV9//0EVKlSGRYW5nB2dkL79u1x6tQpIaawhXHixO8BFG/B19bWxtixY4X9ZuzvYtq0aTh27DjWrl2HK1euwtfXF/7+/tixY/tH216+fAUxMbHC5uTkJNRlZ2fDzs4OM2fOgL29Q6F9VKhQQdTHxYuXRH1ERkZi4kRfnD0bhu3btyMpKQldunTG+/fvhbg3b7LRpElTTJkypdBx3r3LQfv2HTBypOoPY507dxbNIyYmFj169IC9vQNq1qwJAIiIiIC5uTnWrl2HS5cuY+rUaVi0aCGWLVsm9DNmzFilfho0aICGDRvCwsLif8ftMtzc3BAYGISLFy9h0KDBGDduLIKDdwn9rF+/Hn5+fpg8ebIwlq+vL44ePVroPpZWmiU9Acb+Dho3boJ169aJymQymfD/J0+ejMGDh4jq9fX1Ra/37NmLKlWqCK+1tbUBiBcvW1tbXL9+HePGjUVubi58fX1VzicxMRGdOn0LuVyO7dt3wMgo/1Pq5s2bUbOmBxwdHYXYfv36Ijv7DVatWo3y5csjNTUV58+fR1pamhATExMr6j88/AZ69OiBTp06AxAv+A8RZPEAACAASURBVFWrVkVGxitMnz4dXbp0xoULF6Gpmb+UdOvWHTNmzMDdu3fh6upaxBFlrPS4cuUyevbsgUaNGgEA7O3tERQUhGvXrqFnz15FtrWwsICZmZnKOg8PD3h4eAAAli5dWmgfmpqasLKyUllnbGyMAwcOiMp+/nkFPD2/QXR0NNzd3QEAo0aNBoAizyxPnz4DALB//36V9bq6utDV1RVeZ2dnIyQkBGPHjoNEkv+TgP369RO1cXR0RGRkJA4ePCisVwYGBjAwMBBiHj9+jAsXLojW0D+vbUOGDEFYWBgOHDiIbt26AwB27twBHx8fdO3aTRgrPPwGfv55OVq3bl3ofpZGnGwxVgza2lqFLoYAYGBgWGQ9AJiamqqMKc7i9aF79+6hU6dvUbNmTfz22wbo6OgIdbt3B2PAgAHC6/T0dFy4cAH79x9A48aNAQB2dnbCH4ACf57XkSO/w9nZGQ0aNABQ/AXf1NQUnp51sHt3MGbOnFXk8WCstKhTpy6OHg1B//4+sLW1xeXLl3Hr1i2MHTv2o20bN/ZCTk4OXFwqYdKkSULC9ikSEhJQqZILZDIt1KrlgVmz/EQfmP4sMzMDAFCmTJlPHutT7Nu3D69fv0bfvn2LjMvMzCxyLkFBgTA2NsZ/2bvzuJqz/w/gr9st3bRrj1YSIUsx9qhEkjBkrSwx02IZyr5kF4ZBmClLJFvLZBtbZESDJINCoTBUaBHSfn5/9O0z83HvTWNE/N7Px+M+Ht97zvtzzvl8fDvzvudzPvcOHOjynnYKoa/fmHtfUlIKeXkRL0YkEiEpKQllZWW8D7z1Hd1GJKQekjZ5Xb2aiH79+sLW1ha7d4fxEq28vDzcuXMH7dt34MqqP2EeP/4biouLa913dHQUPDzGvidO8oRvZWWFixcv1qovQuqD1atXw9KyDVq1soCGRiP07++IgIDF6NdP+uqJrq4u1q1bj927w7Bnzx6YmTXDwIHO//r/+9bW1tiyZSsiI6OwceNGPHv2DA4OfZCXlysxvrS0FPPmzYOjoyMaN24sMeZjCQ3diX79+kFXV1dqzPXr17F3bzgmTJggsb6yshJ79uzByJEjudV8SU6cOI7ff/8d48aN5crs7OywZ08YkpKSwBjDtWvXsHv3bpSVlfG2VHwJaGWLkFqIjY2Fvr4er8zTcyKWLFkCAFi6dAlWrVrJq9+xYwdvsu7f3xEyMn9/vomMjELXrl3F+qqevEJCtonVjRkzBv37O2Hz5i1idX/99RcYY7xVKllZWWzZshVTpkxGaGgoLC0t8c03nTF48CBYW3eUeK6RkZEoKSnBqFGjJNYDNU/4enq6ePTokdRjCfmcDh48gGnTpnHvIyOjkJSUhEuXLmH//gMwMDBAQsLF/+2zMoS9fR+J7ZiZmcHMzIx736nTN3j06BE2bdqIbt261Xo8ffo48N537NgRbdtaYu/effD19eXVlZeXY+LEiXj58iX2799f6z4+xO3bt3HlyhVERERIjUlPT4er6zB4eXnDxUXyqtWpUyfx119/wd3dQ2o7ly5dgqenJwIDV8PKypornzlzJp49y4GDQx8wxqCtrY2RI0dhw4afIBQKP/zkPgNKtgipha5du2HDhg28sn+u6Pj4+IrdDnz30+C2bdt5+5j09fXF+nnf5OXkNAAnThxHXFwcevfuzasrLn4LALzVLgBwcXFB3759kZCQgMTEK4iNjUVQ0CYsWLBQ4m3KXbtC4eQ0AJqammJ1wPsnfJFIAW/fvpV4LCGfm6Njf95/0PX19TFwoDN27drN7QNq3bo1bty4iY0bN0lNtiSxtrZGVFTUfxqfkpISWrZsifv37/PKy8vLMX78eKSmpuDYsd/QqJHkfWIfS2joTjRp0kTq+aelpWHAACd8++23WLx4sdR2du3ahW+++UbqHs4//vgDw4YNxdy5c+Hpyd/3qqCggM2bt+Cnnzbg2bNn0NXVxc6dO6GsrCx1n1x9RckWIbXQsKEC7ymjdzVq1KjGeqBqUq8ppjaT19q1a6GpqYERI4Zj7959sLOz4+qqJ5+CggKxRE8kEsHW1ha2traYNWs2fH19sWrVSkyZMgUNGjTg4m7cuIHk5GQsXCj5icLaTPj5+flSEzVCPjdlZWUoKytz7wsLC1FWVgahkL+rRigU8p4Iro2bN29CR0f6LbfaKC4uRlpaGnr06MGVlZWVYdy4cbh9OxXHjv323v2h/1VxcTH279+P77//nrcaX+3OnTtwdh6AwYMHY+XKVVLbycrKwsmTJ7Fpk+Sv0bh48SJcXYdh9uw53AZ/SeTk5LgV9OjoKPTt21fiuOozSrYIqQdqO3kJBAKsXfsj5OTkMHLkCISHh3O3IUxMTKGiooI7d+6gRYsWNfbXokULlJeXo7i4mJdshYbuhKGhkdiqGVD7Cf/27VS0bdu2NqdNyGenoqKC7t27IyAgAIqKSjAwMMDFixexf/8+bpsAAHz33SQAwC+/VD1Rt2XLZhgaGqFlyxYoLS3DgQMHcPToUYSF7eGOKS0txZ07dwBUJTA5Oc9w48YNKCoqch+8qm/HN2nSBC9ePMfq1atRVFSEkSOrbuOXl5fDw8Md165dw/79ByAQCJCTk8ONvfrpwZycHOTk5OD+/XsAgLt37+Dly5do0qQJGjVqBAB4/Pgx8vPzudv8N27cAACYmprynh48dCgGhYWFGDOGv1oPVN1edHYegB49emDGDD9uLID4gzZ79oRBUVERgwcPFmsnPj4erq7DMGGCJ1xdXbl2hEIh92Ht3r10XL16FR07dkRBQQGCgoKQmpqKrVt/lvyPWY9RskVILZSUlPImFYA/Kbx+/UqsXiQSQVVV9b1t/5vJq9rKlasgFMpi1KhRCAsLQ79+VfvBbGx64dKlPzBo0CAAQF5eLtzdPeDmNgatWrWGkpISkpOTsWHDT7Cx6cV9ZQRQ9Zh3REQE7zHvarWd8IGq2wLz5s1773kTUl/s2LETixcHYOJET+Tn58PAwADz5s3HpEnfcTF//fUX75jS0jLMnz8PWVlZEIlEaNmyJSIiIuDg0JeLycrKQo8e3bn3GRkZ2LlzB7p3745jx34DADx9+gQTJoxHbm4uNDU1YW3dEbGxZ2BoaAgAePLkCY4dOwYAsLHhP+m4ZctWjB49+n/nsB2rVv39QW3YsGFiMStWLMfevX9/KWj12I4ePcZbSdu1axfs7OxgYGAgdq1iYn7F8+fPER0djejoaF7dy5eF3P9mjGH37jAMGzYMDRs2FGtn795wFBUVYdOmjdi0aSNXbmhoiJs3bwEAKioqERS0GffupUNOTg49evTA6dOxMDIyEmuvvhMwxj5X36yw8NXn6puQWvPy+p43QVXT19fH7dt30KZNa4kbwl1dXRESsg0PHz6EpWUbxMWd474Y8J9WrlzBmyT/qXryio+Px4ABTnjwIIO3V2Hx4sUICtqEnTtDMWDAAMTGxsLb2wu3b9+BUChESUkJVq1ahbi4s3jwIAOlpSXQ09ODo6Mj/Pz8uU+8ALBnzx5MmTIZKSmp0NPjPwxQfQ6S/HMyv3LlMoYOHYa7d+/yErBPSUVFGTS3EEI+NhUVZQAQvC9OEkq2CPnK2NvbwdPT871fxlgX3N3dYWlpKfXLWD8FSrYIIXXhvyRbX9YOM0LIe/3004Z/vbH3YygpKUGbNq3h4yN9oyshhPx/RCtbhJCvCq1sEULqAq1sEUIIIYTUU5RsEUIIIYTUIUq2CCGEEELqECVbhBBCCCF1iJItQgghhJA6RMkWIYQQQkgdomSLEEIIIaQOUbJFCCGEEFKHKNkihBBCCKlDn+0b5BljFQKBgJI9QshHxRiDQPBBX/JMCCFSMcYqBQKB8EOO/aw/1/O5OiaEEEII+QD0cz2EEEIIIfUNJVuEEEIIIXWIki1CCCGEkDpEyRYhhBBCSB2iZIsQQgghpA5RskUIIYQQUoco2SKEEEIIqUOUbBFCCCGE1CFKtgghhBBC6hAlW4R8hQICAjB+/PhP3m9QUBAGDhz4yfsl5L94/fo1Jk+ejCZNmkBBQQHm5uZYv359jcecO3cOAoFA7HXnzh0uJiUlBUOHDoWpqSkEAgECAgLE2gkICBBrQ1dXl6svKyvDrFmzYGlpCUVFRejp6WHUqFF49OgRr53g4GD07t0bampqEAgEyMzMFOtr+fLl6NatGxQVFSX+pFVoaKjEcxIIBEhMTAQA/Pnnnxg5ciQMDAy4a7VmzRpUVlbWeE7Vr2fPnnHXz8XFBXp6emjYsCEsLS2xY8cOsTFt3rwZLVu25PravXt3jf8u9RUlW4TUwtixYyVOHJ07dwYAGBsbS6yfPXs2ACAzM1Ni/aBBgwDUbgKrntxfvHjBlT1//hxWVlbo0KEDN4k9e/YM69atw/z58wEAY8aMQbt27VBaWso7pzNnzkBOTg4JCQlc2Z49e9CuXTuIRCJoamrC3d2dd8zBgwfRrl07NGzYEEZGRlizZg2vfuLEibh69Sri4+P/0/Um5FOaPn06jh07hrCwMNy+fRvz5s3D7NmzERYW9t5jU1JSkJWVxb3MzMy4uqKiIhgbG2PZsmUwMTGR2oa5uTmvjZs3b/LauHbtGubNm4dr167h0KFDePz4Mfr164fy8nJenIODg8SErlpJSQmGDBmCadOmSawfPnw4bxxZWVkYM2YMTExMYG1tDQBISkqClpYWwsLCkJKSgsWLF2PJkiVYtWoV146fn59YOzY2NujVqxe0tbUBAAkJCWjTpg0iIyNx69YteHl5YdKkSdi7dy/XztatWzFr1iwsXLiQ68vHxwdHjhyReo71FmPsc70I+WJ4eHgwe3t7lpWVxXvl5uYyxhgzMjJiCxcuFKt/9eoVY4yxjIwMBoCdOHGCV5+fn88YY2z79u1s8uTJLC4ujt2/f5/t27ePKSkpseXLl3NjiIuLYwDY8+fPGWOMZWZmsubNmzMbGxv28uVLLm758uXMzs6Oe5+fn8+aNGnC5s6dy5W9fPmSGRoasjlz5nBlGzZsYLq6uiwsLIylp6ezGzdusMjISK7+t99+Y0KhkG3evJndv3+fHT16lOnp6bFNmzbxrtWMGTPY0KFD//M1J+RTadWqFVu4cCGvrGfPnszHx0fqMe/+Pdamj0WLFomVL1q0iLVq1epfjTclJYUBYDdu3BCrS0xMZABYRkaG1OMjIiJY1X/+a/bmzRumqqrKm4ck8ff3Zx06dJBa/+jRIyYjI8PCw8NrbGfYsGFsyJAh3PsuXbqwadOm8WKmT5/OunXr9t6x16EPynlkP2eiR8iXRF5enre8/y5lZeUa6wFAQ0NDYsy7t/xMTU1x7do1REVFYe7cuWLxqampcHBwQMeOHbFv3z6IRCKubu/evZg0aRL3Xk1NDTt37oSjoyNcXFzQqVMn/PDDD1BXV+c+BRcUFGDOnDmIiYlBnz59uGPbtGnD/e+wsDA4OzvD29ubG+OcOXMQGBgIHx8f7rbEwIED0adPHxQVFaFhw4Y1Xg9C6oPu3bvjyJEj8PT0hIGBARISEnD9+nX4+/u/91hra2uUlJTAwsIC8+fPR+/evf91/w8ePEDjxo3RoEEDfPPNN1ixYgVMTU2lxhcWFgIA1NXV/3Vf/8bBgwfx5s0bjBs3rsa4wsLCGseyfft2qKmp4dtvv31vO02aNOHel5SU8OY2AFBQUMCVK1dQVlYGOTm5WpxF/UC3EQmpp6RNYJcvX0aPHj3g4OCAyMhI3mSUl5eH1NRUbsm/mr29Pby8vODu7o7IyEiEh4cjLCwMDRo0AACcOnUKFRUVyMnJgYWFBRo3bozBgwfjwYMHXBvSJr6//voLDx8+5Mqsra1RXl6OP/7446NcB0Lq2saNG9GuXTsYGhpCTk4ONjY2CAwMxIABA6Qeo6enh61btyIqKgrR0dEwNzeHnZ0dzp8//6/6/uabbxAaGorjx48jJCQE2dnZ6Nq1K3JzcyXGl5aWYsaMGXB2duYlJnUhODgYAwYMgJ6entSYa9euITQ0FF5eXhLrKysrsWPHDri7u0NeXl5qO0ePHsWZM2d4HxT79u2LHTt2IDExEYwxXL16Fdu2bUNZWRlvO8UX4UOXxD7Ci5AvhoeHBxMKhUxRUZH3mjlzJmOs6jZigwYNxOqPHDnCGPv7NqKCggKv/vz58xL7S0pKYvLy8rzbeNW3LRo0aMCGDRsm8bjk5GQGgD148ECsrqioiJmbmzMZGRm2evVqXt3KlSuZnJwcMzc3Z8ePH2eXL19mTk5OzNDQkL1584Yxxtgvv/zCRCIRO3nyJKuoqGB3795lLVq0YABYQkICrz11dXW2bdu2Wl5dQj6dPXv2iP0Nrl27ljVv3pwdPnyY/fnnn2zTpk1MUVGRHT9+/F+17ejoyJydnSXWSbuN+K5Xr14xLS0t9uOPP4rVlZWVsWHDhjELCwv24sULicd/rNuIt27dYgDYsWPHpMbcuXOH6erqslmzZkmNOXLkCAPAbt26JTXmwoULTFlZmW3ZsoVXXlRUxMaNG8dkZWWZUChk+vr6bObMmQwAy8nJqXH8deiDch5KtgipBQ8PD9a7d2+Wnp7Oe1Xv1zAyMmKzZ88Wq3/9+jVj7O9k69dff+XVFxUVifUlbQKrTrZcXV2ZgoICO336tNixCQkJDAB7+vSpxPMICQlhCgoKrKKigle+fPlyBoCdPHmSKysoKGAikYjt37+fMcZYZWUlmzlzJhOJREwoFDJ1dXUWEBDAALDLly/z2tPX1xfby0VIfVBYWCj2NygnJ8diYmJ4cRMmTODtfayNgIAA1qJFC4l1tU22GGOsV69e7Pvvv+eVlZWVsaFDhzJzc3OWlZUl9diPlWxNmTKFGRgYiM0V1W7fvs10dXXF9lS9a+DAgaxr165S6+Pj45mysjJbv3691JjS0lL2+PFjVl5ezrZs2cKUlZWljusToD1bhNSlhg0bolmzZlLrNTQ0aqwHgCZNmtQYc+fOHfTu3RsjRozgPd3zT0FBQdDS0oKzszMOHToEBwcHrk5TUxMAkJ+fL3HpX1ZWFjIyMpCR4e8gqI61sLDgylRVVaGvr889Yi4QCBAYGIgVK1YgOzsbWlpaOHPmDICqpzH/KS8vD1paWlLPk5DPRVlZGcrKytz7wsJClJWVQSgU8uKEQiHvaeDauH79eo233GqjuLiYmweqlZWVYcSIEbh16xbOnTv33r2h/1VxcTHCwsIwZcoUsbkCqNozamtrC1dX1xq/IuPp06c4duwYtm3bJrH+/PnzcHJyQkBAgNQnJAFATk6Ou2W6f/9+DBgwQOK46jNKtgipJ2o7gQkEAgQFBUFOTg4DBw7Er7/+CkdHRwBA06ZNoaKigtTUVF7i9D7dunUDANy9e5eb1F6/fo2srCwYGRnxYoVCIRo3bgwA2LdvH7p06cI9zg0A9+/fR3FxMTp06FDr/gn5XFRUVGBjY4PZs2dDSUkJRkZG+P3337F7926sXr2ai6v+GpTq73n66aefYGxsjFatWqG0tBR79uxBTEwMoqKiuGNKS0uRmpoKoCqByc7OxvXr16GkpMR96PLz84OzszMMDQ3x7NkzLF26FG/evIGHhwcAoLy8HMOGDUNiYiKOHDkCgUCA7OxsAFUfiBQUFAAA2dnZyM7ORlpaGoCq+aSgoACGhoZo1KgRAODRo0fIy8vjvoPr+vXrAIBmzZpBSUmJG3dkZCRevnwp8bv6UlJSYGtri969e2Pu3LncWACIJYE7duyAoqIiXF1dxdo5d+4cnJyc4O3tjdGjR3PtCIVC7oNaWloaLl++jM6dOyM/Px/r1q3DrVu3sGvXLon/lvXahy6JfYQXIV8MaV/98OzZM8aY9K9+KCgoYIz9fRsxMTFRYvu3bt1i2trabPjw4WJtVJP0qLmfnx9r0KABtzeMMcaGDBnCpk6dKrGfnTt3MkVFRYl1Li4urFWrVuzChQssJSWFDR06lBkZGXF7tp4/f862bNnCUlNTWXJyMpsyZQoTiURitxB37tzJTE1N33dJCak3srKy2NixY5m+vj4TiUTM3NycrVmzhlVWVnIxNjY2zMbGhnsfGBjImjZtykQiEVNXV2fdu3cX299U/Xf/7uuf7QwfPpzp6ekxOTk5pq+vz4YMGcJSUlLe2wYAtnPnTi5u0aJF743x8PCQGBMXF8cbd8+ePZmjo6PEayWtH7xzW7KyspIZGxszLy8vie1IG4uRkREXk5qaytq1a8cUFBSYiooKc3FxYXfu3JHY3idEe7YIqSvSJobGjRszxqqSLUn1o0ePZoy9P9mqzQQm7Xt95syZwxo0aMB+/fVXxhhjJ06cYLq6uqy8vFysn5qSrcLCQjZhwgSmrq7O1NTU2IABA9i9e/e4+ufPn7POnTszRUVF1rBhQ2ZnZ8cuXbok1o6DgwNbuXJlTZeTEEK+VB+U8wgYYx93qaz2PlvHhHztunTpAm9vb7i5uX3Sfm/dugU7