{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 空间向量数据\n",
    "\n",
    "## GeoPandas 简介\n",
    "\n",
    "GeoPandas 的目标是使 python 中的空间数据更容易使用。它结合了 `pandas` 和 `shapely` 的功能，提供了 `pandas` 中的空间运算和多个几何图形的高级接口。GeoPandas 使您能够轻松地用 python 执行运算，否则将需要诸如 PostGIS 这样的空间数据库。\n",
    "\n",
    "### 数据结构\n",
    "\n",
    "GeoPandas 实现了两个主要的数据结构，GeoSeries 和 GeoDataFrame。它们分别是 pandas Series 和 DataFrame 的子类。\n",
    "\n",
    "### GeoSeries \n",
    "\n",
    "`GeoSeries` 本质上是向量，其中向量中的每个条目都是一组对应于观察结果的形状。一个条目可能只包含一个形状（如单个多边形）或多个被认为是一个观察结果的形状（如组成夏威夷州或印度尼西亚等国家的多个多边形）。\n",
    "\n",
    "Geopandas 有三种基本的几何对象（实际上是 shapely 的对象）：\n",
    "\n",
    "- Points / Multi-Points\n",
    "- Lines / Multi-Lines\n",
    "- Polygons / Multi-Polygons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import geopandas as gpd\n",
    "\n",
    "plt.style.use('bmh') # 更适合绘制几何图形。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    POINT (1.00000 1.00000)\n",
       "1    POINT (2.00000 2.00000)\n",
       "2    POINT (3.00000 3.00000)\n",
       "dtype: geometry"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from shapely.geometry import Point\n",
    "s = gpd.GeoSeries([Point(1, 1), Point(2, 2), Point(3, 3)])\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 6))\n",
    "s.plot(ax=ax);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    LINESTRING (-77.03687 38.90719, -76.61219 39.2...\n",
       "dtype: geometry"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from shapely.geometry import LineString\n",
    "l= gpd.GeoSeries([LineString([Point(-77.036873,38.907192), \n",
    "                              Point(-76.612190,39.290386,), \n",
    "                              Point(-77.408456,39.412006)])])\n",
    "l"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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5bCmHLeWwpRw9tFzWBGJ4eBjXXnstBgYGkJ6ejo0bN2Lv3r247LLLAADNzc3YsWMHxsfHUVFRgdtvvx033XRT3Gu0tbXFLhIzsqSkpFN/EcFuMaMiMwkVmQtXLdxzm+a1DE5gLGCO3SVqYCqARe4+i3FfGOO+aTQNxN+dwGYxoch1zB2i0o9ed5HmWF2b5vG4lMOWsthTDlvKYUs5bClHDy2X9dPTT37yk5M+f9999+G+++476dfMX3l+Is8999xyhqRbfX19SE9P13oYCctkMiEjyYaMJBvM492oO/vouX7hqIKBqUDcbWfnr7tw+xdumheKKOia8KNrwg/AHfdcutMaW6k4duWiIM0BqwFXLXhcymFLWewphy3lsKUctpSjh5ar69evZAhWswmlGU6UZjixCfH/Ak35w+ibmr2Au2duw7xe9+zeFaFFLrZw+8NwD4bx9mD8pnkWE1DoOmZikeFE2dxf053814aIiIhWL/4kpJKKigqth2AYy2npclrhclqx/rhN8yJRBUPTwdmVimNuPdsz6cf4zMJVi4iCuesxAgueS3NYjplYzK1apM/eftZmObNN89TG41IOW8piTzlsKYct5bClHD205ARCJePj40hOTtZ6GIYg0dJinr0OosjlwPml8c95g5EFE4v5vwYXudjCE4jg4LAXB4fjVy3MJqAgzR63ajF/3UVmklUX97/mcSmHLWWxpxy2lMOWcthSjh5acgKhkqmpKa2HYBhqt0yxW7A2NwVrc+NXLaKKgpHpEHrc/rg9LXrcAYx6QwteJ6oA/VNB9E8F8eee+OeSbea4DfPmJxbF6Q44rCu3asHjUg5bymJPOWwphy3lsKUcPbTkBEIl3MNCjlYtzSYT8tPsyE+z47wSV9xzM6EI+tyBuH0t5icZ/vDCTfN8oSiaR3xoHvHFPW4CkJdqR2nGMXeISneiJMOBnGSb+KoFj0s5bCmLPeWwpRy2lMOWcvTQ8ox3otZCIuxETauToigY9YUW7GvRMxnA8HQQy/mXzWk1z61YzN92dnblojjdgSQbj3siIiKSs6I7UdPiDh06hPXr12s9DENIpJYmkwm5KXbkpthxTnH8pnmB8OymeT3H7cjdM+mHL7Rw1cIfjqJ1bAatYzMLnstJsS3Y16I03YncVBvMJ1m1SKSWeseWsthTDlvKYUs5bClHDy05gVBJAi7s6JZRWjqsZlRmJaEya+GmeRMz4dj1FfO3nu1x+zHoCWKRu89i1BvCqDeEN/vjN81zWEwoPmZiMb+vRUm6Eyl2i2Fa6gFbymJPOWwphy3lsKUcPbTkBEIlGRkZWg/BMIze0mQyISvZhqxkGzYWxq9aBCNRDEwdc63F5NEN9DyByILXCkQUtI/70T7uX/BcVpIVuUkm1Ix3x00s8lPtsBhw0zy1Gf24XGnsKYct5bClHLaUo4eWnECoJC0t7dRfREuymlvaLWaUZyahPHPhtvVuf3jBhnk9bj8GpgJY5O6zGJ8JY3wGaB4fi3vcNneL2+NvPVuS7oCLm+ad0Go+LtXAnnLYUg5bymFLOXpoyZ8OVNLT04O6ujqth2EIbLm4dKcV6QWp2FCQGvd4OKpg0BNYsGFejzsAt3/hpnmhqIKuST+6Jv1Al3vB94hNKDKO7sxd6HLAuspXLXhcymJPOWwphy3lsKUcPbTkBILIYKxm09wKghNAetxzr731DlIKKhbsa9HvDiC0yMUWbn8Ybn8Ybw/Fb5pnMQGFc6sWs7ednV+5cCDdqY9N84iIiEgdnECopKysTOshGAZbyllXVY7U1BSsz4vfNC8SVTA8HZzbNO+YlQu3H+O+hasWEQVzE5AAXkb8hjZpDkvsAu75CUZpxuyqhd2ycpvmqY3HpSz2lMOWcthSDlvK0UNLTiBUMjU1hdTU1FN/IZ0SW8o5UUuL2YRC1+wP+eeXxj/nDc5vmje3ajHpj/3/4CIXW3gCERwa9uHQcPymeWYTUJBmj79D1Nx1F1lJibdqweNSFnvKYUs5bCmHLeXooSUnECqZnJxEUVGR1sMwBLaUczotU+wW1OYmozY3Oe7xqKJgZDq0YMO8XrcfI97QgteJKkD/VBD9U0G80hP/XLLNHHdnqPnrLorTHXBY9blqweNSFnvKYUs5bCmHLeXooSUnECpJtN+m6hlbypFsaTaZkJ9mR36aHeeVxD83E5pftYi/kLvXHYA/vHDTPF8oipZRH1pG41ctTADyUu3H7Wkxu3FeTrJN02ODx6Us9pTDlnLYUg5bytFDS5Oih90olikcDqOxsRH19fWwWCxaD4eIlkhRFIz5QgtuPdszGcDwdBDL+TByWs1zE4v4DfNK0h1IsvFzgYiIaDkikQiamprQ0NAAq/XkawxcgVBJc3Mz1q5dq/UwDIEt5Wjd0mQyISfFjpwUO84pir+PdSAcRf/U3LUWk0fvENXrDsAbXLhpnj8cRevYDFrHZhY8l5Nsi7vtbGnG7F/zUu0wC/3mRuuWRsOecthSDlvKYUs5emjJCYRKIpGFP/DQ6WFLOXpu6bCaUZmVhMqs+E3zFEXB5Ex4dqUibuUigEFPAIvcfRajvhBGfSH8pX867nG7xYRi1+yF28feIaok3YkU+/JWLfTcMhGxpxy2lMOWcthSjh5acgKhEpfLpfUQDIMt5SRiS5PJhMxkGzKTbdhYGL9qEYpEMTAVXHAhd4/bD09g4QdsMKKgY8KPjgn/gueykqyxDfOOvZC7IM0OyyKb5iViSz1jTzlsKYct5bClHD205ARCJZmZmVoPwTDYUo7RWtosZpRlOlGW6VzwnNsfnrvl7DGnQ0360T8VwCJ3n8X4TBjjM9N4azB+1cI2d4vb+VOh5icWWcnaf4AbidGOTS2xpRy2lMOWcvTQkhMIlXR1dWm+zbhRsKWc1dQy3WlFekEqziqIv1d2JKpg0DN7ClTPMRdy904GMOlfuGleKKqge9KP7kk/0OVe8D3mL+QuPWb1osjlgHWRVQs6sdV0bKqNLeWwpRy2lKOHlpxAENGqYjGbUJzuRHG6E+8tS497bjoQPnrr2cm5SYbbj353AKFFLrZw+8Nw+8N4Z8gb/z1MiK1aHLthXkm6AxnOxNs0j4iI6FicQKikpKTk1F9ES8KWctjy5FIdVqzPs2J9Xkrc45GoguHpY661mAygc3waA9MRjPkWbpoXUTB3TUYAwFT897BbZicWc6dDza9cFLkcsFv0uWneSuCxKYct5bClHLaUo4eWnECoxOfz6eIiFyNgSzlseXosc9dBFLocOL909rHBwUEUFBTAF4ygd+ro6VDz1130uf0ILHKxxXQwgsMjPhweid80z2wC8lPtsQu5Y7egTXciK9n4qxY8NuWwpRy2lMOWcvTQkhMIlYyPj6OgoEDrYRgCW8phSznzLZPtFtTmJKM2Jznu+aiiYNQbOjqxmLuQu2fSjxHvwlWLqAIMeIIY8ATxam/8c8k2c2yTvJLYhdwOFKc74bQaY9WCx6YctpTDlnLYUo4eWnICQUSkArPJhLxUO/JS7Tj3uNXmmVBkdtO8uA3zZicaM6HogtfyhaJoGfWhZdS34Lm8VFvsOov5DfNK0p3ISbGJbZpHRER0LJOiKIvc0FDfwuEwGhsbUV9fD4tleZs/ERHplaIoGPfNbZp37B2i3AEMeYJYzoe1w2qOv0PUMasXSTZ+bhIRUbxIJIKmpiY0NDTAaj35GgNXIFTS0tKC2tparYdhCGwphy3lqNHSZDIhO8WG7BQbzi6K3zQvGI6ibyqw4HSoXncA3uDCTfMC4SjaxmbQNjaz4LmcZNuCDfNKMhzIS1l807yVwGNTDlvKYUs5bClHDy05gVBJOLzwfvJ0ethSDlvKWemWdqsZlVlJqMxKintcURRMzoTjToOan1gMeAJY5O6zGPWFMOoL4S/9x22aZzGh2DU3sTj2Qu4MJ1Ls6q5a8NiUw5Zy2FIOW8rRQ0tOIFSSlpZ26i+iJWFLOWwpRy8tTSYTMpNtyEy2YWNh/KZ5oUgUA55g/IXcc9ddTAUWrlqEIgo6J/zonPAveC4zyRq7kLv0mNOhCtIcIqsWeulpBGwphy3lsKUcPbTkBEIlOTk5Wg/BMNhSDlvKSYSWNosZZRlOlGU4Fzw35Q8fs6/F0VOiBjxBhBdZtpiYCWNiZhoHBuNXLaxmE4pcjriJxfx1Fy7n0v8Tkwg9EwVbymFLOWwpRw8tOYFQSUdHh+bbjBsFW8phSzmJ3tLltOIsZyrOyo9ftYhEFQx6Znfhnp9YzK9eTMwsXDYPRxV0T/rRPblw1cLlsMSfDjV33UVhmh224zbNS/SeesKWcthSDlvK0UNLTiCIiCjGYjahON2J4nQnUJYe99x0IHz0zlCTgdh1F31TAYQW2TRvKhDBwWEvDg574x43m4DCNEfs+oqSdAci7igKZ0LIcBp/0zwiokTHCYRKioqKtB6CYbClHLaUsxpbpjqsWJdnxbq8lLjHI1EFw94