readHDF.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "from osgeo import gdal\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "gdal_dataset = gdal.Open (\"data/MOD11A2.A2013001.h28v07.005.2013017015136.hdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('HDF4_EOS:EOS_GRID:\"data/MOD11A2.A2013001.h28v07.005.2013017015136.hdf\":MODIS_Grid_8Day_1km_LST:LST_Day_1km',\n",
       "  '[1200x1200] LST_Day_1km MODIS_Grid_8Day_1km_LST (16-bit unsigned integer)'),\n",
       " ('HDF4_EOS:EOS_GRID:\"data/MOD11A2.A2013001.h28v07.005.2013017015136.hdf\":MODIS_Grid_8Day_1km_LST:QC_Day',\n",
       "  '[1200x1200] QC_Day MODIS_Grid_8Day_1km_LST (8-bit unsigned integer)'),\n",
       " ('HDF4_EOS:EOS_GRID:\"data/MOD11A2.A2013001.h28v07.005.2013017015136.hdf\":MODIS_Grid_8Day_1km_LST:Day_view_time',\n",
       "  '[1200x1200] Day_view_time MODIS_Grid_8Day_1km_LST (8-bit unsigned integer)'),\n",
       " ('HDF4_EOS:EOS_GRID:\"data/MOD11A2.A2013001.h28v07.005.2013017015136.hdf\":MODIS_Grid_8Day_1km_LST:Day_view_angl',\n",
       "  '[1200x1200] Day_view_angl MODIS_Grid_8Day_1km_LST (8-bit unsigned integer)'),\n",
       " ('HDF4_EOS:EOS_GRID:\"data/MOD11A2.A2013001.h28v07.005.2013017015136.hdf\":MODIS_Grid_8Day_1km_LST:LST_Night_1km',\n",
       "  '[1200x1200] LST_Night_1km MODIS_Grid_8Day_1km_LST (16-bit unsigned integer)'),\n",
       " ('HDF4_EOS:EOS_GRID:\"data/MOD11A2.A2013001.h28v07.005.2013017015136.hdf\":MODIS_Grid_8Day_1km_LST:QC_Night',\n",
       "  '[1200x1200] QC_Night MODIS_Grid_8Day_1km_LST (8-bit unsigned integer)'),\n",
       " ('HDF4_EOS:EOS_GRID:\"data/MOD11A2.A2013001.h28v07.005.2013017015136.hdf\":MODIS_Grid_8Day_1km_LST:Night_view_time',\n",
       "  '[1200x1200] Night_view_time MODIS_Grid_8Day_1km_LST (8-bit unsigned integer)'),\n",
       " ('HDF4_EOS:EOS_GRID:\"data/MOD11A2.A2013001.h28v07.005.2013017015136.hdf\":MODIS_Grid_8Day_1km_LST:Night_view_angl',\n",
       "  '[1200x1200] Night_view_angl MODIS_Grid_8Day_1km_LST (8-bit unsigned integer)'),\n",
       " ('HDF4_EOS:EOS_GRID:\"data/MOD11A2.A2013001.h28v07.005.2013017015136.hdf\":MODIS_Grid_8Day_1km_LST:Emis_31',\n",
       "  '[1200x1200] Emis_31 MODIS_Grid_8Day_1km_LST (8-bit unsigned integer)'),\n",
       " ('HDF4_EOS:EOS_GRID:\"data/MOD11A2.A2013001.h28v07.005.2013017015136.hdf\":MODIS_Grid_8Day_1km_LST:Emis_32',\n",
       "  '[1200x1200] Emis_32 MODIS_Grid_8Day_1km_LST (8-bit unsigned integer)'),\n",
       " ('HDF4_EOS:EOS_GRID:\"data/MOD11A2.A2013001.h28v07.005.2013017015136.hdf\":MODIS_Grid_8Day_1km_LST:Clear_sky_days',\n",
       "  '[1200x1200] Clear_sky_days MODIS_Grid_8Day_1km_LST (8-bit unsigned integer)'),\n",
       " ('HDF4_EOS:EOS_GRID:\"data/MOD11A2.A2013001.h28v07.005.2013017015136.hdf\":MODIS_Grid_8Day_1km_LST:Clear_sky_nights',\n",
       "  '[1200x1200] Clear_sky_nights MODIS_Grid_8Day_1km_LST (8-bit unsigned integer)')]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdal_dataset.GetSubDatasets()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "lc_data=gdal.Open('HDF4_EOS:EOS_GRID:\"data/MOD11A2.A2013001.h28v07.005.2013017015136.hdf\":MODIS_Grid_8Day_1km_LST:Clear_sky_days')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "lc=lc_data.ReadAsArray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.171661376953125"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(lc.nbytes/(8*1024*1024.))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0 0 0 ... 0 0 0]\n",
      " [0 0 0 ... 0 0 0]\n",
      " [0 0 0 ... 0 0 0]\n",
      " ...\n",
      " [0 0 0 ... 0 0 0]\n",
      " [0 0 0 ... 0 0 0]\n",
      " [0 0 0 ... 0 0 0]]\n"
     ]
    }
   ],
   "source": [
    "print(lc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 255, 16.687774305555557, 46.564385851195986)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(lc.min(), lc.max(), lc.mean(), lc.std())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "passer = np.logical_and ( lc > 0, lc <= 255)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 255, 52.718119553866806, 70.35774080023769)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(lc[passer].min(), lc[passer].max(), lc[passer].mean(), lc[passer].std())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x13c8f6d0>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT0AAAD8CAYAAAAFWHM4AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzsnXl8VOW9/9/POZlJMkMUIkFZAsMSQNGKy89S1Lrb1rbaW9uK3opYLdYqbZVFBBEUQUSstdTaKq7c1qXV3outbW1Fe6uIXtdSZAlLJOBCIIBhJsnMnHl+fzzznDln5kwymEAmct6+zmvOfs4E88n3+3yXR0gp8fHx8TlYMLr6BXx8fHwOJL7o+fj4HFT4oufj43NQ4Yuej4/PQYUvej4+PgcVvuj5+PgcVBxw0RNCfFkIsU4IsUEIMf1AP9/Hx+fgRhzIPD0hhAmsB84BtgL/B1wspXzvgL2Ej4/PQc2BtvROAjZIKTdJKePAE8AFB/gdfHx8DmJKDvDz+gP1ju2twOedJwghJgIT05snHKD38vE5mNkhpazqyA2+9KUvyZ07dhR07ptvvfVXKeWXO/K8jnCgRU947HP511LK+4H7AYQQfo2cj8/+5/2O3mDnjh28/tprBZ1rBgK98x0TQlQDjwFHACngfinlPUKIOcD3gYb0qTOklM+lr7kRuAKwgB9JKf/a1vMPtOhtBaod2wOADw7wO/j4+OwHpGV1xm2SwGQp5VtCiArgTSHE39LH7pZSLnKeLIQ4ChgHjAL6AX8XQgyXUuZ9mQM9pvd/QI0QYrAQIoh62WUH+B2Klksf+SqXPvJV17aPT3dASkkqHi9oaec+H0op30qvNwFrUMNi+bgAeEJK2Sql3AxsQMUO8nJARU9KmQSuBf6K+jJPSSlXH8h3KFa8xG7phD95HvfxKTqkRFpWQUuhCCEiwHGA9puvFUL8SwjxkBCiV3qfV5ygLZE88Hl6UsrnpJTDpZRDpZTzDvTzixUtcPozW+ScAujjU3RIScqyClqA3kKINxzLxOzbCSF6AE8DP5FSfgLcBwwFRgMfAnfpU73epq1XPdBjej5tkC1sTuHzRc+nmJGATBVsxe2QUp6Y76AQIoASvN9IKZ8BkFJ+7Dj+APDH9OY+xwn8MrRugC94PkVPJ7m3QggBPAiskVL+1LG/r+O0/wD+nV5fBowTQpQKIQYDNcDrbT3Dt/SKCK9xO1/wfLoHsrOitycDlwKrhBDvpPfNAC4WQoxGGZV1wFUAUsrVQoingPdQkd9r2orcgi96RcOBFLxLH/mqL6Y+nUtKthuZLQQp5ct4j9M918Y184CC4wO+e1sE5IvM7s+IrR8N9ulM9JheIUtX41t6RU4+ceqIpdbetV4pMz4+bSOLQtAKwbf0upiOWlz7I5k5X9qMj09epCSVsgpauhrf0usiOiIoTgss33pn4Ft6PoUi6bQytP2Ob+l1ER0RlANhgS2d8CdCvafu9+f4fEaQklQyXtDS1fiWXhdx6SNfpdxQf3OaUynKDYPmVMo+Pri0DIDNrS051x4oCyy2484D8hyfzwDSH9PzaYelE/5ki5wWP/2pBc+5Pri0jKenHFWQ4GVbgv7YnM/+R3ab6K0vel2IFjCnhaeFT7No0hCennIUiyYNAWjH5Rxl39cvYfM5kHSnlBVf9LqY+8c/myN0pYbg1NJDOLX0EI74WtB17Mif5Be+UO/z0p9Tc4TPx2e/IruPpeeP6RUBS8ZnEtCvfCzTIOKbP66i3zcyglh1dpA1P4vnHWvL3v/pLbxRgN/xy2ffKAZBKwTf0isylowXvN/ayhoZo983SgEwy5UoNvxdRb7yWXrasrtw0Xs5DUn3jdVoV9nHpxCkTGEl4wUtXY1v6RUBKZZRUT2NwGFK3I4O13GkCJFoSrH7nSSghK/y5AC9j9b/00zlzZsyll2o91TeXFVOqPdR/NeEfyJZ6RK+fbf6tKXnW30+heFbej77RFP9QubMquPJm7cDsEbGCFQYBHoatsVXc8ZbHHrYOg49bB0AJ9zmtvjeu+tWAMp7n8qlj3yVgFAi2p7gCcZ47s9YlL7V59MO3WhMzxe9IuJHFz4JwJEiZFt64YhBoilF1VkBz2t2rHqTM+87nzFz1/H3p77nOvbwZTsICFFQkrFgTI74xXbcaQdHfHzao7uInu/eFhkX3dqHqlODJJoyaSxDvvCWvW4YCVKpADv+HWToaavs/Xt2juCGnZlgxtIJcPPjF7K5tQXhrZcIxiBZiWRlXmtPCd9UYjvAd3N98iNpp41d0eBbekVG1alBdq9K0vBCwt636dXjaW3uzaZXj2fPzhEYRoI+n4vStGsIX//L/bRE+1BatguAvz/1PUK9pxLqPZXNrS0snfAnoh/e6WntSVYCbvfWS/yUkPrBDZ/8SClJWYmClq7GF70iY93iuXz80u2Ehpou4dv2zkDqHlnF2vuC7Nk5gpJAMyWBZlKpAJZVRioVIBDcy9nfechh7WXqZ7W1Z2+n3dl8Fp7zXBhFuM9U39X1aQNJSloFLV2NL3pFyscv3Q5AwwsJ6h5ZRcMLCapOH8Ww75dQEmi2zzOMBIaRoLWlF6lUgHDfqQjG0Lzjnwz+7kyqzg4S7juV2If/JNx3Ks07/glkrDy97tzWQti6ozHznJDwa3F92kTKVEFLV+OP6RUxoaEm4YgBL4wkWr+W0NBR9DikntdnHs7xc5ooLd/BxhdGMGDsToKln7B3ZyWxD5+3r4/Wuf+qxj9OUWKcTK+xp1MxooS9Gy0enraN+pYIAD/4Zp19rmAMKVbb436gc/78FBafXKTfcMCnM/j4pdupe0QFK8LVI2l4aTXbN0b4wh2bKS3fwb+WDAPgrTkV1D4e5qPlrZx7/6H29Q0vvwRA7MN/Eup7KsnUKyRTr9DzmADJqKTsCIPfNzRiCjAFPPCHCA/8IeJ6B20BNtUtTO/xBc/HG9/S8+kUUiwjmp6/PTLhGGoXv0vD6COJ1lqEa6DHIJNojUlznfqf6dUFxwL/S9UppyNVXjO9x5xOj2EmZ5zTm//6/kgAjBJIJSFSWspAythCpoXV5Y/25uHLdhzIr+nT7fEtPZ9OpOfoI+k5+ki2/a6VcLUSrXCNSbTW4uOX4ogSCA1T/5SJRknPUaex8+UGRPpPmihRrm6ktJRE/GV2r1IBkoa/x0lKaA1a9CsN0q9UNTcYe0gPJZqOcT4fnzaRkpRMFrR0Nb7odQMa37mD3e+sIVhpEK1fS2KnakoQrjHtcxKNkn4XlpJKSGJ1FiXhXogSQdkRBoFeBotvUOZiqO+pbH95AXs3WExZvMnzeZaEL125yvOYj48XEpDSKmjpaj616AkhqoUQLwoh1gghVgshfpzeXymE+JsQojb92Su9Xwghfi6E2CCE+JcQ4vjO+hIHAymW0VS/0P7c/c4aqk4N0nN0CbvfUK5ow4txgpWZf9KGl1az5ffzAbj+/kEs/lkNoIIUDSsXcNf1QygRYIpMl5fDgyq35ZRDKg7UV/P5TCC7zZheRyy9JDBZSnkkMAa4RghxFDAdeEFKWQO8kN4G+ApQk14mAvd14NkHPSmWsW7xXLb9rpWScC9kAmQCovVrAUhE15NiGQFjMg1/VU0K9ryVJPahSlkRjOGiBWsAsKS0F4BtrQmu+uYT/PqZcV3wzXy6K90lT+9TBzKklB8CH6bXm4QQa4D+wAXA6enTHgVeAm5I739MSimBlUKInkKIvun7+HxKWqOLADACU2nefSeHnXgDe9eo/7EmPvZ1loyvRcSraPxnpef1da2tJCXcevHTOceu+uYT++/FfT5jyKKw4gqhU8b0hBAR4DjgNeBwLWTpzz7p0/oD9Y7Ltqb3+XQCzbtV4vDON+6whXDJeIGgCoD47kasuCpV08nIfoTWp7OQsvuM6XU4ZUUI0QN4GviJlPIT4Rgfyj7VY5/MOUmIiSj316cDpFjW7jmhvqcCa9gab+Xmxy/0tPZ8fApDkkp1fV1tIXTI0hNCBFCC9xsp5TPp3R8LIfqmj/cFtqf3bwWqHZcPAD7IvqeU8n4p5YlSyhNHjzqqI6/nk8UhQ6bZ69k1tyV5/1b5+BSCRJIqaOlqPrWlJ5RJ9yCwRkr5U8ehZcBlwIL05/849l8rhHgC+Dywp73xPGGYvP3721kcfQVQ/eH83LFPzyebFtrrkpVEP1xJpPRCbh7nW3g+Hae7jOl1xL09GbgUWCWEeCe9bwZK7J4SQlwBbAG+nT72HHAesAGIAZe39wARCDD0xHH8jHEYpsnDfMdRC+rTGfiC59MZyG7UT68j0duX8R6nAzjL43wJXLMvz3DePGVZLF02hEvP3+QLn49PsSEhdRBYevsdCZQfcQTNH30EQDwlueLRKlJIHrqsa9/Nx8fHyUESyNjfCMAwTAxTLf2NIKf3quCUQyv43qNf6+rX8/HxSSORSKyClq6mqEUPoPnjj+z1k4+byxcPHUfQUI7vp5/X1cfHp7PpjDK0A1HeWtSil0p4m8tVBPh270p7ikMfH5+uptMsvf1e3lrUoufFmj1Pc/JxcxEpQblh8L1Hv+a7uj4+RUBn5OlJKT+UUr6VXm8CnOWtj6ZPexT4RnrdLm+VUq4Eeuo84XwUvei9/M4s1/bJx83llbdn8exuVVI1vLycRy87HFAT2fgC6OPTFch9KUPrLYR4w7F4VmDtr/LWoo7eApwyei5Xv3A1kyu+yLCTLgaU8J0MvPK2EsQ99bOB2ZDe91AXvauPz8GKBKRRcMrKDinliW2d0NnlrU6K3tIDeOSSPzDspIv5/OIlrv0nHzeXk4+bC0D54UdQfvgRjDl6Fnvrt7Q5taGPj0/nI4UsaGmP/VHe6qRbiJ6O4L426UoAVr/867znmAHV8vyBP0T43qNf88XPx6cbUUB5K+SWt45PR3HHUEB5a1GL3t5mb8EedcpVnvud6S0XHnUzd41ZyC1P9G93Uuu2MDj/U13n43PQIQpc2kaXt54phHgnvZyHKm89RwhRC5yT3gZV3roJVd76APDD9h5Q9GN6etwOsF1ZJ4nYXgKhHjn7A6EeJGJ7mXTcXP7fnxbwux2NPHxZRvgKKWPTgmdwfkGtmnx8DloEBbmu7XEgyluLXvScOAUQlAh6CZ4mEOqhrjHhol6HwaPYjTO15VdoDa8vfD4+7dBN0maL2r1tCy+rz4uTRtzQ5vG23F5f5Hx8CkUijcKWrqaoRU+kI+DS8RdEr2dbffkIhHpw6uduA2BwWRmXP9qbyx/tvc/v4gugj0/bSFHY0tUUtehJQ/2Qxh4zx2XZSZFJUi5U/E4+bi5fL/l/jAyV2+KncQY6soMeKZb5gufj8xmiqEVPs2LVHLsyQ0glglC4i6t5PvUGAAEhcibFkazE4HwMRqnnFBDt9SO7Pj5pCo3c+pZe+wipFicrVs2x1wu1+BKxvfxwzF2ckTqKL5sncsfvql3HVWPS7UgaEPRB0sRl7XRx8S1AHx+FpPOSk/c3RS96GiEz4wFCsk+uLcD7/34WgCPHXmGXsznRFp4Svu2UcBYB0W1+PD4+XY40Clu6miJ4hbY5+bi5mK0m0si1+EA1JCjEzc0WunPE8TTVP8XbT/8Hbz/9H44jYQAsXufBy2IdeXUfn4ML7Za1t3QxRS96AB+VtiBSmb8STpETMrcTS1tseP1xdV3aitNi+MOlO7jjd9UYRBxBjmjHX97H52CgwMhtMURviz45+ZW3Z1FFAIBTjs2InRa+V96ehZCFBTXWr3zM/hw+ZjyQEcErQmMBeH/pK4DB5Y/25uHLdviTEPn4FEoRCFohFLWll5CSBtqebMTZacWJlYhjJeKufUNPGGevr1/5GOtXPpbj9n7L6MO3RB/ChskPl/bBYFSHand9fA4eZIFL11LUotcr1J8qAjSQKMiScwY2dLeVlGWRsizXvuFjxmMYAQwjwIbXH3cJX6+yGvsvVkJKfrC0gR8u7YOPj0/bdBf3tqhFLxpVXVaqCBQUqc0WRjMQJJWMs/GNJ2yrzzCUq+wUOu3iOicu+aZRxcXm4XZH/x8u7YPJFfucm+fn8vkcLHSXMrSiH9Pb1wRkJxtef5zBx13IkOO/jRkIusbyQAmfFjwX6X8XacB3TGXlnXtJyB6yMDifKx9TJ90//lnPZ/ti53NQUSSJx4VQ1KKno7Ve7aVeeTs3VSWnC8tJc9nw+uOkUgm2l9dyypi5LpEbdtLFtsW34fXH7Yhur/IadjXX8uPV/bln1DYARt3ci9W3qnk5BFUsGd9Q8PfwO7T4fNaRElJdb8QVRFGLnsbL2tOVGO1Zgs+n3uDY0hAAL787CxHIXO9p5aX5yfqM4AGkLDhyZi8Msxf/vnWrvd9p0TmFzRc5n4MLNd13d6DoRa+9JqJePfb0/lfensXnykOQgn81xzi2NIQ03KkvoITxgtCXAfhg16sAlIXKuW5tf+4emRE+w1SfgnC6XC3kuo/JOCQxX/B8DkoKnhaoi+lwIEMIYQoh3hZC/DG9PVgI8Vp6JvInhRDB9P7S9PaG9PHIvj4ru/SsLSvP1ZXFgGNLQ7zbGkOk4JcrJ/PLlZMB5eKea5zI+FXvMH7VO/xkfX9+sr4/LbFK9f1S8AerwRY8p4sLcMVjUa54TCUxHzVzBBOXwg+Wng/psjaNP8bn81lGotzbQpaupjOitz9GTciruQO4Oz0T+S7givT+K4BdUsphwN3p8z4VbQlfdm6e3ZPPgM+Vh3irJYol1U/++dQb/HLlZJ5PvcHaJeUAlIUaKQs12tdP31rO69sGsvrWXbbgAfQYdhgAD44P8+D4sL3/N7NGAnD7U0e6Ghb41p/PZx1LyoKWrqZDoieEGAB8FViS3hbAmcDv06dkz0SuZyj/PXCWaGMyy33BmaD86ntzsRJxe7zv5OPm2sLXFjNv38zaJeWsXVKOGYi5xO/XNQM4YYHkhAWSUTf3AiC6oYVQZCAAochATrj9cOp+0wxAn5IAzZbk0Ql/6oyv5+NT9EiUe1vI0tV01NL7GTCNzHc5DNgtpUymt52zjdszkaeP70mf70IIMVHPfL5nT0veB3vl7WmBW/nvuUgjc46X8Dn/6sy7cbC9P1BpYCXcY3VX1WYCF3W/bWb+7z7kjaf7M2PhJlv41vy61D6n3BSUm6Jgl9Z3fX0+C0hZ2NLVfGrRE0J8DdgupXzTudvjVFnAscwOKe+XUp4opTzx0EPL2nyHttpLaZHT55x83FxXAONLYjQLZgyxBW/ejYOZeftmhn4zaru6GjMQwwyojisjr2zmXENNzm4KwYyFm9RJlusSWlOScPVIKqqntfkdINf19UXQpzuSQha0dDUdsfROBs4XQtQBT6Dc2p8BPYUQOirsnG3cnok8ffxQoJFOQAuf11ifNDLpLb9cORkz7VH/Vb7D9Pmb7POrzggy78bBtuBpNxdg9X2Hsf7JqhwxPNc4kfnThqiNdKADC+ZPHkKpIbh43hqa6hcCuULWlrBpEVSdnAu/zsenq5AcBJaelPJGKeUAKWUEGAcsl1L+J/Ai8K30adkzkesZyr+VPn+ffwTZgQtpwJijZ/Hyu7NcDQpffncW1zxbzTVPV9uWns7XM4Wwl5m3b7avqTpD1eYGKg1GXqnG57TwJRpTjLyymbVLynk+9Qan3bDTdnuPvKrVXiLjy5lx1yZmfifO4zOPpKJ6Giaq0YG2+pzz6bYnfvkEsL1rfXwONElkQUtXsz9qb28ArhdCbECN2T2Y3v8gcFh6//XA9E9zcy939tX3lBB+4ahZtggC6JHFH/6hmv5n/IJ3W/M3BW14MRP1TTSmWLukHCsRwkqEGHllsy2CCxZuYeGdQwFlDQYrBWt+XWovdb9pZnNLKxOXwoy7NjF9UWbcL1q/NkeoBKE2BUzv1+KXYpld4aHXfXy6mkKtvG5t6TmRUr4kpfxaen2TlPIkKeUwKeW3pZSt6f0t6e1h6eOb2r5rO8/Maj39haNm8ep7c/nCUUrwrnnaPQdG71ODPL3xCFfQYt6Ng13bTuHTIge43NpH1leRaMxERZKfSIKVjrE9YHBZKYNKldVYH49z8a0qo8crbUWSEeJ8FqBzWwueb+n5FBsHS/T2gJMtdiKFHbEVKWX1jXvhh4gS0COLwlF3MvLK5hyx88IpdNqtzR7T08QbJRWmye13va/G9PQ4HzCoNMjgMhXZNTifcGQk4erM4iRcPTJH7Lzwxc6n2FDJybKgpasp+jI0Tb4JRaSBKx1FpKD29ZMy2x7C50WgUj1AW3Fa6LJZu6Q8xwoMVgrODJxBS+sOLp73Gs2pFO+3mra1BxCOOATOJC9lvUcQ23EnkF/cst3a7IYG+eqBfXz2J10vZ4XRbSy97Dw7beE590tDjd/lY+fGQ/Naaz2PzaiiU9Q0OsgBmRQWMxCzxVLzg/LPc1TI+xlezHsqqKy/tCia5aJN19VLxHxh8ykGDqYytANGe5UVItW2Reccs/M61vPYEqrOCOZ1ZbXwrX9S1d0+PHIswy9qYMXc4bS0uicPd1p5ADMWbuLoa3cRrBQEKzMpi05X2Em26wvuVJZ8lp3zXOfYnz8G6LM/kUisApeupuhFzzmGp13ZQsrKPg0Tz13HvV+vd1l1moYX4wR6ZMRKC5+Tv8p3+Kt8x/PeF5SdzYPDTwDglpl1avwvG4fbG61fCyjxc4qdpi0XNsUyOz1GX59imaeQ+vh0Fr6l18lowWtvwuB7v16f95gWs2xR09sVplKdX537AaOu3pnj5ib2SkZdvZPhFzUw/CLVRPSXkeFcvnYFK4xVeZ+r73vF+jcZfkkjZwbOYOKX05k8WZUcmBkrL1w9kqb6hYR6T3VZbnrdK4/PadFVRKaBqfIDvSpDCqkW8fEpBFV7+9mvyDggZI/Zea0790mjbeEDqDnpdZcABnoIApUGTZbFu60xas0Yz39nNslkyCV8TktPU17Wm19GhnNm4IycYxWmSYVp0mRZLE+8yIPDT7CtPYBn7mpwBzUsbBEMR0YSrV9rC1Oo91TPDszZLqsWQqtZkopJrL0Sq1n9j2Y1S0K9p9rn6moRH5/O4KDK09uftGXV5XN9r3m22lOgNCvuGE2fkR8SqDTY/a7KYH5i6nYqTJP6ljjvRZu58aVJ9Dn8bbsio+qMIB8828r6J6vs5eRbagHVouqPrS/Y99diBzCCkL2+LfGa6z2W7PmIo6/dZY/1AWBCsEqthyMjwQQz/V3Keo8g1HuqvYA7admJjgBrrGaJWS4wy4Vv4fnsF/w8vQOIU/icgpctfM5AhteYXI0V4qhwOfddOoj7Lh3EB/VfILpnAMMmCHa/m8yJ1GouCH3Z7rzcHtsSrzHsrO+y4YX/YulFv+MfV98NwPBLGpXgpcXPFfCwVFQ3G6fVBk7hGwWMIrr9OWI77rQXq1na1p2+1g9u+HQGUnZePz0hxENCiO1CiH879s0RQmwTQryTXs5zHLsx3Zx4nRDiS+3d/zMhetkk9mZ+sE7h8wpQRDdY1D3awtevUl2upk8baB9bfesuDj1sPaXlO1zjeACvzK7hldk1LG/9m73vS2I0AE2WZS/j5uXOmXv/X65g2FnfBeC0+66z9x997S6GX9LI8EsaidY6BvtMbDdYW2t6vaJ6modwrXYsGbT1F61fS8uOdYCf7uLTeXRiIOMRwMuKuFtKOTq9PAcghDgKVfs/Kn3NL4UQbWTCdlPR84reatc20EMQ6CFI7JUk9koaXknQ8GKc3e8mVQS20six2PqcHaTP2UEmrehPvFESqCyl6kuqG/KKH1fx+uRw7gPTnFl6jr3uFcyYMn0jTZY7WjHCMbeGHuNrjfW2963/bSXhGpNorUViZ+bLmj0ERgh7jA6UgH1a4fKtPJ/OojObiEop/5fCOzBdADwhpWyVUm4GNgAntXVBt6jIyCdy2ZitSuATeyWBHoLFY7fBuepYreluNjBrQQSA8DCT7X+P2+vhYSbRDRZXTljHzzcOI7pBNTJ9fXKYk+6KMvyiBtb9pjfLW//mErzlrX/DFMIOXGRz4+RBPHNXA6d9eTEAlz75bQCWXvQ7uyPDFetVrt+gb2hRNigN7WD9byuJN6aDEnvT37VcFByIcNbrZkeBfXw6i32YDa23EOINx/b9Usr7C7juWiHEeOANYLKUcheqOfFKxznOxsWeFL3oFZqTpwUPyAheG1x93Xr6lQaZtSDCT5fUc/2V1Vx93Xr7+O6kxczbN7tqdK2EZOMzYTsB+m8tz2MKwZml5/AFeRzPp97IGbNwiuCkfwxgMZMAePedEzl2dObf/Yr1b7quKw1lkp21qytT0Bpd5DqvUPFyCl/2fvDdXJ+Osw85eDuklCfu4+3vA+aijMq5wF3A9yiwObGTohe9QrjmWVV65hy/m7RCif3isduYtKI/PztjCwDvtsbsaCrA3Ol1AEy5dyMVJWp/fUucx24Z4XrGqKt3AjD8opgdBDGFwJJSjesJJXC7k0n7Gi14XlUXx45+gy2NA7j0yW+zpXFAznGnu3vcbGXt7XorM/+SwfmYRg0AqVR+8ctXrdG22OmZ3FZ7HPPx8WZ/ZqNIKT/W60KIB4A/pjft5sRpnI2LPemWoqdFrhC0+GlLUAtev9IgH7TGuTD4ecrLevNB7FXWlu6lybKoLgsyfvY6qsuCLLxzKFdft5777h7O8IsaeHjkWJgNy1vr1H3Twqc7MjsFVTNj4SbmTxvCtmWtjHtZBzbSn5fkvnNpaIdL9FpjvRl+yQ645HBenaL2pVgGqcLG5LxELl++n9qvxW4UvvD5FIIEkvsxCU8I0VdK+WF68z8AHdldBvxWCPFToB9QA7ze1r26legVKnbZrq0Wvmz6lQZ5MLoC3dLuCjmWqzZu5c3pgvAwNT/HgoV1QKbmdvl0NZZ3Zuk5duQ2W/icVJgms+dFCFaqoMaiBUN5YuZ2O6q7/rdqft3hlzTa6wCDvuEWP/156Ihp7FmnxvKcwlVI0nL28cJcWl/4fAqjszRPCPE4cDpq7G8rMBs4XQgxGqWvdcBV6plytRDiKeA9IAlcI6XMHVR30C1Eb18sO6+xPOe+GivEP5K76ZduCFBdFqTCNLn+ymrua9xG9hDB9GkDc6K9OoihhU+P42nhay8mgrOCAAAgAElEQVQXadI/BlB1CjS87MgbdAieRgtdSSBGMhGiNLSDknDueV60J2he9brerMYXPp/2kJ1YYialvNhj94Me+/T584B5hd6/W6SstFdWti/UmjF77A6gKWkxa0GEK+9RQYxAZSk9TwoRb8z9B4xusPigVQnV8ta/uXL0NPkET1t58UbpEruqU4JUnZKbP+gkmZ6Scv1vK4nWWjlJyfuP1VmfPj758SsyOpm2hO9X56pxSx2s8CI7ZUUnD+9OWlx93XqOCpdzw+OZ+W3Dw0yXhZdoTBEepsRSC5/GOdGQF7fMrGP+tCEuIdXCpz91UrJeLw3tcEVw9X6AsgEGAWNy3u+6fxiV9enj4+BgmyPjQOElfHrfr879wJW24oUWvvqWOPUtSmyOCqu+eddfWY0BJBpb2f16RiC18OUrQdPUWJmZ1pxocdVzaOjSMqd11/BynPW/reTB4SfYY3va3c0WvnCNiTAgkfpLm+/jpHOSkJ1W3yh88fNx4ndZOQBosfvJiwNB5PlBOvZrUQJ4fPGR3HfpIECJUr/SILf8uo5F1wwlUFnqeau50+vs9BZwW3vDZLnLksxn8QG2tdfwcpx4o3RZf6fO2Zwzttca620L34PDT+CfcwbzzzmDOez4r+V5Qq4YefXjy0dhAplb4uZzcKOit4UtXU23CGQAyLSOOK29e79er6w76SEyWvCE9Dx+4+NbqW+xbEtPTeuogj6BylJ7roxApeESO53qAkr4+pUG2SBy28t7oVNX4o2SPmcE2f1uAsgIobOjMqgxvGXXtwA96HXIIJbufZ7+pQG2tSb43BXwRuM0UjFJdLuzo0rHxKgjJW1+gvPBTTFM+lMIRW/pSeHWLCky0Vyz1cQqdUSnhcws+kLHxTVWyC4/A+hZYjJrQcRVkqbR7uzc6XWeZWWAHQHOx+x5ETtvz9luykm01rLFToufs9nAWVdnrvnrhkzC