OzukpaVBVVX1k/ZNCCGfgPjvHNXCl7XDjBBSK7/88su/3tz7MTx9+hS7d++mRIsQQv6BVrYIIYQQQmqHVrYIIYQQQuobSrYIIYQQQuoQJVuEEEIIIXWIki1CCCGEkDpEyRYhhBBCSB2iZIsQQgghpA5RskUIIYQQUoco2SKEEEIIqUOUbBFCCCGE1KHPlmwxxj79b4kQQr56n/FXMQghX7H/krd81p/rKSx89bn6JoR8pVRUlEFzCyHkY1NRUQbo53oIIYQQQuofSrYIIYQQQuoQJVuEEEIIIXWIki1CCCGEkDpEyRYhhBBCSB2iZIsQQgghpA5RskUIIYQQUoco2SKEEEIIqUOUbBFCCCGE1CFKtgj5Cq1cuQI+Pt6fvN/nz5/D1NQET548+eR9E1KXXr9+DX9/P7Rs2QI6OtqwsuqAzZuD3nvchQsX0LNnT2hra8HS0hLbt2/n1b969QqzZ89C69atoKOjjT597JGUlMSLUVVVkfiaMWP6vxrf5MmT0batJXR0tGFqaoKRI0fg7t27vJh799IxatRImJgYo3FjfdjZ2SI29jQvJikpCQMHDoShoSEMDQ3g7OyMpKSrvJiUlBT07+8IHR1ttGhhjsDAVbyf0iorK0Ng4Cq0bWsJbW0tdOvWVayff1q7di1UVVXg5zdDakx9RskW+ap4eX0vcVKys7MFALRp0xobN27k4p2c+kuMLygoEGt7ypQpUFVV4R1f3aakNhYtWgQAePjwIa9cS0sTHTq0F2tn5coVXIy6uhosLFrC19cXL1684Nrx8fGBpWXVZGlpaYmAgAC8ffuW187z58+xefNm+Pn5c2UvXrzA9Ok/oE2b1tDS0kSzZk3h7OyMs2fP8o69dy8do0ePhqGhAXR1ddCjRw/eZCzpeo0bN5ar19LSwsiRI7FixYr3/lsR8iWZO3cuTp48hV9+CcaVK4nw8/NDQEAA9u/fJ/WYzMxMDBs2FN980wnx8Rcwffp0zJzpj0OHDnExkydPxpkzZ7B1689ISPgDtra2GDTIBU+fPuVi0tLSea8DBw4AAAYPHvKvxte+fXts3fozrlxJRHT0r2CMwcVlIMrKyrgYV1dXFBcX4/DhIzh/Ph6dO3fByJEj8eDBAwBVSd233w6Bnp4uTp8+jdOnY6Grq4PBg4fg1auqn8kqLCzEoEEu0NLSRlzcOQQGrsbGjRsRFPR38rd06VLs2LEDq1evxuXLVzBu3HiMHj0af/75p9h1TEy8gl27dqF169a1/veqb2Q/9wAI+dh69eqN4OBgXpmcnJzU+DFjxmDhwkW8MlVVVd77mJgYXLt2DXp6ehLbmDVrFiZM8OSVKSoq8t5HRUWjTZs2KCkpwfnz5zF16hQ0btwY3377LRdjZmaGY8d+Q0VFBW7c+BO+vr7IynqKqKhopKenobKyAuvWrUPTpk2RlnYXU6dORV5eHi9x27VrFzp0sIKJiQlX5uY2BkVFb7FpUxBMTU3x/PlzXLx4EXl5eVxMZmYmHBwcMHLkSPj7H4GqqirS09PEzuPd6yUSiXj1o0ePQa9eNli6dCkaNWok8XoR8qW5cuUyRowYjp49ewIAjIyMEBYWhqtXr2LEiJESj9mxYwd0dXWxZs1aAIC5uTmuXr2KTZs2wsXFBW/fvsXhw4cQFrYHPXr0AADMmTMXx4+fwPbt27BgwUIAgI6ODq/dY8d+Q7NmzdC9e/d/Nb7x48dz8UZGRpg/fwG6deuKzMxMmJmZITc3F/fv38dPP21AmzZtAACLFy/Gli2bcePGDZiamiItLQ35+fmYM2cujI2NAQDz5s3HwYMHkZ6ejg4dOuDgwYN4+/Ytfv75ZygoKMDCwgJpaXexeXMQfH19IRAIcODAfkybNg19+/YDAHh6euLcuXMICtqEkJBt3DhfvnwJT09PBAUFYfXqwA/4l6sfaGWLfHXk5RtAR0eH96rpP/oKCgpi8QLB3781+ujRI8yePQvbt2+XmrQpKSmLtaGkpMSLadSoEXR0dGBoaIgxY8agdes2Yp/iZGVloaOjA319ffTr54jvvvseZ8+exdu3b2Fv3wdbt/4Me3t7mJiYoG/ffpgxww+HDx/itREZGYH+/R259wUFBUhISEBAQAB69eoFQ0NDWFlZYcqUKRg6dCgXt3TpEtja2mL58hVo164dTExM4ODQF02aNKnxer2bmFpYWEBXVw9HjhyRes0J+dJ07twFx4+fwF9//QUAuHz5Mm7evAl7e3upxyQmXoGtrS2vzM7ODsnJySgrK0N5eTkqKiogLy/Pi1FQEOHSpUsS23z16hWio6Pg4TH2P43vzZs3CA/fAwMDAxgaGgKomqPMzc1x4MB+vH79GhUVFdi5cyeUlZXRuXNnAFUfCDU1NREWthslJSUoKSnBrl27YGBggJYtW3Ln3aVLFygoKHD92draISsrCw8fPgQAlJSUQF6e/0FN0nlPnToVLi6DYGNjI/E8BdbPSwAAIABJREFUvhSUbBFSg/LyckyYMB5+fv4wNzf/KG0yxnDp0iWkpd2FtbV1jbEKCgqorKxEeXm5xPpXr15BTU2Ne5+Xl4c7d+6gffsOXJmSkhKUlJRw/PhvKC4ulthOZWUlTpw4AXPzFhgyZDBMTU3Qq5cNoqKixGKjoqJgYmKMb77phHnz5nG3Dv7JyqoDLl68UOO5EfIlWb16NSwt26BVKwtoaDRC//6OCAhYjH79HKUek5OTA21tbV6ZtrY2ysvLkZubC2VlZXTq1Alr167B06dPUVFRgQMH9uPKlSvIzs6W2GZkZCRKSkowatSoDxpfSEgI9PX1oK+vh9OnT+PQocNcsicQCBATcwipqalo0qQxtLQ0sWrVSkRGRkJXVxcAoKysjGPHfkN0dDR0dXWgq6uD6OgoxMTEcMmVtPMGgGfPcgBUJZ1bt25Beno6KisrcfbsWRw5coR33qGhoXjw4AHmz58v9Rp/KSjZIl+d2NhYbjKpfi1cuFBqfGhoKC922rRpXN2KFSvQqFEjeHp6Sj0eqFoVerfPEyeO82L693eEvr4etLQ00bevA8aOHYuBAwdKbTMtLQ3bt2+DlZUVlJWVxeofP36MTZs2wtNzIlf2119/gTHGu+0gKyuLLVu24sCBAzA0NIC9vR3mzZuHq1cTuZjnz5/j9evXWLfuR9ja2iEm5hCGDh2GiRM9eecxdOgwhIRsw9Gjx+DvPxOHDx/GmDFjxMamp6eHR48e1XjNCKmvDh48wPtbTkhIwC+//IJLly5h//4D+P3381i5ciUWLJhf46ZuALxVcgDcJvHq8l9+CYaMjAxatmwBLS1N/Pzzzxg6dCiEQqHE9nbtCoWT0wBoamryyms7PldXV8THx+O3346jWbNm8PDwQFFRETe2GTOmo1GjRjhx4iTOno2Di4sL3NzcuD1kb9++hY+PNzp16oTY2DM4deoULC3bYuTIkXjz5s0/z7zG8w4MXA0zMzN06tQRmpoa8Pf3w+jRo7nzTk9Px5Ili7Ft2zY0aNCgxmv8JaA9W+Sr07VrN2zYsIFX9s/Vn3cNGTIEs2bN5t6rqKgAqHqKaO/ecFy4cPG9ffr4+MLNzY1XVv1JsNq2bdvRsmVLlJeXIyUlBbNmzUTDhg25fRkAcPfuXejr66GiogIlJSXo3r2H2LkAwLNnzzBkyGD07t0bPj4+XHlxcdVm+Xf3Ubm4uKBv375ISEhAYuIVxMbGIihoExYsWAg/Pz9UVlYCAPr37w9fX18AgKWlJZKTryEkJIT7dDxu3DiuzVatWsHExBi2tra4fv062rVrx9WJRAp4+1byKhoh9Z2jY39YWf296qyvr4+BA52xa9duODpW/S20bt0aN27cxMaNm2Bv30diOzo6OsjJyeGVPX/+HLKystzWBlNTU/z223G8efMGr169gq6uLsaOHQsjIyOx9m7cuIHk5GSxPaZv377F4sUBtRqfqqoqVFVV0bRpM3Ts2BFGRoY4fPgQRowYid9//x3Hjx9HZuZDbs5s164d4uLiEB6+B/7+MxEREYGMjAycOnWaS4y2b98OIyNDHD16BMOHj4COjg63gvXP8wYALa2qFS5NTU3s3bsPxcXFyMvLg56eHhYtWsSd95UrV5Cbm4vOnb/h2qioqMDFixexY8cOZGVli91+rc8o2SJfnYYNFdC0adNax6uoqEiMj48/j+zsbDRvbsaVVVRUYNGihdi6dQtu377DlTdq1Oi9ferr63Mx5ubmyMzMxPLly+DvP5NLjkxMTBAREQmhUAg9PT2Jk0lOTg6cnQegZUsLBAeH8D45a2hoAKjap/VusicSiWBrawtbW1vMmjUbvr6+WLVqJaZMmQINDQ3IysqiRYsWvGPMzc0l3kqs1r59BwiFQty/f5+XbOXn50NTU6PG60FIfaWsrMxbTS4sLERZWRmEQv7NIKFQyH1QkaRjx044duworywuLg7t27cX2/+pqKgIRUVF5Ofn4+zZM1i8eIlYe6GhO2FoaITevXvzysvKyj5ofIwxMMZQUlIKANyTzTIy/HZkZGS4dt6+LYJAIODFyMjIQCAQcDEdO3ZCQMAiFBcXc3NbXFwc9PT0xJJIkUgEfX19lJWV4fDhQ9wTlk5OTvjjD/7+LW9vLzRt2hQzZvh9catddBuRECk8PSciIeEPXLhwkXvp6enB29sHhw//983fQqEQ5eXlKC0t5coaNGiApk2bwtjYWGKilZ2dDSen/mje3Bw7duyArCz/85KJiSlUVFRw584dsWPf1aJFC5SXl6O4uBgNGjRAhw4dkJ6ezou5d+8eDAwMpLaRkpKCiooKscTu9u1UtG3bTspRhHxZVFRU0L17dwQEBCA+Ph6ZmZkIDw/H/v374Ow8gIv77rtJ+O67Sdz78ePH4+nTp5g9exbu3r2LXbt2Ye/ecEyePIWLiY2NxenTp5CZmYmzZ8/C2XkAmjVrJnZ7vqioCBEREXB3dxe7NVmb8d2/fx/r169HcnIyHj9+jMuXL8PDwx0NGsijX7+qJwI7deoEdXV1eHt74+bNm7h3Lx3z589HZmYm99Rg7962ePXqFaZPn467d+/i9u3b8Pb2glAoRM+eVZvYhw0bBgUFBXh5fY/U1FQcPnwYP/20Hj4+vtzYr15NxOHDh5GRkYGEhAQMGTIElZUMU6dOBVB1N8LCwoL3UlRUhLq6OiwsLMSuQX1HK1vkq1NSUiq2dC8UCsX2OLyPlpYWtLS0eGVycnLQ0dGBmZkZr/z161difYpEIt6Tenl5ecjJyUF5eTlSU1Pw889b0aNHT+625ftkZWXByak/9PT0sGrVKuTm5nJ1mpqaEAqFkJGRgY1NL1y69AcGDRr0v35z4e7uATe3MWjVqjWUlJSQnJyMDRt+go1NL67/qVOnYexYD3Tp0hU9e/ZEfHw8oqKisHfvXgDAgwcPEBFxEH36OEBDQwN3797BvHnzYGnZlntSCaj6j8L169fFbnUQ8iXbsWMnFi8OwMSJnsjPz4eBgQHmzZuPSZO+42KqnwSsZmxsjIiISMyZMwfbt2+Hrq4eAgNXw8XFhYspLCzE4sUBePr0KdTV1TFw4EAsWLBQbOUrOjoab968kbhHsjbjk5eXx4UL8QgK2oSXL19CW1sbXbt2RWxsLLfHU0NDA1FR0Vi6dAmcnQegvLwczZs3x969e7mV6+bNm2P//gMIDFyFPn3sAQhgadkGkZFRaNy4MYCqW5UxMYfg5zcDvXrZQE1NDb6+vtwWBQAoLi7BsmVLkZmZCUVFRTg4OCA4OLjGLR9fMsE/v9H1E2OFheJPMRHyX3h5fc8lB/+kr6+P27fvoE2b1pg4cRKmTKn6ZOnk1B8tW7bE2rU/1qr9d4+vLpO0GdzV1RUhIdvw8OFDWFq24cqFQiF0dXVhb98HCxcu5JLAlStX4NChQ7h06bLEvsPDw+Ht7SWx7saNm9zyfGxsLLy9vXD79h0IhUKUlJRg1apViIs7iwcPMlBaWgI9PT04OjrCz8+f97UY4eHh+PHHtXjy5AmaNm2K6dOnY+jQYQCq/kMyadJEpKam4s2bN2jcuDH69u2LWbNm89qIjIzAqlWrcPUq/1uwPxUVFWXQ3EII+dhUVJSBd3f+1xIlW4R8hezt7eDp6Sn1yxbrUu/eveDt7Y1hw1w/ed8AJVuEkLrxX5It2rNFyFfop5821Lgxtq48f/4cLi6DuNUwQgghtLJFCPnK0MoWIaQu0MoWIYQQQkg9RckWIYQQQkgdomSLEEIIIaQOUbJFCCGEEFKHKNkihBBCCKlDlGwRQgghhNQhSrYIIYQQQuoQJVuEEEIIIXWIki1CCCGEkDr02b5BnjFWIRAIKNkjhHxUjDEIBB/0Jc+EECIVY6xSIBAIP+TYz/pzPZ+rY0IIIYSQD0A/10MIIYQQUt9QskUIIYQQUoco2SKEEEIIqUOUbBFCCCGE1CFKtgghhBBC6hAlW4QQQgghdYiSLUIIIYSQOkTJFiGEEEJIHaJkixBCCCGkDlGyRchXKDQ0FLa2tp+835KSEhgaGuLq1aufvG9CPpRAIJD48vHxkXpMcXExxo4dC0tLS8jJyaFXr1419nHhwgXIysqidevWvPKUlBQMHToUpqamEAgECAgIqLGdFStWQCAQwNfXl1c+duxYsfF37tyZF5OdnQ03Nzfo6upCUVERbdu2RXh4OFd/7tw5qdciIiKi1jHVTp48iS5duqBhw4ZQU1ODnZ2dxHN68eIFGjduDIFAgBcvXkhsQ1lZGZqamnBxcUFaWlqN16g+omSLkFp4/vw5vL29YWxsDHl5eejo6MDOzg6nT58GAPTq1Uvi5DNixAiujX+WKysrw9raGtHR0QAAY2NjqROYQCDgJvL79+9j8ODB0NLSgoqKClxdXZGTk8Mba2lpKebPn49FixZxZUVFRZg7dy6aNWsGkUgETU1NdOvWDfv27eNiKioqsGDBApiYmEAkEsHExATz589HeXk5F/O+CV1eXh7+/v6YNWvWx7v4hNSxrKws3uvIkSMAAFdXV6nHVFRUQCQSwdfXF05OTjW2n5+fD3d3d4nJRlFREYyNjbFs2TKYmJjU2M6lS5cQEhICS0tLifX29va88/jtt9949e7u7rh9+zYOHTqEmzdvwt3dHW5ubjh//jwAoGvXrmLXYs6cOVBSUoKjo2OtYwAgJiYGI0aMgJubG5KTk/HHH39g/PjxEsc9btw4tGvXTqw8IyMDLi4u6NGjB5KTkxEbG4u3b9+if//+NV6neokx9rlehHwxevTowaysrFhsbCzLzMxkV65cYWvWrGH79u1jjDFmY2PDxo0bx7KysnivgoICrg0ALCQkhGVlZbHbt2+z8ePHMxkZGZaQkMCePXvGHXPixAkGgF25coUry83NZa9fv2ampqbMxcWF/fnnn+zGjRvMxcWFdezYkVVUVHD9hIeHs6ZNm/LG7+bmxkxNTdmRI0dYRkYGS0pKYlu2bGFBQUFczPLly5m6ujo7fPgwy8jIYIcOHWJqampsyZIlXIyHhwezt7fnnWNubi6vr9zcXNagQQN269atj/pvQMin4unpyZo3b17reB8fH2ZjYyO1fvDgwSwgIIAtWrSItWrVSmpcq1at2KJFiyTWFRQUMFNTU3bmzBlmY2PDfHx8ePUeHh7MycmpxnEqKiqyHTt28MoMDQ3ZmjVrpB7TvHlzNnHixBrbfTemvLycGRgYsODg4BqPY4yxn376idna2rIzZ84wAOz58+dcXUREBJORkWHl5eVc2dmzZ8XiPrEPynko2SLkPfLz8xkAdvr0aakxkia/dwFgERER3PvS0lLWsGFDNnv2bF5cYmIiA8AyMjJ45SdPnmQCgYDl5eVxZQUFBUwgEPDG5uTkxH744QfesaqqqiwkJKTG8Tk5OTF3d3dembu7O28Cr82EzhhjvXv3ZvPmzXtvHCH1TWFhIVNSUqoxAXlXTcnW5s2bWZcuXVh5efl/SrZcXV3ZzJkzGWOS5xsPDw+mqqrKtLS0mJmZGfP09GQ5OTm8mL59+7J+/fqxFy9esIqKChYTE8MUFBRYcnKyxD7j4uIYAJaYmCh1zJJiLl++zACwXbt2sfbt2zMdHR3Wp08fdu3aNd6x165dY3p6euyvv/7i2vlnEpWRkcHk5eXZzz//zMrLy1lhYSHz8PBgHTt2lDqeT+CDch66jUjIeygpKUFJSQmHDx9GcXHxR2tXTk4OsrKyKCsrq1V8SUkJBAIBRCIRVyYSiSAjI4MLFy5wZRcuXIC1tTXvWF1dXZw4cQIvX76U2n737t0RFxeHO3fuAABSU1Nx9uxZsSX7CxcuQFtbG82bN8fEiRPx7NkzsbY6deqE33//vVbnRUh9sm/fPpSUlMDDw+M/t3Xz5k0sXrwY4eHhEAqFH9xOSEgI7t27h6VLl0qN6devH3bv3o0zZ87gxx9/xJUrV2Bra4uSkhIu5uDBgxAIBNDU1IS8vDxGjx6Nffv2SbyFBwDBwcFo27at2HzyvpgHDx4AABYsWIC5c+fi2LFjaNKkCWxsbPD06VMAwJs3bzBy5Ehs2rQJjRs3lti2sbExTp8+jUWLFkFeXh6qqqq4efMmjh49Kv1i1VOUbBHyHrKysggNDcWePXugpqaGLl26wM/PD5cvX+bFBQcHc4lZ9WvLli0S2ywpKcGyZctQWFgoddPouzp37gwlJSX4+/vjzZs3ePPmDfz8/FBRUYGsrCwAQEFBAV6+fAk9PT2xsV2+fBmampro0KEDfH19uf1m1WbNmgU3NzdYWFhATk4OrVq1goeHB7y9vbmY2kzoAKCvr4/MzMxanRchn1J4eDjvbzQ+Pp5XHxISgkGDBkFLS+s/9VNSUoIRI0Zg7dq1792LVZO7d+9i7ty5CA8PR4MGDaTGjRgxAgMHDkSbNm3g7OyM48eP4+7duzh27BgXM3/+fLx48QKxsbG4evUq/P394e7ujj///FOsvdzcXERHR2PSpElS+5QWU1lZCQCYN28ehg4dCisrKwQHB0NNTQ1hYWEAgClTpqBbt2749ttvpbafnZ2NCRMmwN3dHYmJiTh37hyUlZXh6urK9fHF+NAlsY/wIuSL8vbtW3bq1Cm2ePFi1qVLFwaALV++nDFWtaw/ZswYlp6eznu9u2dLJBIxRUVFJiMjw9TV1dnatWvF+pF2G5GxqluJpqamTCAQMKFQyMaMGcM6dOjAvLy8GGOMPX36lAFgCQkJYseWlpay8+fPs5UrV7I+ffowAGzSpElc/b59+1iTJk3Yvn372I0bN9ju3buZuro627Ztm9Rr8uTJEyYrK8uioqJ45cHBwUxDQ6PmC0rIZ1BYWMj7Gy0qKuLqkpOTGQB26tSpf9WmpNuIGRkZDAATCoXcSyAQcGUnT54Ua0fSbcSdO3eKtQOAmwOKi4uljsvY2JitWrWKMcbYvXv3GAB2/fp1XoydnR2bMGGC2LHr1q1jCgoKvDmstjHV+6ri4+N55ba2tszb25sxxpiRkRGTkZHhzklGRoY7z7lz5zLGGJs/fz5r164dr43Hjx9LbPsT+qCcR/ZzJHiEfIlEIhH69OmDPn36YOHChfD09ERAQAD8/PwAAKqqqmjWrFmNbaxZswb9+vWDiooKtLW1//UYHBwccP/+fbx48QKysrJQU1ODrq4u98lZQ0MDAoEA+fn5YsfKycmhR48e6NGjB2bPno1ly5ZhwYIFmDNnDoyNjeHv7w8/Pz/uCco2bdrg4cOHWLlyJSZMmCBxPPr6+mjSpAnS09N55Xl5ef95ZYCQuqCsrAxlZWWJdcHBwTA2Noa9vf1/7qdx48a4efMmr2zLli04ffo0fv31VxgbG9eqnUGDBondxhs3bhzMzMwwd+5cqatdL168wJMnT7hV7qKiIgAQu50pFAolrhJt27YNrq6uUFVVlTo2aTFWVlaQl5fH3bt30b17dwBVq133799H3759AQCnTp1CaWkpd0xiYiLGjx+Pc+fOwczMjBuzpPFWt/cloWSLkA9kYWGB8vLyf7WPS1dX970JWW1oamoCAM6ePYtnz55h4MCBAIAGDRrAwsICqamp73082sLCAgDw+vVrANIntpomtXcn9Gq3bt1Chw4d/t1JEfIZFRUVITw8HDNnzoRAIBCrnzNnDq5cuYIzZ85wZampqSgtLcWLFy/w+vVrXL9+HQDQrl07yMnJiX2nlra2NuTl5XnlpaWlSE1NBVD13V3Z2dm4fv06lJSU0KxZM6ipqUFNTY3XjqKiIho1asS18/r1awQEBODbb7+Fnp4eMjMzMWfOHGhra2Pw4MEAgBYtWqBZs2bw9vbG2rVroaGhgZiYGJw+fRqHDh3itX/hwgWkpqYiODhY6vWqKUZFRQXff/89Fi1ahCZNmsDY2BhBQUHIz8/HmDFjAADNmzfnHVP9/VotWrTg5jcnJyesX78eixcvxqhRo/Dq1SvMnTsXBgYGsLKykjq2eulDl8Q+wouQL8KLFy9Y7969WVhYGPvzzz/ZgwcP2MGDB5mOjg6zt7dnjEn/6od/fi0C3nkaUZqabiPu2LGDJSQksHv37rGwsDDWqFEjNn36dF7M9OnTmYuLC6/MxsaG/fzzz+zq1assIyODHTt2jJmbmzNzc3PusWoPDw/WuHFjdvToUZaRkcGio6OZpqYm1/6rV6/YjBkzWEJCAsvIyGBxcXGsc+fOrHHjxqywsJDXn5GREdu9e/f7Ly4h9cSOHTuYUChkT548kVjv4eHBjIyMeGVGRkYMgNhLGklPI1bfbnz3VdNXSbz7NGJRURFzcHBgWlpaTE5OjhkaGjIPDw/26NEj3nFpaWlsyJAhTFtbmzVs2JBZWlqy0NBQsfbd3d1Zy5YtpfZfm5jS0lLm7+/PdHR0mLKyMrOxsWFJSUlS4yU9jchY1faG9u3bM0VFRaapqckGDBjAUlJSahxbHfugnIeSLULeo7i4mM2ZM4dZW1szNTU1pqCgwJo1a8Z++OEHLpmysbGROGF269aNa+djJFuzZs1iOjo6TE5OjpmZmbEff/yRVVZW8mJu377N5OXleYneihUrWLdu3ZiGhgaTl5dnRkZGzNPTkzcZFxYWsqlTpzJDQ0MmEomYiYkJmzNnDnv79i1jrPYTekJCAlNTU+PthSGEkK/EB+U8AsbYp11K+9tn65iQr92IESPQqlUrLFiw4JP3PWzYMLRv3x5z58795H0TQkgdE7/HXAv01Q+EfIVWr14NFRWVT95vSUkJ2rZtix9++OGT900IIfUVrWwRQgghhNQOrWwRQgghhNQ3lGwRQgghhNQhSrYIIYQQQuoQJVuEEEIIIXWIki1CCCGEkDpEyRYhhBBCSB2iZIsQQgghpA5RskUIIYQQUoco2SKEEEIIqUOfLdlijFV+rr4JIV+vz/irGISQr9h/yVs+68/1FBa++lx9E0K+UioqyqC5hRDysamoKAP0cz2EEEIIIfUPJVuEEEIIIXWIki1CCCGEkDpEyRYhhBBCSB2iZIsQQgghpA5RskUIIYQQUoco2SKEEEIIqUOUbBFCCCGE1CFKtgj5guTn56NZs6Z48ODB5x6KRG5ubggKCvrcwyCEkHqFki3y1fPy+h6qqipQVVWBhkYjNG1qigEDnBASEoyysjIuzsmpP1RVVXDgwH7e8eHh4dDX1+Pex8fHQ1VVBQYGTVBUVMSLvXv3LtdXbm4uVq5cwb2X9nr48CFu374NNzc3WFpaQlVVBStXrpB4Lj/++CMcHBxgamrKlR09ehT29nYwNDSAvr4erK2t4OvryzsuOjoa3bt3g66uDlq3boUNGzbw6qvP6d1XWlqaxHFERkZAVVUFrq7DeOWzZ8/GmjWr8fLlS4nHEVIfSfvbnDFjeo3HpaSkoH9/R+joaKNFC3MEBq7i/VxUWVkZAgNXoW1bS2hra6Fbt66IjT0t1k52dja+//47mJqaQFtbC506dcSFCxe4+mXLlsLa2gp6erowNDSEs7MzLl++zNXn5eXB398P1tZW0NHRhoVFS/zwww/Iy8vlYh4+fAgfHx9YWlpCR0cblpaWCAgIwNu3b7mYmzdvYvz4cbCwaAkdHW1YWXXAhg0bUFlZyWtH0rV697xCQoLRsaM1186+fXt59b/++itsbGxgaGgAPT1ddO/eDXv3hku91mvXroWqqgr8/GbU9E9Sb8l+7gEQ8in06tUbwcHBqKiowIsXL3D+/HmsWLEC+/fvx+HDR6CoqAgAEIlEWLZsGQYNGgx5efka21RRUUFMzK8YNWo0V7Z7924YGBjg8ePHAIDJk6dg/PgJXL2TU3/07dsPU6ZM4co0NTVx/fp1GBoaYuBAZyxdukxif0VFRdi9ezcOHDjAlZ07dw4eHu6YM2cutmzZCqFQBmlp6Th69CgXc/r0KXh6TkBg4GrY29sjLe0upkyZAgUFESZN+o7Xx+XLV6Curs4b27syMjKwYMECdO3aVayuVatWMDY2wcGDBzBx4iSp146Q+iQtLZ33Pjn5GoYPH47Bg4dIPaawsBCDBrmga9duiIs7h/T0dHh7e6FhQ0VMnjwZALB06VIcOLAfGzduRPPm5jhz5gxGjx6NU6dOo23btgCAgoICODg4oEuXzoiIiICGhiYyMzOhpaXF9WVmZoa1a3+EkZERiouLsXnzZnz77RBcu5YMbW1tZGdn4+nTLCxZshTm5ubIysrCjBnTMX78eMTEHAIApKenobKyAuvWrUPTpk2RlnYXU6dORV5eHjZu3AgAuH79OjQ1NfHLL8Fo0qQJkpKSMHXqFJSVlcHPz493/lFR0WjTpg33/p/zxrZt27Bo0SJs3LgRVlbWXDtqaupwdHQEADRq1Aj+/v5o3rw5ZGVlcfLkCfj6+kJTUxMODn15fSUmXsGuXbvQunXr2v2D1kP024jkq+fl9T1yc3Nx8GAErzw1NRU9e/bA9OnTMXfuPDg59YehoSFiY2Mxdeo0bnUoPDwc/v5+ePo0C0DVKtCAAU6YOXMmLl68iN9+Ow6g6lNsy5YtMH78eAQGBuLBgwxoaGjw+uzc+Ru4uLhgzpy5UscrLSYmJgbTpk1FRkYmBIKqn+eaPXsWkpOTcfLkKantTZgwHsXFxQgP//uT5S+//IwNGzYgJSUVAoGAOydJY/6nsrIy9O3rAE9PT8THx0u8roGBq3D27Nkax1SX6LcRyX81efJkJCRcRFLSNakx27ZtQ0DAIqSn34OCggIAYM2a1di+fTtu374DgUAAc/PmmDZtGry8vLnjxowZAwUFEUJCtgEAFi9ejIsXL+DUKfEVL2kKCwthYNAEUVHRsLe3lxhz6tRJuLq64tGjx1BRUZEYExISguXLlyEz86HUvhYsWIDff/8d58+fB1C1smVp2QZxcefQoUMHicf06WMPa2trrFy5iiubN28url69WuO80KNHD9jZ2SEgIIAre/nyJXr27IGNGzdh9epAtGzZEmuujoFQAAAgAElEQVTX/ii1jbpEv41IyAewsLCAvb09Dh8+zJUpKipi5sxZWLt2DQoKCmo8fvjw4UhKSuL2T504cQKKioro3r1HnYz3jz8S0K5dOy7RAgBtbR2kpaXh5s2bUo8rKSkVW6UTiRTw5MkTPHr0iFfeq5cNmjc3g7OzMze5/tOSJUtgaGjEW817l5WVFZKSkni3Jwj5Urx69QrR0VHw8BhbY1xi4hV06dKFS7QAwNbWDllZWXj4sCp5KSkpgby8iHecgoIIly5d4t4fO3YU1tbWGDt2LJo2NUX37t0QHPwLpC2ElJaWIjQ0FCoqKrC0tJQ6vsLCV5CXl0fDhg1rPFc1NbUaz1NajJvbGDRtagoHhz6IiYnh1VXNOfzzFolESEpK4m3dqMYYw7lz53DvXjq6deOvmE+dOhUuLoNgY2NT4zjrO0q2yP9r5uYtkJmZySsbN24cGjVqhPXr19d4rLp6Izg69seePXsAAGFhuzFmzBheMvQxPX78GLq6uryy7777DtbW1ujevRssLFrCzc0N27dvx+vXr7kYOzs7HDt2DGfOnEFlZSXu3UtHUNAmAEBOTjYAQFdXF+vWrcfu3WHYs2cPzMyaYeBAZ1y8eJFr58yZM/j11+j3XhddXT2UlZUhKyvrY506IZ9MZGQkSkpKMGrUqBrjcnJyoK2tzSurfv/sWQ6Aqr+9rVu3ID09HZWVlTh79iyOHDmC7Oxs7pjMzExs27YNxsbGiI7+Fd9/74WAgACEhATz2j5x4jj09fWgra2FLVs2IyYmRqz/agUFBVi+fBk8PDwgKyt5t9Djx4+xadNGeHpOlHqO169fx9694Zgw4e+tEEpKSli2bDlCQ0MREREJGxsbjBs3lrfX1c7ODnv2hCEpKQmMMVy7dg27d+9GWVkZcnP/3kf28uVL6OvrQVNTA66uwxAYuBp9+jhw9aGhoXjw4AHmz58vdYxfCtqzRf5fY4yJJUeysrJYsGAhvLy+x6RJNe87cnNzg6+vD8aPH4+4uDisX/9TnT0p+PbtW2hp8SdXRUVFRERE4sGDB4iPj0diYiIWL16M9evX4ezZOGhra2Ps2LHIyMjAqFEjUVZWBmVlZXh5eWHlypUQCoUAqvaEmJmZce126vQNHj16hE2bNqJbt27Izc2Ft7cXtm3bztubIYmCQtUn2uLi4o98BQj57w4ePIBp06Zx7yMjo3j7D3ftCoWT0wCJ+xXF8eeO6tWo6jklMHA1pkyZjE6dOkIgEMDExASjR49GePjfG8ErKyvRvn177tZZ27Ztcf/+fYSEhPD2VPbo0RPx8ReQl5eL0NBdGDt2LE6fjhX7APbmzRuMGDEc+vr6WLJkqcRRP3v2DEOGDEbv3r3h4+MjMSY9PR2ursPg5eUNFxcXrlxDQ4PbkwYAHTp0QG5uLjZs2IDhw0cAAGbOnIlnz3Lg4NAHjDFoa2tj5MhR2LDhJ27Owf+1d99hUVxfH8C/y9KRKr2qCAgIKsUSRMSOilhjTGKJLSJGYxRLjEJsqKhv9GcD7L2BWEiMMWKLGsWGiggoWCKggqiILO28f/A6cdwF0Tcb1N/5PM8+T/bOuXfurNnLmTt3ZgHo6urixImTeP78OY4dO4Zp076Hra0t2rZti/T0dMyc+SMOHvwV6urqij/+DwjPbLH/ajdupKJevXpy5b169YKLiwvmzlV8V+BL/v7+kEqlGDXqa7Rp0wZWVlZK6mnlIFfVpc0GDRpg8ODBWLZsGY4fP47s7GysWVO5JkQikWDmzJm4fz8bV69eQ3p6Bjw9PQEAtrZ2Ve7Py8sLN2/eBFC5vi0nJwdBQT1gZGQIIyNDbNu2DYcOHYKRkSHS0/9eYPz48WMAihfXM1bbAgK64sSJk8KrWbNmwrbk5GRcvHgRgwcPfmM7ZmZmwgzWSw8fPgQA4aTI2NgYW7duQ3Z2Dq5evYakpPPQ0akDO7u/v3fm5uZwcmokasfJyRH37t0Tleno6MDe3h7e3s2xfPlyqKqqYuPGDaKYwsJC9O3bBwCwY8dOaGqKL+UBlTNy3bt3g7OzC6KjYxTOxKelpaFbt67o06cPfvzxxzd+Fq+OFQCgpaWF5ctXICcnF1euXMW1aymwtbWFrq6uaE2oiooK7O3t4e7ujm+++QZBQT2xaFHleqyzZ88iLy8PLVu2EMackydPYvXq1TAyMoRMJntjv94nPLPF/mulpKTg8OHDCA0NVbh95sxZ6NEjsNqZHBUVFXz++eeYP38+NmzYqKyuAgDc3ZtUe2v0S3Z2dtDW1kZh4XNRuVQqhaWlJYDKSyXNmzcX3fH0uitXrsDMrPKs2cPDA6dPnxFtnz17FgoKCoS7pF5KSbkOCwuLKi9xMFabdHV1oaurq3Db+vXrYGtrB39//ze24+3dHOHhYSguLhaSmsTERFhYWIi+D0DleiVLS0uUlpZi3769orscW7RogYwM8d2QGRkZsLGxqXb/FRUVooTj2bNn6Nu3D4gIsbFxqFOnjlydnJwcdO/eDY0aOWPt2rUKLzGmpqYiMLA7evXqJVrgXp1Xx4pXqampCSegcXGx6Ny5M1RUqp7jIapASUnlMXXr1k1uzBk9Ohj29vaYMGHiBzfbxckW+68gk5UgNzcXFRUVePToEY4dO4ZFixaiadOm+OabsQrrtG7dGh06dEBMTLRo6vt1oaGT8PXXo954ea06JSUlSE1NBVB5+S039wGSk5OFs1mgch1EWNgM5Ofnwcio8uwwImIuiopeoFOnTrCxscGTJ08QFbUKhYWF6Nq1KwAgLy8Pe/bsga+vL2QyGbZs2Yz4+Hj8/PPPwv5XrFgOW1s7ODs3QklJKXbs2IEDBw5g06bK9Wg6OjpwcXER9VlfXx9lZWVy5adPn0L79orvkGLsfVVUVIRdu3Zh7NhxCmd7wsPDcf78eezfvx8A0K9fP8yfPw/BwaMQGjoJGRkZ+Omn/8HkyVOE+klJ53D/fjbc3NyQnZ2NiIgIVFQQxo0bJ7Q7enQIOnXqiMjISPTu3RvJycmIiorCjBkzAFTeebhkyU8ICAiAmZk5Hj16hNWrY3D//n0haXv27Bl69eqJZ8+eYevWrSgqKhKeAWhoaAh1dXVkZ2ejW7eusLCwwLx580Rrp4yNjSGVSnH9+nUEBnaHr68vJkyYiNzcv2fuzMzMAABbt26Bmpoa3N2bQEVFBb/88gtiYmJEM2AZGelISkqCt7c3CgoKsGzZMqSkpGDlylVCTGRkJLy8vFCvXj2UlJTg0KFD2L59OxYsiAQAGBgYyC3M19HRgaGhodyY8yHgZIv9Vzh6NBGOjg6QSqXQ19eHi4sLpkyZgq++GlrtGVJ4+I/w8flEdMfR69TU1Kp9XEJNZGdnw9e3tfA+MzMT69atRevWrZGQUJkUubq6wtPTE7GxscIzrHx8WmP16tUIDh6FBw8eQFdXF87Ozti+fTt8fHyE9rZv34YZM6aDiODt3RwJCQnw9PQStpeUlOKHH6YhOzsbmpqacHZ2xq5du+Sed/MmxcXFOHDgAOLi4v4/Hwdj/7q4uDg8f/4cX375pcLtubk5yMrKFN7r6+sjPn4vJk6cgLZt/WBgYIAxY8aIHihcXCzD7NmzkJWVBR0dHXTq1AnR0dGiJMLT0xNbt27FzJkzERm5ANbW1pg2bZqwcF1VVRWpqanYvHkz8vPzYWRkBA8PD/zyyy/Cc6cuXbqEc+fOAYDc4xgOHEiAr68vjhw5gps3b+LmzZtwdRUnK8nJV2BnZ4f4+D14+PAh4uLi5L7DT548Ff47MjISd+/ehVQqhb19QyxfvlxYrwUA5eUVWLZsOTIy0qGmpgZfX1/89tth0Yzf8+fP8d1343H//n1oamrC0dERUVFR6NtX/KDkjwU/Z4uxD8jhw79h8uTJOHv2XLWzbbUlJiYaCQkJwoMUawM/Z4sxpgz8nC3G/kt06NARI0aMwF9//VXbXVFIVVUNkZELa7sbjDH2XuGZLcbYR4VnthhjysAzW4wxxhhj7ylOthhjjDHGlIiTLcYYY4wxJeJkizHGGGNMiTjZYowxxhhTIk62GGOMMcaUiJMtxhhjjDEl4mSLMcYYY0yJONlijDHGGFMiTrYYY4wxxpSo1n6uh4jKJRIJJ3uMsX8UEUEieadf1GCMsSoRUYVEIpG+S91a/W3E2toxY4wxxtg74N9GZIwxxhh733CyxRhjjDGmRJxsMcYYY4wpESdbjDHGGGNKxMkWY4wxxpgScbLFGGOMMaZEnGwxxhhjjCkRJ1uMMcYYY0rEyRZjH5D169ejXbt2td0NhWQyGWxtbZGUlFTbXWGMsfcKJ1vsgzJkyBBIJBJIJBKoqqrC1tYWwcHBePz4sRBTr149IUZbWxuNGzdGVFSUsL28vBzz58+Hs7MztLW1YWhoCC8vLyxdulS0r6dPn2Ls2LGwtLSEhoYGGjZsiJ07d4r60r17d1GdAwcOQFtbG9OmTQMAhIeHC32RSCQwMDCAv78/zpw5I6oXHR0Nf39/GBgYQCKRICsrS+7YS0pK8MMPPyAsLEwoKyoqwvfff4+GDRtCU1MTxsbG8PHxwbZt2xR+fnPnzoVEIsGYMWOEstLSUkyePBnu7u7Q0dGBhYUFPv/8c9y5c0eIycrKEh3Hq6/IyEgAgIaGBkJDQzF58mSF+2bsfZaWlobevXvDwMAA2tra8PDwwPXr16uts3z5cjg7O0NLSwtOTk7YuHGjXMySJUvQqFEjaGlpwdraGiEhISgsLBS2Hz9+HD169ICVlRUkEgnWr18v10Zubi6GDBkCS0tLaGtro0uXLkhPTxfFjBgxAvb29tDS0oKJiQmCgoKq7H9xcTGaNGkCiUSi8ORo8+bNaNq0qTCmDBo0SLT9ypUr8PPzg5aWFqysrDBz5ky8+ms0bdu2VThWuLq6itp50xgbEREBb29v6OnpwcTEBIGBgbh69arCY3rfqdZ2Bxh7Wx06dMCmTZtQVlaGlJQUDB06FAUFBaIEY8aMGQgODkZhYSHWr1+PUaNGwcDAAP3798ePP/6IFStWYNmyZWjevDkKCwtx8eJFUXJRWlqKTp06wdDQEDt37oS1tTXu3bsHDQ2NKvu1adMmDB8+HAsWLMC4ceOEcicnJxw9ehQAkJeXh9mzZyMgIADZ2dnQ1NQEUJk0derUCUFBQRg/frzC9nfv3g1NTU34+fkJZaNGjcIff/yBJUuWoHHjxsjPz8eff/6J/Px8ufpnzpxBTEwM3N3dReVFRUW4cOECpk2bhqZNm+LJkyeYMGECunTpguTkZKiqqsLGxgbZ2dmienv27EFISAj69u0rlH3xxReYOHEirl27JjewMva+yszMhI+PDwYNGoQjR47AwMAAqampqFOnTpV1Vq5cicmTJyMmJgYtWrTA2bNnMWLECBgaGiIwMBAAsHXrVkyaNAmrV6+Gr68vbt26hWHDhqG4uBhr1qwBABQWFqJx48YYNGiQXFIDVP7WZ8+ePaGiooL4+Hjo6+tj8eLF6NChA1JSUqCjowMA8PLywqBBg2BjY4P8/HyEh4ejQ4cOyMrKgpqamqjNiRMnwtraGsnJyXL7W7p0KSIiIhAZGYmWLVvixYsXSEtLE7Y/ffoUHTt2RJs2bXDu3DncuHEDQ4YMgY6ODiZMmAAAiIuLQ0lJiVBHJpPBzc0Nn376qVBWkzH26NGjGD16NLy9vUFEmDFjhnDcRkZGVf+Dvo+IqLZejL21wYMHU7du3URl3333HRkZGQnv7ezsKDIyUhTj4OBAn332GRERNWnShKZNm1btfqKioqh+/fokk8lq1JeffvqJ1NXVaePGjaKYsLAwcnV1FZVduXKFAFBKSopcm+fOnSMAlJmZKbetW7duNH78eFGZvr4+xcTEVHssREQFBQXUoEED+v3338nPz49CQkKqjb927RoBoOTk5CpjOnToQB07dpQr9/f3f+Pny9j7ZMCAAfT555+/VZ1WrVrRt99+Kyr77rvvyMfHR3gfEhJCbdq0EcXMmDFDbkx4SUdHh9atWycqu3HjBgGgS5cuCWXl5eVkYmJS7Xf/8uXLBIBSU1NF5fHx8eTi4kIpKSkEgM6dOydse/z4MWlra9OhQ4eqbHfFihWkq6tLRUVFQtmsWbPI0tKSKioqFNbZvHkzqaio0J07d4Symoyxr3v27BmpqKjQvn37alxHCd4p5+HLiOyDduvWLRw8eFDuzO11mpqaKC0tBQCYm5vj6NGjyM3NrTI+Pj4ePj4++Oabb2Bubg4XFxeEh4cLbbxq+vTpmDp1KuLi4jBw4MBq+1FcXIxNmzbB1NQU9erVe/MBvuLkyZPw8vISlZmbm+PgwYN48uRJtXVHjhyJvn371ni919OnTwEAhoaGCrdnZmbi999/x8iRI+W2NW/eHMeOHavRfhirbRUVFdi/fz9cXFzQpUsXmJiYwNvbGzt27Ki2nkwmE2amX9LS0sLZs2eFcaJ169a4dOmSsGzgzp072LdvH7p27Vrj/slkMgAQ7UtFRQUaGho4efKkwjrPnz/HunXrYGtrKxpn7t27h+DgYGzZsgVaWlpy9Q4dOoTy8nLk5ubCxcUFVlZW6NWrF27duiXEnD59Gr6+vqL6nTt3xv379xUufwCAmJgYBAQEwMbGRih7mzH2pWfPnqGioqLKcem99q5Z2j/wYuytDR48mKRSKeno6JCmpiYBIAC0ePFiIebVma3S0lJat24dAaAVK1YQUeWsjbOzM0kkEnJxcaFhw4ZRbGys6KzMycmJNDQ06KuvvqKkpCTavXs3mZmZ0YQJE0R9UVdXJwB04MABhf0NCwsjFRUV0tHRIR0dHZJIJGRkZERHjhxRGF/VzNbjx48JgFy9Y8eOkbW1NamqqlKzZs0oJCRE7qw0OjqaPDw8hDPIN81syWQy+uSTTygwMLDKmKlTp5KJiQmVlJTIbVuyZAlZW1tXWZex90l2djYBIG1tbVq0aBFdvHiRFi1aRFKplPbv319lvalTp5KpqSmdPXuWKioq6Ny5c2RmZkYA6P79+0LcsmXLSE1NjVRVVQkADRw4sMoZIEUzWyUlJWRnZ0e9e/emvLw8kslkNG/ePAJAnTp1EsUuX76cdHR0CAA5OTlRenq6sK2srIzatGlDCxcuJCKizMxMuZmtiIgIUlNTIycnJ/rll1/ozz//pG7dupGtrS09f/6ciIg6duxIX331lWi/t2/fJgB06tQpuWN6OTMXHx8vKq/JGPu6fv36UdOmTamsrKzKmH/BO+U8nGyxD8rgwYPJ39+f0tPTKTk5mb755hvq2rWr6MtnZ2dH6urqpKOjQ6qqqqStrU2hoaFUXl4uxJSXl9PZs2dp8eLF1LNnT5JKpRQQECDEODg4kI2NjajdqKgo0tbWFgbKwYMHk4eHB9nb25O3tzc9fvxYrr9hYWHk4OBA6enplJ6eThcuXKDJkyeTrq4unT9/Xi6+qmTr/v37VQ5mJSUldPz4cYqIiKCOHTsSABo5ciQREaWmppKxsTFdv35diK8u2SotLaV+/fqRi4sLPXr0qMoYCwsLCg0NVbg9Ojqa6tatq3AbY7Vt8+bNwsmPjo4OHT16lADQgAEDRHEDBgygLl26VNlOUVERffXVV6SqqkpSqZQsLS1p0qRJBIByc3OJiOjo0aNkZmZGMTExlJycTHFxcWRjY0PTp09X2KaiZIuIKCkpiZo0aUIASCqVUufOnSkgIIACAgJEcQUFBZSWlkbHjh2jwMBAatq0qZAkzZw5k9q3by+MX4qSrTlz5hAA+vXXX0Vtampq0vbt24moMtkaOnSoaL9ZWVkEgE6fPi3X94kTJ5KFhQWVlpaKymsyxr5q/PjxZGFhQTdv3lT42f2LONliHz9Fa7batm1LYWFhwns7OzuaMmUKpaen019//VXlWeSrNm3aRAAoMTGRiIjatGlD7du3F8UcP36cANCDBw9Efbl37x45OjqSp6cn5efni+ooWrNFVHlW9+WXX8qVV5VsyWQykkgklJCQ8MZjmTVrltDGy1k9qVQqvACQRCIhqVRKxcXFQr3S0lLq27cvOTk5UXZ2dpXtx8XFEQC6ceOGwu3z5s2jRo0avbGfjNWGp0+fCic/6enpVFBQQKqqqjRr1ixR3MyZM8nFxeWN7ZWUlNDdu3eprKxMWM/08qStdevWcuu6Nm3aRBoaGnLJB1HVydZLBQUFwvjTvHlzGj16dJWxMpmMtLW1hXWkfn5+pKKiIjcWSKVSYb3a2rVrCQDdvXtX1FaDBg1owYIFREQ0cOBA6tq1q2j72bNnCQDdunVLrg8mJib0/fffy/WvJmPsS99++y2Zm5uLThpr0TvlPLxmi33wwsLCMH/+fNy/f18oq1u3Lho2bAhLS0tIJJI3tuHi4gIAwi3ZPj4+yMjIQEVFhRCTlpYGbW1tGBsbi+paWVnh6NGjeP78Odq3b4+8vLw37k8qlaKoqKhGxwcA6urqcHFxQUpKylsdS8+ePXHlyhVcunRJeHl5eeGzzz7DpUuXoK6uDqDyzqD+/fsjOTkZiYmJMDc3r7L9mJgY+Pn5wdHRUeH2q1evwsPDo8bHxti/SVdXFw0bNhRe+vr68Pb2xo0bN0RxaWlpsLOze2N7ampqsLa2hlQqxfbt29G9e3eoqFT+aS0qKoJUKhXFS6XSypmOd6Cvrw8TExOkp6cjKSkJQUFBVca+/CP/cs3XunXrcPnyZWEc+PnnnwEAW7Zswfz58wFUjnsARJ9FYWEhsrOzhc+iVatWOHHiBIqLi4WY3377DZaWlnLrUPfs2YNHjx5h2LBhcv2r6Rg7btw4bN26FUeOHEGjRo1q9Dm9l941S/sHXoy9NUUzW0REnp6eFBwcTESK70Z8VZ8+fWjx4sV05swZysrKosTERGrZsiWZmppSXl4eERHduXOHdHV1acyYMZSamkoHDx4kKysrmjhxYpV9ycnJIVdXV3J3d6eHDx8SUeXM1suZouzsbEpLSxNmnjZs2CDUzc7OposXL9KWLVsIACUkJNDFixeF/hBV3ukUFBQkOhY/Pz9atWoVJSUlUWZmJiUkJJCTkxM5OTlVua7h9cuIpaWlFBQURJaWlnT+/Hmhr9nZ2aI7jogq12aoqKjQ5s2bq/x87ezs5O7KZOx9tmfPHlJTU6OoqChKT0+n6OhoUlVVFa3FHDhwIA0cOFB4f+PGDdq4cSOlpaXRn3/+Sf379ycjIyPRrHRYWBjp6urStm3b6NatW3To0CGyt7en3r17CzHPnj2jixcv0sWLF0lLS4t+/PFHunjxIt2+fVuI2blzJx05coRu3rxJ8fHxwhqul9LT02nevHmUlJREt2/fpj/++IMCAwPJwMCgyllqRZcRiYiCgoLI1dWVTp48SdeuXaO+ffuSnZ2dcDmyoKCAzMzMqH///nTlyhWKjY0lXV1dYS3Yq9q3b08dOnRQuP+ajLGjR48mXV1d+v3330Xj0rNnzxS2+S/hy4js41dVsrVlyxZSV1enrKysNyZb0dHR1L59ezI1NSV1dXWytram/v3709WrV0Vxp0+fplatWpGmpibVq1ePpk+fLrpNWVFfHjx4QO7u7tS4cWPKzc2lsLAwYRE//m8RrpubG61cuVJU7/W4l69XLylcv36dNDQ0RAnY3LlzycfHh+rWrUsaGhpkZ2dHw4cPF91i/brXk62Xg+6b9k9Uedu6oaEhvXjxQmHbp06dIgMDA7kkjbH33bp168jBwYE0NTXJzc2Ntm7dKtru5+dHfn5+wvuUlBRq2rQpaWlpkZ6eHgUFBck9ZqG0tJTCw8OpYcOGpKmpSdbW1hQcHCxabpCYmKjwuzd48GAh5uVNJ2pqamRra0s//PCDaCy6c+cOdenShUxMTEhNTY2sra3p888/r/ayW1XJ1tOnT2nYsGFkaGhIBgYG1L17d8rIyBDFJCcnk6+vL2loaJC5uTmFh4fLLde4efMmSSQS2rFjR5V9eNMYW9W49OqykVrwTjmPhN5xOvMfUGs7ZuxD9dlnn8HV1RXTp0+v7a4o1K9fPzRr1gzff/99bXeFMcaU4c3rUhTgNVuMfUAWLFgAPT292u6GQjKZDE2aNKnyCfiMMfbfime2GGOMMcZqhme2GGOMMcbeN5xsMcYYY4wpESdbjDHGGGNKxMkWY4wxxpgScbLFGGOMMaZEnGwxxhhjjCkRJ1uMMcYYY0rEyRZjjDHGmBJxssUYY4wxpkScbDHGGGOMKVGtJVtEVFFb+2aMfbxq8SfIGGMfsf9P3lKrv4349Omz2to3Y+wjpaenCx5bGGP/ND09XYB/G5Exxhhj7P3DyRZjjDHGmBJxssUYY4wxpkScbDHGGGOMKREnW4wxxhhjSsTJFmOMMcaYEnGyxRhjjDGmRJxsMcYYY4wpESdbjH2EIiLmIiRk9L++34MHf0Hr1j6oqOAfiGCMsZc42WIfleDgUdDX15N7tW/fDgDg5tYYS5cuFeK7deuqML6goECu7bFjx0JfX09U/2WbitoICwsDANy+fVtUbmJiDA+PZnLtRETMFWIMDQ3g4uKMMWPG4NGjR0JMZGQkOnXqCAsLc+jr6yn8DB4+fIjly5dj4sRQAFDYt1dfwcGjhLqHDx9Ghw7tYW5uBltbGwQGBoraPn/+PHr06AFbW1th+/nzScL2Ll0CoKIixc6dO6r+R2LsPZSRkY4vvvgCtrY2MDc3g6+vL27cuFFtnZiYaHh7e8HMzBSenh7Ytm2raPv169cxcOBAuLu7Q19fDxERc6toJwZubm4wNTVBmzZtcOrUKdH23NxcjBw5Ag4ODWFhYQ4fn09E37Hbt28jJCQE7u7uMDMzhbu7O8LDw/HixQsh5tGjR+jVqyecnBxhYmIMFxdnTJjwHZ48eSLaFxFhxYrl8PLyhImJMRwdHYSx7KWSkhLMmTMbbm5uMDExhqurC1atWimK2bt3L5o394aJiTGaN/fG/v37hW2lpSo6beAAABA4SURBVKWYMWMGPvmkFSwszOHo6IBhw4bi7t27b3XcHxLV2u4AY/+0tm39ER0dLSpTU1OrMv7LL7/EjBniwURfX1/0Pj4+HhcuXICFhYXCNiZPnoxhw4aLynR0dETvY2Pj4ObmBplMhuPHj2PcuLGwsrJCnz59hBgHBwckJPyM8vJyJCdfxpgxY5CdfR+xsXEAgJISGQIDe6B1a18sWrRQYV82bNgADw9P1K9fHwCQlpYubDt48CDGjv1GVKapqQkAOHDgAEaPHo3p06dj5cq2qKiowOXLl4S4wsJC9OnTG507d0Zk5G8AgIULI9GrV29cu3YNurq6//d5foFVq1bhs88GKOwfY++brKwsdOrUCQMGDEBo6H7o6+sjPT1N7jv8qtWrVyMsLAxLly6Fp6cXzp8/j3HjxsLAwBABAQEAgKKiItja2qJHj0DMmjVbYTuxsbGYMmUyFi1ajFatWmH16hj07dsHf/55FjY2NgCAr78eicePC7Bt2zbUrWuMAwcOYOTIkbCysoaPjw/S09NQUVGOxYsXw97eHmlpNzBu3Djk5+cLJ3UqKhJ07x6IGTPCULduXdy6dQsTJ07A2LFjsWHDBqE/06Z9j4MHD2LWrNlwcXHB06dPkZubI+rz0KFD8ddf97BkyRLY29vj4cMHePGiWNh+9uyf+OqrIZg69Xv06NED+/btw+DBg3Do0CF4eXmjqKgIly9fxoQJE+Hu7o6nT59g2rRp6NOnN06dOg1VVdUaHfeHhH8bkX1UgoNHIS8vDzt37lK43c2tMUaMGImxY8cCqJzZcnZ2xsKFi6ps886dO+jUqSP27t2Hvn37iOoravN1t2/fhru7GxITj8LDw0Mo9/Pzg5+fH2bOnAmgcmZr7969OHPmTyEmMjISc+fOwf372dDS0hLK4+PjMXjwIDx58lRufy1btsCQIUMwalSw3Laq6pWXl8Pd3Q2hoZMwZMgQhcdx4cIF+Pu3xeXLyahXrx6Ayj9STZq4i47t7t27aNzYFRcuXIS9vb3CtpSJfxuRva1hw4ZCIpFg9eo1Na7TsWMHeHl5ISJinlA2bdr3SEpKwq+/HpKLb9myBYKCgjB16vei8nbt/OHq2hj/+c9/hLJmzZoiKKgnwsPDAQCWlhZYsCASX375pRDTuLErRo78uspxJyYmBnPmzEZW1u0qj2HVqpVYvHixcPKVnp6Oli1b4NSp03ByclJY5/fff8eQIYNx6dJl1K1bV2HMkCFD8PjxY+zdu1co69GjB4yN62Lt2nUK66SmpqJFi+Y4deo0XF1d3/m4lYl/G5ExJSkrK8OwYUMxcWJolYPP2yIinDlzBmlpN+Dl5VVtrJaWFioqKlBWVlajtvPz85GamopmzTzeHPyKS5cu4t69e9DQUIevry8cHBqiZ88gXL58WYhxcHCAsbExNm3aCJlMBplMhg0bNsDGxgbOzs5CnI2NDUxNTfHHH3+8VR8Yqw0VFRU4ePAgnJwaoXfvXmjQoD7atvVDbGxstfVkshJoaGiKyjQ1NXH+/HmUlpbWaN8lJSW4dOkS2rVrJypv164dzp79+6SrZcuW2LMnDvn5eaioqEBCQgIePXqEtm3bVtn2s2fPYGBgUOX27Oxs7N+/XzRDlJCQgHr16uHw4d/g7u4ON7fGGDXqazx8+PCVmANo1swDy5Ytg7NzIzRr1hSTJoWisLBQiDl37qzcMbVv3x5nz56tpr+VJ4Cv9vldjvt9xckW++gcPnwYlpYWoteMGTOqjF+/fr0o9ttvvxW2zZ07F0ZGRhg+fHiV9QFg1qyZcvs8ePAXUUzXrgGwtLSAiYkxOnfuhCFDhqBHjx5VtpmWloY1a1bD09NTuET3Jvfu3QMRwczMrEbxL2VmZgEA5syZgwkTJmDnzl2wsrJCt25dkZ2dDQDQ1dVFQsLPiIuLg7m5GczNzRAXF4v4+HjRrBsAmJtb4M6dqs+oGXtfPHz4EIWFhVi8eBHatWuP+Pi96Nu3H0aMGC73HX5V+/btsXnzJpw/fx5EhAsXLmDjxo0oLS1FXl5ejfadl5eH8vJymJqaispNTU2Rm5srvF+/fgMkEgnq168PExNjjBgxHGvWrIW7u7vCdu/evYv//Gcphg8fIbdt6NCvYG5uhkaNnFCnTh2sWPH3WqusrCzcvXsXsbGxWLlyJaKiopGWlob+/T8VbnrJysrCmTOncfXqFWzatAmRkQtx+PBhBAf/PZOem5sLU1OT147JRHRMryopKcG0adMQEBAAKyurdz7u9xmv2WIfnU8+8cGSJUtEZdWd4fXu3RuTJ08R3uvpVS48P3nyJLZu3YKTJ988QxMSMgYDBw4UlZmbm4ver169Bs7OzigrK8O1a9cwefIkaGtrY/r0vxPBGzduwNLSAuXl5ZDJZGjd2lfuWKpTXFy5IPblOqyaIqocSCdMmIiePXsCAJYsWYqjR49i+/btGD9+PF68eIGQkNFo3rw5Vq9eg4qKcixd+h8MGDAAR48eE61v0dLSFK3hYOx9sXPnDtEJ1cslB127dsWYMWMAAO7u7rh48QJiYmLQpUuAwnYmTZqEBw9y0alTRxARTE1NMWDA51iy5CdIpdK36pNEIr4yRUSistmzZyEvLw979+5D3bp1kZBwAKNGfY2ff/4Fbm5uoroPHjxA79694O/vj5CQELl9RUTMw5QpU5Geno6ZM3/ElClThDGmoqICMpkM0dHRaNjQAQAQHR0NT09PXLhwHl5e3qioqBAuub5c2xoZuRC9e/fCgwcPhMTxTcf0UllZGUaMGIEnT55g+/btom1vc9zvO0622EdHW1vrrdYK6enpKYw/ceI4cnJy4OjoIJSVl5cjLGwGVq5cgevXU4VyIyOjN+7T0tJSiHFyckJWVhbmzJmN0NBJQnJUv3597Nq1G1KpFBYWFtDQ0KjxcQAQ1lAUFBTIJXvVMTOrjG3UqJFQpqqqigYN7HHvXuUdQrt27UJmZiYOHfpN+GOyZs0a2NnZ4sCB/ejf/zOh7uPHj2FsbPxWfWfs3xAQ0BWenn9fvjc2Noaqqqro/32g8jta3aVELS0tLF++Aj/9tAQPHjyAubk51q1bB11d3SrXMr2ubt26kEqlcjM+Dx8+FJKWW7duISoqCidP/iEkGG5ubjh16jSioqKwbNkyoV5ubi4CA7vD2dkF0dExCpMbMzMzmJmZwdHREUZGRujSpTNCQ0NhbW0Nc3MzqKqqCokWANjbN4Sqqiru3r0HLy9vmJubw8LCQnQT0cslFnfv3oWpqSnMzMyQm/vgtWN6JDeDV1ZWhqFDhyIl5RoSEn6GkdHfn9vbHPeHgC8jMlaF4cNH4NSp0zh58g/hZWFhgdGjQ7Bv3/43N/AGUqkUZWVlKCkpEcrU1dVhb2+PevXqvXWiBQD16zeAnp4eUlNT3xz8iqZNm0JDQwPp6X/fpVhRUYGsrEzY2NgCAF68KIJEIoGKyt/DhoqKCiQSiei5WsXFxcjMzESTJk3euv+MKZuuri7s7e2Fl76+Pjw8PET/7wNARkaGcDdgddTU1GBlZQWpVIq4uFh07txZ9B2pjrq6Opo2bYrExERReWJiIpo3bwEAwuMbXp8tk0pVhBlpAMjJyUG3bl3h6OiEtWvXCnf0Vefl91YmkwEAWrRoibKyMty6dUuIyczMRFlZGWxtbYSYnJwc0RqtjIwMAICtbeVY4e3dHImJR147piNo3ry58L60tBRDhgzBtWtXceBAgtzSh5oe94eCZ7bYR0cmK5E7U5RKpW8902JiYgITE/G6AzU1NZiZmcHBwUFUXlj4TG6fmpqaorO//Px85ObmoqysDCkp17Bq1Ur4+rYRLlvWxN27d/H48WPcuXMHAJCcnAwAaNCgAerUqQMVFRX4+bXFmTOnhcuBNaGnp4ehQ4ciImIuLC0tYWdnh+joKBQUFKB///4AAH//dpg+fTq+++47jBo1ChUVFfif/1kMqVSKNm38hLbOnTsHDQ0NtGzZssb7Z6w2jRv3LYYMGYxWrT5BmzZtcOLECcTGxmLr1r+fm/X11yMBAFFRlY+VychIR1JSEry9vVFQUIBly5YhJSUFK1euEuqUlJQIJz7FxcXIzX2A5ORk6OjoCLPcISFj8PXXI+Hp6YmWLVti7do1yMnJwdChQwEAjo6OaNCgASZM+A6zZ8+GoaEREhISkJiYiG3bKi+7ZWdno1u3rrCwsMC8efNEa8aMjY0hlUpx8OAvyM/PR9OmzaCjo4PU1OuYPn06vL29hb74+/ujSZOmGDMmRLjLcurUKfDy8hJuuunXrx8iIxdg9OjRmDp1Kp48eYIpUyYjKKinMF4GBwcjIKALFi1ahMDAQOzfvx8nTpzAr7/+CqByRmvw4EG4cOECtm/fAYlEIoyfenp60NLSqtFxf0g42WIfnaNHE0WX/oDKS3ivXvb7p82fPx/z588XlX366aeIiVktvO/TpzeAysTP3NwcHTt2qnbhviJz584R/QHw9W0NADhwIAG+vr4AKm+7Hj06GHPmzH2rtSOzZs2Gmpo6goNH4cWLF2jSpAn27z8gPFvM0dER27fvwPz589CxYwcAEri7u2H37ljRotbdu3ejX79Poa2t/VbHxlht6d69O5YsWYpFixZiypTJsLe3R1RUFDp37iLE3Lt3T1SnvLwCy5YtR0ZGOtTU1ODr64vffjsMOzs7ISY7O1v4jgKVs0Tr1q1F69atkZDwMwCgT58+yM/Px8KFkcjJyYGzswt27dotzBKpqalh9+7dCAsLR//+/fH8+XM0aNAAK1asEJ7ndeTIEdy8eRM3b96Eq6uLqJ/JyVdgZ2cHDQ1NrF27FmlpaZDJZLCyskL37oEYP368EKuiooKdO3di0qRJ6No1AJqamvD398fcuRHCbF2dOnWwd+8+hIZOhL9/WxgYGKBbt24ID/9RaKdFixZYu3YdZs+ehYiIuahfvz7WrVsPLy9vAMBff/2FhIQEAICfXxtRf1esWIkvvviiRsf9IeHnbDH2EerQoT2GDx/+rz9Y9NGjR/Dy8sTRo8eEZ3H92/g5W4wxZeDnbDHGRH76aUmt/D7h7dtZWLRoca0lWowx9j7imS3G2EeFZ7YYY8rAM1uMMcYYY+8pTrYYY4wxxpSIky3GGGOMMSXiZIsxxhhjTIk42WKMMcYYUyJOthhjjDHGlIiTLcYYY4wxJeJkizHGGGNMiTjZYowxxhhTIk62GGOMMcaUqNZ+roeIciQSiVmt7Jwx9tEiogqJRMInkoyxfxQR5UokEvN3qVubv43IGGOMMfbR47M/xhhjjDEl4mSLMcYYY0yJONlijDHGGFMiTrYYY4wxxpSIky3GGGOMMSXiZIsxxhhjTIk42WKMMcYYUyJOthhjjDHGlIiTLcYYY4wxJeJkizHGGGNMiTjZYowxxhhTIk62GGOMMcaUiJMtxhhjjDEl4mSLMcYYY0yJONlijDHGGFMiTrYYY4wxxpSIky3GGGOMMSXiZIsxxhhjTIk42WKMMcYYUyJOthhjjDHGlIiTLcYYY4wxJeJkizHGGGNMif4Xk8KOUVsj5aEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x495 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#code for extracting the top 10 up and down regulated substrates\n",
    "log2tab=pd.DataFrame(data=df['log2']) # Taking the log2 fold change values\n",
    "log2tab.columns = ['FC'] # renaming the columnn\n",
    "log2table=pd.concat([df1,log2tab], axis=1, join_axes=[log2tab.index]) # table of the substrates and its fold changes\n",
    "\n",
    "a10=log2table.nlargest(10,\"FC\" , keep='first') # The top 10 Upregulated substrates\n",
    "b10=log2table.nsmallest(10,\"FC\", keep='first') # The top 10 Downregulated substrates\n",
    "#print a10\n",
    "\n",
    "#Creating an table function to create table and store the the top 10 up and down regulated substrates \n",
    "def render_table(data, col_width=3.0, row_height=0.625, font_size=14,\n",
    "                     header_color='#40466e', row_colors=['#f1f1f2', 'w'], edge_color='w',\n",
    "                     bbox=[0, 0, 1, 1], header_columns=0,\n",
    "                     ax=None, **kwargs):\n",
    "    if ax is None:\n",
    "        size = (np.array(data.shape[::-1]) + np.array([0, 1])) * np.array([col_width, row_height])\n",
    "        fig, ax = plt.subplots(figsize=size)\n",
    "        ax.axis('off')\n",
    "\n",
    "    mpl_table = ax.table(cellText=data.values, bbox=bbox, colLabels=data.columns)\n",
    "\n",
    "    mpl_table.auto_set_font_size(False)\n",
    "    mpl_table.set_fontsize(font_size)\n",
    "\n",
    "    for k, cell in six.iteritems(mpl_table._cells):\n",
    "        cell.set_edgecolor(edge_color)\n",
    "        if k[0] == 0 or k[1] < header_columns:\n",
    "            cell.set_text_props(weight='bold', color='w')\n",
    "            cell.set_facecolor(header_color)\n",
    "        else:\n",
    "            cell.set_facecolor(row_colors[k[0]%len(row_colors) ])\n",
    "    return ax\n",
    "#Using the function \n",
    "render_table(a10, header_columns=0, col_width=5.0)\n",
    "#plt.savefig('FCtop10.svg', transparent=True) #saving the table as an image\n",
    "render_table(b10, header_columns=0, col_width=5.0)\n",
    "#plt.savefig('FCbottom10.svg', transparent=True) #saving the table as an image"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calculating Relative Activity (KScore)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note: You have to have the file and the correct path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                              Key       Kinase Modification_Site  \\\n",
      "0      E2AK1_HUMAN(S52)eIF2-alpha  E2AK1_HUMAN               S52   \n",
      "1      E2AK1_HUMAN(S49)eIF2-alpha  E2AK1_HUMAN               S49   \n",
      "2           KPCD_HUMAN(S259)HDAC5   KPCD_HUMAN              S259   \n",
      "3      KPCD_HUMAN(S204)PTPRA iso2   KPCD_HUMAN              S204   \n",
      "4         KPCD_HUMAN(S302)hnRNP K   KPCD_HUMAN              S302   \n",
      "5            KPCD_HUMAN(T71)SHOC2   KPCD_HUMAN               T71   \n",
      "6             KPCD_HUMAN(S237)BVR   KPCD_HUMAN              S237   \n",
      "7           KPCD_HUMAN(T1224)MUC1   KPCD_HUMAN             T1224   \n",
      "8            KPCD_HUMAN(S726)ADD1   KPCD_HUMAN              S726   \n",
      "9         KPCD_HUMAN(S370)p47phox   KPCD_HUMAN              S370   \n",
      "10          KPCD_HUMAN(S504)ENOX2   KPCD_HUMAN              S504   \n",
      "11          KPCD_HUMAN(T143)TNNI3   KPCD_HUMAN              T143   \n",
      "12           KPCD_HUMAN(T217)FRA1   KPCD_HUMAN              T217   \n",
      "13          KPCD_HUMAN(S358)BEST1   KPCD_HUMAN              S358   \n",
      "14        KPCD_HUMAN(S473)P70S6KB   KPCD_HUMAN              S473   \n",
      "15        KPCD_HUMAN(S303)p47phox   KPCD_HUMAN              S303   \n",
      "16          KPCD_HUMAN(T231)CARD9   KPCD_HUMAN              T231   \n",
      "17          KPCD_HUMAN(T758)ITGB2   KPCD_HUMAN              T758   \n",
      "18           KPCD_HUMAN(T218)PKCD   KPCD_HUMAN              T218   \n",
      "19        KPCD_HUMAN(S5)L-plastin   KPCD_HUMAN                S5   \n",
      "20          KPCD_HUMAN(S162)TRPV4   KPCD_HUMAN              S162   \n",
      "21         KPCD_HUMAN(S349)SQSTM1   KPCD_HUMAN              S349   \n",
      "22              KPCD_HUMAN(S74)K8   KPCD_HUMAN               S74   \n",
      "23          KPCD_HUMAN(T246)GAPDH   KPCD_HUMAN              T246   \n",
      "24      KPCD_HUMAN(S286)NRG1 iso6   KPCD_HUMAN              S286   \n",
      "25        KPCD_HUMAN(S328)p47phox   KPCD_HUMAN              S328   \n",
      "26            KPCD_HUMAN(S31)DAP3   KPCD_HUMAN               S31   \n",
      "27          KPCD_HUMAN(S727)STAT1   KPCD_HUMAN              S727   \n",
      "28           KPCD_HUMAN(S503)PKCD   KPCD_HUMAN              S503   \n",
      "29             KPCD_HUMAN(S235)S6   KPCD_HUMAN              S235   \n",
      "...                           ...          ...               ...   \n",
      "10413      IRAK4_HUMAN(T352)IRAK4  IRAK4_HUMAN              T352   \n",
      "10414       IRAK4_HUMAN(S70)PELI1  IRAK4_HUMAN               S70   \n",
      "10415    IRAK4_HUMAN(S288)p47phox  IRAK4_HUMAN              S288   \n",
      "10416    IRAK4_HUMAN(T153)p47phox  IRAK4_HUMAN              T153   \n",
      "10417      TNIK_HUMAN(S177)TCF7L2   TNIK_HUMAN              S177   \n",
      "10418   TTBK1_HUMAN(S202)Tau iso8  TTBK1_HUMAN              S202   \n",
      "10419   TTBK1_HUMAN(S199)Tau iso8  TTBK1_HUMAN              S199   \n",
      "10420   TTBK1_HUMAN(S198)Tau iso8  TTBK1_HUMAN              S198   \n",
      "10421   TTBK1_HUMAN(T427)Tau iso8  TTBK1_HUMAN              T427   \n",
      "10422   TTBK1_HUMAN(Y197)Tau iso8  TTBK1_HUMAN              Y197   \n",
      "10423   TTBK1_HUMAN(S422)Tau iso8  TTBK1_HUMAN              S422   \n",
      "10424   TTBK1_HUMAN(S416)Tau iso8  TTBK1_HUMAN              S416   \n",
      "10425        M3K20_HUMAN(T162)ZAK  M3K20_HUMAN              T162   \n",
      "10426        M3K20_HUMAN(S165)ZAK  M3K20_HUMAN              S165   \n",
      "10427        M3K20_HUMAN(T68)Chk2  M3K20_HUMAN               T68   \n",
      "10428          M3K20_HUMAN(S28)H3  M3K20_HUMAN               S28   \n",