geicX3iFqzLf4pnl9UwH0TQXw556p2OM/eudtpNotx22YNzvBKHY5YDfIpnlqW43HplrYUg5bytFDS04gVBIIBLQegmGwpRy2lMOWR1nMJhSmOVCY5sB7Sl1xz/mCEfROzZ4Odey+Fr3uAALhhZvmTQcjODziw+GR+E3zzCYgL9UeW7WI3SEq3YmsZK5aHIvHphy2lMOWcvTQkhMIlYyNjSE/P1/rYRgCW8phSzlsuTTJdgtqc5JRm5Mc93hUUTDqDcVWKt7q6IfXkoJetx/D04uvWgx6ghj0BPFaryf+e9jMKE6P39eiNMOB4nQnnKtw1YLHphy2lMOWcvTQkhMIIiJacWaTCXmpduSl2nFuCbDGNIK6uhoAgD8cRd/8nhaxi7ln/zwTWrhq4QtFcWR0BkdGF26al5dqi98wb24FIyfFBjNXLYiITotJUZRFthnSt3A4jMbGRtTX18NiUXdzo9MVjUZhNq++33ypgS3lsKUctpS1lJ6KomDcd/T2s/MXc/e6/RiaDi66ad6JOCyzF4sfu6dFSYYTJS4HklXeNE9tPDblsKUctpSjVstIJIKmpiY0NDTAaj35GgNXIFTS3t6OmpoarYdhCGwphy3lsKWspfQ0mUzITrEhO8WGs4viN1IKhqPo9wRiG+XNr1z0ugOYDi7cNC8QUdA+PoP28YWrFtnJttj1FbO3np39/3mpdpFN89TGY1MOW8phSzl6aMkJhEqCwaDWQzAMtpTDlnLYUtaZ9rRbzajITEJFZlLc44qiYNIfXrBhXq87gAFPYNFVizFfCGO+EJoG4jfNs1lMKHYdc61FxtH/n+rQz39OeWzKYUs5bClHDy3184lnMCkpKaf+IloStpTDlnLYUpZaPU0mEzKTbMhMsuFdBfGb5oUiUQx4guiN7Wtx9A5Rbv/CTfNCEQWdE350TizcNC/DaUXJ/IZ5sTtFOVCQ5ljxVQsem3LYUg5bytFDS04gVKL11fFGwpZy2FIOW8rSoqfNYkZZhhNlGU6gPP65Kf/Ray2O3ZG7fyqA8CLLFpP+MCYHw3h7MH7TPKvZhMI0e9y+FvPXW6Q71flPMI9NOWwphy3l6KElJxAqaW9v13ybcaNgSzlsKYctZemtp8tpxVnOVJyVH79qEYkqGJxbtZjfiXt+9WJiZuGqRTiqzJ425Q7gpeO/h8MSu+VsyTH7WhS67LBZTv8CSb21TGRsKYct5eihJScQRERES2Qxm1Cc7kBxugMXHPecNxiJXV9x7OpF31QAwcjCVYupQAQHh704OBy/amE2AQVpjrkVi9nToeZXLjKSuGkeEWmPEwiVFBYWaj0Ew2BLOWwphy1lGaFnit2CdXkpWJcXf35yVFEwPB2cnVhMxq9cjPoW3zSvf2r2dKk/9yz8HrMrFXOrFnPXXRS7HLDPbZpnhJZ6wZZy2FKOHlpyAqGScHjhUjadHraUw5Zy2FKWkXuaTSYUpM1eUH1eiSvuuZlQZO7CbX/sFrTzG+gFwgs3zfMGI2ge8aF5xBf3uAlAfpodJekO5NgVrCkIx667yE62cdXiNBn5uFxpbClHDy05gVDJyMgIcnNztR6GIbClHLaUw5ayVmvPJJsFa3KSsSYnOe7xqKJg1Bs6OqE4ZnIxPB3E8SdEKQAGPUEMemZv77in/egtaJNsZhS75k+Fml2xKM1woDjdCaeVG3udzGo9LtXAlnL00JITCCIiIp0xm0zIS7UjL9WOdxfHPxcIR9E3t2rRfcyGeb1uP3yhhasWM6EoWsdm0Dq2cNO83BTbohdy56baYOaqBRGdgElRlEW20dG3cDiMxsZG1NfXw2KxaD2cRYXD4VNuA05Lw5Zy2FIOW8pizzOnKArGZ8LoGvOifzp8zOqFH0PTwUU3zTsRh8WE4mNuORvbmTvdgWS7Pv+7qwYel3LYUo5aLSORCJqamtDQ0HDK1+c/SZV0d3ejqqpK62EYAlvKYUs5bCmLPc+cyWRCdrIN7sFxvHt9fMtgJIr+qcBxG+bN/tUTiCx4rUBEQfv4DNrHF65aZCVb4zbMm59c5KXaV3zTPLXxuJTDlnL00JITCJX4/Qt3KqXTw5Zy2FIOW8piTzmLtbRbzKjITEJFZlLc44qiwO0PL7xDlDuAgakAFrn7LMZ9YYz7ptE0MB33uM1iQpHrmDtEHTPBSHMk5o8bPC7lsKUcPbRMzH+jE0BSUtKpv4iWhC3lsKUctpTFnnKW09JkMiEjyYaMJBs2FMRvmheOKhiYChzd12LuQu4edwBu/8K7wIQiCrom/Oia8ANwxz2X4bTGbjlbMr8jd8bsnamsOl614HEphy3l6KElr4FQSTAYhN1u13oYhsCWcthSDlvKYk85K9Fyam7VIrYj99yF3P1TAYSWcbGFxQQUuhxxp0TNX3eR7tT+d5w8LuWwpRy1WvIaCB1obW3VfJtxo2BLOWwphy1lsaeclWjpclpR57SiLj9+07xIVMHQdHD2DlGTRzfM63X7MT6zcNUiomBuIhJY8Fyaw3J0xWLuLlGl6Q4UuRywWVbm9rM8LuWwpRw9tOQEgoiIiERYzLPXQRS5HDi/NP45bzCycMO8ST/6pgIILnKxhScQwcFhLw4Oe+MeN5uAgrT5ay0csQ3zStKdyEyyctM8ohXACYRK8vPztR6CYbClHLaUw5ay2FOOXlum2C1Ym5uCtbnxqxZRRcHwdDA2oTj21KhRb2jB60QVoH9q9nSpP/fEP5dsM8cu3J6/zqI03YlilwP209g0T68tExFbytFDS04giIiISDNmkwkFabMXVJ9X4op7biYUQd/cRdzHrlz0ugPwhxdumucLRdE84kPziC/ucROAvFT7gg3zSjIcyEm2cdWCaJk4gVDJ0NAQsrOztR6GIbClHLaUw5ay2FOOkVom2SyoyUlGTU5y3OOKomDUF1qwr0XPZADD00Ecf0KUAmBoOoih6SBe6/XEPee0muNuOTt/rUVxusNQLbXGlnL00JITCCIiIkooJpMJuSl25KbYcU5xWtxzgXAUfcfeIeqY6y18oYWrFv5wFK1jM2gdW7hpXoYdqOw8ErevRWm6E7mpNpi5akGrGG/jqhLerkwOW8phSzlsKYs95bDl4hRFwcRMOP4OUXMTjEFPEMu4+ywcFhOKj9kwb/56i5J0J1Ls+vy5RGs