{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Debug Python 3 Porting issues in SalishSeaTools Package"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### `nowcast.figures.plot_map()` PNW Coastline Polygon Plotting Issue\n",
    "\n",
    "Reported by Jie on 2015-10-13"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from importlib import reload\n",
    "\n",
    "import netCDF4 as nc\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.io as sio\n",
    "\n",
    "from salishsea_tools.nowcast import figures\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "bathy = nc.Dataset('../../NEMO-forcing/grid/bathy_meter_SalishSea2.nc')\n",
    "PNW_coastline = sio.loadmat('../../map_data/PNW_coastline.mat')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'salishsea_tools.nowcast.figures' from '/home/doug/Documents/MEOPAR/tools/SalishSeaTools/salishsea_tools/nowcast/figures.py'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reload(figures)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f9690b017b8>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/doug/miniconda3/envs/SalishSeaTools/lib/python3.5/site-packages/matplotlib/collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
      "  if self._edgecolors == str('face'):\n"
     ]
    },
    {
     "data": {
      "image/png": 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WWU3R0dbC2sqUwvmsqVwqPzmzmzOkSx2G/lWXXNkt/siY2D9VthQL/BvRsGoxnrvNQhRF\n9SFEeYe8lHfIq27TrXklvoaEM9XpIJfvvOBrSBjBIaE8efJE3SYkJAQALZlI6UI2mJsYktvagjPX\nH/PwmbeGzCPu95NceQ4Zonk4YWFmmOQz9GxVhVHzdyOXy5HrmTJmTB9mz56NTCbQuLoD7Ueupnvz\nSoRGRHLsoidFixZlzZo19GhRGeMs+t/9jERRZP+Z24yYuxOAu3fv0rZtW4wM9eJt4yUkMjOZbgv8\nK3wNCUehUKCvp42OduKV1O48fsOQmdt4k0i1rF69erF+/XoAqpXOj/tNr3htnh2dqVbQoigSERml\nUb2tYNMJREYp8PLyYt++fYwePZpuzSthamTA0q2n1O1q1apFaGgID+7d4dq2cd+tAPfwmTftRjoR\nEhZBPjs79u7bR4f27Xn0+DE75v9NuWJ5kuwvIZGWSDbAZJISCvBHWfbfKQRBxtItJzXC7bS0tIiK\nikJbS87jQ98ON16+92Xjvou4XXjApy9B8ca7vHUsa3afZ+vhq0REqA5ZtLW1uXjxIuXLq0LzBnSs\nycrtZ5k6dSqOjioXnEWLFjHJ0ZGgoCDkWnLkchnZLU1oXqM47RuWwyaryi1lmtNBNrpeQi6XM2fO\nHEaNGqWW3axGcUZ2r4+v/1dKF8md8h+WhMRPICnAZJIeCjCGK3eeUzBvdk5cfsCYRXuxsbHh3TuV\nbS5mTvtO3mLWuqP4+sdXfAmR1dyIf3s1YvzSfUQpRIYNG4az82a+fPGnRIkSvHv3Tl3/F8DJyYly\n5crRtWtX9PT0CPD35733e8LCVKn7ZYKgzkizevVqLl26xObNmxEEAUtLCz59+pa78NT6keS1SfqE\n90/0h/tTZUt+gBLfxczYgPYNyjFm0V6NeiGVuswiX04rLt1+lqxxtLTk2OfKyr7FA9DR0cJpx1me\nvvZh/nxVhpUNGzbQs2dPAA6uGMyFG0+Zs8ENW1tbRo0axcOHD9VjGRqo4nAbNGiAUqlk27ZtfPz4\nkQEDBnDu3DlAtf3+9MkXExNjAgICkcvl1Om1gHqVi7LasWuKfDYSEhkVaQWYwhRsOoEohZKuXbvi\n4uKSYBvbbGacXDcCHW0tbj18TZvhq9TvDe5cm+Hd6mm07zlxI2evfzug0dHRISIiglw5zHnt/Zki\nRQqTO3cejh49Spcm5Zk6qCWBX0MZPHM7F249TXSuXZpUYOvhqxr3li9fTkBAAOPHj2fL7F5ULikV\nVZdIPyQ3mN+MlnVKoq0lZ+vWrWzYsEF939zEkHkj27Jmcjdqly9IoWYTaTVkhYbyA1i+7TRxf5RC\nwzSjVSIiIqhatSqvvT9TokQJBEHG0aNHGdm9HtMGt0IQBEyMDHCe1ZOnh2fwwHUKc4a3Vvc3yaLP\nc7dZ5MuZFQBLS0sM9HQpXsCWQYMGUbx4cfT19fl34Z6U/ngkJDIU0gowBUjIRlK390KCwuHTp0+J\n9tPT1Y4XigeQzdyIQyuHYGGahamrDrJp/yUACttl5+HzD+p2oihiaWmJn58q+uXmromYJpB+Knac\nL4DLrF5ULpmPQs0mEhmlqodSLL8NB5YPwr7JeBwcitOxY0fGjBlDbmtL1jh2wT5P9u8+c1ohyf4z\n5IJkA/xtsc5qwoUE3F9ieHxwGtqx6vVOX32YDfsuAPDxcxDlOs7QaL9kTEfqVy5KyTZTCI+M4tq1\na+TPn4+AAFWdk5PrRiSo/AAUym8n1H3bVqdKqfys3X1erfwK21mzf9lAADo2LMfWw1c5c+YMu3fv\nxsPDg5U7z7EoOrGphERmQtoCpwAJ/Tp2b14ZQF206M4eR54cmkblEnaM79tYQ/kBTPi7CQ9cJyc4\nvraWnBOXPSncfCLa2qqIkw8fPvDs2XN1otce4zclOr/YCRKcD15m1rojzFp3VH3v0IpBap/EhlWL\nAaiVX4lCOZk2qEWynjmtkGT/GXLTAkkBphLVy9oDcP36dQD+GrsBLS0ttszpQ6/W1RLso6+ny8MD\n0xjTu5HG/bJFc3Po3F0AdYp5QRA00m29/fiZZgOXfXdeVlbZ2HzgW/qvGmULaIxzJTqZa0wkzJJ/\nO6RLwtWkKNpyEnYNx9Jn0uZk9zl8/h5OO8+l4qwkfkckBZgCJBQrqa2lRbOaJfDz82Ps2LHce/qO\nYxcffHcsXR0t+sbJ6HI51vh9J6sq0jVr1ozly5drtHvw7D2NByzF/cYTrt9/wWKXk9g1HItdw7Es\nGdMRmUzgzdu3REREkjNnTgA6Niqn7u/nH8wm10uULFECGxsbQLU1T+4zpxW5c5gDcPraY6r3mMve\nkzcTbbvl0BXGLd7L4Jn/MXeDG+ERP5/cFqRY4MyGpABTkXLFciOKIiYmJoiiSP9pW7j96E2SfZRK\nJQs2H9e4VzS6Ql1cBg4cqH49Y0grZDKBR8+96T5+Ix1GrdEImRs6ezvVyxZg4t9NKZrfhjdv3lC0\nSBH6T9vKycuezFx7hCp/zSZSIXL6zBkuX74MQK82Ca9W05OR3et/MwX4BjF6wW6KtJhEv6lb1MXo\nj196gF3DsTgu3892N9UqvGThXN8NFZT4s5BOgVORsPAIirSYpHFv3+IBlCiUM8H2CzefYPm200mO\nWbBgQYKCgvj48SMKheK7cyhVKCcKpUhYRCQrJ3TBztaKrYeuMHH5fooWLcqDB99WpZaWlnh5eREQ\nEEDu3LlpW78Mc0e0TcaTpj0hoeH8NXYDtx69xto6BxUqVOTMmdP4+wdotJPLZNStWJixfRqRK4eU\nwut3Q/ID/I3R09WJlx4+MeUHJKj8RvdooHH9+PFjPDw81MpPVzvhg3wHBwdV//81wHXpQNychmFn\na0VUlIKJy/cD8PVrEFmzZlX38fX1xdTUlNy5c5Pd0oQ5w9sk4ynTBwN9XfYs7s+K8Z2RKcPZt28f\nWnI5PXr0QF9flRFHS0vO/FFtWeXYVVJ+EgkiKcAUIDEbSZvhTvGKp8feloJqlXjk/N1E02nN23QM\ngK9fv6KMdmextv62JQ6PjOKC87/x+sXEIo9buo9Pn1XxxzcfvqZMh+nIZAJr1qzByWk1Pj4+8foe\nWTWUS1vGaByOxCWj2MIaVXPg/KbRnFo3gvJFbdi1czsR4eGMGDGCkiVLMnzuTobP2ZEqstMayQaY\n8kgKMBV59uZTvOzSi11O0nfytxC5obO3M2jmtiTH2bZtG1myZNGoN3Jt2zfH5mwWRuxdPECd9QUg\nT548mJqa8vKdHxU6z2TfqZu0Hb6KkLBI7t69x9u3b9UuOjGULJgTj+0TKJRX0+n5dyCvrRXLx3Xm\n3t5JNKhShIULF7Jz5y4WLVrE/jO31RX0JCRiI9kAU5Hr91/SYdRqjXvt27dn165d5MphzsCONclm\naUL3caqQudy5cvHq9WsmTJjA1KlTCQwMxMjICF9fX7Jly6YeI4uBLodXDmH/6dsIMoH+7WuolWOx\nlpMICYvg8ePHZM+eHRMTEw35jo6OTJ06NcH5XnD+F+usqVvRLS0QRZGSbadiZGzGlq1b6d69G2/e\nvCV/7mzsW9xPo7iVRMZGsgH+xpQrlodbux15eGAqjw5OpUCe7Li5uXHkyBF8voTwz8I9dB+3Acd+\nTQF49fo1AAMGDFDF85qYIJPJyJo1K5GRkepC719DwqnRYx4LnU+wYNNxOv+7Ti3zvusUZDKBdevW\nYWxszM2b31xEdu7cyY4d37aDxsbG6tcmWfQzhfIDlY/kgWWDiAj7Su3atbGzs2PDhg08e+2DQ6sp\n7D9zO72nKJFBkBRgCpCUjcQkiz66OqoM0xumdicwMJBGjRrRrl07dZupTocAKFkwFwCTJ0+ON45C\noWD8+PEJyggODde4rlIyP/PmzWP79u2ULq0qUL5t2zauX79O3bp1sbKyInv2bAQGBqr7dGpcnkpd\nZiXbwTij28JyW1vQpYkqiWyunLnQ0tLCykqV4/DO46RdkX5Vdmoh2QBTHikWOA2xzmqK69KBtByy\nAmdnZ3LkyI6397fkBu0alMbYSI/r1+NXklu8eDGhoaGsndyNPtHO0DE88HqPKIoUbu5IROS3cp2d\nOnVi/vz5jBo1it69exMcHKx+r27Fwqx37ECTAUsBNKIkCv6GNsC4rNpxliVbTjFjhiqmulu3bhgZ\n6HHR5V9ypHLhdonfhzS1AQqC8BIIBBRApCiK5QVBMAd2ALmBl0B7URT9E+jbEFgMyIF1oijOifN+\nhrMBJkZ4RBSvvf1o8PdicuTIoc7s/MB1CjPWHObMrde8f69ZeMnX1xdra2uUCgUKpZLVq1dz/vx5\ntm7dipNjV9budueG56t4sj5+/KhhP0yKyQOa81ezikme/mZ0znk8YcJSV975fGHgwIEsX74cMzNT\n/P0DEixHKpGxyWw2QBGoKYpiKVEUy0ffGwOcEEWxAHAq+loDQRDkwHKgIVAE6CQIQuE0mnOKo6uj\nRV5bS8yMDTTS2h+/7EnXZpXw9v7Ay5cvNfpYWloSEBBA7z598PDwoG/fvty7d5dsFiYMmbVdrfws\nLCzYsGEDoihiaGioofwK5klcEa6f2p1uzSv9lsovMjKKFdvO4NBqMj0nbkKmm4Vy5crx8OFDLC0t\n8PcPUCd5kJCITXrYAOP+H9YciDE6bQZaJtCnPOAliuJLURQjge1A/BQl6cTP2EiUSpEr/31zZSlc\nuDDD5+xAJkAOKzM6dOgQLzGqvr4+Tk5OlClTBoCHDx/y0S8AA8MsaEdXsfPz81Onu9+6dSuFChVS\n93/88iPP3WbRolZJjXFlMoGa5Qr+0PzT2xZ2+NwdWgxeQethKynWagrL/jtDnrz5sLKy5M2bN7x+\n8QSf14+pVz4f7s7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PQqlpEspioMe5TaMwMzZM1hwSo3r3uepSj/b29nSpUwcnJycADixP\nuKSBROoj2QAzAd3Hb8D9hqabybNnz7Cz+35UxK/Qs2dPNm7cSHZLE1yXDiSruVG8NqFhERRtqbLr\n+fn5YW4eP1HBlStXuHLlCqNGjUKhUMR7P7e1OWc2jFZfKxRKZDIh0VNc+8bj1Ss3+Ga7e/LiA+du\nPGHPiZu8fO9LRGR8WaAqWl+huB0bp3VPkfooMSn9e/fuzblz53j69Clyucq5e+WELtSvXPSXZWRW\nJD/AZPInK0CATa4Xmep0CICTJ09Sp04d/Pz8WLNmjbo2cEoiiqKGcshioMfdWAcYsfkSGELDvxcT\nGqHk8ZMnSTprv3v3jo4dO3LhwoUE37ezteL520+YZNHj1u6E5Y2YtwPXU98y1hjo6RCpUKqLTVla\nWuLrG99Vpkqp/Dj2a4p97u9vlX+EGAW4YMECRo5Uue1cdBlDDiuTFJWTGZEOQX4DMoJvWI+WVXju\nNotqZexp1LAhwcHBODs7M27cOARBSDCU7Fc4d+4cT548AVQ1Rb6GhDFxmSuBX0PjtTUzNuDsxlGY\nGemSL18+vLy8Eh3XxsYGd3d3AgMTPj1+/vYTAKZJbEnnj1SlDMuVKxcAIWERDB06jIULF5InT258\nfX0xNTbAeeb/2LdkALOHt+b6jvG4zOr1XeX3M39rQRBwKGCD06pVvH37FoCa/5v3nV4pIzslyMw2\nQEkBZjI2TuuBlpaMMqVLM3z4cPX9PHlyp7gse3t7RFHkxIkTFHdwYNuRa5RsO5WuY9bFa6uvp8Pp\n9SPIZ2tBsaJFE0zuGhsjI6MElfaeRf2ZNqgFrksGJNpXJpMxqHNtXr9+rb63YsVyRowYgV02fZwc\nu3Jz50Sqli5AiYI5ad+gHBYmqRsT7Onlja+vL3PnzgVg1USpbklGQNoCZ0KOut9j4Iz/KFmyJNev\nX0c7+kBg8eLFDB06NNXkRkZGaiRWNTcx5Nym0Rjq66rvKZVK/hq7gct3nlG8uANXrlxFX18/0THD\nw8PR09OM103u3znGfy9Xrly8fv2anQv6UbZoyv8QJIZCoUQulzFvoxurdpxj0aJFDB8+HHMTQzx2\nTEizefzOSFtgiR+mUTUHAN68eYOfnx8ARexyMHz4cLJly8rx48dTRa62tjZKpRILCwsAPgcE49Bq\nMiu2nebTlyBAtTrbOqc3B5YN4tWLZ9ja2nD+/PlEx9TV1SU8PJzNmzer73kls+zl9nl9AciePTsA\nDva/nigiObievkWpdtOwbzIeu4ZjWbXjHPny5aNHjx7R8/i1WG2JlENSgClARrABxmVgp1p8/vxZ\nnctv75IBeOwYT/4cxjRo0IDdu3f/ktzEapEIgoCvry+iKBIYGEjr1q1ZseM8FTrNpO9kF3W7YvY2\nXHAejZmhNjVq1GD8+PGJ2il1dHTo1q2buk5J/b6LkjXHmNXetWvXgG9psH6FhD7vj74BNBmwlOrd\n5zJ45n+MmLsTXX1D1qxZQ8OGDVX9rlxh2LBhADg5/pVistMCyQaYQgiCIBcE4ZYgCAejr0sIgnBZ\nEIS7giAcEAQhvh+Fqt3L6Da3BEG4lpZz/l0Z0a0eMpnA7NmqzCev3vliZmzIljm9qVG2AL169lQr\nFA8PDxyKFcPYyIjixR24du1aihyaGBkZsWfPHkJDwzhw4AAnr3hi13AsZTtMJyAoFEN9PU6sHU7f\nttWZOXMmpUsn7Qwc2+1l/qbvO3jLZDLaNyirvvZ48Iodbr+eJCKGu0/eUrvnfCp1nc3D5968/fiF\nw+fv0bJlS3x8PtG3b190dXVRKpXo6uqqV7G6OpL7bUYhrVeAQwFPIOb/rnXAP6IoFgf2AaMT6ScC\nNUVRLCWKYtoUyP0BKpZIXX+7n5EtCALtG5Tlzp07FCxYkEb9l7Ll0BVA5aAcHBLMggUL8PHxoVy5\nckQG+9GjeXlevXhGhQoVkMlkVK5cOdHtcs2aNRO8L4oigiDw6NEjDSXarFkztQL4HBBMqXZTGTZn\nO9fvv2RM70b8N6c39+7dpVq1pFNkKZVKbGysWbn9LHYNxzJt9aEk2w//qx4AZcqoYphjkiH8LKWL\n5GLGWlWkSMshK3j53o+KFStiY2ODoaEhjo6OODs7A1AkXw7279/Pjh07aNhQlbj1+JrhSQ2fJOn1\nPUvP73dqk2aHIIIg2AKbgBnACFEUmwmC4C+Komn0+zkBN1EU43mFCoLwAigriqJfEuNLhyBxUCqV\nlGgzleDQcPR0dQmPCKewnTWbZ/6PAVP/w/PlR969e4+pqSmjejRgQMeaQPwkBABPnjzB3t7+uzLf\nvHmjdj+J4fLly3h7exMVFUX79u3j9dHV0eL69vE8feVDm+Gr6Ny5c7w44bjEXg1O6t+M2hUKkzO7\nWbx2H/0CqdTl2/figvO/WGc1/e5zJMRr789q9xVjY2Pkcrk6IWts2rRpw549e8iX04pnbz6RNWtW\nfHx8WD6+M42j7bMSySMzHYIsQrXCi50u+IEgCC2iX7cDcibSVwROCoLgIQhCn1Sc40+REW2AoNoC\nXtryLwBh4eFYWFjy/N1nyneYQfNaJQgODiFfPtWv+/xNx1jiclJj1aar++309vHjxxpjJ2YDjKv8\nACpVqkTr1q0TVH4A4RFRFG89hbcfPwPw33//JdjOzc1NXRwpNlNWHaRGj7nU6RU/DZalqaa/YNVu\nc/joG5Dg+N+j1dAVANja2hIYGMiXL19wmdmLZ0dnqvMlymUy9u3bx8yZM3n2RuWzOGuWSgF7/6Tc\nGCQbYMqTJgpQEISmgI8oireA2N/ensAAQRA8gCxARCJDVBFFsRTQCBgoCEK1hBqNmr+LxS4nWexy\nkg17L2j84a7cef5HXhsZ6nNr10QAfH19CQsLo3mLFkxc7kq5Ynnw8/us7rNk6ynyNRoHgLW1NW5u\nbuqi6VmyZNFQerdv31Zfh4WF0ahRI06fPk1cWtYuycUtY+jZqkq89+IydPa3tF27du3SkHf27Fm1\n43Vc/vnnH0CzHnDM88vlcnYv7K8Ry+ty6MpPfZ4FcmcFUK+EteQyqpTOjyAI6vbXd4xHqVQybtw4\ndd+ePXuSN29e5q53S3L87117Pnv/S/1/h+srd56z2OUko+bv+unCVT9CmmyBBUGYCfwFRAF6gDGw\nRxTFbrHaFABcRFGs8J2xJgFfRVFcEOe+tAVOgpDQcOr/vYj3PgF4e3vToUOHJN1PgoKCyJIlec7B\n69ato0+fPkRERHDgwAFcXV3ZsmULANZZTTm3cRRyuSqhQVSUAueDl2lWowQVOs/UGGfu3LlqZZbY\n9zI8PJy8efPi7f0tfdTnz5/Jli0bkZGRDOxUkxXbzgIwvk9j2jYoi0kWfXw+B1Kxs+r74bl/qjrT\nzI8SYx4wNTVFVERwa9dEPO6/ZN1ed45f8kRHW0sjgWzMs8yZM4cxY8ZwY+dEzIwNfkp2YjgfuETj\nag5YmiV4hvhbk+ligQVBqAGMirYBWomi+EkQBBkq++BpURQ3xWlvAMhFUQwSBMEQOA5MEUXxeJx2\nkgL8Duc9ntBjwkb1tYWFBX5+fhQrVoz79+8DKrvh169fNTK1/AwJJSqoWNyOK3e//eq3rV+G3cdv\nqK9HjhzJ/Pnzvzt2YvOrX78+Z8+eISIiMsn+5R3yqn0EfxS7hmPR1tYmMjKSRlWLoRRFjl1M/GAl\nMDAQIyMj/P39MTMzY/KAZnRrXvmnZCfEicue/D1F5V70+OA0tLUz1wlzZrIBxiZG63YWBOEx8BB4\nG6P8BEGwFgThcHSb7IC7IAi3gavAobjKL73JqDbAuFQppUooqq2lWo3FOEl7ej5AT0+XHj16IAhC\nspRfYjbAGGK2zjt37vw217uac41RfjG1fBcsiG/DSwgPDw98fHwoUaIEERER+Pj40KZNGw4ePEhI\nSCgREREJriD9/f1xdnbm+v2X3Hv6Llmy4tKvfXUiIyPJlSsXRy/cT1D5WZl9WznHfJampqqDl32x\nkjT8KAn9rSs4fMuhWC+Z/pEpITez8EM/F4LqZz27KIo/nb5WFMVzwLno10uAJQm0eQ80iX79HCj5\ns/IkviGXy9VhZL5fgtiw7yL/9GxIRGQks9YexcXFmQsX3Ll9+w6Ghr+W/y6Gxo0bs3HjRi5cuMD6\n9et58+YNtra2ADx48IAJEybg6ur6w+NaWVlx+/Zt9evYjt0x221RFDl48CABAQHo6OhgYmLCX3/9\nxezZs2gxeDkAZsaGtKlXiuF/1UNfTye+oDgUzKuKKomJMzbQ1ycwKIjw8HD1Z/bpiyotf6dOnQCY\nPn26Ohzx2ZvkRbEkF+Ms+hTMk53HLz/w2vuzOvxOInkkawssCEIWVIqqC6AURdFAEISWQAlRFKek\n8hyTRUJb4G5j1/PsrS9uTkMwMkw83lRCxav3frQevgr/wBCcnJzo2/fntok/QsxW+e7duxQtWjRF\n8u99j4iICHR1dTE0NKR169bs3LEDhVJBHmsL2jcoS9emFdRFl2KjVCpp8PdiXrzzUzuRP3r0iIIF\nVdXzzMzMCAwMpH///pw/f5579+4RHh6uPk2vW7cuHtcucXPnxBR9no6jVnPt/ksAnh6ekakUYEbZ\nAi9AtRWtAoRH37sOdEyNSf0qj198oM+kzVy45YX3J3+OXfRM7yn9FuS2tuDGjglUKmHHiOHDGTBg\nAP7+/qkqMzQ0lOvXr+Pg4JAmyg9QJ2ywt7fH2dmZ4JAQRo4cRbac9szbdJwiLSbRcsgKxi7ei39g\nMKBaTTYZuIxnbz6plZ+ZmSlnzpwBVIrc398fpVLJfy6b1VXx/Pz8qF69Og4ODpw8eZLKJZOua/Iz\nxCi/LAZ6mUr5pQXJ/bSaAV1EUbwR6957IG2iy3+A8IhImgxcyqmrjwBVdt/WdUulqszfxQaYXJwc\nu1KyoDWrVq3CxsaaTZs2xbOpfc8GmFz09PQoW7bs9xumsGxRFLl16xag2jLPnj2bCxcuEB4ewapV\nqzDJlge3S4+p1n0eB8/eYdT8XTx+8UFjjC9f/HFyWsWMGTPU97o1r8Sh5YMAMDExJkeOHJw7d47g\n4K8Y6uuydMzPrxkS+lvHlBAAGNKl9k+P/aNyMwvJVYACEDfTZRYgKGWn8+v0neKCMrqug66OFjd2\nTEizlUVmIYuBHi6zenFnzySqlrSjV6+e6OvrkTOnLfXr1+fy5cuAyiUlsyEIAv369eP8eXe8nj2j\neIlSjJy3i5PXnibYXqlQMnHiRIb/VZfnbrOYPKA5Vbqp4q8bNGhItmzZEASB589fcGjFoBT/Lt6P\ndZhz4rK00/lRkmsD3A3cF0VxsiAIX0RRNBMEYSxQRBTFn0ttkcIIgiAuH9eJCcv2ExwWSWRkJM4z\ne1K1dMLhW0HBYTQbtIyg4DBupLBNJrMREBTKicsPuOH5ihuerzXSUXXs2JEJEyZw+PBhPDw8sLe3\np3Xr1hQqVCjFDlIyCh8/flSn1orNivGd1SnIACp2nonP5yA8PT0pUqQIoEqBtX/ZoBSdT1SUgsYD\nluL12gdtLTlX/xubZKbs35HUtgEm9xR4BHBaEISugKEgCPcBHSB11tw/yaCZ2wDUv7KJ2VvCwiOp\n0WMe/kEhaTa33xkTI33a1i9L2/qqrWrg11B2HffAQE+XORsOsH37drIY6pHN3JgTx44wa9Ys9Zb5\n4cOHFCpU6Lsy7t27R/Hixfny5YvaZSSjkTVrVo3ryZMnM3nyZN58+BZN47TjLD6fg+jZs6c6/T3A\nvafv+BwQTFh4JNracixMDH9pNahQKGjUf8m3cLthrTOd8ksLku0ILQiCHtAUyAu8ROWPF78ARDoh\nCIIIqrjTy5cvY2FqyPXtCWfdjV1FzevIjF/elly58zzdMmakl+yk5IqiyKj5u9h36haCIDBv3jxc\nXV25cOECe/bsoWXLlshkMrVLjCAI7Nmzh7Zt26r7J8XZs2cTzUaT2pw9e5a7d+8ydOhQ6tevz/Hj\nxzE1MiQ4NExtj7OysuLDhw/I5XKaNWvGwYMH440jEwQK57OmX/vqVC1tj0mW73spxHzma3efZ7HL\nKULDv0WOPjs6M9Eqeb9Ken6/M8oKEFEUw4Bfy6KZyhQpUkRtnzq8ckii7WKUn212c8k+mAoIgsCC\n0e1ZMLo9S7ecYtSoUer32rRpQ4sWLZg1a5Z6e3jv3j2aNm3K8uXLef484xvchwwZwpAhQ4iKimLe\nvHl8+vSJDx8+4O7uTp8+fXB0dATgxYsX5MmTh3nz5jFt2lRWrlxFq1atCAgIYO/evax2cmLY7B3q\nEp4NqhTh6atP/NOrAfUrJV4qc9a6oxrXnZtUSDXll9lJdAUoCMJGVBEbMZ9sgg1FUeyZOlP7MWJW\ngDHsWzqQEgVs47U7e+0xPR03oa2tTXZLY85tHBWvjUTK8uTVR3LlMEOphMkrD2iEvyVGZqlV8z2a\nNWvGoUNJ5zSMQVdHG31dbQ3TzZheDXnn44/3pwBWTeyidgLPLKSnH6Ai+l8UqpViV6AAoB393678\nYCRJWiETBPRjZd39GhIGwMkrD+npuAlQFfDplYwMJRK/ToHc2dDT0cFAT4c5w9vQv0NNslsaJ9nn\n06dP6tRXe/fuTaOZpg2xi78/f/Ys2f3CIyLj2a1nr3fD5eAVTl55iH2TCXQcteaP+fFICZJ7CuwM\nnBBF0SXWva5Ag4x0Cjzh7yZYmmahea2SPHruTeMBSxNsO336dBwdHXlyaFqKbIElG+DPIYoil257\nYWpkwILNJ3jv48+TVx/jtevbty+rV69WX6e3DfBnZPfv359NmzYiIBAapvpBrlSpEnp6empn6sTo\n3qIScpmMI+73MNDTJWd2M3JmN8ft4n2CQ8NpULkorqe/xRjvWzKAEgUTS63540g2QGgB9Ihzbzuw\nIkVn84v0bKVKp+77+Suthq1MtJ2HhweWplnUym+R8wl2Hb9Bs5rFGdu7cZrMNa2JiIxCJ4NlClHZ\nrQSaDVqeZDsnJ6e0mVAKI4oibm5uTJs2jcuXL9OvfQ2MDPWYt1FVz+Thg7uYm8Q/uU0sq1HdikU0\nFNHUQS3Uryf1b8bBs3dpVK0YFqapW+M4M5HcFeAzoK8oiqdi3asNrBNFMUMUDIiJBVYoFNg3Sbrm\nas6ctmgpQ5kxtDWd/1mrvm+bzYzzm/9J7ammOTE57HJbW3BmQ8azeXb6Zy3X7j0n9lcxxqgviiJ6\nurpYWJiTP78902fMoFy5cujo6PwWhv/z589To0YNQJWFZ8mYjjSsWixeu8jIKLS05L/FM6UlGSIf\noCAIPYHlwC5ULjB5gbbAYFEUf73WYAoQ9xBELpdr2FqSw+3djhgn4o4wZeUBPvgFsWpil5+fZDoR\nu2lLl0wAACAASURBVMbH2indqFOhcDrOJmEUCgVhEZF8+BSITTYzdcLSzwHBHDx7B6/XPly8/ZyX\n7z5p9DM1NWXNmjVMmjQJT8+MGQkR4+MYg52tFVtn9yKbpUk6zur3IEMkQxBFcQPQAFXK+nKoEiI0\nzCjKLyGSUn5TBjaPd69z4/Iayu/F209EREYRFaWgyYClbD5wmWMX7yc4XkaPBZbFWlWUKZI7zeT+\nCHK5HEN9PfLlyqqRrdncxJDuLSozbXBLTq8fwb19k1k6piPF8qvC0P39/Wnfvj0PHz6kePHijBkz\nJkXnFZefiUN2cHBAFEVy51Z99s/ffqJa97k/PI5UEyTl+RE/QHfAPRXnkuJ0alSeG56v4hnW2zco\ny6QVBzTuGRnqqV+PnL+TfSdvxRsvJpHo70b3FpXZ6HoRAFOjlE3HntYY6utiaWZEycK5uO/1rUZG\nSEgIBgYGvHnzhjJlyuDt7Y27uzu7d+9mwoQJTJs2Ld3mfPLkSerVq6dxL7Nlbv5dSdZfQRCELiTu\nB5hwCa90YOLfTTXqxG47eg2tOOmBPPdPTVCR3X2iClsSRTFB5WdtZcrqSQkfeGfEusCx+at5RbUC\nTEu5qUXFEnZcvO2lcc/AwABRFDE2No5Xfa5NmzYpJvtnToBLly5N3bp1GT16NDdu3GDcuHFkMzci\nSqFA6wf89qS6wClPcn1AZsT5txZVDY/pqTOtn6Nrs/j1lKIU36pwymUCerraCbq+PHj2ntELdqmr\nosXlgsu/FM2f4bJ/JYvl/2fvrMOizL44/rl0iGAgCqKImGuvuWvr2rV2d67+XHMVA7vXzl0Du9G1\ndW3XTuzGxkARlWaY+/tjmBeGEFBS5/M8PM77zn3fe2ecOXPvued8z3pNtbZvycE+uFMtihfQDXQP\nDw/n0yeNQJGVhRmTf28KQMmSJSldujSPHz9O6WECkDlzZg4ePEitWrWUDZHH3u9Yt/tcqoxHTyQJ\n9QE6SSnzaP8AazR1fuOvYJOC7Dl+/bPPd2kSd+DzR/9gPA5ejvW5uGZ+WtK6D9Aui8bZLqWk6K9j\nFUHP5O43udD2vW3ObzrnjYyMsLW1BWD64Oa0rlsGr/1TWDWpC6+ee5EnTx6srDKQz8WFH374QQm0\njipaEB9fq0X4008/sWPHDgAqJHJmpfcBJj1fFAUspVQBbkDyepwTyaAZmz/7/No9ml/cw2dvJ/ie\nZYvm4ZcKhb9qXKnN0C616dxYU4ksICiEQ4l4/WkZIQR3d2sWIVrZeR8fH0xNTOgzYS0/d5zObxPX\n8eKNH7vm9+PQ0oH83rYKP+Sy4uXzx8p9HB0dsbKy4vXrmEHYyYHWH5jbPkuK9Kcnbr7GE5sDjShq\nuiE4JIzaveZwP5Zsg9gQkKDyiantD0sI/kGR4qXh6q9PlUorr1nrz40qzhoSqlFJefnmPS/fvGf/\nyRuMmLsdS3MTfqlQmICgEN5/1E0p8/f3JzgiQ+NzJEUGSmCgpm+f9/7ktMuU4Ov0PsCkJ0EzQCHE\nUiHE31H+XY+mRKVH8g4vcaxYsYKgoM8rdCXE+GW2tmTp2I7c2ZV6O4dJybv3/ooAQf3KRakbSyBu\nembWH5pNj6ql87NgRBvu75mE51Y3WtbWldoPCArlnyOeHL+ku4GycOFC1Gq1EqaS3EyerCkIH1dY\nlZ6UI6GB0CvR3QX+BFwC1kUsh1MdIYTUvpaEFPY2MjJEpYoZK/jXmA6JXvImVa7krYfeFM6buI2W\nhPRdrOlY/AM1M6R7eyYmaufxa/pNLhLTd9MBi/C884whQ4boFF0vVqwY165dU4537NhBo0Yx40Oj\nk1R5yJkzZ8bSFE6sTHjmUXrO+/5S0kogdGcpZZcof/2llKvSivGLToYMGXB3d/+sikhsKWEGBiLV\n/H3nrz+iQd/5ONdxVXJFkwqt8QOSxPilJzzvPANg9erVPHnyRDkf1fgBXL4c+wZYclGhQgWev3qf\n6GylqNx59IqqXWbgXMeVCu2mMnbRTsJUafIrmWZJ6AzwtpQyRv6UEOK6lLJobNekNFFngFHx8vIi\nb15dafyVE7sA8OyVL6MX7NBtH0cienKjVqsZOG0Tu45rvpjOOW05uHTgV4WuqNVqSraYwKcAjW9r\nQr/GtGtQPknGm144e81Lyff29fXF2NiYZs2a8e+//8ZoW6NGDQ4ePJgi4UJSSszMzDA3NWLVpC4U\ni0W7MjpBwaEcPX+Xf0/f5MSlB/h9CojRZsGINtSrXCyWq9MnaSUX+JOUMsaaUlsgKVlGlkjiMoBR\nno/3Hp0b/4Rbn4ZJOaxE4/cpkFItNL7HAR1q0r9djS+6T9T8XwC7zFacWR97jOO3TlRptKCgIExN\nTVm7di0dO3YEoFChQty+HbkzrlarU8QIent7kzt3bqRazd9jO1CtbMzaKfPXHWbhxqMYGRkTGBSM\nsbExDg72NGjQkIEDB5InTx6cnHLz9Klmpntx06hYFWbSK6m6BBZCjBRCjASMhRAjov25AwkPoNLc\nz1AIcUUIsSviuLgQ4owQ4poQYqcQIlbHnRCijhDijhDivhBiWGL61BIYGIi7u3uM856enkr4w8od\np+kwfBkfAxJX6iS+OKngkDAuRBSvjgspJY+ev9XxtM5Zc+iL+y7i4gCg+EJLF3GK916JIS3EASaU\ngs45GNdXIx1lbm7Ox48fFePn5ubG+PHjAaj8o6aC4Oc0IpOqHjKAvb09d+/epWSpUnRzW4VzHVce\nPY8Ue2j0vwXMXnOI0LBwhg13ZcOGDYSGhvLo0WPmz5+Ps7Mz/v7+ivH7c0iLZDF+33Mc4C9ATTTh\nMr9E+auBpipcl0T29ztwi8iv+TLgDyllMWA7MDT6BUIIQzRKNHWAwkAbIUSi5UzMzc3p3LkzUkqd\nv+LFi5MtWzallsgpz4eUaDaeF2/eJ7aLWFGr1RRu7EarIX/hXMcV5zqubD90meev3zN+8S4KNRqN\ncx1X8tYdQY3uMzEzjT8y6caDF9x59PKzbXYu6EflH/MpmREtaiWu+Hh65u7jlyzZfEw5Pnn5PuMW\nReZ+b926lRYtWmBvb8+oUaNo3rw5jRo14sSlyNq/+fLFXk41qTl37hwXL14EwNLSgqYDNNqHJy7d\n48b9FwwePBi1Wo2bm1usJTmtrKywsbGmRMFcVCjuzKPnPnz0TzO1ytI8CV0CL5BSflVRUyFETjTp\nc5OAQVLKhkIIPymlTcTzjsB+KeUP0a6rAIyRUtaJOB4OIKWcGq3dZ5fACaF27dqMHDmSKlWqYGZq\nzK0d47/qfgDv/Pwp03pSvO1MjI3Y9GdPhs/ext3HrwBoW68cE/s30Wn3Y8sJSgxbfBXtSjQfr3wZ\nUsu3mRpol/8mxobsnN+POr3nKs/Z2dnx6tUrSpUqxZUrmpzvP//8k759+3L16lV+/vlnZWOiXbt2\nrF27NtnG+ccffzBjxgwADhw4QO3atQG4smU02w9fYfyS3YwfN47REUWW4mLfvn00bNiA8HA1As3s\nwtrKgrJFnOjRvBKlf3BKtteQ3KSVXeCkqOg8G80ML2oe1k0hhFbWtgUQm463A/AsyvHziHNJzoED\nB6hUqRIQGTTd5o+lPH/95bPBv7eciPO5gR1/wWv/FLz2T+HOrgn0n7JRMX4A6/eei1HfIWoAr0u9\nkRy/eC/GfZ+99KVMm8mK8XOf0PmLx58eqf2z5jc0NCxcx/gBirS+mVmk+s+QIUMwNzenfPnyGBtH\nSnGtW7eOUaM+L677NVSqVImsWbLQsGFDxfiZm5mxcONROjf5maY1S+E2Zky896lbty4qVThSStRS\n8vDhQ3r16cfD10G0GvIXjfvHrY7+vRPneksIsVNK2Sji8cE4mkkpZa34OhFCNADeSCmvCCGqRnmq\nKzBPCDEa2IlGbzBGH/HdX0vnzp1xcnICNEKZJUqUUGK2tL6bhB5DZNB05U7T6dT4J2r/9IMSD6X1\ni5Qv7qzjI4n6/K5jnmzYdyHWsZoaG1Emyi/z2ateOgW2tfQYu5pl4zpx5Nwduo9ZFeP5LqPcMTAQ\nlC2aB8fsmahQPC+us7cREqYJh/i5pAtVyhTQGW/08X/J8YptJymc1z7J7peY47jeb+3x4tHtOXvV\ni1Hzt+P1/K3O+9WmTRsCAwNxdXWlUaNG5LTLpPMDFxwcrCOmO2nSJJydnXF2joyDq1q1aqI/T7Ed\nW1lZ4fP2LaGhoZiamrJ06VL27t3LvpPHqF62EJVKurDt0GX27NmDpaUlnp6eDBgwIN77Ozs7U7du\nXd69e4eX13Ku33tGd7dVdG9WKVne76Q8Bs3O/ddMOhLD58pijpBSTo54PDaO66WUcly8nQgxGeiA\npsKcGZAR8JBSdozSJj+wRkpZLtq15YGxUZbAroBaSjktWruvXgJHu1+cz+1bMoACTnbKcWyBogs3\nHGHmqpi/GyVKlMDTU1PA5v6eiTplDKPv3Do5OfH48WOy2mTgrZ9/ol/D2XUjyJbl8wHhX0p6CYQu\n02oi7z7ohotIKbl48SJlypSJ8zohRIQcvzHBIWEMGDCA2bNnJ3tBpp07d9K4sWZRZGVpzqeAIHLn\nzsXjx08S1ffgwYOZNWsWALlz5+LJk6fMGdaKRtVKJHpM33IgdIJ8gEnaoRBVgCERPkBbKaWPEMIA\njX/wiJRyZbT2RsBdNBsv3sB5oI2U8na0dklqAAHGjh3LuHGx2/ez61zJliVmacf7j1/RZthyfD/o\nGqw///yTU6dOsX37dp3zUwc0pX7lYhRtOjbGvfz9/alVqxavXr2Kt2B4xVIu2Nva8Oy1L89evWf6\nwGaUL573s9d8D0gp6TtpPftPatLO/vrrL3r27Im3tzcODgnzpBTOm4PbXq8oUaIEmzdvxsXFJdnG\n++TJE6pVrcrzFy/o1KkTb968oUWLFrRv3z7B95g0aRKjR49CCIFaLcmWLRtv3rzByT4LR9JgTZjP\nkSYMYFIGQkcYwMFSykZCiN8BraaRh5RyREQbe2CplLJ+xHFdYA5gCCyXUsbw6CeHAdTy6dMnMmaM\naeyWju1IjfKRb8uf7gdYtOmYcpw/f37u3dP46K5evUrx4sUT1a9KpcLQMGGFcr6nTY4v4dLNJ8xe\nc5AzVx+yZInGCAI4ODjg7e2NEGBsZETlKlU5dEg3/MhACExNjQkK1nhostlmpVnzFkybNi3elMuU\nJigoCAsLC3q1qMwfXeswaPpmTns+RC0lG6Z3xyWXXfw3SUOkiU0QIK4w9fjD16MhpTyu9S1KKedK\nKQtE/I2I0sZba/wijvdFtHGJzfglN1ZWVkgpGTlypM75HmNXk7fuCPb9d52B0zaxaNMxihT5gZ07\ndzJx4kRKliwJQMuWLROc8hQcHMyJEydo1qwZvr6+CTJ+7RvEFIJNbtJTHCDAjz/kZu3U7jT75Ud6\n9+6NEIJhw4bx4sULAKTUlA718fGJca1aSpzzRs76ggI+sWL5MmysrWnUqBFv3rz58heTCBISgxga\nGoqxkRHLt50ib90R7Djqic/7TzSpXuKLjd+3HAf42RlgRBA0wGggekxIPqB0Wk+FS2qePHmibLRE\np2vXrixfHlknKnfu3Dx9+jTB9446/o8fP2JtHVk1rHG14ly4+QTvN34618xzbU31cgWxMDNNcD9J\nQXrxAcbG4k3HdPKtQ0JCMDQ0xMhId0+wWtmCHD1/B4C1a9fy66+/0q1bNw7s3897Pz+sLM0IDA4l\nPFxN2bJlGTlyJA0bNky2LJKE+gDVajXr1q1j4MCBnDhxggEDBnDD8yKn1nxZydfv1gcohDiGZhe2\nEroFkdTAK2C2lPJicg0uMaSUAQSNodqyZQutWrWK8Zyvry9Xr15VPqgJ/TLcu3dPJ/hWpVLphGTE\nxZ1dE9JcwfP0gMfBSwyduVU5fvHiBZMmTWLRokUYGxsTFhbGg72TOHrhLnPWHObWQ2/Gjh2Lm5ub\nEkgdlWyZM/LG9yOg+T/fsGFDrJ+PlOTt27eUL1eWh16P6PprRUb1qh//RWmMtOID/OpA6OQmJQ1g\nlD4BqFatGkePHtV5TkqZION34sQJJfZQS0hICObm5jFiAKNjY2XOqTXDMTczSeTI9QB0c1ulzPC0\nhIWFMWzYMGbNmoWRoQH39miC2OeuPcTctYcBTQ6vvX1M2bJtc/pw6spDZq6KFFpI6c+kljVr1tCx\nY0fsslizdmpX8jpmS5VxfC1pwgeY1o1faiGlRKVSKcbP0tKSQ4cOoVarE6QuHBISEsP4PX/+HDMz\nM50vjraQTnQub3Hj6t1EpWMnGenNBxgby8d3Yt/i33XOGRsbM3PmTEBTUKt2r9kEh4Txe/uaygzK\n3t6e2bNn8+HDB0WKH+DhUx/6tKpCQafIlDUhBBkyJI1wemLykJs3b45zHife+n366hII37IPMKGK\n0BZCiMlCiHNCiIdCiEcRf9/uO5NADA0NGTt2LKAJW6lRowZCCMzMzGJ1qGuxtrbGxER35qZSqXT8\ni35+fhQsWJDjx48DcHvneMb3a8ylTaP0u75JRIE82dkxry857WwAcHbOg4+PDyqVCgcHB+4/eUPh\nxm40G7iYWw8j6xAPHDgQW1tbvL29cXTUJDANnbUVl3ojuRMlmwcgICAAIYSS7ZESmJub89DrEYUK\nFWba8v2UbTOJE7FkDX3vJHQJvASNH3AxMBVNMaR+aBSh04RufGosgbV8brlbv3599u7dG+N8eHi4\nTh5vbNdnz56dV680X6YjK4bgpC+ik2xIKZmz9hBbDlzi1dsPlClTmgsXLmKfzYYKxZ0pUTAXo+f/\n89l7/PDDD4SEhPDgQaTkfhabDOS2z8zlW5rNsMKFC3Pu3LkkmxXGhzbgO5+LC/cfPKBZzVLMGNIi\n/gvTCGnFB+gNVJJSPhRCfJBSWgshCgPzpZRfJliXxKSmAYyPM2fOkCtXLtq1a8eSJUsoWFCj+xYc\nHIy5uXmC7qGf8aUcbgt2sHb3WUA34P3izce0HPxXvNfnyZOHR48eAVD5x/y