      "10429        M3K20_HUMAN(T161)ZAK  M3K20_HUMAN              T161   \n",
      "10430      M3K4_HUMAN(T1494)MEKK4   M3K4_HUMAN             T1494   \n",
      "10431   NUAK1_HUMAN(S356)Tau iso8  NUAK1_HUMAN              S356   \n",
      "10432      NUAK1_HUMAN(S472)MYPT1  NUAK1_HUMAN              S472   \n",
      "10433   NUAK1_HUMAN(S262)Tau iso8  NUAK1_HUMAN              S262   \n",
      "10434      NUAK1_HUMAN(S257)CASP6  NUAK1_HUMAN              S257   \n",
      "10435      NUAK1_HUMAN(S445)MYPT1  NUAK1_HUMAN              S445   \n",
      "10436        NUAK1_HUMAN(S392)p53  NUAK1_HUMAN              S392   \n",
      "10437         NUAK1_HUMAN(S15)p53  NUAK1_HUMAN               S15   \n",
      "10438      NUAK1_HUMAN(S910)MYPT1  NUAK1_HUMAN              S910   \n",
      "10439      NUAK1_HUMAN(S464)LATS1  NUAK1_HUMAN              S464   \n",
      "10440      ULK2_HUMAN(S846)SEC16A   ULK2_HUMAN              S846   \n",
      "10441      ULK2_HUMAN(S472)DENND3   ULK2_HUMAN              S472   \n",
      "10442      ULK2_HUMAN(S490)DENND3   ULK2_HUMAN              S490   \n",
      "\n",
      "         Neighbour_Seq      Search_key   Substrate Substrate_Gene  \\\n",
      "0      MILLsELsRRRIRsI     EIF2S1(S52)  eIF2-alpha         EIF2S1   \n",
      "1      IEGMILLsELsRRRI     EIF2S1(S49)  eIF2-alpha         EIF2S1   \n",
      "2      FPLRkTAsEPNLKVR     HDAC5(S259)       HDAC5          HDAC5   \n",
      "3      PLLARSPsTNRKYPP     PTPRA(S204)  PTPRA iso2          PTPRA   \n",
      "4      GrGGrGGsrArNLPL    HNRNPK(S302)     hnRNP K         HNRNPK   \n",
      "5      VAFSVDNtIKRPNPA      SHOC2(T71)       SHOC2          SHOC2   \n",
      "6      sFHFksGsLENVPNV     BLVRA(S237)         BVR          BLVRA   \n",
      "7      RyVPPsstDRsPyEK     MUC1(T1224)        MUC1           MUC1   \n",
      "8      KKKFRtPsFLKKsKK      ADD1(S726)        ADD1           ADD1   \n",
      "9      PAVPPRPsADLILNR      NCF1(S370)     p47phox           NCF1   \n",
      "10     ENLKEKEsCASRLCA     ENOX2(S504)       ENOX2          ENOX2   \n",
      "11     RGKFKRPtLRRVRIs     TNNI3(T143)       TNNI3          TNNI3   \n",
      "12     LEPEALHtPTLMTtP     FOSL1(T217)        FRA1          FOSL1   \n",
      "13     SAQFRRAsFMGSTFN     BEST1(S358)       BEST1          BEST1   \n",
      "14     PPSGTKKsKRGRGRP   RPS6KB2(S473)     P70S6KB        RPS6KB2   \n",
      "15     RGAPPRRssIRNAHs      NCF1(S303)     p47phox           NCF1   \n",
      "16     CKVERKHtLKLRHAM     CARD9(T231)       CARD9          CARD9   \n",
      "17     NPLFksAtttVMNPk     ITGB2(T758)       ITGB2          ITGB2   \n",
      "18     TAANSRDtIFQkERF     PRKCD(T218)        PKCD          PRKCD   \n",
      "19     ___MARGsVsDEEMM        LCP1(S5)   L-plastin           LCP1   \n",
      "20     FDIVSRGsTADLDGL     TRPV4(S162)       TRPV4          TRPV4   \n",
      "21     sskEVDPstGELQsL    SQSTM1(S349)      SQSTM1         SQSTM1   \n",
      "22     tVNQsLLsPLVLEVD       KRT8(S74)          K8           KRT8   \n",
      "23     NVsVVDLtCRLEkPA     GAPDH(T246)       GAPDH          GAPDH   \n",
      "24     LHDRLRQsLRSERNN      NRG1(S286)   NRG1 iso6           NRG1   \n",
      "25     QDAYRRNsVRFLQQR      NCF1(S328)     p47phox           NCF1   \n",
      "26     MGTQARQsIAAHLDN       DAP3(S31)        DAP3           DAP3   \n",
      "27     TDNLLPMsPEEFDEV     STAT1(S727)       STAT1          STAT1   \n",
      "28     kENIFGEsRAstFCG     PRKCD(S503)        PKCD          PRKCD   \n",
      "29     IAKRRRLssLRAsts      RPS6(S235)          S6           RPS6   \n",
      "...                ...             ...         ...            ...   \n",
      "10413  tsRIVGTtAYMAPEA     IRAK4(T352)       IRAK4          IRAK4   \n",
      "10414  PQAAKAIsNKDQHsI      PELI1(S70)       PELI1          PELI1   \n",
      "10415  QKsGQDVsQAQRQIK      NCF1(S288)     p47phox           NCF1   \n",
      "10416  KSTATDItGPIILQT      NCF1(T153)     p47phox           NCF1   \n",
      "10417  QALkDARsPsPAHIV    TCF7L2(S177)      TCF7L2         TCF7L2   \n",
      "10418  sGyssPGsPGtPGsR      MAPT(S202)    Tau iso8           MAPT   \n",
      "10419  GDRsGyssPGsPGtP      MAPT(S199)    Tau iso8           MAPT   \n",
      "10420  sGDRsGyssPGsPGt      MAPT(S198)    Tau iso8           MAPT   \n",
      "10421  VDsPQLAtLADEVsA      MAPT(T427)    Tau iso8           MAPT   \n",
      "10422  KsGDRsGyssPGsPG      MAPT(Y197)    Tau iso8           MAPT   \n",
      "10423  GsIDMVDsPQLAtLA      MAPT(S422)    Tau iso8           MAPT   \n",
      "10424  sNVsstGsIDMVDsP      MAPT(S416)    Tau iso8           MAPT   \n",
      "10425  sRFHNHttHMsLVGT   MAP3K20(T162)         ZAK        MAP3K20   \n",
      "10426  HNHttHMsLVGTFPW   MAP3K20(S165)         ZAK        MAP3K20   \n",
      "10427  SsLEtVstQELYsIP      CHEK2(T68)        Chk2          CHEK2   \n",
      "10428  ATkAArksAPATGGV   HIST1H3A(S28)          H3       HIST1H3A   \n",
      "10429  AsRFHNHttHMsLVG   MAP3K20(T161)         ZAK        MAP3K20   \n",
      "10430  KLKNNAQtMPGEVNS   MAP3K4(T1494)       MEKK4         MAP3K4   \n",
      "10431  RVQskIGsLDNItHV      MAPT(S356)    Tau iso8           MAPT   \n",
      "10432  AGVTRsAssPRLsss  PPP1R12A(S472)       MYPT1       PPP1R12A   \n",
      "10433  NVKsKIGstENLkHQ      MAPT(S262)    Tau iso8           MAPT   \n",
      "10434  TLVNRKVsQRRVDFc     CASP6(S257)       CASP6          CASP6   \n",
      "10435  LGLRktGsyGALAEI  PPP1R12A(S445)       MYPT1       PPP1R12A   \n",
      "10436  FktEGPDsD______      TP53(S392)         p53           TP53   \n",
      "10437  PsVEPPLsQEtFsDL       TP53(S15)         p53           TP53   \n",
      "10438  sLLGRsGsysyLEER  PPP1R12A(S910)       MYPT1       PPP1R12A   \n",
      "10439  NIPVRsNsFNNPLGN     LATS1(S464)       LATS1          LATS1   \n",
      "10440  LAQPINFsVSLSNSH    SEC16A(S846)      SEC16A         SEC16A   \n",
      "10441  THRRMVVsMPNLQDI    DENND3(S472)      DENND3         DENND3   \n",
      "10442  ELAPRNSsLRLtDTA    DENND3(S490)      DENND3         DENND3   \n",
      "\n",
      "      Substrate_Num                                Uniprot_link  \n",
      "0            P05198    www.uniprot.org/uniprot/P05198/protvista  \n",
      "1            P05198    www.uniprot.org/uniprot/P05198/protvista  \n",
      "2            Q9UQL6    www.uniprot.org/uniprot/Q9UQL6/protvista  \n",
      "3          P18433-2  www.uniprot.org/uniprot/P18433-2/protvista  \n",
      "4            P61978    www.uniprot.org/uniprot/P61978/protvista  \n",
      "5            Q9UQ13    www.uniprot.org/uniprot/Q9UQ13/protvista  \n",
      "6            P53004    www.uniprot.org/uniprot/P53004/protvista  \n",
      "7            P15941    www.uniprot.org/uniprot/P15941/protvista  \n",
      "8            P35611    www.uniprot.org/uniprot/P35611/protvista  \n",
      "9            P14598    www.uniprot.org/uniprot/P14598/protvista  \n",
      "10           Q16206    www.uniprot.org/uniprot/Q16206/protvista  \n",
      "11           P19429    www.uniprot.org/uniprot/P19429/protvista  \n",
      "12           P15407    www.uniprot.org/uniprot/P15407/protvista  \n",
      "13           O76090    www.uniprot.org/uniprot/O76090/protvista  \n",
      "14           Q9UBS0    www.uniprot.org/uniprot/Q9UBS0/protvista  \n",
      "15           P14598    www.uniprot.org/uniprot/P14598/protvista  \n",
      "16           Q9H257    www.uniprot.org/uniprot/Q9H257/protvista  \n",
      "17           P05107    www.uniprot.org/uniprot/P05107/protvista  \n",
      "18           Q05655    www.uniprot.org/uniprot/Q05655/protvista  \n",
      "19           P13796    www.uniprot.org/uniprot/P13796/protvista  \n",
      "20           Q9HBA0    www.uniprot.org/uniprot/Q9HBA0/protvista  \n",
      "21           Q13501    www.uniprot.org/uniprot/Q13501/protvista  \n",
      "22           P05787    www.uniprot.org/uniprot/P05787/protvista  \n",
      "23           P04406    www.uniprot.org/uniprot/P04406/protvista  \n",
      "24         Q02297-6  www.uniprot.org/uniprot/Q02297-6/protvista  \n",
      "25           P14598    www.uniprot.org/uniprot/P14598/protvista  \n",
      "26           P51398    www.uniprot.org/uniprot/P51398/protvista  \n",
      "27           P42224    www.uniprot.org/uniprot/P42224/protvista  \n",
      "28           Q05655    www.uniprot.org/uniprot/Q05655/protvista  \n",
      "29           P62753    www.uniprot.org/uniprot/P62753/protvista  \n",
      "...             ...                                         ...  \n",
      "10413        Q9NWZ3    www.uniprot.org/uniprot/Q9NWZ3/protvista  \n",
      "10414        Q96FA3    www.uniprot.org/uniprot/Q96FA3/protvista  \n",
      "10415        P14598    www.uniprot.org/uniprot/P14598/protvista  \n",
      "10416        P14598    www.uniprot.org/uniprot/P14598/protvista  \n",
      "10417        Q9NQB0    www.uniprot.org/uniprot/Q9NQB0/protvista  \n",
      "10418      P10636-8  www.uniprot.org/uniprot/P10636-8/protvista  \n",