8LuXwNq4G1tfXh8rKSq2HYQhsKYct5bClLPaUw5aLM5lMyEq2ISvZho2F8asWwUgUA1OBoysWc6dGdY3PwBdeOLMIRBS0j/vRPr5wR+CsJOuCC7lL0p3IT7XDouNN89TG41KOHlpyAqGSmZmFS6F0ethSDlvKYUtZ7CmHLZfPbjGjPDMJ5ZnxO/y+8847KK6qnduN++iGeT1uPwamAljk7rMYnwljfGYaTQPTcY/b5m5xe+ytZ+cnGmkO4/84xuNSjh5aGv+I1YjT6dR6CIbBlnLYUg5bymJPOWwpJykpCRlJNmQk2bChIDXuuXBUwaAngJ75C7knj1534fYv3DQvFFXQNelH16Qf6HLHPZfutMb2sijJOLozd6HLAatBVi14XMrRQ0teA6GScDh8yvPHaGnYUg5bymFLWewphy3lnG5LTyC8cF+Lydm9K0LLuNjCYgIKXY5jduR2xjbQS3cm1qZ5PC7lqNWS10DoQEtLi+bbjBsFW8phSzlsKYs95bClnNNtmeawYn2eFevz4jfNi0QVDE0HF+7I7fZj3Ldw1SKiILbvxcLvYYldZ3H0DlGzqxZ2y/I3zVMbj0s5emjJCQQRERHRCrDMXQdR5HLg/NL457zBYzfNO7py0esOILjIxRaeQASHhn04NBy/aZ7ZBBSk2ePvEDW3epGVlFirFqRfnECoJDc3V+shGAZbymFLOWwpiz3lsKWclWyZYregNjcZtbnxm+ZFFQUj06EFG+b1uv0Y8YYWvE5UAfqnguifCuKVnvjnkm3mBRvmlaQ7UZzugMOq7qoFj0s5emjJCYRKeJ6fHLaUw5Zy2FIWe8phSzl6aGk2mZCfZkd+mh3nlcQ/NxOaX7WI3zCv1x2AP7xw0zxfKIrmER+aR+JXLUwA8lLtcbeeLZ27oDsn2SayaqGHlkahh5baj8CgBgYGkJmZqfUwDIEt5bClHLaUxZ5y2FKO3lsm2SyoyUlGTU78qoWiKBjzhWK3nu05ZuVieDqI40+IUgAMTQcxNB3E632euOecVvPcxCJ+X4uSdAeSbEu/kY3eWyYSPbTkBIKIiIjIQEwmE3JS7MhJseOcovhN8wLhKPqnFt56tmfSD19o4aqFPxxF69gMWscW7j2Qk2I7evvZY/a1yEu1w8xrLQyNEwiVVFVVaT0Ew2BLOWwphy1lsacctpRjxJYOqxmVWUmozIrfNE9RFEzMhGMTiqOb5gUw6AlgsbvPjnpDGPWG8GZ//KZ5dosJxa7ZC7dL0mdPh8p3FcIbjCDFrs/b7ycSPRyXnECoZGhoCOXl5VoPwxDYUg5bymFLWewphy3lrKaWJpMJWck2ZCXbsLEwftUiFIliYCo4e4eo2MrF7CqGJxBZ8FrBiIKOCT86JvwLnstKssY2zDv2Qu6CNDssBtk0T216OC6XNYHYvXs3du/ejc7OTgDAWWedhTvvvBPbtm0DALS1teGrX/0qXnjhBQQCAWzduhU/+tGPkJ+ff9qvmai8Xq/WQzAMtpTDlnLYUhZ7ymFLOWw5y2YxoyzTibLMhTsgu/3h+Oss5lYv+qcCWOTusxifCWN8ZhpvDcavWtjmbnEbv2He7AqGy8nfdx9LD8flsv6JlJSU4L777sOaNWugKAoeeeQRXHXVVXjzzTdRUVGBLVu2oL6+Hvv37wcA3HHHHdi+fTtefvllmM2L3x7sZK951llnnfk71Ijdbtd6CIbBlnLYUg5bymJPOWwphy1PLd1pRXpBKs4qSI17PBxVMOgJxG45e7BnBG7Fjt7JACb9CzfNC0UVdE360TXpB7rcC77H/IXc83eHKk13otDlgHUVrlro4bg0KYqy9D3VF5GVlYXvfve7KC0txbZt2zAxMQGXywUAcLvdyMzMxL59+7B58+Zlv+Y//MM/LPp8OBxGY2Mjqqqq4iYmDocDDofjTN6OmGg0esJJEy0PW8phSzlsKYs95bClHLaUc2xLTyC8YE+LHncA/e4AQotdbHECFhNQ6HIs2DCvJN2BDKdxN81T67iMRCJoampCQ0PDKW8Ve9prQpFIBL/61a/g9XqxadMmtLW1wWQyxf0A73Q6YTab8cILLyxpAnH8a57Khg0b4PMdvZfxddddhxtvvBGFhYVoa2sDAOTn50NRFAwPDwMA1qxZg97eXszMzMDpdKK0tBRHjhwBAOTl5cFsNmNwcBAAUF1djcHBQXi9XjgcDlRUVKC5uRkAkJOTA7vdjv7+fgBAZWUlRkZGMD09DZvNhmAwGDtws7KykJSUhL6+PgBARUUFxsfHMTU1BYvFgrVr1+LQoUNQFAUZGRlIS0tDT8/s7i9lZWWYmprC5OQkTCYT1q9fj+bmZkQiEbhcLmRmZqKrqwvA7GqOz+fD+Pg4AKCurg4tLS0Ih8NIS0tDTk4OOjo6AABFRUUIBAIYGxsDAKxbtw7t7e0IBoNISUlBfn4+2tvbAQCFhYUIh8MYGRkBANTW1qK7uxt+vx9JSUkoLi5Ga2trrDcwe34eANTU1KCvry/Wu6ysDC0tLQBmN0KxWq0YGBgAMHtR0NDQELxeL+x2O6qqqnD48GF4PB5UVFTA4XDE9R4dHYXH44HVakVtbS0OHjwY652cnIze3l4AQHl5OSYmJk7Y2+Vyobu7GwBQWloKj8dzwt5ZWVmx0+2Ki4sxMzMT671+/Xq0trYiFAohNTUVubm5cb2DwSBGR0cBAGvXrkVnZycCgQBSUlJQUFAQO2YLCgoQjUbjjtmenp5Y75KSkrhj1mQyxXpXV1djYGAAPp8PDocD5eXlcb37+/ths9livYeHhzE9PR3XGwCys7PhdDoXPWaP752ZmYnU1NS4Y9btdsPtdsNsNmPdunU4fPgwotEo0tPTkZ6eHtd7enoaExMTC47ZxXr7/f5Fj9nU1FTk5eWd9Jjt6upCIBBAcnKyyGeEx+PB2WeffdqfETU1NTh06FDsmF3tnxHDw8PIzc09rc+I+WOWnxGzvb1eb+yHi+V+Rhzfe7V/Rng8HtTU1Gjyc4TRPiM6OztjPyPW1tbCMT2E4pAfNTlJKK4vQWtrK6KKDea0HAx4QmgeGMfwjIJpUxK6xn1wBxdOLCIK5iYiAQBTcc8lWYHyzGSkwY+8JBOq81woz0yG4hmB1WxK6M8Ij8eD8847T/zniOWsKSx7BeLAgQPYtGkT/H4/UlNT8eijj+KKK67AyMgIampqcN1112HXrl1QFAW33norHnjgAXz2s5/Fgw8+uOzXPJFEWIE4ePAg6urqtB6GIbClHLaUw5ay2FMOW8phSzln2tIbnN80b25H7rnrLvrcfgQWu9jiBMwmID/VHruQu/SYlYuspMRYtVDruFR1BWLt2rX4y1/+Arfbjcceewyf+tSn0NjYiLq6OvzqV7/C9ddfj3/5l3+B2WzGNddcg3e/+92nXGY52WueTFpaGiwWfd4OLDs7W+shGAZbymFLOWwpiz3lsKUctpRzpi1T7BbU5iajNjd+07yoomDUG0LPcRvm9br9GPGGFrxOVAEGPEEMeIJ4tTf+uWSbOXbh9tELuR0oTnfCadXPqWx6OC6XPYGw2+2oqakBAJx77rl49dVXcf/99+PBBx/Eli1b0NbWhtHRUVitVmRkZKCgoOCU96s92WsmKr2shBgBW8phSzlsKYs95bClHLaUo1ZLs8mEvFQ78lLtOLck/rmZUGR207xjrrPonVvBmFlk0zxfKIqWUR9aRn0LnstLtc1ewB3bjXv2uovcFNuKr1ro4bg84/tiRaNRBAKBuMdycnIAAPv378fw8DCuvPLKM37NRNPf34+MjAyth2EIbCmHLeWwpSz2lMOWcthSjhYtk2wWVGcnozo7ftVCURSM+ULHbZg3+9chTxCLnRA1PB3C8HQIr/d54h53WM3xd4g6ZkfuJJs6Z8no4bhc1gRix44d2LZtG8rKyuDxePDoo4/iueeew969ewEADz/8MNavX4/c3Fy89NJL+NKXvoSbbroJa9eujb3GpZdeiquvvho33HDDkl6TiIiIiEiKyWRCToodOSl2nFMUv2leMBxF31TgmA3z5lcuAvAGF26aFwhH0TY2g7axmQXP5STbFmyYV5LhQF5K4m+at6wJxPDwMK699loMDAwgPT0dGzduxN69e3HZZZcBAJqbm7Fjxw6Mj4+joqICt99+O2666aa415g/xWmpr5moKisrtR6CYbClHLaUw5ay2FMOW8phSzmJ0tJuNaMyKwmVWUlxjyuKgsmZcNxpUPPXXQx6Aljs7rOjvhBGfSH8pf+4TfMsJhS7jq5UHLtykWI/9aqFHlqe8T4QWpi/C1N9fb1uL6Lu6elBaWmp1sMwBLaUw5Zy2FIWe8phSzlsKcfILUORKAamgkfvEHXMhdxTgYWrFidit5jwtYZyNFRlnvTr1Gq5IvtA0Ml5PJ5TfxEtCVvKYUs5bCmLPeWwpRy2lGPkljaLGWWZTpRlOhc8N+UPo+e4DfN6J/0Y8AQRPm7ZIhhR8ErP1CknEHpoyQmESk41c6OlY0s5bCmHLWWxpxy2lMOWclZrS5fTirOcqTgrPzXu8UhUwau9U7jn6Y7Y7tvpTis+tjHvlK+ph5Y8hYmIiIiIaAUdGvbijr1tsVOcCtLsuHdrNYrTF65irJTlnMKkn10xDGZ+O3Q6c2wphy3lsKUs9pTDlnLYUg5bHvXnbjf+6fdHYpOH6uwk/HB77ZInD3poqf0aCBERERHRKrCvZQw/+GN37K5NZxel4q7NVUu6+5KecAKhkqysLK2HYBhsKYct5bClLPaUw5Zy2FLOam+pKAp++dYQfvrqQOyxhsoMfO2ictgtyzshSA8tOYFQSXJy8qm/iJaELeWwpRy2lMWecthSDlvKWc0to4qCf3u5D79+ZyT22EfOysXn31sMs2n5G8rpoSWvgVBJb2+v1kMwDLaUw5Zy2FIWe8phSzlsKWe1tgxGorj32c64ycPfv6cQ15/m5AHQR0uuQBARERERCfMGI7j76Xa8ObcTtdkE3PzBMmypzdZ4ZGeOEwiVlJeXaz0Ew2BLOWwphy1lsacctpTDlnJWW8txXwhf39uG1rEZAIDDYsLXL63EBWXpZ/zaemjJU5hUMjExofUQDIMt5bClHLaUxZ5y2FIOW8pZTS373H58+XctsclDmsOC73xojcjkAdBHS65AqGRqakrrIRgGW8phSzlsKYs95bClHLaUs1patoz4cPveNrj9YQBAXqoNu7bWoCxDboM4PbTkBEIl3CFbDlvKYUs5bCmLPeWwpRy2lLMaWr7WO4W7n+6APxwFAFRkOrFrazVyUuyi30cPLU2KoihaD2K5wuEwGhsbUV9fr4uIRERERLR6PdM6ju81diEy91P1uwpS8c3LKpHqSJzf1UciETQ1NaGhoQFW68nHzWsgVHLo0CGth2AYbCmHLeWwpSz2lMOWcthSjpFbPnZgGN9+7ujk4QMV6bh3a7Vqkwc9tEycaVGCScCFHd1iSzlsKYctZbGnHLaUw5ZyjNgyqih46JV+PHZgOPbYh9fl4AvvK4HFfHp7PCyFHlpyAqGSjIwMrYdgGGwphy3lsKUs9pTDlnLYUo7RWoajCr7/fBeeaT16R6Rr312AT55TANNpbhC3VHpoyQmESlwul9ZDMAy2lMOWcthSFnvKYUs5bCnHSC1nQhHc80wHXuv1AJjdIO7G95fiQ+tyVuT766Elr4FQSXd3t9ZDMAy2lMOWcthSFnvKYUs5bCnHKC0nZ0L4pz+0xiYPdosJd1xauWKTB0AfLbkCQURERER0CgOeAG57sg19UwEAQKrdgru3VGFDQarGI1t5nECopLS0VOshGAZbymFLOWwpiz3lsKUctpST6C3bxny4fU8bxmdmN4jLSbZh59ZqVGYlrfhY9NCSpzCpxOPxaD0Ew2BLOWwphy1lsacctpTDlnISueVf+j34yhNHYpOHsgwnfnhlrSaTB0AfLTmBUMnk5KTWQzAMtpTDlnLYUhZ7ymFLOWwpJ1FbPt8+gdv3tMEXmt1dui4vBT/48BrkpcruLr0cemjJU5hUovYtvFYTtpTDlnLYUhZ7ymFLOWwpJxFb/uadEfzrS72Y33XhglIXbr+0Ek6rtr9/10NLk6KH3SiWKRwOo7GxEfX19bBYLFoPh4iIiIgMQlEU/MdrA/jvpqHYY5fXZuHLHyhTdYM4rUUiETQ1NaGhoQFW68nXGHgKk0qam5u1HoJhsKUctpTDlrLYUw5bymFLOYnSMhJV8IM/dsdNHv7m7Hzc/EH9TB700JKnMKkkEoloPQTDYEs5bCmHLWWxpxy2lMOWchKhpT8cxc5nOvDnnikAgAnAF95XgivrcrUd2HH00JITCJXoYZdAo2BLOWwphy1lsacctpTDlnL03nLKH8ad+9pxcNgLALCZTbjlonJcWJWp8cgW0kNLTiBUkpWVpfUQDIMt5bClHLaUxZ5y2FIOW8rRc8vh6SB2PNmKHvfsBnHJNjO+cVkVzi5K03hki9NDS14DoZLOzk6th2AYbCmHLeWwpSz2lMOWcthSjl5bdozP4Eu/bYlNHrKSrPj+h9fodvIA6KMlVyCIiIiIaNU5MDiNu/a1Yzo4e01BscuBXduqUZjm0Hhk+scJhEqKi4u1HoJhsKUctpTDlrLYUw5bymFLOXpr+WLnJHY924lQZHY3g7W5ybhnSxUykmwaj+zU9NCSpzCpZGZmRushGAZbymFLOWwpiz3lsKUctpSjp5ZPHBrFPc90xCYP55Wk4TtX1CTE5AHQR0tOIFQyPj6u9RAMgy3lsKUctpTFnnLYUg5bytFDS0VR8LM3BvAvL/YgOreN8uaaTNy9pRpJtsTZmFgPLXkKExEREREZWiSq4IE/9eD3h8dij33sXXn4h/OLYDbpY4O4RGJSFEXRehDLFQ6H0djYiPr6elgs+pwxKooCEw9IEWwphy3lsKUs9pTDlnLYUo6WLQPhKO59thN/6nLHHvvcBcX46LvyNBnPmVKrZSQSQVNTExoaGmC1nnyNgacwqaS1tVXrIRgGW8phSzlsKYs95bClHLaUo1XL6UAYO/a0xiYPVrMJt15UnrCTB0AfxyVPYVJJKBTSegiGwZZy2FIOW8piTzlsKYct5WjRctQbxG172tA54QcAJNnMuPPSSpxbov1OzmdCD8clJxAqSU1N1XoIhsGWcthSDlvKYk85bCmHLeWsdMvuCT927GnFiHf2h+10pxU7t1ajNid5RcehBj0cl5xAqCQ3N1frIRgGW8phSzlsKYs95bClHLaUs5ItDw55cce+NngCsxvEFabZsWtrDYrTjbFBnB6OS14DoZKOjg6th2AYbCmHLeWwpSz2lMOWcthSzkq1/HO3G7f84Uhs8lCTnYQfbq81zOQB0MdxyRUIIiIiIkp4e1vG8M9/7I7t8XBOUSru3FyFFLs+79iZyDiBUElRUZHWQzAMtpTDlnLYUhZ7ymFLOWwpR82WiqLgF01DePi1gdhjF1Vl4KsN5bBbjHeyjR6OS04gVBIMBrUegmGwpRy2lMOWsthTDlvKYUs5arWMKgp2v9SH3xwciT129Vm5+Nx7iw27QZwejkvjTct0YnR0VOshGAZbymFLOWwpiz3lsKUctpSjRstgJIp793fGTR7+4T1F+LyBJw+APo5LrkAQERERUULxBiP4xlPtaBqYBgCYTcDNHyzDltpsjUe2OpgURVG0HsRyhcNhNDY2or6+HhaLPi+MiUQiuh1bomFLOWwphy1lsacctpTDlnIkW477Qrh9bxvaxmYAAA6rGXdcWoHzS9NFXl/v1DouI5EImpqa0NDQAKv15GsMPIVJJZ2dnVoPwTDYUg5bymFLWewphy3lsKUcqZZ9bj++/LuW2OTB5bDgO1fUrJrJA6CP45KnMKkkEAhoPQTDYEs5bCmHLWWxpxy2lMOWciRaNo948fW97XD7wwCA/FQ7dm2tRmmG84xfO5Ho4bjkBEIlKSkpWg/BMNhSDlvKYUtZ7CmHLeWwpZwzbfla7xTufroD/nAUAFCZ6cSurTXITrFJDC+h6OG45ARCJQUFBVoPwTDYUg5bymFLWewphy3lsKWcM2n59JFxfP/5LkTmrtp9V0EqvnlZJVIdq/PHWD0cl7wGQiVtbW1aD8Ew2FIOW8phS1nsKYct5bClnNNt+dhbQ/hO49HJwwcq0nHv1upVO3kA9HFcrt76RERERKRLUUXBv/+5D//79tE9Hj68Pgdf2FQCi9m4ezwkCk4gVKKH5SWjYEs5bCmHLWWxpxy2lMOWcpbTMhSJ4vvPd2N/20TssU+dW4i/OTsfJgNvELdUejguOYFQSTQa1XoIhsGWcthSDlvKYk85bCmHLeUsteVMKIK7n+7A630eALMbxH3p/aXYti5HzeElFD0cl7wGQiXDw8NaD8Ew2FIOW8phS1nsKYct5bClnKW0nJgJ4Wu/b41NHuwWE+7cXMnJw3H0cFxyBYKIiIiINDUwFcCOPW3on5rd4yDNYcHdl1XhrIJUjUdGizEpiqJoPYjlCofDaGxsRH19vW63mA+FQrDZVt+9idXAlnLYUg5bymJPOWwphy3lnKxl66gPt+9tw8TM7AZxOSk27NpajYrMpJUcYsJQ67iMRCJoampCQ0MDrNaTrzHwFCaV9PT0aD0Ew2BLOWwphy1lsacctpTDlnJO1PLNfg+++vsjsclDWYYTP9xey8nDSejhuOQpTCrx+/1aD8Ew2FIOW8phS1nsKYct5bClnMVaPtc2ge80diEcnT0Zpi4vBXdvqYLLyR9PT0YPxyX/CakkKYkzZylsKYct5bClLPaUw5Zy2FLO8S0ff3sY//ZyH+bPo99Ulo7bLqmAw8qTY05FD8clJxAqKSkp0XoIhsGWcthSDlvKYk85bCmHLeXMt1QUBT99bQC/bBqKPbdtbTa++P5SbhC3RHo4LjnNU8mRI0e0HoJhsKUctpTDlrLYUw5bymFLOUeOHEE4quD7z3fHTR7+5ux8fPkDnDwshx6OS65AEBEREZGqAhEF33iqHa/0TAEATAC+8L4SXFmXq+3A6LRwAqGSvLw8rYdgGGwphy3lsKUs9pTDlnLYUsaUP4x/bwFaJ2YnDzazCbdcXI4LKzM1Hlli0sNxyQmESkwmLsVJYUs5bCmHLWWxpxy2lMOWZ27IE8SOPa3odQcBAMk2M755WRXqi9I0Hlni0sNxyWsgVDI0NHTqL6IlYUs5bCmHLWWxpxy2lMOWZ6ZjfAZf/l0Let2zu0tnJVvx/Q+v4eThDOnhuOQKBBERERGJemtgGnc91Q5vMAIAyHWa8P3ttShIc2g8MpLACYRKqqurtR6CYbClHLaUw5ay2FMOW8phy9PzQsck7n2uE6HI7C4Pa3OTccdFJcjj5EGEHo5LnsKkkoGBAa2HYBhsKYct5bClLPaUw5Zy2HL5njg0im/t74hNHt5T4sJ3rqiBb2JE45EZhx6OS65AqMTn82k9BMNgSzlsKYctZbGnHLaUw5ZLpygKfvbGIH7+5