9IVHBHjmrgai258ruFVUZ4pSdvt5fw5eHz+Q0ck49Uxbe8myjDjo9WRpytOym7SiP+PuVLlxc6fX0a80SEWJqrONbsjcJzzMJFgpmDZ1I4FKwxZEPTanrTtQlp7TzXUK6ux5mXUtds5921+M0/PYAOEadczZSkrv0+t/NN5n6d7nee/OBFMmVPPSB4exrTXBOmLEo68Rq99CRWSa6pTsYv+Nuzm7Njv3+RycSDqvtdT+puhFL99wndY1KZTglbQoN7ekJSMYsVDCXl88dpvLTQUV0AhWCkIRA5mUSMeAw4xv92Xa1I1Mm7rR3mdJyeHBwKf6HlrwnOK2/cW4Z2qMk4lTaulfqp4ZrjE5bvYeAF764DCOa+7HP/4yib88rVz0GQs32cJXUT0Nk2MwGYfJuPTdOlcE/cmGfDIUFsTwAxkF4jUs57T8hMRTHUOxjEDpQIMWvuuvrGbJj4ere5UIe9GEh5VR3xJ3TQyuAxSWlC7XdktL7ixr+l5O685J9vidF7fMrOP+Raq+9v5FNURrLVdkF+C0Ly/mtC8vZuvyiYASvtuf+hZ9zna73ibjMBhqi2BniJVv2flodBlaIUtX0y1ED/JbfGarmUlVEZJJr+SWnGWXoV1/ZbUtCl6pKHqfs+mAU/ic0VltHG5pibu6tDhpT/hcDUOzuGVmnX195HJl0TlL1r70yHgAJr40yXaj508bwvYX4/zpj5lIdNWZgxGEqDpzMGN/VkKfM5XV19HpIX3h84HO7ae3v+lQ9FYI0RNYAhyN+t7fA9YBTwIRVI3cd6SUu4QQArgHOA9V7TpBSvnWvjxPBzCcEVyr1MqInhT86Iu11KLKYoZbYZeLq3EGLKIbLNc2qETkQKVhR3A1FabJaSWnszzxIqYQtrV3/ZXVyIRSv7sf3cr136smPNz7O2RHagM9Bdl/e26ZWQdkxFILn05kXv/bSqpOCdLU8yMmVJTyj79MYulFv6PvqXMZfkmjnRM44ac1PPQ/ddxwT4RvXL6aL/w4zPcu2MwdPxbcABxx5o0ANCzfjMSdvP1p8NtUHcTI/NVIxUZHLb17gL9IKUcCxwJrgOnAC1LKGuCF9DbAV1AdEGqAiaj+WPuMU/Debsn/iyoQTHqlP6FYgDvOrrODDB+0xolusOzGoV54JSTPvH0zAP9IvmT30NP8dEk9U+/fxHW/3sSWljjh4UpEpceftexIrcj6F9ACN3tehFtm1tnbWgg1x45+g4e3bweUi3vpk9+m6pQgp/fbyQVlZ/MlMZrwIJPDzSDhQSb//fAovneB5KiZI7jhnghWi3p+zfmZn2dHXV6v4IbPwYFEpawUsnQ1n9rSE0IcAnwRmAAgpYwDcSHEBagOCQCPAi8BN6DaOj8mpZTASiFEz6x2MXnRFl7Di3HePTcjdIZQwneiqKDWULlyNVaIWjPGz/9Z4+od8NDsbVx0qbqP7o6siW6w+OmSzC//rAURl5WXrxrD2VnFOca3d03SrpzwIlgpXAEMva0sNDNH4LKFb/a8CH//xecYfkkjw4I9+NEzl3BDxclcM/B9Lu1xLrs+UfNfHDY8xV3bPgaqCQ8y4czB9KzaSM+0ttUuq6Z2WTVVZ6rtj5bf7v3CPj4FUAyuayF0xNIbAjQADwsh3hZCLBFChIHDtZClP3UDuf6As47Ms62zEGKiEOINIcQbe/a0cM2z1TS8GHfNZOb6AgLeookaK8TP/1nDpBX9+fn/qsH/xSdvJRZK2AGNJ5d+ROSyMpfggdvddaadgLLwpk3dmJNjp9vDe6FTTrwsPY1XIGP+tCHcOHmQva3d2xGEeGLmdmbPi9jroNzct8tV3fH9La/z71/04qLXPuQHaw4BYNm5qiX9W7MmMGTMGxxz0duu59WcX28voNxdk3GE+xyohgY+nyW6i6XXEdErAY4H7pNSHgdEybiyXhTU1llKeb+U8kQp5Yl75CEFv4xVarF47DY1EdAKNY4XK0+SQvKP5G4AJj060PPa6AbLFrs5Nyg3Ntu603l6Oc/1yD+yo8H78NMNVgpmLNxkj8dBxsJbR4xJ/1DdlcfN68M6Ynbt7ux5EX5395H0Mkv4z7lruWfUNt6bt44frDmE99Y9wqonj+PV9+YC0NLc2/VMbenVLsu07opcPozo9ufwa2t99gWJJCELW7qajojeVmCrlFLPYP17lAh+LIToC6rbKbDdcf4+tXUGPC08HUl1pZOkgxlVJ2fSVEKxAAaCEw4J8donUaaP20jdoy2Eh5mulA6npWcKYae1LFiYv2uLF5aU3DRfWWoyJff5p7towdCcfU5XV7ehmj0vwrWnrbdrd+ONkoWXqO9zziVq5qCTR77NU5b60V/zdP5+hNrSC/TK/E064szzqRr7dXzh8ymU7hS9/dSiJ6X8CKgXQui8jrNQ3UuXAZel910G/E96fRkwXijGAHvaG89LNuX+iObdOJiZt2/m2NKQPZ1jhWna1Ragxu8A28IDOCNwKFvT1RPRDRbROveYXnbicvZ2IWh3V6Z0kCJ/q6l8LFow1GVRjiDkSnlpeDlOtNZKd2POJDp/f2mMBy7NNFV44NIQD1waomH5ZvodW5dj5Wm0lRc5dQsNyzezPf1HxiwTVI39uu/q+hSGPDjcW4BJwG+EEP8CRgPzgQXAOUKIWuCc9DbAc8Am1LyUDwA//LQPnXfjYK55ttq26mYtiLgsvBv+HuGOs1Wp2bbWBG9+EuPFhKpkmHKvqrCIbrCYcu9Gpty70RXEcLIn2WbX6ZwQvcvFTQueM+FZky9vD5Qg6gmFnCkrTvScuE5+M2tk3nvWLqumrHxHjivrjNzubhjK2J+VEKvbooIeaULDTHyLz6c9ulP0tkOiJ6V8Jz3+9jkp5TeklLuklDullGdJKWvSn43pc6WU8hop5VAp5TFSyjfau39baLe36uSAS/A0OnjxQWuc3UnLLuVKAdffu5Hr793oMrW95uw8tMT0bBSgLTGvQIYwRF4Lz4lXhNZJhamiuOPm9WEEIa49LZP4rAUvWmu5GhZkE6jIzLK26snjbJHTwuf8bHhV/Twjlw9z3cMsS094lFPX21F8If2sYRW4dDXdpiIjm6ozgmz/Z3q8z6FXi8duY/HYbXbZWb/SIP1Lg3ySTHl2OXHiJXxeAQznfUwhMISKIqfYN7c4X2pKNuPm9XElJ4drTHtJNG0l3ii5dv4GAhUDXEKXaMp0gg70Ei4rz7nesFwFb1b8JMn2F+NE30+LepnAapEcceb5xOq20LlC5ffj+yxx0Fh6B5KqM4JUnaEG62fevplfnfsBfU4Jek62OWlFf1us3os2Ywiob20F3HPT7k4m6Vsa4P2WOJ8kCxti1QKoo706cAEQEIKbbhvkalyg8Wos4CVwt8yscwntLTPrmDilNkcgtZXX8/hBxOq2sPCSoC1yWvxcArhLPT/QS9iLpt+FmXl5lbiB1SLtBGZwWoC+heaTi19728lUnRGk4cU4MgW9T1Nz0SIki0/JWDKLT1brVqlFYq+0rbGeJSZNSYtfXVpFfWurLX5a+PZaKQaWBehhGgjPrBo3c6cOtgVv1oKIcmfT/2Xn+OWjrUAGZCxJPa638JJgTlWGtvSy0cLnEkAPoQPoeXQJgV6CxC6JWa7qcwG+cflqGlY8S8OKZwElgNH3LUyOSV85ymPxOdixpCho6WqELALlzUdJ2RFy8PjvA5kxvH5fK+Xus7bwnR8fTv/zMwX121+Ok9yd+S4zb99sBwRAtZFKIRkVLmdba6Ye95OkRQrJ0eEQu5NJl+saS3lbf/NuHMztC98nJZW15hWs0GirL94oXWNvTgGbPS+CTLlL0rTFd8sVEUCJWM/jM1ZldiDD5cpmubiBigFUnZvb8DTc3yS6zSLVIrGalbhpl/aaH9Vy789rCEdMGv4eJzTMJBwxqfvtfwNQNfbrNKxYkHNPn27Jm1LKEztyg0Mih8oxM08u6Ny/Tfxzh5/XEYra0iupMOyqhkClQUlPgdUK170wkAWL3mf7y3G2p8e5eh6rAhXOKgjnWNxR4XJ6lqiqu/6lAXvpWWJSYZaQkJJw1phfyDA8xwFLeirLzk5R8XBnZVLSuj3zMtmlZ9q1zRfJnT0vwvxpQwgcZtiCF2+UtlhqK68taw/cAphNdJv6+RjpYEWwl7Bd2nt/XsMhI9TPKzTMJLbB4t7vuvMWq8a0lYvuc1AhcXcrb2vpYopa9IQBwQpBoIegamyAPqcEMUux3dq5M+qYO6OO7S/H2f1ugpKegmBv9ZV04vK5xomca5zIF+RxGOCy8kAFOgaVBWmIJzDIH7ioMM1M5UUKbrptkHJvs/rwOckWunxooc52e2+/630AQpGB7H5LrTvL1CBj8bUlbgANz7uTvBO7JOH+JoldkpYPU1gtkvguSVlfg8YVdZw3cRUbH/4DDX+P07DiWVq212OmDC57JKLut2IBDSufbfe7+RwsCGSBS1dT1KIHqOI1Z3TWMY43a36EWfMjOZfoEjLdGQWgvKw33z3kq/bEOurWmXE43RE527Jz5t4dWmJiiozIeVl49munxdApfPlEUBhqybb6fvGP4QQrhR1c0J+flhzha1LvYpYJe2n5MEXVmYP562Ofw+QY5db2OY/KsRG++rVWTj60AoD7/zAuLYD+eJ6PQkqjoKWr6fo3aI+0Riw+ZWuO4CWyBERvD7+ogdfvGcE54nikTKklZSFTGQsuJVUgIjvFJN8kQKCCHpaUTJ6ygdtuUpZXW8IHmeRkrxnPbp4bafPaa09b77L+QpGBrntlu7bZY3lONzebQC9hp6bolBVQAqi3LVbZwYzYBguLVbyypwnA/gSoGtuemzsqz7obwZh27uNT1EijsKWL6fo3aIM+FS1M+uJ6Fp+ylfVGjEkvq19q/TljwWYSjdJeApUCmZKsf7KKy9e8SnnpYfayPPECyxMvAGpM78O4sva0paetrGxLz5mAXGGars7JhVh8AKV98v+Y2+rEcuPkQS53Nla3xc7udArfdb/e5HU54Ba/bBF0RnM/Wr7MHs+rHBux95scQ8v2eoyQwOQYfj/tKMJ9zuO/JlTw+2lHYXIMDSue5bJHvoq3uDk/swXPvS1Z6Qtft0UgZWFLV1PUoudk8f8Ot8VPBy/uXDiEgMNy0tFbmZJ8d0iTLXTPx1/ImXBYu7Nzp6sGo7fd9D6z50UwhaBnSQl7rVSb0Vstls4xvTk3bLYF0CtJ2cu1nTOrzhY+3TlFj99pqzBUPZBQtbLyYvVbXDW3AHdflcmzy87P0+gobmKX5Lbxm7ltvLLmGpZvpurMwWoSoXTktmHFs7YAWqyicmyEWN0WyvpUY4QE0e3PEYoMxAipdzA5hkcn6O/rFLfCXF/BGJfY+cLXXREFLl1LUaesDBpWKaO9JtrbfU4J2oLnJNEo7XQPmYJApeC2Ge+7