      "10419      P10636-8  www.uniprot.org/uniprot/P10636-8/protvista  \n",
      "10420      P10636-8  www.uniprot.org/uniprot/P10636-8/protvista  \n",
      "10421      P10636-8  www.uniprot.org/uniprot/P10636-8/protvista  \n",
      "10422      P10636-8  www.uniprot.org/uniprot/P10636-8/protvista  \n",
      "10423      P10636-8  www.uniprot.org/uniprot/P10636-8/protvista  \n",
      "10424      P10636-8  www.uniprot.org/uniprot/P10636-8/protvista  \n",
      "10425        Q9NYL2    www.uniprot.org/uniprot/Q9NYL2/protvista  \n",
      "10426        Q9NYL2    www.uniprot.org/uniprot/Q9NYL2/protvista  \n",
      "10427        O96017    www.uniprot.org/uniprot/O96017/protvista  \n",
      "10428        P68431    www.uniprot.org/uniprot/P68431/protvista  \n",
      "10429        Q9NYL2    www.uniprot.org/uniprot/Q9NYL2/protvista  \n",
      "10430        Q9Y6R4    www.uniprot.org/uniprot/Q9Y6R4/protvista  \n",
      "10431      P10636-8  www.uniprot.org/uniprot/P10636-8/protvista  \n",
      "10432        O14974    www.uniprot.org/uniprot/O14974/protvista  \n",
      "10433      P10636-8  www.uniprot.org/uniprot/P10636-8/protvista  \n",
      "10434        P55212    www.uniprot.org/uniprot/P55212/protvista  \n",
      "10435        O14974    www.uniprot.org/uniprot/O14974/protvista  \n",
      "10436        P04637    www.uniprot.org/uniprot/P04637/protvista  \n",
      "10437        P04637    www.uniprot.org/uniprot/P04637/protvista  \n",
      "10438        O14974    www.uniprot.org/uniprot/O14974/protvista  \n",
      "10439        O95835    www.uniprot.org/uniprot/O95835/protvista  \n",
      "10440        O15027    www.uniprot.org/uniprot/O15027/protvista  \n",
      "10441        A2RUS2    www.uniprot.org/uniprot/A2RUS2/protvista  \n",
      "10442        A2RUS2    www.uniprot.org/uniprot/A2RUS2/protvista  \n",
      "\n",
      "[10443 rows x 9 columns]\n"
     ]
    }
   ],
   "source": [
    "#Read our (editied) database using information Phosphosite plus\n",
    "# You have to have the file and the correct path\n",
    "dp=pd.read_csv(\"Phosphosites_basedOn_PSPlusdata_28Jan.csv\",delimiter = ',' , index_col=0) \n",
    "#print dp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "sig=df5[(df5['AZ20_p-value'] < 0.05)] #extracting significant phosphosites\n",
    "sigp=pd.concat([sig,df1], axis=1, join_axes=[sig.index]) # substrate and p-values\n",
    "dfp=sigp[\"Substrate\"] #Getting substrate name for matching"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "match=list(dfp) # list of the phoshosites\n",
    "match2d=pd.concat([dfp,fcut], axis=1, join_axes=[dfp.index])# made a table of the phosphosites and their fold change\n",
    "match2d=match2d.replace([np.inf,-np.inf,np.nan]) # removing NaN values\n",
    "matchds=match2d.rename(index=str, columns={\"Substrate\": \"Search_key\"}) # renamed the substrate to search key for the matching"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['ABCF1(S109)', 'ACACA(S80)', 'ADD2(S613)', 'AKIRIN2(S18)', 'AKT1S1(S183)', 'ANAPC1(S355)', 'ANAPC1(S377)', 'ARHGEF6(S225)', 'ARHGEF7(S518)', 'ATF2(T71)', 'BAD(S118)', 'BLVRA(S230)', 'BRCA1(S1189)', 'BRCA1(S1191)', 'BRCA1(S1497)', 'C1orf198(S37)', 'CAD(S1859)', 'CARHSP1(S52)', 'CBX5(S92)', 'CCDC6(S240)', 'CCT2(S260)', 'CD4(S440)', 'CD44(S706)', 'CDC20(S41)', 'CDC20(T157)', 'CDCA5(S83)', 'CDCA8(S219)', 'CDK12(T893)', 'CDK16(S153)', 'CELF1(S28)', 'CGN(S131)', 'CRMP1(S522)', 'CRMP1(T509)', 'CTNND1(S879)', 'CUEDC2(S110)', 'DDX24(S82)', 'DDX3Y(S592)', 'DLGAP5(S725)', 'DNMT1(S127)', 'DNMT1(S714)', 'DPYSL2(T509)', 'EDC3(S161)', 'EEF2K(S72)', 'EEF2K(S74)', 'EIF4A3(T163)', 'EIF4B(S406)', 'EIF4EBP1(S65)', 'EIF4EBP1(T46)', 'EIF4EBP1(T70)', 'EIF4G1(S1231)', 'ELAVL1(S202)', 'EPRS(S886)', 'EZH2(T367)', 'EZR(T567)', 'F11R(S284)', 'FAF1(S582)', 'GAPVD1(S950)', 'GBF1(T1337)', 'GINS2(S182)', 'GORASP2(T222)', 'GSK3B(Y216)', 'GTF2F1(S385)', 'GTF2F1(T389)', 'GTF2I(S784)', 'HNRNPA1(S199)', 'HNRNPU(S59)', 'HSPB1(S15)', 'HSPB1(S82)', 'HSPB8(S57)', 'HTT(S1179)', 'HTT(S1199)', 'KAT5(S90)', 'KIF11(T926)', 'KLF3(S101)', 'KLF3(S92)', 'LARP1(S766)', 'LMNB1(S393)', 'LMNB2(S37)', 'LRCH3(S419)', 'MAP7(S209)', 'MAPK1(Y187)', 'MAPK3(T207)', 'MAPK3(Y204)', 'MARCKS(S163)', 'MARCKS(S167)', 'MDC1(S299)', 'MDC1(T301)', 'METTL1(S27)', 'MFAP1(S116)', 'NCL(T121)', 'NDC80(S69)', 'NEK6(S206)', 'NELFE(S131)', 'NFATC1(S245)', 'NIFK(S230)', 'NIFK(T234)', 'NIFK(T238)', 'NINL(S585)', 'NOLC1(T607)', 'NOLC1(T610)', 'NUMA1(S1887)', 'NUMA1(S1969)', 'NUMA1(T2106)', 'NUP153(S529)', 'NUP50(S221)', 'OGFR(S378)', 'ORC2(T116)', 'ORC2(T226)', 'PAICS(S27)', 'PATL1(S179)', 'PAWR(S231)', 'PDCD4(S457)', 'PDPK1(S241)', 'PGR(S162)', 'PML(S36)', 'PPME1(S15)', 'PPP1CA(T320)', 'PPP1R12A(T696)', 'PPP2R5D(S573)', 'PRC1(T481)', 'PRKDC(S2612)', 'PROSER2(S43)', 'PTPN6(Y536)', 'RAD18(S99)', 'RAN(S135)', 'RB1(T821)', 'RBL2(S662)', 'RIF1(S2205)', 'RPS27L(S27)', 'RPS6(S235)', 'RPS6(S236)', 'SLAIN2(S48)', 'SLC9A3R2(S303)', 'SRC(S17)', 'SSH3(S37)', 'STAT5A(S780)', 'STMN1(S38)', 'TCF3(S359)', 'TINF2(S295)', 'TMPO(S424)', 'TNKS1BP1(S691)', 'TOR1AIP1(S143)', 'TTK(S281)', 'ULK1(S638)', 'VCPIP1(T761)', 'ZBTB11(S511)', 'ZC3H11A(T321)', 'ZFP36L1(S334)']\n"
     ]
    }
   ],
   "source": [
    "#Performing the matching\n",
    "phos = {}\n",
    "listformatch = []\n",
    "kinase = list(dp.Kinase) #list of kinases from our read database\n",
    "match = list(dfp)  # list of significant (p-value) phosphosites\n",
    "searchkey=list(dp.Search_key) # list of search key from our read database\n",
    "\n",
    "# made a dictionary of the kinases and phosphosites match from the phosphosite plus database\n",
    "for i in range(0, len(kinase)):\n",
    "    if kinase[i] not in phos.keys():\n",
    "        phos[kinase[i]] = [searchkey[i]]\n",
    "    else:\n",
    "        phos[kinase[i]].append(searchkey[i])\n",
    "\n",
    "# print phos\n",
    "\n",
    "# made a list of phoshosites from the phosphosite plus database to use for matching\n",
    "for x in phos.values():\n",
    "    x = list(x)\n",
    "    listformatch.extend(x)\n",
    "# print listformatch\n",
    "\n",
    "# list of the matches\n",
    "matchexist = []\n",
    "for y in match:\n",
    "    if y in listformatch:\n",
    "        matchexist.append(y)\n",
    "\n",
    "    else:\n",
    "        pass\n",
    "print matchexist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Getting rid of all column except search key and kinase\n",
    "z=dp.drop(['Key', 'Substrate','Substrate_Gene','Substrate_Num','Uniprot_link','Modification_Site','Neighbour_Seq'], axis=1)\n",
    "\n",
    "wsz=z[z[\"Search_key\"].isin(matchexist)] # isin function to get the kinase which matched our list of matches\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'KPCD_HUMAN': [-2.767835556728845, 1.1605820198040362, -2.6640066292721247], 'STK26_HUMAN': [-1.8705473492389508], 'MK14_HUMAN': [1.2319609309410757, -2.3905986189611195], 'UHMK1_HUMAN': [0.35174868849111096], 'MK03_HUMAN': [1.1605820198040362, -1.9977600629033834, 1.2319609309410757, 1.0599046065351994, 0.9678298914119913, -0.9096125607913198, 1.0085506851101669, 1.316614906906406, 0.35174868849111096, 0.672858501851916, -0.6920495059981514], 'KPCB_HUMAN': [0.35174868849111096], 'PDPK1_HUMAN': [0.5398893314922536], 'LMTK2_HUMAN': [0.5035530053056071], 'DYRK2_HUMAN': [-1.9977600629033834, 0.9113847193507547], 'M4K4_HUMAN': [-1.8705473492389508], 'NEK9_HUMAN': [-3.0372525499175156], 'MELK_HUMAN': [-0.31906894934820756], 'INSR_HUMAN': [-2.586157526818021], 'AKT1_HUMAN': [-2.9056010492809605, 0.49037202198038343, 0.5035530053056071, -0.11966015336377424, 1.0208824303746504, -3.41346599487291, -0.66323820808457, -1.8839331879359271, -0.6529381571339258, -1.0928084965137668], 'KPCG_HUMAN': [0.5073848875704527], 'ARAF_HUMAN': [-0.5372450278740717, 0.703793678105434], 'CHK1_HUMAN': [3.3528555195791374, 0.8495053946592236, 1.1864574574371596, 0.4413465817257819, -1.267112371433989, 0.6024648400190756], 'KS6B1_HUMAN': [-2.767835556728845, -2.6640066292721247, -0.44917134978977763, 1.0208824303746504], 'KGP1_HUMAN': [0.9888704506751471], 'RET_HUMAN': [-0.6920495059981514, -0.5469792453849518], 'STK10_HUMAN': [-1.8705473492389508], 'PLK1_HUMAN': [1.1463934156815472, 0.48481848033746655, 1.060473537814611, 2.0066255458264295], 'AAPK2_HUMAN': [0.9574821189356051], 'LRRK2_HUMAN': [-1.8705473492389508], 'KS6A1_HUMAN': [-2.767835556728845, -2.6640066292721247, -0.11966015336377424, 1.0208824303746504, -3.41346599487291, -0.66323820808457], 'PAK1_HUMAN': [-0.5372450278740717, 0.35174868849111096], 'MK01_HUMAN': [-1.9977600629033834, 1.2319609309410757, 1.0599046065351994, 0.9678298914119913, 1.0085506851101669, 1.316614906906406, 0.672858501851916, -1.2297092614391762, -1.9650856090093676, -2.555540221243428], 'MK08_HUMAN': [1.2319609309410757], 'MP2K1_HUMAN': [-0.9096125607913198, -0.6920495059981514, 3.5796260931016475, -0.5469792453849518], 'AAPK1_HUMAN': [0.9574821189356051, 2.9393197015339636, 1.2000807087808074, 0.29066735307065544], 'RAF1_HUMAN': [-0.5372450278740717, 