mDsscvWZOGmD5bBajaxpSA9tOQEQiUOB5fppLClHLaUw5ay2FMOW8phy6WJRBX86E89+MPhsdhjn9iYh79/T1HsjkFsKUcPLZd1CtPu3buxceNGuFwuuFwubNq0CU8++WTs+ba2Nlx99dXIzc2Fy+XCxz/+8VNeKX7vvffiPe95D9LS0pCXl4ePfOQjaG5uPr13oyPl5eVaD8Ew2FIOW8phS1nsKYct5bDlqQXCUdzzTEfc5OHz7y3GP5xfHHe7UbaUo4eWy5pAlJSU4L777sPrr7+O1157DZdccgmuuuoqvPPOO/B6vdiyZQtMJhP279+PF198EcFgENu3b0c0Gj3hazY2NuILX/gCXn75ZTz11FMIhULYsmULvF7vGb85LbW0tGg9BMNgSzlsKYctZbGnHLaUw5Yn5wmEsePJVvypyw0AsJpN2HFxBf5qw8KNzthSjh5aLusUpu3bt8f9eefOndi9ezdefvll9PX1obOzE2+++SZcLhcA4JFHHkFmZib279+PzZs3L/qae/bsifvzf/zHfyAvLw+vv/46LrzwwuUMj4iIiIhWwIg3iNv2tKFrwg8ASLKZcdfmSry72KXxyGglnPZdmCKRCH7xi1/A6/Vi06ZNCAQCMJlMcedlOZ1OmM1mvPDCC0t+Xbd7dhablZV1yq/1eDyYmpqK/S8QCCz/jagkNzdX6yEYBlvKYUs5bCmLPeWwpRy2XFz3hB9f/m1LbPKQ4bTiex9ac9LJA1vK0UPLZV9EfeDAAWzatAl+vx+pqal4/PHHUVdXh9zcXKSkpOCWW27Brl27oCgKbr31VkQikSXfbioajeLLX/4y3v/+92PDhg2n/PoNGzbEXYl+3XXX4cYbb0RhYSHa2toAAPn5+VAUBcPDwwCANWvWoLe3FzMzM3A6nSgtLcWRI0cAAHl5eTCbzRgcnL2DQHV1NQYHB+H1euFwOFBRURG7PiMnJwd2ux39/f0AgMrKSoyMjGB6eho2mw3Z2dk4ePAggNnJUFJSEvr6+gAAFRUVGB8fx9TUFCwWC9auXYtDhw5BURRkZGQgLS0NPT09AICysjJMTU1hcnISJpMJ69evR3NzMyKRCFwuFzIzM9HV1QVg9hQzn8+H8fFxAEBdXR1aWloQDoeRlpaGnJwcdHR0AACKiooQCAQwNjZ7zuK6devQ3t6OYDCIlJQU5Ofno729HQBQWFiIcDiMkZHZW7DV1taiu7sbfr8fSUlJKC4uRmtra6w3cHSXxJqaGvT19cV6l5WVxZbecnNzYbVaY8dHVVUVhoaG4PV6YbfbUVVVhcOHDyMUCiEajcLhcMT1Hh0dhcfjgdVqRW1tbVzv5ORk9Pb2Apg9V3BiYuKEvV0uF7q7uwEApaWl8Hg8J+ydlZWFzs5OAEBxcTFmZmZivdevX4/W1laEQiGkpqYiNzc3rncwGMTo6CgAYO3atejs7EQgEEBKSgoKCgpix2xBQQGi0WjcMdvT0xPrXVJSEnfMmkymWO/q6moMDAzA5/PB4XCgvLw8rrff7491qqqqwvDwMKanp+N6A0B2djacTueix+zxvTMzM5Gamhp3zLrdbrjdbpjNZqxbtw6HDx9GNBpFeno60tPT43pPT09jYmJiwTG7WG+/37/oMZuamoq8vLyTHrNdXV0IBAJITk4W+YwIhUJwuVyn/RlRU1ODQ4cOxY7Z1f4ZMTU1BY/Hc1qfEfPHLD8jZnunpqbG3utyPyOO773aPyNCoRDMZrMmP0fo9TNif1Mb/v1wCL4wZt+HE/h8nRnVWU60trae8DPC6/Vq9nPE/DFrlM+IUCgUex3JnyMUZfbWu0thUpbz1QCCwSC6u7vhdrvx2GOP4aGHHkJjYyPq6uqwb98+XH/99ejo6IDZbMY111yDgwcP4vzzz8fu3btP+drXX389nnzySbzwwgsoKSk54deFw2E0NjaiqqoKZvPRRRSHw6GLK9MB4ODBg6irq9N6GIbAlnLYUg5bymJPOWwphy3jvdTlxq79HQjM7fFQk52EnZdXIzPZdsq/ly3lqNUyEomgqakJDQ0NsFpPvsaw7BUIu92OmpoaAMC5556LV199Fffffz8efPBBbNmyBW1tbRgdHYXVakVGRgYKCgpQVVV1yte94YYb8MQTT+D5558/6eThWGlpabBYLMt9C0RERES0DHuax/DDF7oRnfu18zlFabhrcyWS7fw5bDU6430gotHogmsPcnJyAAD79+/H8PAwrrzyyhP+/Yqi4MYbb8Tjjz+O5557DpWVlWc6JF1YyqSJloYt5bClHLaUxZ5y2FIOW87+nPbffxnCf7x+9HT0i6sz8dULy2CzLP1SWraUo4eWy7qIeseOHXj++efR2dmJAwcOYMeOHXjuuefwyU9+EgDw8MMP4+WXX0ZbWxt+/vOf42Mf+xhuuukmrF27NvYal156KR544IHYn7/whS/g5z//OR599FGkpaVhcHAQg4ODmJmZEXqL2pg/74zOHFvKYUs5bCmLPeWwpZzV3jISVfDjl3rjJg9Xb8jFLReVL2vyALClJD20XNYKxPDwMK699loMDAwgPT0dGzduxN69e3HZZZcBAJqbm7Fjxw6Mj4+joqICt99+O2666aa415g/xWne/LURF110UdzXPfzww/i7v/u703hL+jA9Pa31EAyDLeWwpRy2lMWecthSzmpuGQxH8e3GLvyxYzL22KfPL8LH3pUXt0HcUq3mltL00HJZE4if/OQnJ33+vvvuw3333XfSr5m/8nzeMq/hThh2u13rIRgGW8phSzlsKYs95bClnNXa0huM4BtPtaNpYPYHVbMJ+MqFZbhsTfZpv+ZqbakGPbRc9l2Y9GD+Lkz19fW6vYg6Go3G3SGKTh9bymFLOWwpiz3lsKWc1dhyzBfC7Xva0D4+eyq5w2rGHZdW4PzS9DN63dXYUi1qtVzOXZj4T1Il8/cdpjPHlnLYUg5bymJPOWwpZ7W17HXPbhA3P3lId1rx3StqznjyAKy+lmrSQ8szvgsTERERESW2w8Ne3LGvHW7/7A5x+al23LutGiXpTo1HRnrECYRKsrNP/zxBiseWcthSDlvKYk85bClntbR8tWcKdz/TgUA4CgCoynJi5+U1yE459QZxS7VaWq4EPbTkBEIlTidn7FLYUg5bymFLWewphy