KiwEwtXWJpCnF56zMWiTZXlGb73y8WRS2hUVoiTTqUWfK5Myx8XVaSrZ6SrxRkmsbosdsVUvBtH6tenvEiJQMcB2b9uaYwPcFt73l8b4wiFhbrgn9zs0LN+Mxap0Oopya1W3lYzbq4VPTTL+HBWRrxKr20Ll2Ih9TaEIjkDygsf+MUhW7tO9fDpEx1NWBvWSJ95wZkHnvnjNM37KSj62N5UBSuwAT8ED7IitXncKnk44lkhKBJQI9aX1DGazFkSQ6f+2tsaZMqHaFbxwRnNnLYjQZFn2dJFOt/a2m95nzh0quddL8CC3cWh2vz1t6YEav3Nahlaz/j6qk4pTyLzSVvQ5iaatfH9pptu07sTiHMf7aPkyl8XXuKLOPqaTlD9avgyLVelee9ifv7inXl1XVvhf8HCf8wA8BU/t9wWv+6Hneilk6VqK2tIrP7yfDPUbz+GnKzGY9MX1drQ21QyGmhzMVeDvdCsl0iV6oAIYGu28BoRwnZtNk2Ux78bBlByijt8ys44bJw9yiZhzfM+ZwqIFT5QI29rLFj+npaePZ7vC1l5Jy451tuhpdMJyPmsvXzDjof8R3HBPxCV+lWMjmGWCb1y+mgcuDdlWH5DXistUaShXGLQF95Hn+Rnar731Lb4DRoctr4qBlfLEG85p/0TgpWuf8i29fCT2Slvwtr8cd6WnGOVK+FznN+aOwTldXGerqBSZL5+QkrZiERWmSSqZGZPTvexcz3FYfvkCG9kpLPZ+A3sSIHBXb0Tr1oIFZrkgXD3SjuBqdA1uoUhiSGJcfkEUKyapHBOxxUpbeNoa1ON8ZpngiDPbnzRIC+B3Hymz8/m8WU2ot+rTpz9zGYWkKc8xn6LET07uOCVh9QPK59aCW/hm3r6ZJsuy3VBdEwvwSTKFQLAnadkWXgr4oDV3ishsZi2I2BHYeKOkZWtGXL2Sk9uL6nq1gtIzoIGasNuOzlaPJFq/Vo3ntd0kxhNnUMPiCdexnSvfw0g3C7VYZdfe6k/ISmdJi5rbunvCFk39uXTCnxyBjWyUhde8458IxhDbcafHOX7uX3eks6K3QoiHhBDbhRD/duyrFEL8TQhRm/7sld4vhBA/F0JsEEL8SwhxfLv3L2b3tqS8rzxk6GW2G6sRhrC7E6eaAUNZQk60m+vMu0ul5+asKFHqYZBxcRviCdeMZtlkj8+1RT73Nvv6fK2knMELTWJ3isBhmb9RzkTltqoxst1bLXzO6R5TqMaqJsdgsYpAyVcwy/O7xkbJABLJP7v2VY39OmaZYOf/JhzHnC7sKLJdWu2+6mhtxpV1nys4K+/4n0+n0Anu7WHyhKlfLujcf/zot20+TwjxRWAvavbEo9P7FgKNUsoFQojpQC8p5Q1CiPNQzYzPAz4P3COl/Hxbzy9qS8/Jk9O30+eUIH1OVcKkx/GMciCVGegHb8EDmDc5Y8FMHa/6yRnAh60J+pbmNiKdtSBiL06x8nIptajpz2xX20ss89Xd6ioMHa0FiDetz9ssVAcsvAIa2YJoMi5nflttuVk8gcFQrOR64k3ryUcquZVsAdPBjkTyzwRKvpLe67TYcsfwtMhJVnqM3bmtPcFZed/HpzjoLEtPSvm/QGPW7gtQU8qS/vyGY/9j6SbFK4Geeo6efBS16PXu28K8uXWkmrHz8xpeSWBFpUvkjPJ0xUCzW1h0zayePGjmXZsxhaAllUIYMGVCNbPnRSgR5AQxPmiNu4Iit8ysyxEup/BlBzDyzZWb73r9DL2EIgMJR0bawheOqHbwOkcve2wPMvl92dUY+XL3QE3QLYlhcgwG59sTduv9RonbPdaLYjW5YraaRHIRggrXsfxjd5CbuKyu0/l7khd8S69bsF/z9Do0tayToha9jzcnmDkrAmAHMayodLmzwhDENiiras7sza7rp08bSJNl2TW4h5QY3LlwCCHD4LpfbyLRtJVorcV9dw/n+iur7YmDIDN5t54jV+ffiRKhJvIOCEQgY91lj+t5WXZ71yRz9nkFIZxVGE7hy54gvD3iTW6LzUv4DM63I8IpljmOjCLFRmW5VQygJNxWQ4Nc8QsETyFgTLa3YzvudAmfWm9r7G51jgXoW3vFjEBKs6AF6K3ntk4vE9u7e5sPzqXNMaiiFj2zrIJ4YwqrWZJqVgJnhoUteCnVD5RUq8QoF8xdOASrWbqShytMkx6mQUqqYMbsG+sAVYoWqBjAokfqmXPDZqbcu9Hzh/HTJfXMnV7nEjVRIrjzgS3c+cAWorWWd2upVK71l+1+6kag0VqLeKPkxxcK/h1rtrur2M9zpKm017XFaxwu3rRevU8Kl3ilWIYglGW9ZTA5xnZ9W6POMbx8jUNX2+2mEvGXSaZecR11Bi1Uik57aSvuJqXK2vODHEWJ3Cf3doee2zq93F/AEzptatmiFj2AYKWBWS4wytW4ndOFNcsFTauU9aTnrp0zezNWs2RP0kKmlLWX3Qpeby16pN7uuNKvNOgZyLjptkHcdNsg5k6vI7rB4urr1jN3eh0fxxPMnhexRcuZriKTkthGZcGl4vseKJoywT1Pbah6YE6HFe3KZqNTUkCJpV6S0a12N5dAeDigrDx9rsH5jrE+JSwWq9TSTHqcTguOl1uraFi5IP0eK9PvMMbDQhtFdPudwCjCfaamk5ULFUCfomX/pqx02tSyRR29NYwjZM+jJqQ3sg6mwEyntGghjG2wMMoF1l5JuMbEKIep09zF+IZIR3DT5WVTJlRz3a83cfdVQ+hxZEnOO+jyMk2TZXHXIjVfxJwbMu70lAnVyJSy3nSi8d51FsEqo11XVFtv2cKmx+1idVsIRQbSVPcn1e4pkiuC9vumRWziUlzz4GqcLm68ab3DpVWCoiO47eMlUtnBhyOy3k0nLK92nR/uc15aBPPfS12TGwH26RQ6HL3tUd1bjr7+goLOfeX6h9qL3j4OnA70Bj4GZgP/DTwFDAS2AN+WUjYKIQTwC+DLQAy4vL2ZFote9AKBS5VbmMcmNcsFVrO0rT5pKdcqEDyFRPxlDEYx76lPXNccWmKSkNK+pRa+B3423G5AkM3c6XVYUtJkWZhCEDIMUsCcuRFX3a+ztEymYPc7awhHRrYpfE6XNZ/weR2zWOXKmdOCB26X2ItAxQBamhaltwoTvEDJV7LSUUY5PnPxFr3sNBYtes95HvO6px/U6HQ6QfSq5OjrChS9yQ/6FRn5MErTQuHxli3bUrRsSxHdYBHbYNG0KomRHuurPPE07nlCjW2l0r9IOoixcP4QZt46iA8dScl6rM0ZaMg3lWOFaboEz9klBZTQ7XprjS2APUcfiVleWAflWN0Wvr805hIvZzspL8r6VLtc2nD1SLshQT4ksbTguSOmWkS9kpCBPOko7bucmeirFki3q6rreH26N/sQyOhSilr0AMIjzJzEY8iM4aWaJTItCj9dUo/ZQ3Dz9M3cNH8QP/v9QIz0L5dAMHdGHaJEtXO6+6ohrtbxd181xI7GAnZunkzKnHE5LXhOnMIXrh5p7xMGGKUq2uqs5NC5fs7obSgykEGlwRwrLVq/1lP4TI7JEQwd6dWtpOz3S4uixSoEIUzGAe4k5Uy+3ipP4csIHjnXeCH5yKMGV6ejHGEvzv3tIfnIj+IWKX67+M7AgCPODubk34EaxwsPM1U78xEmRrlgxuxBhIeZBA31taZeMpDFz+zllokRbpo/iFnzI8ydUQeoIAZk5szQ43nXX6mCCDIpkSmYMn0jV02rpTGR5F/RGDfPjdCUtJgzq445s+o8XztwmE6nUbl32uUtG2BgpcvmnJHcxM6MGM6fNsTVFQUyrmp2bp4khsFQO68uG2ckV9/DKWygIrjOIIVT8HQgw75f2rV1il9h43/5p4sM9z8eQUVWPz0tat4BEz+KW4wUGMTwa2/bIQVWi/rU1p7+7PPFIFZUjeWZ5QKZkLa7O2tBhB9MrmXSwxtJpCR3PbSF2IaUXcVRImCrw8r74dRaohss23q8+rpMbltKqqSfJivFo1ePILEz029vztyI7eJmoy247KoLM6ukTicSO8frfjNrpL1uBzPqtxCtW0soMtDlzgI5FRZOvCb+zqDcTafbmi2Kee/rEL62rL18aAtQJiDU51Qg7ChH87YOM6ixRN/iKyJk95kjIzdcuQ8IIa4DrkTpwirgcqAv8ARQCbwFXCqljAshSoHHgBOAncBFUsq6tu5vOry8T95R421DrymnaZPF4rPrmUQ1PzxjHUHDYEtLnEXjhzB96aZ06kmQm+YPcrSdsti7JslNt0a47eY6HvhpDbfcWGcHMWRC2onI9909nIlT1tO3NEBTEhqTCZaMF1z52DoGlZYCgiZHx5ZZMwbliFm4xmTvOgthZKzKbAFU6S4DbItMR2lnLNzE/GlDiNVtscVQi1ysbguCkEv0ALuaQqeheI3rlYQHkIw68/iUtaQFTNfUBkq+goG7vtYpctl1t+0JpDOgodzTI9Ku7wvEtkfT3VSUAKs6Wy16zmhtdpBjlMPi8yO6xUHXW3GF8KllVwjRH/gRcGK6KNgExgF3AHdLKXu7OGIAACAASURBVGuAXcAV6UuuAHZJKYcBd6fPa5Nkk2Tbf7dQ9cUg4REqkTcVh/AAk0l/r2bx2fUcaYaIp1L0CZYw7NpyTivpCaiWUnNn1DF3ulrKI4ZKRE5bZXNnqFw7UInKix6pJxQxSDS2cvV16/nlzcP4yYXNrjkylowXvN/aiiUld9w4hMTO9Gxi5cK+r86FEwb0GJFJi8lXZ5udsByr28L8aUPS3yGWY9Xp/flwurmJpq2uigwteE6R0hFZLWRlFV9xHdNLZ6EFUH+qhgNH2FZb/j58oxwusC9yRUk3cW8/dcpKWvRWAscCn6DyaBYDvwGOkFImhRBfAOZIKb8khPhrev1VIUQJ8BFQJdt4gbI+/WRJyXfpc1aQpvUWySZJ1WkBfvHlrQjHVdKQmImMftca7kZ7e5IWh5QYJCX86MJ/Y6Z/eYI9K5GWtPP07O8WEISHmaTiksROaY/RAbbQ6YBBIDzczs1zdk2J1lpYUUl4RAm33VbHTTdFuHpWLfcvqsm8dwoSu3Nz9LSlFqoeSLR+LVc+JlkyXnhaeNloa88ZDOl5/CA7mdkpeCbH2LW1WvTCfc5rv+ojy9Jrj+zUFch0Tc40Cm27JM1nv9LxlJUBh8ujJ40r6NzXpv+8e6asSCm3AYtQiYIfAnuAN4HdUkqd++Es/rULg9PH9wCHZd9XCDFR1+RZzZlf8Cembqe5TrmU1/5lANc+X821z6c7pSQNpKGaErwnYnbjUImanPuQEsP+src+MZKyvpUEe1YCMPV+JXi6FjfZpOpvoxssRNr510IHEG9MMX3RJsLVI+k5+kh1bq2VM1F3uMYkldpG05r37QoLp+BBujqip/AUPEnMFtYl