1.8108739057905692], 'BRAF_HUMAN': [-0.5372450278740717, 0.4441764989329139], 'ATR_HUMAN': [0.7609297580147782, 3.7527144168960316], 'MAPK2_HUMAN': [1.080902711058977, 0.49037202198038343], 'KPCE_HUMAN': [-0.5372450278740717], 'AURKB_HUMAN': [0.7405836438486664, -0.33198986509887873, 3.3528555195791374, 0.9635537770383185, 0.9525952162077084, 0.38139900610755517, 0.6608419896056305, -0.39930831038161696, 0.3957801178367598, 0.6721982386931358], 'JAK2_HUMAN': [-0.6920495059981514, -0.5469792453849518], 'AURKA_HUMAN': [1.1565186774147893, 1.6014439709324568, 0.7405836438486664, -0.33198986509887873], 'AKT2_HUMAN': [-1.8705473492389508, -1.8839331879359271], 'KCC2A_HUMAN': [0.4039716043265323], 'KPCD1_HUMAN': [-0.5372450278740717, 0.49037202198038343], 'ROCK2_HUMAN': [1.8108739057905692], 'ROCK1_HUMAN': [1.8108739057905692, -1.8705473492389508], 'HIPK2_HUMAN': [1.316614906906406, -0.6399675989041801, -0.43600479279102033], 'MK13_HUMAN': [0.35174868849111096], 'CDK6_HUMAN': [-0.6775979110872226], 'BUB1_HUMAN': [-3.3974646426885338, 0.7440159626238787], 'CDK5_HUMAN': [0.5035530053056071, 0.3165329664523222, 4.191302330194968, 0.616399985316474, -1.7209841627087834, 0.9113847193507547, 0.887559964410741], 'M3K10_HUMAN': [-1.9650856090093676], 'PRKDC_HUMAN': [2.0066255458264295, 2.0066255458264295, 0.7609297580147782], 'KAPCA_HUMAN': [-0.5372450278740717, 0.49037202198038343, 0.8902042559616937, 1.095179151647506, 0.9701962068120394, -3.9123986666732486, -0.44917134978977763, 0.5122936661964945, -1.5497260749042323], 'GSK3A_HUMAN': [2.466782259294153, 2.466782259294153], 'CDK1_HUMAN': [0.35174868849111096, 0.672858501851916, 0.6652637259324792, 0.46871341903524183, 0.36829577943877206, 0.5035530053056071, 2.594222757960077, 2.466782259294153, 0.4733004915406434, 0.6752228476225867, 0.4353718418908416, 1.1463934156815472, -1.2297092614391762, 0.603024632336574, 0.9635537770383185, 0.3165329664523222, 0.48481848033746655, -1.4467123302710334, 0.6948270079523924, 1.3979850272482108, -1.4784171103383272, 0.8083831946138276, -1.271468667196161, 0.48315370050630363, 0.2739737806538623, 0.6489997394896738, 0.7754677789451224, -1.4784171103383272, 0.45541482775470454], 'MP2K2_HUMAN': [-0.6920495059981514], 'SRC_HUMAN': [-2.586157526818021], 'CDK2_HUMAN': [0.35174868849111096, 0.6652637259324792, 0.5035530053056071, 0.3165329664523222, 0.2739737806538623, 0.7754677789451224, 0.45541482775470454, 0.9585143387569232, 4.191302330194968, 0.23465438404153818, 0.3808378936532237, -0.6775979110872226, -0.366641770236327, 0.9538581857016801, 0.526810517882969, 0.653692065306702, 1.2959121180274953, 0.3926383380908299, 0.561398872359024, 0.8846692049691306, -0.2875107773563062, 0.7365966057149524, 1.6532801129166041], 'MTOR_HUMAN': [1.2000807087808074, -1.9977600629033834, -1.2297092614391762, -2.555540221243428, -8.515211727290438, -4.276493931303037, 0.8915639779427552, -1.4884735213728952, 0.4166893609447867, -3.668670985616549], 'KS6A3_HUMAN': [-2.767835556728845, -2.6640066292721247, 0.5965344505742389], 'KS6B2_HUMAN': [0.49037202198038343], 'No such kinase': [1.0640449838644865, 1.0640449838644865, 1.080902711058977, 0.49037202198038343, 3.5796260931016475], 'PAK4_HUMAN': [1.060473537814611], 'PLK3_HUMAN': [1.2319609309410757], 'ATM_HUMAN': [0.7754677789451224, -1.4784171103383272, 0.7609297580147782], 'ARBK1_HUMAN': [-1.8705473492389508], 'KPCI_HUMAN': [-0.5372450278740717, -1.8705473492389508], 'LYN_HUMAN': [-2.586157526818021], 'CSK21_HUMAN': [2.1693306136925106, -2.73032365791967, 0.6585077143629126, 2.1693306136925106, -2.9056010492809605], 'KPCT_HUMAN': [-1.8705473492389508, 1.30623889914847], 'M3K8_HUMAN': [-1.8705473492389508, -1.2297092614391762], 'CDC7_HUMAN': [0.6652637259324792, 0.7500826492722724], 'KPCA_HUMAN': [1.1605820198040362, -1.8705473492389508, -1.0722237200003342, 0.694764847449213, -0.3930076002054863, 0.6083456316950657, 9.267404072396937], 'MK09_HUMAN': [1.2319609309410757], 'GSK3B_HUMAN': [-1.9977600629033834, -1.2297092614391762, -1.4467123302710334, 3.5796260931016475, -2.2318070078549614, 2.466782259294153, 0.6830028014738841, -2.555540221243428, 2.466782259294153, -2.3905986189611195], 'SGK1_HUMAN': [-0.11966015336377424], 'CDK7_HUMAN': [1.1247139136773827], 'CDK4_HUMAN': [0.2896276026922469], 'LCK_HUMAN': [-2.586157526818021]}\n"
     ]
    }
   ],
   "source": [
    "sff = pd.merge(wsz, matchds)  # Dataframe of the Kinase,Substrate and fold change\n",
    "\n",
    "# made dict for kinase and the log 2 fold change\n",
    "kinasedict = {}\n",
    "kinases = list(sff[\"Kinase\"])\n",
    "foldch = list(sff['AZ20_fold_change'])\n",
    "kinasecount = {}\n",
    "# print kinaseff\n",
    "count = 0\n",
    "for i in range(0, len(sff)):\n",
    "    if kinases[i] not in kinasedict.keys():\n",
    "        kinasedict[kinases[i]] = [foldch[i]]\n",
    "\n",
    "    else:\n",
    "        kinasedict[kinases[i]].append(foldch[i])\n",
    "\n",
    "\n",
    "\n",
    "# number of matches per kinase\n",
    "for key, value in kinasedict.items():\n",
    "    if key in kinasedict:\n",
    "        # print len(value)\n",
    "        kinasecount[key] = (len(value))\n",
    "    else:\n",
    "        pass\n",
    "\n",
    "print kinasedict\n",
    "#print kinasecount"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Creating a dictionary of the kinase and their average log 2 fold change\n",
    "avgDict = {}\n",
    "\n",
    "for k,v in kinasedict.items():\n",
    "    avgDict[k] = sum(v)/ float(len(v))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-2.1082007  -1.55664253 -0.81398202  0.13184923  0.50633958 -1.06633539\n",
      " -1.55664253  0.13184923 -1.48509905  0.67033557 -2.44310053 -2.10036031\n",
      " -2.52258029 -0.10201646  1.2705877  -2.11717028  0.61593183  0.80063102\n",
      " -0.85717268 -1.55664253  1.514063    0.5920831  -1.55664253 -3.0015472\n",
      " -0.29115507 -2.35563057  0.80063102  0.27281223  1.7759035   0.49277008\n",
      " -0.24149759  2.23349078  0.65268238 -0.54360469 -1.55664253 -0.85717268\n",
      "  0.93215247 -2.10036031  0.250101   -0.21667873  1.24048681  2.05267711\n",
      " -0.22355585  0.23717469  0.13184923  0.80063102 -0.65024425 -1.6170796\n",
      "  1.85974894 -1.03692975  2.4590959   0.93893876 -0.66122452  0.27479775\n",
      "  1.79584875  0.171528   -5.52754478  1.34702905  0.71914516 -0.12897131\n",
      "  2.1705549   1.28029765 -0.20909941 -0.78628828  0.24718955 -2.10036031\n",
      " -0.51982511 -0.49467451 -1.85713026  0.56890879 -2.20861661 -1.62847232\n",
      " -0.37783536 -0.22632535 -0.77515857  0.08464988 -2.10036031]\n"
     ]
    }
   ],
   "source": [
    "#Formula for calculating the kinase scores (Kscore)\n",
    "log2r = np.log2(df4b) #log2 fold change for all of the substrates in our dataset\n",
    "FCmean=np.ma.masked_invalid(log2r).sum()/len(log2r) #mean fold changes for all of the substrates in our dataset\n",
    "sd=np.ma.masked_invalid(log2r).std()  #standard deviation of the log2 fold change across all of the substrates in the dataset\n",
    "\n",
    "mvalues=list(kinasecount.values()) #list of total number of  substrates that matched to a specific kinase\n",
    "mS=avgDict.values() # mean log2 fold change of known substrates of the given kinase \n",
    "m=[math.sqrt(x) for x in mvalues] #square root of the total number of  substrates that matched to a specific kinase\n",
    "\n",
    "#Kinase scores (kscore) equation \n",
    "kscore=((mS-FCmean)*(m))/sd \n",
    "    \n",
    "print kscore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Making a Dataframe of Kinase and Kscore\n",
    "ksc = pd.DataFrame(data=kscore, columns=[\"Kscore\"])\n",
    "kinsc = list(kinasedict.keys())\n",
    "ksms = pd.DataFrame(data=kinsc, columns=[\"Kinase\"])\n",
    "final = pd.concat([ksc, ksms], axis=1, join_axes=[ksms.index]) \n",
    "\n",
    "sortedf = final.sort_values(by=\"Kscore\", axis=0)#Sorting the kscore values by value\n",
    "\n",
    "#Plotting the graph of Kscores\n",
    "sortedf.set_index('Kinase').plot.barh(title='Kinase Scores',legend=None)\n",
    "plt.tick_params(labelsize = 15)\n",
    "plt.rcParams['figure.figsize']=(35,35)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x495 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Selecting top 10 up and down regulated kinases\n",
    "top10=sortedf.nlargest(10, 'Kscore', keep='first')\n",
    "bottom10=sortedf.nsmallest(10, 'Kscore', keep='first')\n",
    "\n",
    "#Using render table function and saving it as an image\n",
    "a=render_table(top10, header_columns=0, col_width=5.0)\n",
    "#plt.savefig('KScoretop10.svg', transparent=True)\n",
    "b=render_table(bottom10, header_columns=0, col_width=5.0)\n",
    "#plt.savefig('KScorebottom10.svg', transparent=True)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Kscores of all the dataset's Kinases saved to csv file \n",
    "kscore_file=sortedf.to_csv(\"Kscore_file\", sep=',')\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}