0q1+Wae4H8HqmuyJ4\n9uwZOXMmOpLsi9H+yKanz1Ka8AECllLKhxGPQ4QQplLKW0DZZBpXuiI+30yFChVwcHDg2LFjivED\nzdIoIXRsWCHO577HWrHJ2fexC3cV4wcwfsluJYaz9A9OrJ/Wg4n/0yj0WFhYsGDBghj30Bo/0Mha\n9Rq/NobxA005zqjV7OIdWxJqESaG794HCDyKosF3F+gqhGgD+H3mGj3xkCVLFsLCwgCN9FL0DZGq\nZfJzfOVQxvaNv1iPnqThyp3IuM2MGTOy97/rFPl1HDceRPr/2tYvx81/xpHBzIh+/fpRq5auHkie\nPHmUx1kzRS51y5ePWY7A0sKCYkWL0qdPHypWrIgQguHDhzN37txEGceEoE3D1OpSptUVU0qS0CVw\na8BPSrlfCPEL8A8aQdSxUsr4xe5SgLS8BI6Pd+/ekTVrVuW4XYNylCqUi8EztgDgMbsPJQvlSq3h\nfVcEh4RRuHHs+nsrJ3Wh8o/5dc5N/Gs3a3efIzRCfScgIABzc3PFv1utbAGOnr8LwLhx4/j1118p\nViyyZscPLvbYWFly/roXYbFUKdyyZQvNmzcH4PDhw9SsWRPQVJV79+5dol5bv379WLhwoc65Pq2q\nMLRLHSBSjOPixpFktkkbJb/TxBJYSrlRSrk/4vFBIFPEX5rYAEnv3Lp1S+d43e5zivEDyJ1Dv/mR\nEqjVaowMDfipRF46NIycrQk09ZSdc2p+pLye+9B7/BqOnrvDqF4NuLNrAiULan6gqlevrrOhNapn\nZPDxmDFjdFIi/+hSm62zerNmSlc8t7phYBDzex512RvVZeLr68vmzZupVKkSnp6eCZrN/fabJu0+\nagzj4k2aCIOa3Wcq50q3nkTBhqNpNnBxvPdM73yxGowQwgwIlFImdBmdrKTmDDApJJJu375N4cKF\ndZSBtXzOaf091opNjr6jC1lEZZ5raxpUKa70HRgcQvcxqwGwsbLA71OkSK02HbJv374sWhRTiNTY\n2JhChQrh5eVFaEgIoREukKiYmppy7949smfPrhMqFfVztn//furWratznVqtRkr5WZVwLcOGDWP6\n9OkUL5CT1ZO7UbxZpOpRmzZtcHZ2ZtKkyMWdp4cbGS0TtmGXlKSJGaCe5KdQoUJIKalVq1aK1aPQ\nE0lcxg9gwNRNqNWRQubVyxWiXX2NAEVU42diYqLkgi9cuJBNmzZRsWJFnXuFhYVx/fo1/P39FeO3\ndetWJZje3d2dwMBAcuXKFSNONCrv3+sKhg4aNAgDAwNFPejOnTsxrhFCIITg+vXreHk9wMzEmDnD\nWlGp03TsstkqdXLWr1/PxIkTlfhTgBLNvr48RFpEPwNMg0yYMAEPDw+uXr0KgKGB4PauCQjQEVDV\nk3RM+nsPy7edRAiNMoyW2rVrc+DAAawszVkzpQvF8muCnk9feUB7V42x++mnnzA3N+fw4cM698ya\nNQu3bt3Gx8eHHt27czqi8FZ04vrc7tq1i0aNGtG2bVvmzJmDra2tzvP+/v5UrFgRQ0NDLl68yMaN\nG2nbti0AZ8+epVy5SJWg6DNDAwMDCjjZ4fPen7fvPxEQEICFhUWMMWiX867d69KjeeVYx5mcpLYY\nwkjilqQ3RlOsSG8Akwm1Wh2rwctik4F3fv4cXjaIPDltY7lSz9cQEBTCsFlb2X/yJsWKFePM2bNU\nq1aVC+cvULNCIa7cfqYIH4BGuSc2vUgt3t7e5MiRg7CwMJ4/f87w4cO5d+8eq1at0tkQiU7VqlWV\nWZiRkZESMTBt2jRcXFxYunQpBw5oVG2OHDlCtWrVYtxD+53Qzv5MjI0IDVMpitdaYttUKVmypKJe\nnlqxg6m9BP7lM3/VgONxX/r9kFzxWQYGBkgpyZEjB6Ap1Thy5EjeRcjj1+g+C+c6rrQYtIQ2Q/9m\nz4nryTKO2PhW4wABLM1NWTCyHcvHd8Lz6lU2bNjA6dNn6PPbb9x49J5s9rn4449Iaanoxk9bbU6L\nVhTX2NiYPHnysGnTJq5cuRKn8Xv48CHZsmXTWYKqVCqOHTuGSqVi+PDhNG/eXDF+oNl8cXCwp3v3\n7rx9q6mDMmvWLAwMDJSZ3+TJk/mxtKYMQPTJgq+vL9ev635+/Pwio9xUCdSzTG981gBKKatKKavF\n8VdVShnzJ0dPkuPt7Y2Uknv37jFx4kSklISHh9O9e3cyZ86MRZZcnLv+iP9NXo9zHVf+mLk1wQKs\neuKmSpkCNKxanK5du7J69Wrmz5+PWq3mxo0bzJs7O9ZrFi1axNSpU3F0dKRgwYIUKVJEEbOoW7eu\nMhMTQrBs2bJYl783btxQ8sizRAtH0Uqk2WbSVaKe/PuvVPghB9u2bCRbtmz07dtXZ9c4ICAAV1dX\nTp8+Heu4DQwMYqTnRS3fcMbzYfRLvglSvCZIcvEtLoETQ1zLZYAVEztTtXSBFB7Rt0OJ5uPp0Kkr\nCxYsUHxit3eOJzxcTZFfx3722sWLF2NsbEzXrl2xtbWNNXavf//+zJ0bWb7zzZs3vH//niJFiqBS\nqTAwMGDcuHGMHj0agIwZzJg9tBXdxqwiR44cvHz5kgJO2dm3RKNss3TrCWa4H8DMzJwSJUty8uRJ\nHUOr1TM0MjIEKVGFq2nfvj1r1qyJMTbt681ha82pNcMT98YlAcm9BNYraX4jaJfLsQmpdh21Unn8\ncN/kZFMs/tZ4+OwNzQYs5lNgiBKort0UKdTIjd9aV433Hn369AE0tTp8fHzo1KlTDEMzb9485s2b\nh5+fH9bW1hQtWpQ3b95w6NAhgoKCCAgIoHXr1gBc9RiDlaWmprGJkSEZM2bk5cuX/FqjpHK/Hs0r\n06ZeWeauPczOY9cAsLW1VWaV2sBqlSocx+yZefbKl7Vr17J9+3by58/P5cuXAXQk3drU+zazXtPE\nBkZ6J7VyNGPr28jISAlnkFKiVqs5eDCyPGfeuiMICIpfqzA+vmUfoJbbXi/5GBCMlFIJIh42bBj1\n62uCm93/OaWzOfD+/fsY/x+jR48ma9asdOvWDSEEq1ev5u3bt5QpUyaGEIKdnR1CCN68eYOHhwc1\natSgVq1aivEDdMJxihbIyd27miyTqcv36chdZbAwo1CeHGj3MLV+QS1SSp4/f45/cKSrJCAggCtX\nriibLVGLxy/eqPu6vhX0BvAbRwhBzZo1CQwMpHr16gAUazqeA6dupPLI0j4NqhRnWFdNmljTpk0B\nzWxtz5491Pn5B25sH0dAUAhGRoY0btwIGxsbHfHaihV/ZsKECbx9+1bHmGTJkoV9+/axZcsWnf5C\nQjQzzbZt21K/fn3UarWO4CpAyRYTKNViPFJKNv/Zi94tI/vrPMpdiUss0mQMQ2Zuwcf3k8712ji/\nli1bkilTJt75RsYTdurUCUCnNoqUkiZNmhAUEsZvE9YqG3DfCnoDmAQkZ6HspOpbG6cWHh5OgQIF\n6DNhHYOmb+bFm/fxXxwLqZUFktJ992pZhV8qFObUqVO8fv2af/7RaAI65siMEIKPAcGoVOEULVoM\nc3MznKMIIZw8eUp5PHy4rv+sT58+VKgQU+Xn7du3rF27ltWrV8fp0/X7FERAUChCCP6IMNBaSrWY\nwE/tpxAYUcLzxYsXLF++HCklr169olGjRrRr144tW7ZgaWmpc23z5s1j1bbcvn07q1ev5vC5u5Rp\nPYklm7+d4A+9AfzOMDAwwNPTkwIFCrD7+DWqd52J1/O4lav1wIIRbQDN7qw2S0c7M8yR1Zpfa5Rk\n0qRJhIaG8ejxYwBqRMy2tURdut64cSPG7C8qffv25aeffvrsmEbP305wSBg7j3lyZp3GuGpnbq/e\namIUBw8ejL29PV27dlViEXfv3q1zn2vXrimGtmHDhnH216FDB4Ij1Gmmr9jP71M3fnZ86QW9AUwC\n0pIPMCGYmppy584dgkNCyJ49OzW7z6JQIzdaD/2bk5fvJ+ge34MPUMunQM0Xv2TJkty/r3l/ssuf\nYQAAIABJREFUJv69R3m+XuWiir9Vi2W0kBLtzBGgR48eMfoolt+BXi00mRaLFy+mSJEirF27Ns4x\n7Th6lcKN3RgwdRMV2k0F4N9//yV//ki1Gl9fX0CzjC1aNGb12gkTJtC5UyeePHnCokWLePHiBeHh\n4WTJkkVnxqr9jBkYGCj+z13HrsY5tvSE3gB+xxgaGvL02XOuXbuG25ixvP6gouOIFRRrOo7/TdnA\nlgMXEqQy8sT7HRU7TCNfvZGMmLMtBUaesmSw0PjhFi+OVEdZ+U9kPF2NcoU4vGwwoMnpnjFjBjt2\n7OBMlNS3qDL506dPj9HHX2M6MqxbXbz2T2FQx18AaN++fYx2tpmtYpyzsLBg5cqVVKtWDReXyALu\n7u7ueHh4EB4ejq+vLz2bV2aJW+Q9ly9biufVq+TMmZPffvsNe3t7pJT4+voybdo0JV6xWrVq7N+/\nn2PHjrFnj8bwX/UYE8+7lj7QxwHq0cHHx4fevXtz6OBBPn7SONANDASFnXOQJ6ct/dpUI19uOwDm\nrT3E/A1HCQ9X69zjW0rRm+G+n73/3eCJd8z4vejpYR1HrODxmyCePXumnMuTJw+PI5bFUT+fQUFB\nSu5toTzZWTe9BzZWkbm41+49p0l/jXZf9LS1qJibmxMUFARo9Ab379/PjWtXuLBxJKPm/8PWfy/x\n7NkzpXDT1AFNmeF+gHcfAjAxMcHIAMVfOGLECNzc3Jg/fz5jxowhMDAw1j5je+3JRWqnwiUpQghD\nIcQVIcSuiOOyQojzEecuCCHKxHHdYyHEtYh251NyzN8btra2eHh48OHjR0JCQlixYgVt27ZDmGdm\n7383qN1rDgUbjsa5jitz1h4mPFytk0FgZWmGtVXMpPr0yJFzt1m86biO8fOY3YcKxZ2Z79o6Rnsr\nS1O8vV/onLt+/TqlS5dWwlW0RK0F06J2aR3jB1Asf04e7pvMPNfWn52FR43VGzNmDGq1mk8BwQz5\ncwvXIkqmGhsbKyIJE/7azbsPATg4OJAlc2YK57Xn/p6J/Fg4F5MnT8bMzEzJIlGr1fTv3z9Gn6dW\nD4tzPOmNlF4C/w7cIlJgYTowWkpZEnCLOI4NCVSVUpaUUqa5iMz05gNMKCYmJnTp0oU1a9Zw7dp1\nVCoV3t7eNG2mCaTV7iL6+/tTJJ8Dh5cN4qrHGDJbW37utl9NSvkAM1hGhq7Mc22D1/4phISqWDet\nB/Uj9AGjEhqqwtBQN7fAxMSECxcu6PjmtGiXyFfvxV7bWQjBs1cxd+nLly+vLMdPr3Nl3bTuynPn\nzp0DYPfxa9x78ppWrVphZ2fHunXrcMqdm4w2mSlfvjzLly8nJDQE/8Bg2g1bzrX7kZL/FhYWyvJ3\nxIgRynmv/VPw2j+FHNlsYh1veiTFDKAQIidQD1iGRmQX4CVgHfHYBngRy6XKLZJvdHoSSo4cOdiw\nYQNHjx7F399fMYI37r9QxBlaDl7Cuj1n8Xn/KV3XnShbJA+ZMmpmZmEqVbztQ8JUhIWFKYHE2ji+\n589jN3Bly2p+y3cc8SQkNKYwKkCuHJljnDt27JiSYVK9ywwqFM9L9qy6MYhaNm3apOSFP3r8GG/v\nlxw5coQqVarQpk1b7jx6xfkbjwiLkPSPqkXp7++PnZ2dctz095gCr+mdlJwBzgaGAlEdRsOBmUKI\np8AMwDWOayVwSAhxUQgRcwstlUkPcYDJ1a+/v7+SdXL79m2aNm3K49f+jJ6/g3JtJpO37gjy1R9J\n1S4zef76y2IOo5OScYDvP2r8YNXKFoy3775tNNogmTNnYvHixQwePJigoKA4S18aGBgwe7ZGVKFQ\nIzduPoj5+z95qW5N6axZs3Lz5k3luNkvP3Li4j1evfVTgrUBHLNnUh5rU9sA/vrrLywsLDA3N49R\nHwRQdrmj1i7OmzcvAAtGtY3ztadXUmQTRAjRAKgrpewrhKgKDJZSNhRCHAIWSim3CyFaAD2llL/E\ncn0OKeVLIYQtcBD4n5Tyv2htZKdOnXBycgLAxsaGEiVKKF9U7VJRf5xyx76+vlhbW+Pl5UXv3r0x\nMhTsXfQ7zo62yjJWa1DS4rFE0m7YMgwNBGumdE/Q9UXzO9Bj7BrOXo1UT5FSfvb9KlGihCJ+G5Wp\nA5sxfLYHABkyZGDXrl1UrVqVxo0bs3PnTtrWK8vE/r/y4vV7KnWK6T2qUKE81tY27N+/nz///JNi\nxYrpVLBr36Ac4/tpSnxqCyJpsbOzY+PGjVStWpVp06YxfPhw1k7pyk8l8yXr+w9w9pqX8mO57dDl\n1C+M/tWdCDEZ6ACoADMgI7ANaCylzBjRRqCpPGcd54007cYA/lLKmdHOp+uaIOmt78T2e/jwYdq0\naY2Pz1ty5chCp0YV6NCwnE7aVUJJyXoknUasoEmNkorYQGL61hqVfPnyKZqAcRGXms+JVUOp3GkG\nAJs3b2bFihXs378f0N2J7TtxHftORqY3Fi9enCtXrmBnZ4ePjw8qlYrOnTvrxBYK4MY/YzE3M+Xa\nvWc06a9Z4pYqlIvLtzXlQSdMmEDRokVp0qQJQsDDfSkrjPpN7AJLKUdIKR2llHmA1sARKWUH4IEQ\nQuu4qA7E+JQIISyEEFYRjy2BWkDKKX/qSRJq1KjBmzc+XL58mTz5f2Ca+78UbORGxQ7TGLd4F2eu\nPkyTGoarJnfVUVoB2PvfdaW2rnMdV1zqjYj12ll/tAQ0y8roqXDRMTAwICQkBLVazcOHkbNHrfED\naNmypWL8QGMcLt9+AsDjaGE6RkZGirCClBJDQ0Oda/38/JDAwTOa2iHF8jtSqnBuACqUyKu0Gz16\nNE2aaGaJ6didGycpHgcYYfAGSykbCSFKAwsBUyAI+E1KeUUIYQ8slVLWF0I4o5ktgka+a52UMsbP\nkD4OMP3h4eHBtGnT8Hr4kPd+fgggT86sVCqVj06NK5ArjZYD1dYPiU7JQo54zP5NOR48YzPbD+uq\nQ584cYJKlSolqJ/69euzd+/e+BvGwYIFC+jbt69y/OHDB2xsbKhcuTInTpwAdGtOv/H9SOVOM5Qa\nx7GxxK09tX764YvHlFi+iRlgVKSUx6WUjSIeX5RSlpNSlpBSVpBSXok47y2lrB/x2Cvi+RJSyiKx\nGT896ZNmzZpx/vx53r57R1hYGEuXLSN3vqJsP3qDql3+pGDD0cxwP8Crtx/SzG5yaFgYK3fErqp8\n5fYzOo5YoRzHVqKgcuXKOoHSn2PPnj2oVCodebOnT5/qpNV9Dm0AthZra2tOnTpFrlwag9e+YXnF\n+N184M3Mlf/qGL+oS+yrHmOYP6IN+Z3s+JbQZ4IkAenVBxib8kdK9BsfUkpWrVrF5cuXWb5sGYER\nmQ5WlubUqViYKj8WoF7lmLmtKcE/R64waPrmz7bZMrMX090PcOHG41ifHzRoEDNnzoz1uc8R/T0/\ncuQINWrUiLP9/v37Y9SYBt0slB8L5+bOo5cEBIXqtLG3teHkmmFU6/InT16++26LIun5RtGWSYxa\nPzat/BgKIejcuTPz5s0jIDCQwMBATp8+za/NWrDt4BX6TV5PB9flHD1/l3uPXyVJn+/8AuJvBMxf\nfxQDAwNCQ0MJCwtT6gBHpcXgv3SMn1ahu3379nh4eHyR8YuN6tWr4+npqRTNAhSJrbFjx8Zq/EA3\nC+XSrScxjB+At48ffh8DyJtLk9J4/vqjJBlzWkM/A/xO0YZSxIWNjQ3//vsvZcuWJTw8XKembGoT\nfdbar001ujatyImL97AwMyFrpgyUKJjrs/d4/fYD89Yf4dCZ2/i8jxQNXTu1Gz+VcNFpGxqmomDD\n0TrnYvusvX79mqdPn/Lx40eKFClC9uzZ42yb2pQoUYKbN2+gUmk2ntwndqZLlNIJoJH6evn2g3Kc\nGrPAVK0LnJ7QG8DEsXfvXkXaKCo2VuYIIZQAYNDkBw8ZMkSnFGRqIqUkODgYc3NzWrZsGau2npWl\nGX3bVKNn88qo1Wo27D3P3LWHmTa4Gb4fAhj659ZY753R0gzPaEonh8/epsfY1TrngoODY6g1R0f7\nw5EWa7DUqlWLh3eucmjpQOVcsaZj8Q8MYfDgwbHOUvu3q06rOmXJYfvZSLUkRb8ETgekx1zg8uXL\n6xz3aVUFr/1TuLzFjQsbR5LVJoNSSNvHx4dhw4ZhZ2enpHml5ms+fvy4sozbvHkzT5484f79+8pG\nwfXr16la/RemLttHoUajcak3EreFO3nr50+30aviNH6AkucqpeTDpyBuPfCm57g11K5dm6dPn3L0\n6FGklPEaP9DIjSWl8Uuq91xKycGDB/n4KfJH7sb9F/hH6B7+8EPsu7zz1h3BLotVmpzRfin6qnDf\nKZkzZ0ZKSWhoKKampizedJzFm44zz7U1DaoU5/zGkTrtV2w7ydTl+zExMcE2a1YaNmpElSpV0sTs\nRrurqaVIkSLs3LmTGTNm4OnpSceOHalZsyYfP36kSZMmSggIwLn1I7h06wnz1x9hwYg2GBsZ0mLQ\nYi7deqpzzwMHDuDo6KgTo5de6dGjB4aGBhz4O3L2p/EJC9RqyaBBA5k9ezYDBw6Mca1LvZE0qlqc\nYgVycuO+N63rlqZs0dQrj/C16JfAeggJCcEpd25evX4NwPTBzWn+y48x2oWHh3Pp9hNmrTzI+Qgn\nf5UqVTh69GiaMISJIep4Lc1Nub59bIx0sOikh8+XNie7UKFCsf6f/P333/Tq1YtZQ1vSJFqAN0BA\nUAhjFu5k26HLVPz5Z44dP65kqBw+fJiaNWvqtG9UtThzhseUBksq9D7ABKI3gF+PVryzUql8rJrc\n9bNt7z5+RcO+81FFiKEeP36cypUrp8Qwk4STJ08ihKBixYoJap/WNoJiI6o/9OPHj1hZ6apHP336\nlNy5c/ODiz27Fvzvs/c6efk+PcetIUylxtfXl4wZMwIovtfoLBndjlo/F0miVxKJ3geYDkiPPsDo\n3Lx5UwmcXTGhU7zt338I5N6eSZxaM4xCzjmoUqUKGa2s2L59e5KM53MkxWuuWLEiP//8M1JK6tat\nixCCMWPGsG/fvljb29vbJ1nfX0p8fbdu3Rp3d3fUarWO8QsODmbGjBnkzp0bJwdbPGb30bnuo38Q\ns1cfpP+U9azeeRq1Wk3FUvm4vm0M4eHhSrlM0NQKllLGqDPce8K6r3+BqYDeB6gH0PjNAJwcssZZ\njjE2ctjasGdRf+4+ekXfSetp2rQpJUuWwMjQCFNTUzZu2oSDg0NyDTtJiJ5uplarFd9oeHg4RkZG\nvI5wD6RlosphReXkyZO4ubkB8M/cPpgYa772rrM92HTgotIuf7587D+1l+XbTtGzeSVGL9gBRMph\nRSVLliwEBgYqAdUdG8Us8Zke0C+B9QCRPrGvjfU6dPY2y7edRKolV+48JUwVTqGCBShXvgKzZ8/G\nxsYmTYeHfIu8fv0aR0dH8ubMwt7FvwPw99YTTF0WOdstWbIkly9f5uHDh0phJTMzMwYMGMCUKVO4\ndOkS7du3Z/HixUo2StT/v+SKEdT7ABOI3gB+OT///DPNmzfnjz+Gcm/3xCS7r0oVzuYDFzh87i5H\nz9/B0tKSFi1asHLlSkCjhbdy5Upy586dZH3qiYnWUN3dNQHjiNmf1zMffukxi4zW1liYm3Pz1i0y\nZdKIqA4YMIDRo0fj4+PDggULMDU1Zc2aNfj4xF4/+taOcZiZmiTL2PU+wHRAWvYLxceRI0c4ffo0\ngwYNokHlYgm+LiF1OYyMDGlbvzzLx3dixYTOFHKyZe+u7dSvXJRh3epw+eI5nJycsM+Rg7lz5+rU\n1f0c6fn9Tum+tRJYB/4aQLhasvv4VZZsPs7KHaeQwMCBA/F++VIxfgBz5sxh3LhxFCpUiFXuy5kz\nZw4fP/gxuld9zq53JWOGaJsg6XjeofcBfudErSo2c2iLZOunapkCVC1TQOdcrxZVePD0DX+uPMCQ\nwYMZOmQItevU4e+//9bJb9Xz5fzWpw8lCuaidq85gOZHydjYGLVajYuLC3Z2dgQEBCi1XbR4eXlh\nY2XB5S2jFRHYJZuPUb6tZqlbME927jzS5GF3Hr2SjTN6puwLSyL0M8AkID3XBIm6W3jg1I3PtNQl\nqRSZXXJlY4lbB+7sGs8fXWpz6r+j2NvbI4TA1dU11ti79Px+p3Tffh/8eP/BXzm2tbUlKCiYkJBQ\nHjx4QJ8+fciQIQPlypVT2oSGhnLhwgVy2GqyYrT/149faHZ+e/ToAaaR6XCVfowspJTe0BvA75xK\nlSrxKaIAun0qljs0MDCgW7OKXNw4kkURxXemTp2aJlWi0xPbtm3HwjobQggymJtSzDkLx9yHcGvH\neLz2T+H69jH84GLP+fPnyZJFI0BrYmKCgYFAFaUSnnMdVzYfuATAjz/+yO3bd5TiTDNX/otvFCOb\nntAbwCQgvfmFAOXD/fz5c7JkyYKpiTHF8jsm+Prkqs0rhKB6uYLKsampKRUqlCckJEQ5lx7f7/hQ\nqVS0bds21vSzr+m7atWq3Lp9mxEjRmBqbsGhM7c5dPY2ZqYaiS5LczMlKNrX15cDBw4AYG1tw/2n\nbwA4E6XAU+/evejVqxcAhQsXVs6XbjUp0WNLC+gN4HfIiRMnMDY2xtjYGEdHR0JDQ+OsS5samBgb\n47V/Cg/3TcatV33Onz+Pubk5mWxsKFigAE2bNqVv376sWrWKrl276swSQ0Njattp0S6nHz9+zKVL\nl6hfvz6+vr7J/no+R82aNRFCYGxszIYNG9jm4ZEs/UycOJG373wZNnw4k/7ey/6Tuu6Ou7snkitH\nZv4YOlRzfPcuAEHBocr7dvDgQRYvXqJz3a1bt4DY6xenB/RhMN8pUWO4/lv9B5duPqFh1eJpMjZP\nSsnl20/ZedST4xfv8fRlTKNlbGyMqYkJ/gEB/PTTTzg6OrJ79y6yZrWlVKlShIWFsXv37jj7yJfP\nhZEjR+lkPXz69Il9+/bRvHnzJE+Dk1JiZmamY7ATUy/kayhevDjXrl1Tjg0NDKheviA5s9ng/s9p\nnj59ypo1axg5ciS1KhRmyZgOlG0zGf+gUIKCgnXuNX78eMaMGcO93RMxMkp4AH1C0ccBJhC9AUwc\nHh4erF69WhFFPbvOlWxZMqbyqBLPoxdvOXDqBoHBYZgYG3L1zjMevniHgRBky5SBdx8CUEswMjQg\nj0NmShbMRcYMZjx49pbOjSoggX9P32TiX3sAGDNmDMWLF8fExIQGDRoo/SxZskRZ+vn5+dGgQQMu\nXLhAeHg4Tk5O7NmzhwIFCsQ2xBgEBAQoRcejM23atK/SXfTz8+Pt27fs3LmTQ4cO8eTJE/z9/blw\n4QLZsmUDYOvWrXTv1o3pM2bQqlUrNm3aRK9evRj7WyPGLtJ8HqSUtGzZkm0eHtzfO4lnr32p0mkG\nlStV4ngUNR0vLy/y5s3L+QgJtaRGbwATiL4mSOKpXr06R48eBWB8v8a0b1A+nisiScnavCnRt++H\nANoOW8YT73eKO6BQXnvcJ3RimcdJlnv8hzAwQADhscQrrlmzhvbt28c4H73uyoYNG+jZswf+/gFU\nLp2fWUNbkNk6A1JK3LefYtLSvdSuXYvly1co+cdatP/Xz549I3++fASHhDBhwgRGjRqFlJL+/fuz\nYMECACwtzHC0y8SjFz6EhKrw9/ePEeoSFUdHR5ztLHj43IcXr9/j7+/P7du3KVOmDGWLOnH++mOl\nbePGjVmzZg1WVlb8999/VK5cmX//HoBLrqQvmKQ3gAlEbwATT/Tl7s1/xmFulrCI/m/NAEZFK6wa\nddn7+u1H9v53jY8BIeTNaUv/qRt0rsmVKxdPn0ZqCObLlw8p1Xh5PcLU1BQzUxNCQkMJDgrml58K\nM294ayUrQ/e1PWTA9C34+H5k3bp1tGnTRnlO+39ta2uriBH06tWT3r370LhxI7xfeDP5919pUr24\nUnB+yJ9b2HboMmXLluXcuXNxvuaSJUvy6OFdVk3sQpPfF3H+/HnKlCnD8uXL6d69u9Iug4UpQSFh\nZMtmx4kTJ3BxccHU1JQCTtn4Z+5vSe5C0RvABKJfAn8ZKpWKKVOm4ObmRpF8Duyc3y+1h5RuCA9X\ns+u4J6Pm7aBCcWfuPn5Nfic7zl71wtTEiLJF8/BrjZI89fYlJEyFqYkRLWr9iLWVRbz3HjZrKzuP\nX8fP7wNmZmYEBQWxY8cOzp07x5MnT3BxccHFxYVu3bphZGSElaUZh5cPVpahz175UqVzZFH1SZMm\nERgYyNatW7h79x7//fefjhSYsbExKpUKJ4esPPF+R2hoKNmyZaNt27YYGxszatQo3r9/T+HChRVV\ncDNTUy5cvIhKpaJUqVI0rVmSqQOaJkpMIz70BjCB6A3gl6NWqzE0NKRmuUL8Pa5jag9HD3DL6yUN\nfpsHaGbqUkoMDQzImskKM1Nj3r7/REBQCIcPH6ZOnTpUL5ufxaMjl+Bacdd169bRtm3bGDOzly9f\nKkWbtMo3jasV562fP6euPOTjx4+KBiCAS9683Lx1CyMjI9auXatsFhkbGXH5yhWWLFnMkiV/UbGk\nC+4TOyfZ+6DPBU4HpPe4NK3U02K3dgm+JrniAPV9awgNiQxLklLSo1kl1kzpxpl1wzm6YjA1yhUk\nZ04H7t+/T1hYGGc8vbh864lyTZu6ZQFNfY8xY8bEuP/p05HF3W1tNaUvf2tTHfcJXTAyNCRr1qz8\n/rtGOWbmkBa8evkCx5wOhIWF0bFjRy5cuICJsTEg+aVmTRYsWMiKFSs4ceke9X6bzxPvd8nxtiQ5\negOoR/ml3/rv5VQeiR4tJQpp6pxYWVlRsWJFdh67pvN8SJgKHx8fPD09OXr0KAUKF6HV0L85deUB\nAJN+/5VShXNTokQJxV9oamKsXL9jxw7l8ZUrVwDoOnolRkaGDOxQk9DQUCVDKLutNWfXuxISHEjZ\nsmUICwujdOnStO/QnjBVOK9ev6Zv37507NiRGzducMfLm2pd/6Rih2nJ9wYlESlqAIUQhkKIK0KI\nXRHHZYUQ5yPOXRBClInjujpCiDtCiPtCiGEpOeaEkN7yQ6OTP39+AP7aeiKelpGk1gbI99R3h4bl\n8f/0ibt37vApMFin7/mubWhYpSibN66lWrVqXLhwAXt7ezq4LqfNH0sBcJ/QGdDU8gCwNI/c4NIG\nOgM4Ozuzd+9eXrx+D0QGNd+7dw+AvI7ZsDAzYdvsPjy4dw8rKyuyZcuGShXO0qVLlXuAJjukRQuN\nqIa3jx87jlzB67kPznVcca7jyqUos9S0QErPAH8HbhEpoDMdGC2lLAm4RRzrIIQwBBYAdYDCQBsh\nRKGUGe63z9q1a/H29gZIN8uW74VxfRtT6cf8+Lx9S2BQCKevRKakGRkZMn1Qcy5uHMnOBZqNqx49\netK4cWN83mvycq0szRjQvoZi7Hw/BCjXnzt3jjVr1ijHTZv+qjyuX6UYLrmyKTPAcJUm7CdPzqx4\nbh1Nz2Y/4+Pjw+rVq+nRowdt2rRh8ODBeHt78+HDBzZv3oy/v7/m/Iwt1Ow+S7l3i0G6mSSpTYoZ\nQCFETqAesAzQOjVfAlpZCRvgRSyXlgUeSCkfSynDgI1A42QebqJIzz7APHny0Lt3b0Dja0qoJt/3\n4IdLC32vmNAJm4hd4yPnbsfapoiLA7ntszB9+nQuX7pEAafIeLz+7WuSwSL2GsarV0cWex86VBN8\nPW7RTrx9PuD13IerV69SpkgenryM/GE0MjJkYMdf8No/hQd7J2GdwZyjR4/y4sULHBwcsLGx4dSp\nU1haWrJ+/XqePX+uyOYDdEhErGlKkJIzwNnAUCDqN2w4MFMI8RSYAcRWl9ABeBbl+HnEOT1JQMWK\nFVmyJPJX+Y3vp1QcjZ7oGBgYcHnLaLz2T6FmhcKxtmnYT7PpEBQUxLPnz+nS+Ced569tG8v2ub8B\nGgFUc3NzKleuxD///KO0GT9+PHPnzmXroatU7DAVU2MjOjaqwLqpXbl06zHz1h2OdWwZLEzx8fHB\nwcGB+vXqArq1Sezt7QkM1BRgz2Jjydi+jb7uDUliUkQQVQjRAHgjpbwihKga5anlQH8p5XYhRAtg\nBfBLtMsTHNvSuXNnnJycALCxsaFEiRKKj0w7U0qO46pVqybr/ZPzGKB58+Zs3boVgDlrDjF1YDNl\npqP1O0U/1p6L6/nkPC5f3DlF+0tLx1q0x553n3HzgcaFYWxkQL+2VSldxCnG9UHBYZibmfDixQsC\nAwM5duwYFy5c0Pk8FCtWDP+AAC5cuEDZsmXJkdWa3hPWceTcHUDz2dDW/tDef3DnWgyavpkmTRoz\nZOgfbPXYRkhISIzPG8A7vwAlHOdzr+/sNS+eR/gjk5sUiQMUQkwGOgAqwAzICGwDGkspM0a0EYCf\nlNI62rXlgbFSyjoRx66AWko5LVo7fRzgF6BWq2MUKEquAjd6kh4pJU0HLGLG4Ba45Mr22bab91/A\nde527HNkp2279kyfHsPlDkDPnj1ZunQpmTJa8ikwhDFjxjBlyhQCAwPp364GAzroFkd3nePB5gOX\nYnWfqFQqjI01u8+n1w0nexbrGG0+xzcRByilHCGldJRS5gFaA0eklB2AB0KIKhHNqgP3Yrn8IpBP\nCOEkhDABWgE7U2LcCSU9+wBjUzlJiAjp9+SHS8t9CyHYPrdvvMYPoGWdMozuXZ8X3i+ZMWMGs2fP\njrVdx44dccyZk8rVanL37l0qVqxIQEAA8+fPZ966w3gcvKTTvmb5wopklkqlYtq0abRq1YosWTJj\nbGyMEIIFI9sm2vilBKkVB6idqvUEpgshPIGJEccIIeyFEHsApJQqoB9wAM0O8iYpZezeYD1fjIlJ\nZIhEvvqjUnEkepKTn4u7KI8PHjwIgKenJ40bN+b2bc3XqmLFijx99ox//vlHCW8B6NevH0ZGhsqS\nW8syj/+Ux+XKlWX48OFs3+ZBmUL2ZMxgxu0d46lXqWhyvqwvRp8KpwfQFEbXSpwDeMyps9XhAAAW\nS0lEQVTuQ8mIYFw93w5qtZpKnabzxtcfK6sM3LlzFycnJ4KDgylcuDDnzp3DwsIiTv1DIQS/t69B\nn1ZVafvHUu4/fcOngGBGjBjBpEmTcHLKjUMmY9ZO7R7r9Ynlm1gC60n7nDlzhrdv3zJqlGb2N2vV\nv6k8Ij1Jzd3Hr3CpN5KXPh8IDw/Hz+8Dbm5u/O9/Gkn8W7duYWVlhaGhIRYW5jRv3pygoKAY95m7\n9jBFmozh8u2nfAoIpmbNmkyaNImdO3fy5MlTWtaONZ8hTaI3gElAevYBarGyssLa2pqJEzWF0U95\nPiQgMDjO9mnNF6bvO37y57ajYknNEnjy77+SwcKMd+/eMn36dJ3qezf+GUf9Sj/g4eHB/fv3dT5j\ns2ZpgppV4ZEbHtrMj359++KYIzONqhX/qnGmJHoDqEfByMhI54vw6++LuHLnKf6fMYR60g9CCFZP\n6YbX/im0rluW/u2q4+GxDSEElpaWtG7dGgszUyzMTJg+qDnZslgzaNAgnXsMHDhQ0UtUq9W8ePGC\nnj17IqXk2fPnlC6cO5Ve3Zeh9wHqiUFcopZXtozC2ipuVWE9aZ93fgHMcN+PgRA457LlT/cDhIaF\n06xZM9zd3bGxtmblpC5ULJWPjfvOM3rBDlSq+KMCgoODMTc3Z8WEzlQtk7DSAAlB7wPUk+JIKfH3\nj1nntWSLiakwGj2JpfNIdwo0GBVrXN7Lt35sPnCRfafvMnPlIULDwhkxYgSvXr4kp4MDaim5+UCT\nkVoknwPh4WoeP34cb59du3YFIKdd6tWW/hL0BjAJ+BZ8gNGxtLRESomfn5/O+Rnumrqx6dkX9q33\nfeLSPcJU4Vy9+zzGc0VcNFmkHz5+JDgkBLVazalTp7h8+SIfI8QP/rv8QGlrZWnOkCFDPtvf9evX\nFXmt5KgLkpzoDaCez2Jubq5UjgNYvOkYznVcWb7tvwQLJ+hJfnqPX0PN7rO4FSVG7+EznxjtJvyl\nKQ1qYWHB7du3MTU14fjx48wa2oIi+TTG8fz1R0p7m4wWPHjwgLjcSzdv3qRMmdI4O2Ti4ubRSfmS\nUgS9D1BPvEQvEBQVfdpc6hMSGkahRm4AlP7BiYs3H5MrVy6CPr3n3IYRXL//nGUe//HoxTtu3H9B\n27Zt+eWXX+jZsydZbSzZt7g/GTOY027YUs5c9UIIeLhP8/+66/hVBk3bTNGiRbjieVWn365du+Lu\n7k7xAo5sm9MnWWpK632AelIdIQQqlUrJHIiKKgFpc3qSF10FH80kICgoCJ/3n3jj+4kxC3ey69g1\nMLHB09OTPHny0KVLF34s5MjOeX3JmMEc0JRGzWJtyf09k5S7BQeHEa5WK2UTtISEhODu7g7Allm9\nksX4pQR6A5gEfIs+wOgYGhpSs2ZN/Pz86NatG2ZmZgCMW7wrRfqPSnrww6Vk347ZMyuPHz7zQQjB\nf/9p0tMyZTQnOCSMXI6OXL9xg+LFizNp0iQql87P+uk9yJIpsph5XsdsXNg0Sme2PyGiYHxel3yx\n9l22aB6MkrAKXEqjN4B6EoW1tTUeHh4EB2tiA9ftPsee49fiuUpPcmMSUWPY2NSSTZs2MXfuXDJY\nmGFsZMSjF2/JEFHEPEtmjbHs37Z6nPfqMsqdjwGaDJAz64ZTwMmO06dP8/x55KbK+/cauSqrOMRW\n0wt6A5gEpPeaIInl4sWLin4gwP+mbGDF9pMp1v/3UhMkMX23qlMagBXu7jRr1ozNmzZRrpgTfp8C\nCQlV0bdvX+rVq0tWaxOubBlNqTgClsPD1Ry/eI+f22vU5izNTdmzqD8ZLEyVUBeA7Nmz87///Y/D\n5+7wPorUfnpDbwD1JJq8efPSrFkzWrVqpZyb+Nce5q6NqRqsJ/lZtfM0a3adBcDX15cFCxbw3u89\n4/o2pvsYjex937598fcPYNHIdlhbWRAUHEr++iOp1VNXEktG+BADgkJwruNKgQajKNF8Ah/9g3Bw\n0BViHzduHACvfT8m90tMNvQGMAn4HnyAsfW7cePGiKR6P3777Tfcd5yO/8IkIC364VKz73GLNH5Y\nSwsL6taty6tXrzAQBqzecZpr914wYsQIAIyNDHF21NQA/vf0LVThah48fcP1+5FLWyNDQwrkscPS\n0pKFCxcy2m0M7Tt2ZuPGjSxfvlyn30yZMpE7Vy4WrD+SHC83RdAbQD1fhYGBAdbW1ggh+PgpkPcf\n0+9yKD3iHxgCwKpVq/APCEBKycKFC8nraMumA5eoWrUqZ86cIaOlGXd3R2bylCuaR3nc+H8LKfrr\nWKSUDJ6xmbuPXhMQEICdnR0PHz6kZcuWtGrVKkYolFqt5r3fe7LYZCC9oo8D1JMkvHz5Ent7e0b3\nbkCXJj+n9nC+G5zraOqIqdVqhBB0796dtWtWU79yEbYduoKpqSn16tXj2sVTHFw6UOfaNkP/5lyU\noGcjQwMdlRctgwYNYubMmTrnLl++TO1atfjw8QMnV/2BbWarZHh1+jhAPWmUd+/eIYTgw4cPAOTI\nkYO8eZ31O8KpzNmzZwkJDWPboSuAJl5PCEFQSFiMtv9v79yjq6rOBP77yIOEZ4CLIgsLqAvowADC\nDJkWrCAtpcpLUYIgYEHwBUhdFUEQFYIwRUMtVcsMVoQipNYOpjhBQUWRN8gbkhgQYpBniQOYEPLY\n88c+9+Yk3OTe3Nxz87j7t9ZZOWe/vv2ds++XffbZ+9urF03irvhOnuvComKaNWtWak5fK1dT0tLS\nrsv7xBNPkPN9DltXznDM+IUCYwCDQDiOAbpcLgCef75k+dPcufP46mgWWaed3WC9Jo7DVYfsj7aU\nePB2G609e/YwYcJ44uLimDJlCocOHWLbtq20cjXxWuayl8YxpG832rVrS0pKCjk5OSil+PWwn3J8\n/QIu5+bTpElJ3oKCAhYtWsSOHTsoKiqmcUMzDcYQhixatAig1MY6o0aNAmDApMXlrh01VJ3i4mLu\nfeoNHp/3F0BvRASQkZHB5MmT6d27D/fffz9LliyhS5cuXM29wvwpwzz53167ha9P6JUdp87msGXf\nMU6cOMmQISV79o4Z/BOWr93CD7lX+fTTko8cgwYNYvr06Z7r7y/nOqqr05gxQEPQsK8Zzlg3j8jI\nkGw7HXZ8tjOdCXOWe65zc3NJTU1l+PDhnrDoqEiuFRRyb//befWZEZ7wqS+/y7ovDgKQvi6RtOOn\nGTr1dUCv9ikqKuLmVs35fPkzDJi0mMysczzwwAMkJycjIuTn5zNgwAB279rB5nemE9c41tFlcGYM\n0FBryMvLY/t2PR/trb9vqeba1E2ee+1/PMYvOTmZ/v37ExcXV8r49f33jhz8+wscX7+glPED2LA9\njc6dOwNwOPMU/9qhDcfXL2Bov+6e7VD/snACT85fxbdnLgLw3nvvMWvWLADq169PSkoKLVwt6Tli\nHrf+6jnGP/+202o7hjGAQSAcxwC9yW3QoAHx8fG0bt2aLfsyHZNdk8bhQkVRUREdB89mTepOWrZs\nSVZWFgkJCezasZV77tAGbfu7Mzm+fgF/nvcwUVHX974zs86Sf62APn36EFGvHo/OXeWJGz6gp+c8\n/1oBZy5cIv9aoSesV69envOmTZuSlfUtGzduBGDTrgxuGTiTP6yqfRPhjQE0BJ3Y2NhqNVJ1kZ4J\niRQUFJGYmMi5c+dITU0FtCeWV58ZwfH1C7ihufcPHW7qR0UBsHTpUoqKizl/8RKJln/AQ7bJ0EOn\nvkHGybOe5XWgDXDZIab09HSaN2/u2Tv49ys31jrvQGYM0BB0MjMz6dChA1tXzeBGHz9Kg2++yT7P\nLyYuZuKkSWRnZ/Pll5u5dOkSo+6OZ57t44Y/bNqVzvjnl5cKezyhL9073syjc1dWmDc/P5/o6GgK\nCwuZNm0ar7/++nVp0tclEhUZPO8wTo8BmlFqQ9C57bbbaNigAWs37uXREXdWd3VqPePnrKBtu7Z0\n7dqVpUuX8qs+XZgy+i46tb+p0mV527DozeRNCHpXQPcX5bJ06tTR0wOcOXOmV+MHejJ1bSKktRWR\nCBHZKyL/sK6Treu9IvKNiOwtJ98JETlgpdsZyjr7gxkDvJ7OXTrz6c7rJ9AGg3AZA9y8J4M7xv2O\nk99d4E9/WsqTTz4JwGszRwZk/Nx8ueJZbrXWBLtR6Ok0cx4bxGszRnrCH3zwQZKSkjh6NI369fWc\nv4ULFwIQEVGPrz+cz8A+nT3pa5tj1FCb66eAI1hua5VSCUqp25VStwPvW4c3FNDXSturnDTVxr59\n+8JOti+5Q4cOY196tiP7hhw59p3vRA4RStnjZr3NqbM5rF27lpEJCTRpGMPO1bOq7oBUvO8X8tiI\nO3l4WG8G9+1GVFQkCxcuZP/+/Tz99NP061vSk4+IiGDbtm0UFRVzraCQpOklX5qnLVxTtbqFmJAZ\nQBFpA9wNLAOkTJwAI4DVFRXhXO2qRtmd08JBti+5EydOpKCgkEtXgr+p+qUfqm+j9lDJzr16jXr1\n6hEfH8/YsWMpLMhn5N29cDWrmuOBnz60gD5jtK8/9+tq7+63cjRlLtPHDwTg8LFTFBQUsnXrVrp2\n7QpAWnpGqXLS09MBOHn6IjHR0fzvm1MBSNm0n0dfqngssSYRyh7gYuAZwFuX4A7grFLqWDl5FbBR\nRHaLyESnKmgIHi6Xi4iICPamZVV3VWola1J3EhkZwdW8XKIjFFtWTicmOqrK5fb48Y8AmPbQzzn8\nwVyOr1/AyoWPUN9W9rGsCwCkpKSwZo3u0Y0aNYpXXnnF06N3O+I9mPEtAJ3a38Sx1JcB2LDtCF8d\nOVnluoaCkHwEEZFBwDml1F4R6eslyYPAuxUU0VspdVpEWgIbRCRNKbXZiboGgj8bR9c12f7Ibelq\nwRe7M+jXq5PPtJUh+2xOUMurabLz8q+RtGIDN97YigMHD/HO/PE0ahATFNl/nDXaZ5oh/boxpF83\nruRepf8jSZy/eJmkpCQAUlNT+eSTT2jbti3dunXlxTfX0SKuEXfF/xgRYdV/TmTcc2/RqEFMlesa\nCkIyDUZEXgbGAIVADNAEeF8pNVZEIoFsoIdSyucAi4i8AFxRSr1aJtzMgTEY6iBOToMJ+TxAEbkT\n+K1SarB1PRB4VinVr5z0DYAIpdRlEWkIfAy8pJT6OGSVNhgMdZLqmrRjt7oJlPn4ISKtReRD67IV\nsFlE9gE7gHXG+BkMhmBQZ1aCGAwGQ6VRStXoA3gAOAwUAT1t4b8AdgMHrL/9bHHRwH8B6cBR4L5y\nyp4JfA2kAQOCJHuTVd5e63B5KbcdkGdL80Yo5Dqlsy1NCnCwHLkV6uykbF96B3i/1wP7rHxvAVGh\n0tkf2U48ayAW+BD9mzoELAjkWTsl1x+dr0vvK0F1H0AnoAPwGfpDiTu8O9DKOu8MZNviXgLm2q5b\neCn3X6xGFGU9sEygXhBkl0pbQQOp6MfqlFxHdLbC7gNWAQcC0dlh2RXqHeD9bmQ7/xvwUKh09lN2\n0J812hDdaZ1HAV8AA51u35WQ61PnskeNXwuslEqD65fYKKXsSxGOALEiEqWUKgB+DXS0pfXmo30o\nsNpKf0JEMoFewPYqyoYqTtp2UK4jOotII+A3wCTgr34p6QUHZVeodyBylVJXrDxR6DeOC5XX2FHZ\nTjzrPOBzK02BiHwFlN4s2Bmd/ZXrU+ey1K6Vy+UzHNhj3Zw4KyxRRPaIyF9F5AYveVqjp9+4ySaA\nh2mXbQt7x1q3PLuCfO2tNJtEpE+I5Dql8zzgFcCXf/Sq6hyo7GDofd39FpGPgLNAnlJqfTn5nNDZ\nH9lOtm+s39lgoDwngE60b19yK69zRd3DUB3ABuCgl2OwLY3XVzx0VzkTaG9du9CrTe6zrn8DrPCS\nbwkw2ib7InCyKrKtsNbW30bAR8AYL/mirTIPoscrrqHHRJyWG3Sd0a8tHygfrz6Wzs0s2WV1dlr2\nkjLtyq53QPfbFlcfWAuMC4XOlZDtSPu2wiOBVGBqBc86qO3bT7lLgNG262WUM/7vSVNRZE06vN0s\noA36Q8dPbGGCnijtvr4ZOOSlvBnADNv1eiC+KrK95BsHLAlENyfkOqEz8BhwCvgG+BbIBz4NVGcn\nZPurdxXu9xjgj6HQ2V/ZTrZv4M/A733pG+z27UtuZXT2pPFXieo+rJtl/2IUB+wHhnlJu5qSL0gP\nA8le0rgHTKOB9sAxrGlBgcoGIrC+vqIHYv8GTPJSngs9uRvgFnRXPS4EcoOuc5k8bSm/F+aXzg7J\n9kvvStzvhsBN1nkkkAxMCIXOlZDtyLMGEq325bUsJ9p3JeT6rbMnT0WRNeEA7kX/d88DzgCpVvhs\n4Aoln9o9Uz+AH6EHTfejXwHaWOGD0atI3GU/h+5qpwG/rKpsq3HutuQeQjuAkLKy0eMbh6x8e4B7\nQiHXCZ3L5G2H7UtsZXR2UrYvvQO43zcCO637fQBYFMhzdlK2Q+27DXp46bAtfHwI2rdfcv3Ruexh\nJkIbDIawpa58BTYYDIZKYwygwWAIW4wBNBgMYYsxgAaDIWwxBtBgMIQtxgAaDIawxRhAQ61CREZb\nznGDXe5sEfks2OUaajbGABoCwlrkPivUcpVSq5RS3W31WC4i/x3qehjqBsYAGgJFUXprA4Oh1mEM\noCGoiEhbEflARM6LSJaILBaRGFt8sYg8LiI7ReSSiGwTkY62+MYiskJE/iki34jIWBEpFJGfWfEP\ni8jX1vl0YBQwTkQuW+XVE5EXRWRDmXqV6rGKyD0icsTK9w/0kit7+hYi8palwzkRSS7HrZqhFmMM\noCFoWFucfgh8h16P/R9Ab7S/Pjvj0F6cXeg1oUtsca+h1/V2BLoC91BOO1VK/Q7tCXq5UqqxUqqJ\nUqq4nOp5eqwicivwPnqBfVPgD8AjtnhBu5kqQrtmagtcpuK9qw21EGMADcGkF3Ab8LRSKk/pfZ5n\nA+PLpFuklMpWSl0D3gH+DUBEItA9ujlKqQtKqcvoPR4qQqi8B+6RwA6l1LtKqWKl1Aa0wXPTE+gB\nTFZKXVbaI/GzwF0i0rqSsgw1GGMADcHkZuC8ZTDcHAdiRMT+innadv4D0Ng6d6FdGZ20xWf5kBnI\nOGSbMjIATlBiSNujnY2eFZEcEclBexjJQ/dsDXWEGr8niKFWkQW0FJFYmxG8BbiqlPJnz4wLaO/B\n7dBOTsG3wfH2ynsZ7SLMjt01ejbwyzLx7SgxpieBH5RSzXzINtRyTA/QECgCRIlIjPtAuzzPBF4V\nkVjrdXEe2pOvT5RSRehxthdFxCUijYH5PrKdAW6R0jvs7AZ6iEgPEYkUkcloA+dmDRAvIiOt+J+j\nN9RxswvYLyJLRKQ5gIi0FJGR/uhhqD0YA2gIFAW8gN6MyH38HzAB/YqZBewAtgG/9aMsN09ZeTPQ\nDj8/tuLzbWnt6Zehe3v/FJGLIiJKqc+BJLRL9O+AG4AvPcKUOgbcD8wBciyZy2zxCm0QBdgjIpcs\nPX7mQw9DLcM4RDXUaKwpMkfRmz6dqe76GOoWxgAaahQi0h64Cd17dAFvA7FKqX7VWjFDncS8Ahtq\nGjHAUuB79CvwFfTUGIMh6JgeoMFgCFtMD9BgMIQtxgAaDIawxRhAg8EQthgDaDAYwhZjAA0GQ9hi\nDKDBYAhb/h8tCAiqCvCZWAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9690b54c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "figures.plot_map(ax, bathy, PNW_coastline, coastline='full')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The problem in `plot_map()` was that the `zip()` builtin function in Python 3 returns an iterator object,\n",
    "in contrast to the list that was returned by `zip()` in Python 2.\n",
    "The `matplotlib.patches.Polygon` object constructor expects a list of polygon x-y pairs,\n",
    "not an iterator.\n",
    "So, the iterator returned by `zip()` is now explicitly transformed into a list.\n",
    "See changeset [b91036b579d8](https://bitbucket.org/salishsea/tools/commits/b91036b579d8)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### stormtools.get_EC_observations() str vs. bytes Issue\n",
    "\n",
    "Reported 2015-10-13 by Jie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from salishsea_tools import stormtools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Automatic pdb calling has been turned OFF\n"
     ]
    }
   ],
   "source": [
    "%pdb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'salishsea_tools.stormtools' from '/home/doug/Documents/MEOPAR/tools/SalishSeaTools/salishsea_tools/stormtools.py'>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reload(stormtools)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  7.22222222,   7.77777778,   6.11111111,   4.44444444,\n",
       "          2.5       ,   4.44444444,   2.77777778,   1.66666667,\n",
       "          2.22222222,   1.94444444,   2.5       ,   4.44444444,\n",
       "          2.77777778,   6.94444444,   7.22222222,   6.11111111,\n",
       "          5.        ,   4.16666667,   5.83333333,   4.44444444,\n",
       "          4.16666667,   3.61111111,   4.16666667,   6.11111111,\n",
       "          5.83333333,   5.27777778,   3.88888889,   3.61111111,\n",
       "          0.83333333,   3.33333333,   3.61111111,   4.16666667,\n",
       "          4.16666667,   4.16666667,   4.16666667,   4.16666667,\n",
       "          8.05555556,   5.        ,   5.83333333,   5.27777778,\n",
       "          6.38888889,   6.11111111,   5.83333333,   6.38888889,\n",
       "          5.        ,   4.44444444,   4.72222222,   4.72222222,\n",
       "          4.16666667,   4.72222222,   3.33333333,   3.88888889,\n",
       "          2.5       ,   4.72222222,   4.44444444,   2.22222222,\n",
       "          2.77777778,   3.61111111,   3.88888889,   2.5       ,\n",
       "          3.88888889,   5.        ,   3.61111111,   4.44444444,\n",
       "          4.16666667,   3.33333333,   0.55555556,   2.5       ,\n",
       "          1.38888889,   2.22222222,   2.22222222,   2.77777778,\n",
       "          2.22222222,   2.22222222,   0.83333333,   1.11111111,\n",
       "          1.11111111,   1.38888889,   0.55555556,   4.44444444,\n",
       "          7.22222222,   6.94444444,   6.66666667,   5.55555556,\n",
       "          7.5       ,   7.5       ,   7.77777778,   5.83333333,\n",
       "          6.38888889,   5.27777778,   5.27777778,   4.16666667,\n",
       "          2.22222222,   1.38888889,   3.61111111,   3.33333333,\n",
       "          3.33333333,   0.55555556,   2.5       ,   1.38888889,\n",
       "          1.11111111,   1.94444444,   1.66666667,   2.77777778,\n",
       "          4.44444444,   3.33333333,   3.61111111,   1.94444444,\n",
       "          4.44444444,   4.44444444,   3.61111111,   4.44444444,\n",
       "          3.88888889,   2.22222222,   2.5       ,   0.83333333,\n",
       "          1.66666667,   3.88888889,   4.72222222,   3.33333333,\n",
       "          3.05555556,   1.66666667,   1.94444444,   3.61111111,\n",
       "          3.05555556,   1.94444444,   0.83333333,   2.5       ,\n",
       "          1.38888889,   1.66666667,   4.44444444,   3.88888889,\n",
       "          4.44444444,   3.88888889,   5.55555556,   3.33333333,\n",
       "          3.05555556,   2.77777778,   2.22222222,   1.66666667,\n",
       "          1.38888889,   2.77777778,   1.94444444,   2.22222222,\n",
       "          1.66666667,   3.05555556,   2.22222222,   2.77777778,\n",
       "          2.22222222,   2.22222222,   2.5       ,   2.22222222,\n",
       "          2.5       ,   3.33333333,   2.5       ,   3.61111111,\n",
       "          2.5       ,   3.61111111,   3.33333333,   4.44444444,\n",
       "          4.44444444,   4.44444444,   2.77777778,   1.94444444,\n",
       "          1.11111111,   2.5       ,   4.44444444,   4.16666667,\n",
       "          3.61111111,   3.05555556,   3.61111111,   3.88888889,\n",
       "          5.83333333,   6.11111111,   5.        ,   5.        ,\n",
       "          4.72222222,   5.        ,   6.66666667,   6.94444444,\n",
       "          7.22222222,   6.11111111,   8.33333333,   5.27777778,\n",
       "          5.83333333,   5.        ,   5.        ,   4.72222222,\n",
       "          4.44444444,   4.72222222,   4.72222222,   3.88888889,\n",
       "                 nan,   3.88888889,   4.72222222,   3.33333333,\n",
       "          4.44444444,   4.16666667,   3.88888889,   4.44444444,\n",
       "          4.44444444,   3.33333333,   2.5       ,   3.05555556,\n",
       "          2.77777778,   3.61111111,   5.        ,   4.44444444,\n",
       "          4.72222222,   2.5       ,   2.22222222,   1.38888889,\n",
       "          1.11111111,   1.66666667,   0.83333333,   0.83333333,\n",
       "          1.38888889,   0.83333333,   1.94444444,   0.83333333,\n",
       "          2.5       ,   2.5       ,   2.5       ,   2.22222222,\n",
       "          3.05555556,   5.55555556,   4.16666667,   6.11111111,\n",
       "          5.83333333,   7.22222222,   5.27777778,   5.83333333,\n",
       "          6.11111111,   5.55555556,   4.44444444,   5.        ,\n",
       "          5.55555556,   4.44444444,   2.22222222,   1.94444444,\n",
       "          1.38888889,   0.83333333,   1.94444444,   3.61111111,\n",
       "          5.83333333,   6.11111111,   5.27777778,   5.55555556,\n",
       "          5.27777778,   5.83333333,   7.22222222,   6.38888889,\n",
       "          6.38888889,   6.94444444,   6.66666667,   6.66666667,\n",
       "          5.55555556,   4.44444444,   3.88888889,   5.83333333,\n",
       "          5.55555556,   5.27777778,   6.11111111,   5.55555556,\n",
       "          4.16666667,   6.38888889,   7.22222222,   5.83333333,\n",
       "          6.38888889,   7.22222222,   6.94444444,   6.94444444,\n",
       "          7.77777778,   7.22222222,   7.77777778,   7.22222222,\n",
       "          7.77777778,   5.83333333,   5.27777778,   3.88888889,\n",
       "          2.22222222,   2.5       ,   3.05555556,   1.38888889,\n",
       "          1.38888889,   0.83333333,   5.        ,   6.66666667,\n",
       "          4.72222222,   7.5       ,   9.44444444,   6.94444444,\n",
       "          7.5       ,   6.11111111,   9.72222222,   9.72222222,\n",
       "          8.88888889,  10.        ,   8.88888889,   9.44444444,\n",
       "          9.72222222,   6.38888889,   4.72222222,   3.05555556,\n",
       "          3.05555556,   1.11111111,   1.38888889,   1.94444444,\n",
       "          3.88888889,   5.        ,   5.83333333,   8.88888889,\n",
       "          9.16666667,   6.38888889,   5.        ,   4.44444444,\n",
       "          0.55555556,   2.22222222,   2.5       ,   1.38888889,\n",
       "          1.38888889,   2.5       ,   2.77777778,   4.44444444,\n",
       "          4.44444444,   3.05555556,   3.61111111,   4.44444444,\n",
       "          4.44444444,   3.05555556,   1.38888889,   3.61111111,\n",
       "          2.5       ,   2.77777778,   1.66666667,   1.94444444,\n",
       "          2.5       ,   2.22222222,   2.22222222,   2.77777778,\n",
       "          3.05555556,   4.72222222,   5.        ,   4.44444444,\n",
       "          5.        ,   5.        ,   5.        ,   7.22222222,\n",
       "          4.16666667,   4.16666667,   3.88888889,   4.44444444,\n",
       "          4.44444444,   3.61111111,   3.61111111,   3.05555556,\n",
       "          3.88888889,   4.16666667,   3.61111111,   3.33333333,\n",
       "          2.77777778,   3.88888889,   2.5       ,   2.22222222,\n",
       "          1.66666667,   0.83333333,   3.33333333,   2.5       ,\n",
       "          3.05555556,   4.72222222,   3.33333333,   3.33333333,\n",
       "          3.88888889,   3.05555556,   2.77777778,   1.94444444,\n",
       "          2.22222222,   1.94444444,   1.66666667,   1.38888889,\n",