44V9rC0EIXt8z2khRmst29XN7nSsrbxAyVfsNu56n1Pc9lXovIk63lWP33k3CnVHd/dtoiGfA4+k+4zpdcS97YVq6zIY6AeEAS8/SCtGQYXBUsr7dU2eESyn/zfKCFQY/HB5f4b8oJxffCXTUGHimUoUpCFJGarde4lQs51p4TNEZgY0Q0DvYAklhwjueHALP32onsODyrVdeEmmBC3R2Mr1927kB5NrCR4ubEsvsVNVesy5WDUESOyWBCsNglVGjvsab5QcOnqQLTYtWy0mTqlFpiAZVZHheKMksVsSigy0AxaFWHNtocvOghXD7XG9tua/tb9z1vidl0ubLYT7TpiM8IUd7mp2edtql5ur3V/VucUbfwa1YmC/dlnpNDoiu2cDm6WUDVLKBPAMMBbVz0oHSJzFv3ZhcPr4oeT2zHLjkMToVgurBb72H72Jvm+xty7J/HlDMCxBsjRFPGBx9TdXsTrajLPhSVI1ZaEpabErYfFRa5JZt21m+lUD7QoLwE4TkWwnyQvMu/gZfnr1UPauyQQstPhVfK6EwGFCtXIHsJSA6XvFGyUzFm4isVuJpBadu68agjBUR+jWD1SaSiomScUKG2Joq8rCeUwSI9603hbc7IBGuM95tlXnJLr9OeKN0h5ndI735bumELLH6VSy8kco4XMKmTtZOnOe/eZtPMOfS6NrOTjmvd0CjBFChNL1b2cB7wEvAt9Kn5NdGKwLhr8FLG9rPA/AyhKDvXVJQo6Bf7NMMPGP/Zj09EB+8Ktqrnx0CHsti2u/2exKPNZUlJiUGoJPkiluva+O1pSqwf13TI0B3vZUktueSvKLp4+mNDyF1t3rAFVK1viOO+4yZ1YdPUcfqXII06+0aMFQ4o2Sa+dvsM/b/db7rs4me9ephOSyAWmXOyRo2V7vurdTwLLFTFty+c53bjsn+XYmK+v5arNFLNznPBLJP7sSprXFF2+UHaqcsFNUbHd2dTqC63RvnSVto7LO04nOvotbvHzGLT0p5WvA71FpKavS97ofuAG4XgixATVm92D6kgeBw9L7rwemt/cMq/Vj9SxLEuqrXjU8RClMuNok0EvQ8nGKeGOKRy/7kHMqD+G3Vx6JdIwdgaqgODTdIr7UELbwNVkWOxJJBpUGGZTusDJ/8hD2JC2ClQbh6pEkousxDTUW1/SvTJmarsjQ4qUJ9BT8emENM78T5+Jb1yCJkYiq1k46kipTSvx0lYVXAwEtbl6RWy1++jwgp/rCa6pIfV6sbostfF4kkn92RZW18DmjuW1HdHOTinWaildQI3NNdvpJ252XfYoI2X3K0DqUpyelnI3qgOBkE3CSx7ktwLf35f6lvfvSuitF8JDML+jDP1De8uW/6gdgT5b9vSf6IgxBrzEWE64+hD6BEgSCI0U5a2TMbifVmlJzZFSgVLo1pdzSUsc0kgumDGH6ok0smDKEcPVI4o0pjOj5JFJ3sfud8+k5+kjVSCBdbmakDa1db62xU0YMzufxmUcSTneJijem7JZOGrsrcvXIfR7HcwobeFdfaOyIbVNmPVanxNaryUCg5CtEa62sWlvvigxvcnPncgUv22LLbl6w2mO/L3zFS3G4roXQ9aGUNhh4aNwWvF98tZ5wdeavxMNXfUhiT6aHnU5CDh5m8ODdw5lzy2BqrBDrpLNyQbm4G5tbAJUs3GRZ/OyWYQSFwaIFQ8HMjN0FDlNBjHCNSc/RRxIwJhMID2f3O2sAJWTxxhQtW1MqyFE90tWXzp7FjPwTcmu0gBaKV9lZYcK52ha6WN0WyvpU226udl+zx/Q02RZe2+KXLV4ZVFAiU3frrsHV1zhL1nyXtlvQTfL0ilr0AO79ylZ2vJLgO9MOZ/s/4nxn2uFc+6dqvrtA/ZLEd0m2/zVBMprig2daaXg+Tp9Tg8y/5X3WGlFGpsIMLy1j2oRqtrUm+Hc0xkM3juD/mvbyyTtJ5ox7GoBbb4qoZpk9hZ07B+4Jhyo+V0K4xqTX8SpVpTW6iNbonxGGmgjIapaU9xlhz2ehidavJVpr5QiftvycFl8+nA1BnQ0Dss/xQndOURZdpo0UQMv2+pyxut1r/uhKZYH8KSuFWX3gFj9n6kqmOqNta8638oodv+FAJ7BlT5DVVgwMMIKCCbNUYOGqc9bRsHIBDSsW0LDiWfv8RPLPtDb/mcY3E0gkc+4YTLJcDZxd9+tNSFTO2/RFmzgqVM4Vj9YCsHvNHexZtxBQIhfoqcb95syqIxXDtuQSO6UtiIMv/5wtPHbAYLe0x8q8BChb+BLRTLVEe8LntOLyrbdHvkYCbZEtfs59heFuGJohmrXtu6/dHmkUtnQxXf8G7fDL54fz5K0fQwoGlpYy67bN3HbzELw6dpSWf0VZDim47j+ria63+P7D/fn+w/156m9HsfASFYiYdVGc+ZOH8JsZI7n0ka/a1+9ecwf/v71zD5OjrPP951c9PZduRnKZDOSGk0A2wCwew/EoKl7xAomruF5O1IfLqut6kPVGEi7eWAGFXM6zq+4exV03iArowu7mQIRH8X520cXoCrMkJIQxF4OTSQgO3ZOZnq73/PHWW/VWdVV3z0zPTA+p7/PU01VvvV31ds30t3/3X+mIbub9Vx9fxuBo4LjwS9V74SkDP9RBzEaCKrlbACj076TYv8+3uVVIfTGNgAxB2upwvbDJNa6oQLQyS3vnRaFc22znklDqGYQdF/ZrUi5ubTU3GnuXx8TsBYVFo8VI+4hziKRoTtQr5aWSXg2UjrkcvGeEd1zTTdfLsygUn/lQDx/+dBASYr5wAw+UeN6qFrpe9j/InhwUH/3d3Xu58dInKfy2zIJXh0myPKy4Z8PZvh3O4c0UBzdRHNzkq7Uf2/iEPz9zkvjhKYAfVNzZs4YMaymPacmtJb/EJ6Ni/74K4jPILz0zVrKLG6unErJ5tauqmCIGBqWhA2Q6IuWhhpPtddExI/VFszaSic+2zwUEVhmuUs1+lxLfbMBzPiNjOiAtgjjQ/apWBn48yg2fXEbLXGHLR3SebLblIh38G1G3ysPQvbqV4aPbcVqW8P63LmLgB+EvTmH/TkYG9zM8sCu2Hl1xcDtPjmiHx7ov7vVr4rlFRfdrdHjLdRv3ct1G3YMj13NaRQydKQNV6N9JqfB4qJQ8aEdIYf/OChXVlvbqicuD+C5o/meJlpkfjp/3vBdkfPIKqeHes01yalRXd22bXpJDolqoykRhFyhIMeVQpOpto5Cd74AD3a9p9e1upkpxUt+JTIcuJ5/hHP2FdO/HZRuHf6S/WC7b6OheSZlHQo1xhBxt+XV+v9bbL++nIyP+Pd1iYLO7buNeVuXyfkUUCCS//IqMLhbQH1ZV7aZB9SBJuotr1wjxTb7j4I4dCBFVpkNvhd1lv0RWXIByXHxe/VVYqjcN0rDV2ckSX1+apTHNUK6qa5tpND3pAQz8cJTDPy4x56yrKe4uUzqqWa8wsJ3sXAllFrTOFQ7etw2nXVAUuWRrD+aLZEt0cdkF7d1LGSlspuRu8a957Tsf47Pvujsk6T113wg3XrmMD34rQioeT4gDZCrV1Dh7XhTRDIxoeSlFMdZza+P40HdjJb9ohRXbllce1lv7El3CK1ofMA5xhQmguo0vuXSUjYnZ8nS7Sb2997Y3jfv9KSYJVec2w5gVpCeO+L8QQRpa8MUwBHbsF2OMPq3n/f5HupH17Zffl3DVPo/Yog1qev19k2/6+W+/vYIkT13Txl9cvIvrNu6taN4zelRpKTQD+Z7AbvfRr+wN9dKwvbcGSd7YKBlGEfXGmpJRtrRXrcKxLeElEV6SGls9U6OSwKK9M+rP6a1P+lM8xNcuu9c/Fs4LOaxSTAEUfkP5WttMo7lJT2DBq7J61wmrskYFPfZQiVxXUBIp35Oh590XA5oI8t3rEy7eaxFZL1nnwtA5CMj0xiuXxX4x/+bLK/jkO1vIdi7RdjjLyRGqSeeN/+3VZ/Cxr4b78MYhLvAYqoeqmH64Zt8gOz/4E0eJ0ajDpaEDlIfDaq597F8rQbWNlqCKt+9VpqUZFTf4sallh6tP+ou7RvKPX4pGQan6tplGc5OegsM/DgoHKFeFyM8QX3a+cPLKNWRbLuLYr8Y4/P1R8t2r6exZg5OTKsSn0dmzhtYu+1EEX67CwPZYVfiJf/xnf780dAAh55d3L/bv4z037AyVexdyFPbvZOO7x3xVOZqWZhDX88Ju8djetTI0FoWpkwe66VC2c4mfchaHbOcSbefzVGLj6DAqbxTV1dn6Qk1sac/uiDYRO5xRaau9N3VqTC0UoMr1bTONpia9lpMkZPg0hNfzgQ5yKzJIi9Ayx6H4hJaZ8ysyoc5igF+2Kd+9nlxXsNmlkjIdwqI/bYv58gawyW/B61pZ8cG3MvToGJ1nPR9F0Vcj//z2YkU3M0N8JnRldEh7cm311uWJCi+ykKuQ+gr7d5LpkMRwl/bupf6+7dgoHXErYvbsefa+O5bsCQ48tpt11yQbrvJ/iMIhKNXV0nrsfIa0ksjLEJ55NURoxlKnxhRDzR5HxqQKDkw5pFKtVa7iSxce4NELitx4/TKOH3R53gsysRKJ7W0FKD+rrOtoh0O+ezXHHruXY48F78u2rEsMwSgMbKfwLZhz1pvIzncYPeySX3omhf07EXJ89ZKcT3pCt74XA0C4qc/o0OP+frKXNlBHXbaRYa2W7jJoG2KmMvjYyQmdPWtwi7oUVIZzfFLLzj8tND8ayhJ6dmMHfLtgFFql9X4UXEXJvR8TkhKYCeIKBtRCryX1FUJEFSW1KGwytOfUkgBTNBBNYK+rB00t6cVBHOGdV3ejUFx67U62fE1/cZOM76ZI5/yXZVnwutZQv4sw9Jd0wcv+hJ73t3PyyjXkugJp0DbUL3jZn3DssXt1JZJjitYFUqGqfvUSuyZed/gzROrlBSEoUWIIvM4VyMBQf9hOZUgskG4r7ZA20UUJM3ocDW2xkW1Z55FdsE7Az0yJfgYgYjfVau1Ji1f7RJfvXo3pnaHPnxfa6oUtFaaEN32YLTa9ppb0VDkQh6MSn3jpLMVy+OclO9+pUHH99zgwZ1WWw98fJTtfcIvgjiiPHDRBHP63/0u+52LvWsKcVVkWOBdz8NsjgFahV3/gEW77t8C2dWQHGGmms2cNX70kyIIY7j/urbfbl/j0cVS60+Rg2/PMvl1Xz9gOTSYIBFkXtmoLWuqza/WZeebYxBVGidAc242/o5kXvs3Q3UI4uDgph7aPUuTPoniKkd8rWjtWkTsjw7FHHiboZZv35jxYk8SSiC0lvGmEag7PbD2YcDe06UB79yLV0XUpUOnEMCjsGsPpED/wt7C7TGnoQAUBLHhdK4e/P0rXa/WrQcdplndzGEYPu5SOKXre387v7hnx1WDjjbWlnsu29nDb5f0Va7LJyJbybNKDMKnEOSXszmZ2wyAbQi4koRmV3i5Bb6v4SSqtITu/uXg0iyOm5p5+FuONp+v11q2luznn6KZYxx55OGF+tDDBxMhM99N9sPbEExOT7k7Wccoi1fM/31/X3J1fvGF2dkObDizoPO7v24S34FVZFrwiy/EDZXCEm7bq9obK1ZJee/fSCq+rIbpn/lMXEcjOF0pHXY7suIXysG7WA9B2isOSd7dR+oNi0Z+2sfjtbSy6uI3WeVKRAaIJL+ytzHAOpSOu1aTblu7Caq7tTY1TYY2kZ9Rf2/6X7zmTfM+ZPklV67ORlLliYK5hiC+arxuHgPyTHBVJNjz9nBRPkV98LsceedgPNp8qaAkxJbyphErj9BqDg3tbK7IYzPEHX/84bYv08m/89HK/9BPlcGBxHLLzxff4nrxyAzfe2E+mQ8jkYc6qFrJ5h9GnXfr/XpPuWFH5f6x892rf1pfrWk2uqzIcxsTG6TS3w6FzUeILWjOuDRGfvW+ruea12L/Pt+kV+/f5BB9XBt4Pli6H7XZGarRDa5LIzkivyYi3Ryajj8LBHQD+a4ACcRLeRJGqudOEWZKR0fTqrfv0e2KrDud6HI78RMfwiQNOm5DpsL7wmbD0YwfpFnYFJaNA26Wuv/NtuAq2fHw5iy9u5+C/HKd1noM7ppizKstv77ypcg1d6/1y9cXBTdat1/pSU5Tkoiou4LdpVBR9ldbAeG3D1wgkPqN2VstqcHJaSo028Y6qsLmlp0EmsP21zhO/Sbh9r+qop3CAnhPY76KoTni1SCxq+0sdGjUxaXWzvXuRev7b6lNvH/9yqt4mYuTwIUpjmyukvWOP3RLkwnoloIqD2/1eFQZOTigMbNKdvHaNUdg1hnJVqKMa6CDn69fezZMjx8l0CL/bpiW80aMuY39QDP54lPzC9eQXBnF+0EtxUKvQOvTFSHy9lHmEQr+unpI/o538Ge2AJrykIgBArKSXYa1f9NN2ZhhEA46NWl8Y2I6TE1/y86U9C1H7YHF/WNqzCa9+9FI7Nq9W+Epyq0eoHWiseCjR+ZEGKU8R6vTcNoOM1dSk17ZgIaADYY89dgvHHgvaMB687/MAZPJCaeiAbl94ROHkdKOe7BwhO0c4eeUGHUTriN48xBHf7Zffx9Den1A4uCO2Gkrx0E855cJWJAv5hVqyEk6lOLCD4sAOMryPjd852yuBXkDI8eyefRT2HCd/RjtCN6WhA7TOW0rrvLCjpSW/JNZzqyjicDoOp4fmh9XQvqC/hS/x9THUf19I2h09qkLSXXvXSnJLtQe3rSu8nsp7NBq9NYKS89ZrdRKsBjtY2T5OMQVw69xmGE1NegArP/Sp0PGxx24h27IO0D0qkgyjdm8Lm+CKu8sUY6qdmPgyHb3/FIWDOyge2kHx0E9D8wYe1A4RceCkxavJLz6X/OJzAXDp5+p37LeOD+NymDJ9PLvniH+N4aPbGT26n2znEpyWJf5nMLF+RsqLy9Cw7XABwrnCNqJjuZ7TdGBzOVwUNXOS0N69NGTfc4sqRHwTbfY9ccSRnSZBoxonxfEZaW+8MX4pJggFblnVtdWCiPSLyCMi8msRedgbmyci3xOR3d7r3IkutalJb+TwIUAT35yzrvbHS2ObgzmFzbH15UpHFEd/fUvQ28KUQXLvp+Ru4ZldGym5W8jOc2ICajVy3eeS634Fykv/zS18BaAlvsLBHaHNEB3kKwzz2dZVuPRR5hdAUGIedFC1UdHd4SCNK+rNddnm2/Kin9eouPnu1b4TxzhYMpwTIjJvMFQcwcDJCWUeCcXquUVFe/dScj2nTarZ9/gQZ9PLW+f0ZquutVRYW+VNMUVorKT3GqXUCy3b3zXAg0qpFcCD1NE3OwlNTXo2Tnltqy/hxaEwoB0JY08rntm1MeRY0Pt2aEmyTUlLBp1a2vNsY5INzkclP4PSUcWcc15kkV+AzEmCYgjFEGUeie1L4Q4ryq5uVGQKmdrtJB3ejMs2L7ZPOzZsx4LD6SgXv+KMgT2nWtoZaILLd6/2HRm2J9icmx6MX52NSnTV0tJSNB6KKQ9ZeQtwm7d/G3DxRC/U1N5bEalY3Jyzrg7Z9mzku9f7D9UmPdA2OyPRXbJ1TR2lhgJi1IG0BRx6KfMPWhqz7INOFkaHf5VwnQKtHecD4JbCwc2G+Ox/BHdYUXK30JZfx0hBS7TRqivRDA3j9TWf39gjjw/sDwVAG0RtdYYM27uX+kQXF/c3VZJeuIpygXjSM9JfnmTvbj4yNxmpbS+ESXtT2+YvUotXv6+uuU9+48bfAoPW0K1KqVvNgYg8CTyN5tKvKKVuFZFjSqk51pynlVITUnFnjaQHOt8zifAgkPb8+Z6qePLKDf5r1rmKb1x+pGZl3ajjQDFEW9c8cl3rNXm6iiu37vHbTppSSa0dq2jtWOW/zxBe8Bku8snu+NBmysNh9dbpENry6/R+TIkpvZaib+8z5OfH8ll/0bgQkyTCA02SJuxHe77DJDddkp5xcFQ6OvKR1/FeN622MnVQ2mFYzwaDSqkXWdutkYu9XCl1LnAR8CEReWUjVzrrJL0AyX1ST165IeSssB0ZTotQOuZSOPjT2C+AkQgd3ky+50w/ANiu/pFtPZ/R0c20tq5jdNSkYsUF5/aSbbkIJ6ulPB+eNznT4dWriym343SIL/VBfI09CNv+Ons0ubteMHXmJKHYv4/27qUcH9gfPI9IFocht/nnvonRoyo2lW067HnxfTP8FVBJdrZEl/ezLpJseva5lPxCaICkt1AtemN9kl7/HTfVfT8RuR54Fvhz4NVKqUMishD4kVJq5UTWWlPSE5GviciAiDxqjcV6UkTjCyKyR0R+IyLnWu+5zJu/W0Qum8hiDbRTIzni3zQQgsrQFHdM0fI8h83fOa0im8IcZ52rcNnmx7VlWy6itWMVDgvItp5PafRnCOdRGv0ZNuHlu1dbTXS0/bE09l0kWtbBU42TupLZaMuv05If20Kd0QzZ2Xa/of6NlJ9VFAY2+RJf51nPpzCwnfbupbR3L6XMIxWOjc6eNXT2rAkFLxvCW/+Fvf5nm0pUJ7wowmQXHbOdG1Gys8+naCAUqLH6tmoQkbyIdJp94A3Ao8A2wPDGZcC/TnSpNSU9T7R8Fvi6UuqPvbGNwFGl1M0icg0wVyl1tYisBv4SXbLkJcDfKKVeIiLzgIeBF6H19F8C/10p9XSNe09KDDVqbRyKT7i+hBUlRsCXFPMrNWON/F4b3txhhSpDafRnkS+Plur8mECgPPY4wgJc+mhxXo7TJiG7Xta50JfobETHjIMDgiIEUWivbjg7ozCw3U8fM9KbkVxtDzKE08yMdOjkhOs27mXEVWz68HL/mo1GHOElxfBVI8dA0ovP9LAlwZT4Qpi8pDd3oTr1gvokvX13J0t6IrIcMGXJW4BvKaVuEpH5wLeB04B9wDuUUkcnstaakp5S6idA9OJJnpS3oMlRKaUeAuZ4ougbge8ppY56RPc94EImiZ53f6Lq+Wd2bSTTIRR3l8MpagCu4ua79nPzXftDw+II4gi5FRmcDqshUY/D2B+8MlcZyLaeH1GjPMnTEd920dL6R2Ra5/pfMHdEj9sVmo0dzyBuP+OsqMjWsDcw2RV9dC5dQ2Fgk09OQ/33MdR/n++g6OxZQ757dayDw5b+CgPbKfbv43MblrPlmtP97I5qzYUaCdNDw97057TJsBDaD1TXBz0ba7jIgHBBldS3FJNBo7y3Sqm9Sqn/5m29SqmbvPEjSqkLlFIrvNcJER5MvJ7eKUqpQ95iDomISTBdDNgscsAbSxqfFPq/dZOvkka9tQblYZ12Vo5IU9l5DvtGRnCorMwMxAYwmwrNhd1lxsZ+FlzLc5iUxr6rbXhtUtELwFQXDsqp91FyNVFmh6/yCc5IeObYvLahnRuu909jQlh0mtqdGBXbHVF+TjCEJTNTTdn0D9EIHBt2tRV7vB7oMlv3UV+F5DAUT9Wl3karKmuSM7Y+7dUNpDhtdtDEF/XETzzDI0UCFLG26WZEo723cTWMVJXxyguIfEBEHjaR2LWQRHYGtn3PRna+sLStFYD3fircivFTNz5JfmUL+ZUtFRLi8QOGzfQX7SPfeAsld4vncOjz//DiacxqzHxMywZp/XNknasou7srVFx3WPmbQSZv1tLrS3hl7vTU3aAdpu3BtQlON0lKts3Zkt51G/dy1c1P+OPXbQy6uGU4p0Lii6srOHXIe/XxHiIIYQmkviBmzzzzPoRTyXCOJyk2roJLigCzpbRUXd5bEekB7rVseruI8aSIyFe8/TvseWZTSv2FNx6aV+W+DfvpiNr37F664oiuvOIIV2zdzdK2Vm745DK/hp9piwgg2UAiczqE40d3YL5E2dYgPMWQ3shwkD1iQlEM7EwQIwHa9jyzb16NbS8uK0MjLGVdf+eZbLxyORu+pAlr04eX88kvPcmNVy7T148UF03Ktb1u414+t2F5aC5Uq7pSb0+MAON3ZNQfkwfRAOW0oGgEk7bptZ68UHW//L11zT343c/NaJWViZLeJuCI5ciYp5TaICJrgCsJHBlfUEq92HNk/BIw3twdaEdGVb28kaQ374U6ja08rMh0SEjdLe4u+7Y449TwxyJwsmFiyp2R4frPPMlH376PbOv5yxLDJwAAES1JREFUgWRnv9cj15K7xVJv8cdsRM8b9TbaOS3ee11JNJds7eGbl2fILz0TdyQcimL2DfnVqqln5tQiu2gv3Hpgk55ttzOB4Yqh0HFyAHOeoLVkZ0X6WerAiEVDSG/BS+sjvd89MLOkV0/Iyh3AvwMrReSAiLwPuBl4vYjsBl7vHQNsB/YCe4CvAlcAeOR2A/Af3vbZyRgiJ4Kjvw6Cmg3xGacFAK4iv7LFL0hwxdf3xNoopAVUSSEten+4v8xnP7eMOee8yjsfXM9sSbm9ECa5KOEZhAlvGw6nV9TYS5Ksbr+8H5dtFPbv5PjAfob6w+q+Le2ZnhlR2KptMsIkHG0MXgtRorOdF3qsE6HTekdlodGwNHeq95rG5U0LZlELyFkcnDwxtOXX0b7ECRwVFunZx1ds3c3fXXpGaMwEE9ud18rDugBC0DayL5G8qiFOCrQlSjtsBeLKy8eTnu1g6FyqbXtD++/zbXuhSsvGXBlTjACCsJdkaW8ibR8DxKu4UfXVTkMz+3lLXe31yDGYZ8fqpeQXi8lLes9bqLpe/Gd1zT304OebW9J7LuKZXRuD0BBPGsvkJQg3Af7u8hUVhGiCie1XQ4C68kvfpBLabYkwFKvnCBlnhX8utiVkpFeHwW2X38clW9cAfQzt30h5WPHpO85EuYSzLjzCu2bzXtyirrtnHBlRRAmvMoxlvM2CqsGupxeotDrw2BBdwXNeXODVMhwi3rGRYqowDQUHGoYTkvQAP5kfNMGUC5akF+QIVhQfNQgTYCDRKIaqqrOxcMTL4OjVKXDRmEIP0fp6EJeeVild3e4Tn/Z2f/Zdd4fOl59VXLdlL9ds3qs/bk7X1rt+7U6/EKkhRzs1zXhx6ysjH8XE1eFAWuu1PLgQlJzqjMzL+1tKflOEtDFQc6Mtr1PEQrFxNrFFVd66UKtEehW4ikwHFeWmQmtxJFZt1k4N+77xUpapKvPpO94GaPIz9j1x4IYrlnHTh7RXt9i/zw9ErhbiYsrYNwLVHR/xQcjBZ42vvxcOVjZbqt5OCRqUhjYdOOFIz5bworFxIcRId7GIJcZxkp8jlIe11Jh1rmKksJmRwmZNyq7Caav25kqVttpaPvuuneS713P9nW+z+noE+NyG5eR6TvMluuMD+726gtXjIavdM37NlcfVy8dDVGWtBkNwKclNH2aLI+OEIz0IiK/kbgnU17g/RtK4PaVNKtKlsi0XVSdNW2WOzrNUXdDSqO72pk+P30lSSTDKhevX7ozNo7XDWcKl4tdb+0Efjsrr29Vvksi41zofDiCGsGRmsi/iNoMwsQV2v9SWN81Ie2TMDvhSVBJJORIqTx+FW7Lrv9UZ8Gpshkn39PJzjcRXLqjqUmkFNJHYZeNtFAcDsotKcMolsOGVdWFRPS9KkLWly8s8O+JlW3sIO1ri36t4ihbnhSFir1dSs4kwrspKiimGAlWub5tpnHAhK3GYc9bVFW0mDWzCiytXH66aXAhlZYQClZMkSQ+mf66PGhKmqfkX58nV48bzaoeRBAgqsQSk19mzwc/PNWXnxdGEpx0WdhZItJ5hrTCVuHCW2l7e8YSZpCEpE8akQ0ha8gvVnDMvr2vukR03z2jIykQLDjynYFLQKhAhHkOANvkFv1xhwoMgUFmNqZrOEckEqWuhgqMkZ23Eh65omDCSskcsua7VnoSnCccQmy0JGsKDPoqDfaFz7d1LKQxUc5jEqbQ2wcUVWY2ikgjHQ2Ip4c0gFE2hutaDlPQgmfAcqfmHLI1qKS/ben5QZMASGn1pL646crSisv1eSzr0q7h45FcrJEaTYZhkgsIMAbEUBw0hro/0+e213qPnFwbs89VsdX2RefVJdPZ10yyKWQilC/TOBpzwNj3wJLhwDX+NBKnMVnlbWoKeGMZmIVZGg5+WZh1Li+C0eaWjsnozZCcZEtPXJufESFI7eykObqIwsEk7OO48k+vvPJNLtvaQ714fcVrEvz/+fva5qKRXrRvdBRhnRJwTInVONDHKdW4zjJT0CMgklDcL4AhtHfFtJw3xjY39SjszXC3VScYjP+/YttPZBBg16Prvs8bjSK4+4ouTrpKlrnz3enJd6/1qLAD3bDg7VIw0uAaRUJfxSHG1Q3mMxzb5fGX59xRNgDQ4eXYhqIcXPi6NbfYlsiS0tHidzzx12Eh6TpYKB4aKiP9xxKf7bkwG1dTJKPH0+pKcOHqppiz8+i/s9cit0kZXGbNXy3kRXVctoswnel6NsyJVfZsPs4X0Uu/tJGFLXiX3frLOhT6BCuf55aaiam41RMnRRnV73njsZ+H32E6LdV/cy+a/XB6aZdv3Jg47Pi9FE2Hy3tu2heqkJfX1+3pm7y1pwYHZimzLupATJNtyUSwpjZvw6s0GqUBceEp92RHFwU2s++Je1n2xsoxUcXC7R4q2pDjelLsJpuh5SNXZ5oZC4Y7Vt800UtKLQVt+HR1zKoN6bfgSnlUgVAcVr/PPR0NY6kaNmL7qiPOgVkeuS9v0otJdcH51pCx/nMTXS6XDwsbEpDvbcZESXxPDhKykGRmzEyOFzbgllUh8fpxepNeFsQPqain3Uxr9mW+jGx3dzOhocmYHRIKZIwUQqmWFhNEY1dGW+KSu/5Lq2RbhOfXBDl0xW0p8zYvZkpGRxuklYKSw2a/GkghHdAe0iB1PMWSVNa/tnIja8Pwg6DqqKk8OWiqzs0HipD1zLt+9HuWG09iSr9sY8o06LFIHRpNCNYeToh6kkl4VjBQ2x0p7vtTlq7b3R2b0eX1XdV+HUHJ8HTaNrHNVmOQiEmWjURjYTnFQb1Gpzj4uDGyiOLjJT1FLRlIWxviQEtwsgx3rWm2bYaSkVwPDxzbVsO/1kXWCvuXBF1Wrcob4ICCseojPwDQqsvcnR3zxRJTvXk2+e7VPbNXeV73tpk12qZf2hEFacKAxmE0hK6aZd71obdWq83gI0Ma4qzNXoJL88t2rw8HU3k+iPVadEOspOGDmNxchnuDFCiYdQuJkTlXtJ11a19zhP2xKCw7MZkyUfGynRj2SW25FJmhmROA4aRz6KAyE4/UM2SUTnU1ytRwYyceXbF3jV3aeKZzAhNcwNIMUVw9S9bYJUA95GcKzs0fGr+ZWi7ELxmw7Xna+xNbkg2g6mlFrqxNcHGaa8FI0ALMoDS2V9KYB0SopcYhrARlFbkWG0pH1lI66Na9XifqCirWjIkxy2fkCg4TGdZECcxQNWo6v4ZfiOY4mcFLUg1TSm3LU/8Wvh8Sy84XsPGec0l61NVTGztnqbOmIonREVRBhrsuuwNLYgOQUsxOzRdJLSa8KGhMI20fJ3cKY+/9850U1VCO+4u4ypSPKJyWTBled+GoRXpJaGiAaxmLuXxjYVLVbWooTCLPIe5uSXhU0yrhtyLPeCioldwvZeZE/jZehYQgn17We3OnBnImFsSTn6NrSXvTX2Zb6TKXlFCc2FGWUe6yubaaRkt40YCLkWRzcFKqUXBrb7IXF9JLrWk92viCOhIhv8ggHFFeLxxOHSBGClPhObLgoCnVtM42U9KYJEy4+EIK2v2Xna6kvqZlRI5FEfMrVxBdfUHTy2RgpZhvK6LTLeraZRU3SE5GviciAiDxqjW0SkZ0i8hsR+WcRmWOdu1ZE9ojILhF5ozV+oTe2R0SuafxHaW7UKjaQhDgbX3F3WYewuEq/eqrv5DI14gt85rrWeylqmxBHE11xcJOff6tV32hVl/EVFkjxXEDjJL2p5oqaGRki8krgWeDrSqk/9sbeAPxAKTUmIrcAKKWuFpGzgTuAFwOLgO8Df+Rd6nHg9cAB4D+Adyml/qvGvWeHD3yGkW1Z5/fUqAxaruXIMHPi9iubBhUGtoecF4WBTR4xVktNS9HkmHSGhMhJSnhBXXMV/554PxHJMAGuGBeUUjU3oAd4NOHcW4FvevvXAtda5x4AXuptD1jjoXlV7quea5tw3jjm9zbgnr2RbfzXz3Wtr7ieGct3rx/HWtKtSbeH6+GBBn5XE+/HBLliPFsjgpPfC9zl7S+GkNX+gDcGsD8y/pK4i4nIB4APeIfPAkeAwQass1HoYhLrGZ9Toy4VscZ6xpMeFo+wFBduH1nZL2Nyz2eK0Gxrarb1rGzANR5Af6560C4iD1vHtyqlbvX2F1MnV0wUkyI9EfkEMAZ80wzFTFPE2w5V3DW9D28eACLy8EwmJ0eRrqc6mm090Hxrasb1TPYaSqkLa8+qC0kc0jBMmPRE5DLgTcAFKjAMHgCWWtOWAL/z9pPGU6RIkcKgGoc0BBMKWRGRC4GrgTcrpYrWqW3AWhFpE5FlwArgF2hj5AoRWSYircBab26KFClS2Jhyrqgp6YnIHcCrgS4ROQB8Bm1cbAO+JyIADymlPqiU6hORbwP/hVZ7P6SUTjwRkSvRen8G+JpSqt6YhltrT5lWpOupjmZbDzTfmtL1JMCLCJkoV9SFpi4imiJFihSNRpqRkSJFihMKKemlSJHihELTkt5MpK2JyFIR+aGIPCYifSLyEW98noh8T0R2e69zvXERkS94a/yNiJw7RevKiMivRORe73iZiPzcW89dnsEXz4F0l7een4tIzxStZ46I/JOXiviYiLx0Jp+RiHzM+3s9KiJ3iEj7dD6jhFTNcT8PEbnMm7/bi45o5HrS1FGDRkY6N2pDGzCfAJYDrcB/AmdPw30XAud6+53odJizgY3ANd74NcAt3v5q4Lvo2KLzgJ9P0bo+DnwLuNc7/jaw1tv/MvC/vP0rgC97+2uBu6ZoPbcB7/f2W4E5M/WM0MGsTwId1rO5fDqfEfBK4FysrKXxPg9gHrDXe53r7c9t4HreALR4+7dY6znb+361Acu8711mpr6D07HN+AIS/mhTnopS5zr+FZ0DuAtY6I0tBHZ5+19B5wWa+f68Bq5hCfAg8FrgXu/LMmj9A/vPCi/tz9tv8eZJg9fzPI9kJDI+I8+IIIJ/nveZ7wXeON3PiEiq5nifB/Au4CvWeGjeZNcTOTdlqaOzYWtW9TYuFWVxwtwpgaf2rAJ+DpyilDoE4L12e9OmY51/DWwATCnP+cAxpdRYzD399Xjnn/HmNxLLgcPAP3oq99+LSJ4ZekZKqYPAZmAfcAj9mX/JzD4jGP/zmM7/+feipc1mWc+0ollJb8pTUareXOQk4G7go0qpP1SbGjPWsHWKyJuAAaXUL+u853Q8txa06vR/lFKr0AXSqtl7pvoZzQXeglbNFgF54KIq95zR/60q95+WdUn9qaMz/ZymDM1KelOeipIEEcmiCe+bSql7vOHfi8hC7/xCwPQBm+p1vhx4s4j0A3eiVdy/BuaIiAkst+/pr8c7fzJwtIHrMfc4oJT6uXf8T2gSnKln9DrgSaXUYaVUCbgHeBkz+4xg/M9jyv/nJUgdfY/ydNaZXM9MoVlJb0bS1kREgH8AHlNK/W/r1DbAeNMuQ9v6zPilnkfuPOAZo9I0Akqpa5VSS5RSPehn8AOl1HuAHwJvT1iPWefbvfkN/XVWSj0F7BcRU5njAnQGzow8I7Rae56I5Ly/n1nPjD2jmPvU8zweAN4gInM96fUN3lhDIGnqaICZNiombWgv1+NoD9Inpume56NF+N8Av/a21Wibz4PAbu91njdfgL/11vgI8KIpXNurCby3y9H/mHuA7wBt3ni7d7zHO798itbyQuBh7zn9C9rbOGPPCPgrYCfwKHA72hM5bc8IXTj3EFBCS0jvm8jzQNva9njbnzV4PXvQNjrzf/1la/4nvPXsAi6yxqf9OzgdW5qGliJFihMKzarepkiRIsWUICW9FClSnFBISS9FihQnFFLSS5EixQmFlPRSpEhxQiElvRQpUpxQSEkvRYoUJxT+Pw5nPXjf3VbUAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11de12b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow ( lc, interpolation='nearest', vmin=0, cmap=plt.cm.gist_earth)\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "2.7.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}