       "          1.66666667,   2.77777778,   3.05555556,   1.94444444,\n",
       "          1.66666667,   2.22222222,   3.88888889,   4.72222222,\n",
       "          4.72222222,   4.44444444,   4.72222222,   2.77777778,\n",
       "          2.22222222,   2.5       ,   3.88888889,   3.33333333,\n",
       "          3.05555556,   1.38888889,   2.22222222,   2.77777778,\n",
       "          3.33333333,   3.05555556,   1.38888889,   0.83333333,\n",
       "          1.94444444,   3.33333333,   3.33333333,   3.33333333,\n",
       "          2.22222222,   3.88888889,   3.61111111,   4.72222222,\n",
       "          4.16666667,   4.16666667,   3.88888889,   4.16666667,\n",
       "          5.55555556,   3.88888889,   3.33333333,   5.55555556,\n",
       "          3.33333333,   3.33333333,   4.44444444,   3.61111111,\n",
       "          3.33333333,   3.61111111,   2.5       ,   3.05555556,\n",
       "          4.44444444,   5.        ,   5.        ,   3.88888889,\n",
       "          4.44444444,   4.72222222,   3.88888889,   4.72222222,\n",
       "          4.72222222,   4.44444444,   4.16666667,   4.72222222,\n",
       "          4.72222222,   5.        ,   3.61111111,   3.61111111,\n",
       "          5.        ,   5.83333333,   6.11111111,   4.72222222,\n",
       "          5.        ,   5.55555556,   4.16666667,   3.88888889,\n",
       "          4.44444444,   2.77777778,   5.55555556,   6.11111111,\n",
       "          4.72222222,   6.66666667,   6.38888889,   6.38888889,\n",
       "          7.77777778,   8.61111111,   9.72222222,   8.88888889,\n",
       "          9.44444444,   9.44444444,  10.83333333,  10.27777778,\n",
       "         10.        ,  11.66666667,  11.94444444,  11.38888889,\n",
       "         11.11111111,  13.33333333,  12.77777778,  12.22222222,\n",
       "         10.83333333,   8.05555556,   9.16666667,   8.88888889,\n",
       "         11.11111111,   9.44444444,   8.05555556,   5.27777778,\n",
       "          5.83333333,   4.72222222,   3.88888889,   1.38888889,\n",
       "          1.66666667,   0.83333333,   3.88888889,   4.72222222,\n",
       "          6.11111111,   4.44444444,   3.33333333,   1.38888889,\n",
       "          2.77777778,   2.5       ,   1.38888889,   2.22222222,\n",
       "          1.38888889,   0.83333333,   1.94444444,   1.94444444,\n",
       "          1.38888889,   1.94444444,   0.83333333,   1.94444444,\n",
       "          1.94444444,   2.77777778,   3.33333333,   2.77777778,\n",
       "          3.05555556,   3.61111111,   1.11111111,   3.88888889,\n",
       "          3.33333333,   5.        ,   4.72222222,   3.88888889,\n",
       "          3.88888889,   3.61111111,   1.66666667,   1.38888889,\n",
       "          1.94444444,   1.38888889,   2.77777778,   2.77777778,\n",
       "          1.94444444,   1.94444444,   3.61111111,   3.88888889,\n",
       "          3.88888889,   4.72222222,   5.        ,   4.44444444,\n",
       "          6.11111111,   6.94444444,   3.88888889,   5.27777778,\n",
       "          6.11111111,   4.72222222,   3.33333333,   2.77777778,\n",
       "          2.77777778,   3.61111111,   2.5       ,   1.94444444,\n",
       "          2.77777778,   0.55555556,   1.94444444,   2.22222222,\n",
       "          3.05555556,   1.66666667,   1.38888889,   2.77777778,\n",
       "          2.5       ,   1.11111111,   2.77777778,   6.38888889,\n",
       "          3.88888889,   3.61111111,   1.94444444,   2.77777778,\n",
       "          3.33333333,   1.66666667,   3.61111111,   2.5       ,\n",
       "          3.05555556,   4.72222222,   2.77777778,   1.94444444,\n",
       "          1.94444444,   1.38888889,   1.38888889,   1.66666667,\n",
       "          4.16666667,   3.61111111,   4.16666667,   1.94444444,\n",
       "          1.38888889,   1.38888889,   0.55555556,   0.27777778,\n",
       "          1.66666667,   1.11111111,   0.55555556,   2.77777778,\n",
       "          3.61111111,   3.33333333,   2.5       ,   2.22222222,\n",
       "          2.22222222,   2.5       ,   1.38888889,   0.83333333,\n",
       "          1.11111111,   1.94444444,   1.94444444,   0.83333333,\n",
       "          1.66666667,   0.27777778,   1.38888889,   1.94444444,\n",
       "          1.66666667,   1.94444444,   2.5       ,   1.94444444,\n",
       "          1.66666667,   2.22222222,   7.77777778,   8.05555556,\n",
       "          8.05555556,   8.33333333,   8.33333333,   6.38888889,\n",
       "          6.66666667,   5.83333333,   5.55555556,   5.55555556,\n",
       "          4.44444444,   4.72222222,   2.5       ,   2.5       ,\n",
       "          4.72222222,   1.66666667,   1.38888889,   2.5       ,\n",
       "          2.22222222,   1.66666667,   2.5       ,   1.11111111,\n",
       "          0.83333333,   0.55555556,   2.77777778,   5.        ,\n",
       "          5.83333333,   6.11111111,   5.        ,   5.27777778,\n",
       "          6.11111111,   5.27777778,   5.        ,   6.11111111,\n",
       "          2.22222222,   1.66666667,   1.38888889,   1.38888889,\n",
       "          1.11111111,   0.55555556,   1.94444444,   1.38888889,\n",
       "          1.66666667,   0.27777778,   1.38888889,   0.55555556,\n",
       "          5.55555556,   6.38888889,   5.83333333,   6.66666667,\n",
       "          7.5       ,          nan,   5.83333333,   5.83333333,\n",
       "          4.44444444,   2.77777778,   3.88888889,   5.        ,\n",
       "          1.66666667,   1.11111111,   1.94444444,   0.55555556,\n",
       "          2.5       ,   1.11111111,   0.27777778,   0.55555556,\n",
       "          1.38888889,   0.83333333,   0.83333333,   1.66666667,\n",
       "          0.83333333,   4.44444444,   5.27777778,   5.        ,\n",
       "          3.61111111,   3.61111111,   3.88888889,   2.77777778,\n",
       "          2.77777778,   1.66666667,   0.55555556,   2.5       ,\n",
       "          0.83333333,   0.83333333,   0.83333333,   0.83333333,\n",
       "          1.11111111,   0.        ,   1.94444444,   2.22222222,\n",
       "          1.38888889,   1.11111111,   1.94444444,   2.22222222,\n",
       "          1.38888889,   1.94444444,   1.94444444,   2.5       ,\n",
       "          3.88888889,   3.33333333,   3.33333333,   2.77777778]),\n",
       " array([ 100.,  110.,  100.,  110.,  120.,   60.,  180.,  200.,  110.,\n",
       "         170.,  140.,   90.,  170.,  160.,  150.,  160.,  150.,  170.,\n",
       "         160.,  150.,  140.,   80.,  120.,   70.,   40.,   30.,   10.,\n",
       "          50.,   90.,  200.,  200.,  180.,  180.,  180.,  150.,  110.,\n",
       "          80.,  100.,  110.,  150.,  140.,  170.,  160.,  180.,  190.,\n",
       "         200.,  200.,  190.,  190.,  180.,  190.,  190.,  210.,  200.,\n",
       "         170.,  160.,  150.,  100.,   60.,   40.,   20.,   60.,   60.,\n",
       "         250.,  240.,  240.,  270.,  120.,  170.,  150.,  210.,  240.,\n",
       "         190.,  260.,  270.,  260.,  300.,  280.,  270.,  300.,  330.,\n",
       "         320.,  330.,  330.,  340.,  340.,  340.,  340.,  340.,  340.,\n",
       "         340.,  320.,  300.,  190.,  220.,  260.,  230.,  270.,  330.,\n",
       "         190.,  120.,  150.,  230.,  170.,  140.,  150.,  160.,  120.,\n",
       "          50.,  130.,  120.,  140.,  130.,  140.,  130.,   90.,  180.,\n",
       "         340.,  350.,   30.,   40.,   70.,  150.,  180.,  170.,  130.,\n",
       "         170.,  190.,  170.,  140.,   60.,   40.,   30.,    0.,  340.,\n",
       "         350.,   30.,   30.,   70.,  100.,  120.,  140.,  160.,  180.,\n",
       "         170.,  180.,  180.,  160.,  190.,  180.,  170.,  170.,  180.,\n",
       "         190.,  130.,   40.,  130.,  130.,  140.,   70.,   90.,  100.,\n",
       "         140.,  130.,    0.,  160.,  170.,  160.,  160.,  200.,  210.,\n",
       "         160.,  200.,  210.,  200.,  190.,  190.,  190.,  180.,  170.,\n",
       "         170.,  180.,  160.,  190.,  180.,  170.,  180.,  180.,  180.,\n",
       "         180.,  170.,  190.,   nan,  170.,  170.,  180.,  160.,  170.,\n",
       "         170.,  160.,  150.,  170.,  170.,  150.,  140.,  100.,   60.,\n",
       "          60.,   60.,   10.,  310.,  300.,  260.,  270.,  270.,  310.,\n",
       "         100.,  220.,  250.,  250.,  320.,  350.,  300.,  310.,  310.,\n",
       "         340.,    0.,    0.,  330.,    0.,  340.,  330.,  340.,  330.,\n",
       "         330.,  320.,  320.,  330.,  310.,  300.,  310.,  250.,  350.,\n",
       "         330.,  330.,  340.,  330.,  320.,  330.,  330.,  340.,  330.,\n",
       "         340.,  330.,  340.,  330.,  340.,  340.,  330.,  330.,  330.,\n",
       "         320.,  320.,  340.,  350.,  320.,  330.,  320.,  330.,  330.,\n",
       "         330.,  340.,  330.,  340.,  340.,  330.,  340.,  330.,  320.,\n",
       "         320.,   20.,   70.,   90.,  130.,  100.,  270.,    0.,  350.,\n",
       "         320.,  340.,  340.,  320.,  330.,  340.,    0.,    0.,    0.,\n",
       "         350.,  350.,    0.,    0.,   20.,   10.,   60.,   70.,  310.,\n",
       "          90.,  100.,   40.,   10.,  340.,  340.,  330.,  310.,  320.,\n",
       "         310.,  270.,  200.,  300.,  280.,  300.,  330.,   10.,  330.,\n",
       "         340.,  350.,   10.,  340.,  350.,  330.,   10.,    0.,   10.,\n",
       "          50.,  250.,  190.,  190.,  180.,  190.,  210.,  190.,  170.,\n",
       "         190.,  180.,  170.,  190.,  200.,  180.,  130.,  180.,  160.,\n",
       "         130.,  120.,  190.,  170.,  170.,  210.,  210.,  200.,  230.,\n",
       "         170.,  190.,  180.,  200.,  160.,  270.,  170.,  180.,  180.,\n",
       "         180.,  140.,  160.,  150.,  130.,   30.,  300.,   10.,  350.,\n",
       "         340.,  260.,  270.,  230.,  220.,  190.,  310.,  120.,  210.,\n",
       "         230.,  220.,  230.,  230.,  250.,  160.,  180.,  210.,  230.,\n",
       "         200.,  140.,   10.,  140.,   40.,   30.,  120.,  100.,  140.,\n",
       "         170.,  140.,  180.,  160.,  170.,  180.,  180.,  190.,  180.,\n",
       "         170.,  180.,  180.,  150.,  150.,  180.,  190.,  200.,  210.,\n",
       "         190.,  190.,  190.,  180.,  200.,  200.,  190.,  180.,  200.,\n",
       "         200.,  170.,  200.,  200.,  190.,  190.,  180.,  180.,  170.,\n",
       "         150.,  160.,  170.,  190.,  160.,  170.,  180.,  190.,  180.,\n",
       "         190.,  200.,  190.,  200.,  150.,  150.,  160.,  130.,  130.,\n",
       "         130.,  130.,  120.,  120.,  120.,  110.,  100.,  100.,  110.,\n",
       "         110.,  110.,  340.,  340.,  340.,  350.,  350.,  350.,  350.,\n",
       "         350.,    0.,    0.,  350.,  340.,  330.,  320.,  330.,  340.,\n",
       "         330.,  300.,  260.,  270.,   10.,  330.,  340.,  340.,    0.,\n",
       "         350.,   30.,   30.,  340.,  300.,  240.,  220.,  150.,  210.,\n",
       "         190.,  190.,  270.,  200.,  200.,  190.,  180.,  170.,  180.,\n",
       "         180.,  220.,  120.,   60.,   60.,   60.,   60.,   50.,   70.,\n",
       "          90.,  230.,  180.,  240.,  220.,  160.,  180.,  180.,  180.,\n",
       "         180.,  190.,  180.,  180.,  170.,  160.,  170.,  160.,  140.,\n",
       "         170.,  140.,  160.,  160.,  320.,  320.,  290.,  310.,  240.,\n",
       "         270.,  170.,  220.,   60.,  190.,  200.,  180.,  200.,  160.,\n",
       "         140.,  190.,  180.,   50.,  130.,  190.,  170.,  190.,  300.,\n",
       "         280.,  240.,  210.,  220.,  240.,  170.,  160.,  230.,  260.,\n",
       "         210.,  200.,  190.,  190.,  260.,  280.,  270.,  270.,  270.,\n",
       "         260.,  270.,  320.,  350.,  350.,  340.,   40.,   50.,   50.,\n",
       "          40.,  270.,  260.,  260.,  220.,  270.,  210.,  270.,  170.,\n",
       "         180.,  160.,  190.,  150.,  160.,  170.,  320.,  330.,  350.,\n",
       "           0.,  350.,  350.,  350.,    0.,   20.,   20.,   20.,   10.,\n",
       "           0.,  160.,  150.,  190.,  210.,  250.,  250.,  180.,  170.,\n",
       "         170.,  160.,  290.,  270.,   10.,  340.,  340.,  350.,  350.,\n",
       "         340.,  340.,  330.,  340.,  340.,  290.,  270.,  290.,  320.,\n",
       "         170.,  270.,  260.,  340.,  290.,  270.,  190.,  270.,  330.,\n",
       "         330.,  330.,  340.,  330.,   nan,  340.,  340.,  350.,  330.,\n",
       "         330.,  330.,  300.,  320.,  330.,  270.,  290.,  250.,  270.,\n",
       "         270.,  290.,  180.,  300.,  180.,  270.,  320.,  340.,  340.,\n",
       "         340.,  350.,  350.,  340.,    0.,  340.,  270.,    0.,  270.,\n",
       "          60.,  350.,  270.,  150.,   nan,  190.,  160.,  170.,  100.,\n",
       "         170.,  180.,  170.,  170.,  150.,   20.,   30.,   10.,   20.,  330.]),\n",
       " array([ 288. ,  288.1,  287.9,  288. ,  287.5,  287.4,  286.8,  288.2,\n",
       "         288.7,  289.1,  288.8,  288. ,  288.4,  289.1,  288.9,  288.5,\n",
       "         288.2,  288.1,  288.2,  287.5,  287.4,  287.7,  287.7,  287.7,\n",
       "         287.2,  286.6,  284.5,  285.1,  284.9,  283.4,  284.4,  284.9,\n",
       "         285. ,  287.1,  288. ,  287.6,  287.9,  289.3,  288.2,  289.1,\n",
       "         287.9,  287.5,  286.7,  285.8,  284.8,  285. ,  285. ,  284.8,\n",
       "         284.5,  283.5,  283.9,  283.5,  283.4,  283.6,  283.6,  284.7,\n",
       "         285.8,  286.1,  287.1,  287.4,  287.9,  288.5,  288.3,  287.4,\n",
       "         286.7,  286.7,  286.8,  285.7,  285.9,  285.6,  285.2,  284.4,\n",
       "         283.9,  282.9,  282.9,  281.8,  281.9,  282.2,  283.1,  284.1,\n",
       "         285.4,  285.9,  286.4,  287.6,  288.4,  288.5,  289.1,  289.5,\n",
       "         289.5,  289.6,  289.1,  287.1,  286.3,  287.6,  286.6,  285. ,\n",
       "         285.1,  283.6,  283.5,  283.6,  282.9,  282. ,  282.7,  284.9,\n",
       "         285.8,  287.5,  287.2,  288.6,  289. ,  290.5,  290.4,  291.4,\n",
       "         290.9,  290.4,  288.9,  287.7,  288.2,  285.6,  287.4,  287.6,\n",
       "         287. ,  286.6,  286.1,  285.4,  285.4,  285.3,  285. ,  285.7,\n",
       "         286.3,  287.2,  287.8,  286.6,  288.3,  288.4,  289. ,  289.3,\n",
       "         288.7,  288.6,  287.7,  286.7,  287.1,  286.4,  286.3,  285.9,\n",
       "         285.7,  284.8,  285.4,  285.3,  285.9,  285.1,  285.7,  286.1,\n",
       "         287.7,  289.2,  289.7,  289.6,  291.4,  291.9,  292.3,  292.8,\n",
       "         290.6,  290.8,  290.2,  290.2,  289.8,  289.9,  290. ,  289.7,\n",
       "         288.6,  287.7,  287.1,  286.8,  286.9,  287.1,  287.4,  287.6,\n",
       "         287.9,  288.4,  288.9,  289.3,  290.1,  291.2,  291.6,  291.4,\n",
       "         292.7,  292.6,  291. ,  290.6,  290.5,  290.1,  289.3,  289.7,\n",
       "           nan,  287.7,  288.1,  287.8,  288.2,  287.6,  287.9,  288.8,\n",
       "         289.2,  290.7,  292.2,  293.5,  294.8,  295.3,  293.9,  293.7,\n",
       "         293. ,  292.1,  291. ,  289.9,  288.6,  287.7,  289.6,  286.3,\n",
       "         287.8,  287.2,  287.1,  287.3,  286.8,  287.3,  286.3,  289. ,\n",
       "         290.1,  290.7,  291. ,  290.9,  291.5,  292. ,  292.6,  292.9,\n",
       "         292.6,  291.9,  291. ,  290. ,  290.2,  289.9,  288.3,  289. ,\n",
       "         287.3,  287.4,  288.1,  288.1,  288.7,  288.7,  288.6,  289.3,\n",
       "         290.5,  290.9,  291.3,  291.9,  292.3,  292.6,  292.5,  292.8,\n",
       "         292.6,  292. ,  290.8,  290.2,  290.3,  290. ,  290.3,  289.4,\n",
       "         288.8,  288.9,  288.6,  288.3,  288.1,  288.1,  287.9,  288.5,\n",
       "         289.3,  289.8,  290.4,  290.8,  291.5,  292.2,  292.1,  293.2,\n",
       "         292.7,  292.4,  291.9,  290.9,  291. ,  291.1,  290.4,  290. ,\n",
       "         290. ,  289.2,  288.7,  288.2,  288.4,  287.6,  287.4,  287.6,\n",
       "         288.3,  288.7,  289.2,  289.6,  289.4,  289.7,  289.8,  289.4,\n",
       "         289.4,  289.2,  289.1,  287.5,  287.5,  287.6,  287.3,  286.6,\n",
       "         285.9,  285. ,  284.4,  284.6,  283.4,  283.4,  282.9,  284.8,\n",
       "         285.8,  286.1,  286.8,  287. ,  287.3,  288.1,  288.4,  288. ,\n",
       "         287.6,  287.5,  285.5,  284.1,  284.6,  285.9,  285.3,  284.1,\n",
       "         284.7,  284.7,  284.3,  284.1,  284.2,  283.4,  284.1,  284.6,\n",
       "         285.8,  285.4,  285.4,  286.4,  288. ,  289.9,  289. ,  288.8,\n",
       "         288.8,  288.6,  288.3,  287.4,  287.5,  287.1,  286.9,  286.6,\n",
       "         285.9,  286.2,  285.1,  284.9,  283.9,  284.4,  284.6,  285.2,\n",
       "         286.1,  288.1,  289.1,  289.7,  291.7,  291.1,  289.5,  290.2,\n",
       "         289.9,  289.2,  287.9,  287.5,  287.1,  287.3,  287.5,  287.4,\n",
       "         286. ,  285.8,  285.8,  285.6,  285.7,  285.7,  285.8,  286.1,\n",
       "         286.4,  286.8,  287.2,  287.3,  288.4,  289.5,  289.5,  290.2,\n",
       "         288.8,  288.5,  288.2,  287.9,  287.9,  287.8,  287.3,  286.6,\n",
       "         286.6,  285.8,  285.9,  285.8,  285.9,  286.1,  286.1,  286.7,\n",
       "         286.9,  287.3,  287.6,  287.6,  287.8,  288.1,  288.7,  289.6,\n",
       "         289.5,  289.6,  289.1,  288.8,  288.4,  288.4,  288.2,  288. ,\n",
       "         287.8,  287.2,  287.5,  286.9,  287.1,  287. ,  286.9,  286.9,\n",
       "         287. ,  287.4,  287.6,  288. ,  288.3,  288.6,  289.1,  289. ,\n",
       "         289. ,  289. ,  289. ,  289.1,  289. ,  289.6,  290. ,  289.9,\n",
       "         289.3,  290. ,  289.9,  289.9,  289.7,  289.5,  289.5,  289.7,\n",
       "         290.5,  290.7,  290.6,  291. ,  291.6,  292.7,  287. ,  286.5,\n",
       "         287.4,  286.7,  286.4,  286.4,  286.4,  285.9,  285.9,  285.7,\n",
       "         285.2,  285. ,  284.6,  283.8,  284. ,  283.4,  283.2,  284.2,\n",
       "         285.6,  286. ,  286.4,  287.7,  287.6,  287.6,  288.2,  288.6,\n",
       "         287.8,  286.9,  285.5,  283. ,  284.5,  283.9,  283. ,  283.1,\n",
       "         282.7,  282.6,  281.7,  282.2,  280.6,  281.1,  280.8,  282.1,\n",
       "         284.6,  285.9,  286.9,  288.2,  288.6,  288.3,  288.8,  289. ,\n",
       "         288.6,  287.6,  287.1,  285.7,  284.9,  283. ,  284.7,  283. ,\n",
       "         283.2,  282.6,  281.8,  282.4,  283.3,  282.5,  283.3,  282.9,\n",
       "         284.6,  286.4,  288.1,  288.4,  290. ,  290.4,  290. ,  290.3,\n",
       "         289.5,  288.1,  287.2,  286.4,  287.7,  287.9,  287.1,  286.9,\n",
       "         285.1,  285.2,  285.6,  286.6,  286.9,  286.8,  286.3,  287. ,\n",
       "         287.7,  287.4,  287.9,  289.2,  289.5,  290.1,  288.2,  287.9,\n",
       "         288.1,  288.2,  288.1,  287.3,  287.2,  287.2,  286.9,  286.7,\n",
       "         286.8,  286.1,  285.6,  285.6,  285.5,  284.8,  284.9,  284.8,\n",
       "         285.6,  286.2,  286.9,  287.7,  287.4,  287.5,  287.5,  287.3,\n",
       "         287.6,  287. ,  286.1,  284.2,  283.9,  283.2,  284.1,  282.3,\n",
       "         281.9,  282.1,  282.1,  280.8,  283.3,  283.6,  283.7,  284. ,\n",
       "         284.7,  285.9,  286.8,  287.8,  287.8,  288.2,  288.3,  288.2,\n",
       "         287.7,  287.1,  286.2,  285.9,  284.9,  284.8,  284. ,  282.8,\n",
       "         282.6,  281.7,  281.3,  280.9,  279.1,  280.2,  281.1,  281.6,\n",
       "         283.1,  285.1,  285.6,  286.3,  286.6,  286.7,  287.6,  287.2,\n",
       "         287. ,  286.6,  285.2,  285.4,  283.7,  282.1,  283.5,  282.5,\n",
       "         282.1,  281.4,  280.6,  282.1,  281.8,  280.9,  280.3,  281.4,\n",
       "         285.4,  286.2,  287. ,  287.8,  287.7,    nan,  288.2,  288.3,\n",
       "         288.2,  287.5,  285.7,  286.1,  285.7,  285.2,  283.9,  284.6,\n",
       "         282.8,  282.5,  282.9,  281.5,  281.1,  281.5,  281.2,  282.5,\n",
       "         285.7,  286.9,  287.6,  287.9,  288.8,  289.2,  289.4,  289.2,\n",
       "         288.4,  287.8,  286.4,  285.2,  285.1,  283.8,  282.5,  282.9,\n",
       "         283.9,  283.8,  283.4,  282.4,  282.1,  280.5,  281.9,  282.2,\n",
       "         285.3,  287.1,  288.8,  289.2,  288.4,  288.7,  288.8,  289.3]),\n",
       " [datetime.datetime(2015, 9, 1, 8, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 1, 9, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 1, 10, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 1, 11, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 1, 12, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 1, 13, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 1, 14, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 1, 15, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 1, 16, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 1, 17, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 1, 18, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 1, 19, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 1, 20, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 1, 21, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 1, 22, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 1, 23, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 0, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 1, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 2, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 3, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 4, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 5, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 6, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 7, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 8, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 9, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 10, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 11, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 12, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 13, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 14, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 15, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 16, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 17, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 18, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 19, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 20, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 21, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 22, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 2, 23, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 0, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 1, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 2, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 3, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 4, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 5, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 6, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 7, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 8, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 9, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 10, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 11, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 12, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 13, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 14, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 15, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 16, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 17, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 18, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 19, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 20, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 21, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 22, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 3, 23, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 0, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 1, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 2, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 3, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 4, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 5, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 6, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 7, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 8, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 9, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 10, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 11, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 12, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 13, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 14, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 15, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 16, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 17, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 18, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 19, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 20, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 21, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 22, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 4, 23, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 0, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 1, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 2, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 3, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 4, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 5, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 6, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 7, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 8, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 9, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 10, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 11, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 12, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 13, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 14, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 15, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 16, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 17, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 18, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 19, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 20, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 21, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 22, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 5, 23, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 0, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 1, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 2, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 3, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 4, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 5, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 6, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 7, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 8, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 9, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 10, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 11, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 12, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 13, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 14, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 15, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 16, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 17, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 18, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 19, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 20, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 21, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 22, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 6, 23, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 0, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 1, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 2, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 3, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 4, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 5, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 6, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 7, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 8, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 9, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 10, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 11, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 12, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 13, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 14, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 15, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 16, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 17, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 18, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 19, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 20, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 21, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 22, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 7, 23, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 8, 0, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 8, 1, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 8, 2, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 8, 3, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 8, 4, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 8, 5, 0, tzinfo=tzutc()),\n",
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       "  datetime.datetime(2015, 9, 30, 2, 0, tzinfo=tzutc()),\n",
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       "  datetime.datetime(2015, 9, 30, 4, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 5, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 6, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 7, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 8, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 9, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 10, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 11, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 12, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 13, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 14, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 15, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 16, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 17, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 18, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 19, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 20, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 21, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 22, 0, tzinfo=tzutc()),\n",
       "  datetime.datetime(2015, 9, 30, 23, 0, tzinfo=tzutc())],\n",
       " 49.19,\n",
       " -123.18)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stormtools.get_EC_observations('YVR', '01-Sep-2015', '30-Sep-2015')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The problem in `get_EC_observations()` was a `str` vs. `bytes` issue.\n",
    "The `response.content` attribute (`bytes`) was being used instead of the `response.text` attribute (`str`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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