3lrIaWTx8Zx/ef78Lc5tKoL0zFNy6rQorwBnGroeVK0UNLXgOhkr6+Pq2HYBhsKYct5bClLPaUw5ZyjNxSURT8z1tD+E7j0cnDByszsPPyavHJA2DslitNDy25AkFERES0ikQVBf/3z334f2+PxB67si4H17+3BBbz8vd4oNWHEwiVVFRUaD0Ew2BLOWwphy1lsacctpRjxJahSBTfe74bz7ZNxB77u3MLcc3Z+ae1QdxSGbGlVvTQkqcwqWR8fFzrIRgGW8phSzlsKYs95bClHKO19AUjuGNfe2zyYDYBN32wDH9zToGqkwfAeC21pIeWXIFQydTUlNZDMAy2lMOWcthSFnvKYUs5Rmo54Qvh6/vacGR0do8Hu8WE2y+pxKbyM9/jYSmM1FJremjJCYRKTrWDHy0dW8phSzlsKYs95bClHKO07J8K4LY9reifCgIA0hwW3H1ZFc4qSF2xMRilpR7ooaVJURRF60EsVzgcRmNjI+rr62GxyN8pgIiIiMgIjoz6cPueNkzObRCXk2LDvVurUZ6ZpPHISG8ikQiamprQ0NBwykkKr4FQycGDB7UegmGwpRy2lMOWsthTDlvKSfSWb/RN4au/PxKbPJRnOnH/lbWaTB4SvaWe6KGl9msgRERERCTq2bYJfLexC+Ho7IkmZ+Wn4O4tVUhz8Ec/OnM8ilSSmZmp9RAMgy3lsKUctpTFnnLYUk6itnz87WHsfvnoZmObytJx2yUVcFi1O/EkUVvqkR5acgKhktTUlbswyejYUg5bymFLWewphy3lJFpLRVHw01f78cu3hmOPbVubjS++v1TzDeISraWe6aElr4FQSU9Pj9ZDMAy2lMOWcthSFnvKYUs5idQyHFXw3ee74yYP/985BfjyB7SfPACJ1VLv9NCSKxBERERECWwmFMG3nunEq72z+wOYANzwvhJsr8vVdmBkWJxAqKSsrEzrIRgGW8phSzlsKYs95bClnERo6faHccfeNhwe8QEAbBYTdlxUgQ9UZmg7sOMkQstEoYeWPIVJJW63W+shGAZbymFLOWwpiz3lsKUcvbcc9ARw0+9aYpOHFLsF926t1t3kAdB/y0Sih5acQKhED/9wjYIt5bClHLaUxZ5y2FKOnlu2j83gy79rQa87AADISrbiBx9eg42FaRqPbHF6bplo9NCSpzCpxGzm3EwKW8phSzlsKYs95bClHL22fGvAg7ue6oA3GAEAlKQ7cO/WGuSn2TUe2YnptWUi0kNLk6IoitaDWK5wOIzGxkbU19fDYrFoPRwiIiKiFfHHjknc91wnQpHZH9/W5Sbjnsurke7k74TpzEQiETQ1NaGhoQFW68mPJ+2nMAZ1+PBhrYdgGGwphy3lsKUs9pTDlnL01vJ3B0fwrWc6YpOH80td+PYVNQkxedBby0Smh5b6P+ISVDQa1XoIhsGWcthSDlvKYk85bClHLy0VRcF/vjGI/3pzMPbYZWuycNMHy2DVwR4PS6GXlkagh5acQKgkPT1d6yEYBlvKYUs5bCmLPeWwpRw9tIxEFfzLiz14snks9tgn6vPx9+cVwmRKjMkDoI+WRqGHlpxAqEQP/3CNgi3lsKUctpTFnnLYUo7WLQPhKHbt78RL3bN33TEB+Px7i3H1hjxNx3U6tG5pJHpoyWsgVNLd3a31EAyDLeWwpRy2lMWecthSjpYtp/xh3PKH1tjkwWo2YcfFFQk5eQB4XErSQ0uuQBARERHpyPB0ELfvaUPXpB8AkGwz467NVTinWJ97PNDqwwmESkpLS7UegmGwpRy2lMOWsthTDlvK0aJl18QMduxpw6g3BADITLJi5+XVqMlJXvGxSOJxKUcPLXkKk0qmp6e1HoJhsKUctpTDlrLYUw5bylnplu8MTuPmJ47EJg9FLjt+uL024ScPAI9LSXpoyQmESiYmJrQegmGwpRy2lMOWsthTDlvKWcmWL3W5ccuTrfAEZneXXpOThH/eXotCl2PFxqAmHpdy9NCSpzARERERaejJw6O4/8UeRGf3h8O7i9Nw56WVSLZbtB0Y0QmYFEVRtB7EcoXDYTQ2NqK+vh4WC//lIiIiosSjKAoe/csQHnl9IPbYxdWZ+OqFZbBZeJIIraxIJIKmpiY0NDTAaj35GgOPTpW0tLRoPQTDYEs5bCmHLWWxpxy2lKNmy0hUwQN/6o2bPHx0Qy5uuajckJMHHpdy9NCSpzCpJBwOaz0Ew2BLOWwphy1lsacctpSjVstgOIr7nuvCC52Tscc+c34RPrYxX5Xvpwc8LuXooSUnECpxuVxaD8Ew2FIOW8phS1nsKYct5ajR0huM4K597XhrcPZOOhYT8JULy7F5TZb499ITHpdy9NCSEwiVZGUZ+4NgJbGlHLaUw5ay2FMOW8qRbjnmDeH2va1oH5/dIM5pNeOOSyvxnlLtfyBUG49LOXpoabyT7HSis7NT6yEYBlvKYUs5bCmLPeWwpRzJlj2Tfnz5dy2xyUO604rvXFGzKiYPAI9LSXpoyRUIIiIiIhUdGvbijr1tmJrb4yE/1Y57t1WjJN2p8ciITg8nECopLi7WegiGwZZy2FIOW8piTzlsKUei5Ss9btzzTCcC4SgAoCorCTu3ViM72XbGr51IeFzK0UNLnsKkEr/fr/UQDIMt5bClHLaUxZ5y2FLOmbbc1zKGO/e1xyYP9YWp+P6H16y6yQPA41KSHlpyAqGSsbExrYdgGGwphy3lsKUs9pTDlnJOt6WiKPifpiF87/nu2O7SF1ZmYOfWaqSs0t2leVzK0UNLnsJEREREJCSqKHjwz314/O2R2GNX1eXg8+8tgcVs0nBkRHJMiqIoWg9iucLhMBobG1FfXw+LRZ8z+Wg0CrOZCzwS2FIOW8phS1nsKYct5Sy3ZTASxfcau/Bc+2TssevOK8Rf1+fDZFrdkwcel3LUahmJRNDU1ISGhgZYrSdfY+A/SZW0t7drPQTDYEs5bCmHLWWxpxy2lLOclr5gBHfsbY9NHswm4OYPluGaswtW/eQB4HEpSQ8teQqTSoLBoNZDMAy2lMOWcthSFnvKYUs5S2054Qvh9r1taB2bAQA4LCbcfmkl3luWrubwEgqPSzl6aMkJhEpSU1O1HoJhsKUctpTDlrLYUw5byllKyz53ALftacWAZ/aHujSHBfdsqUZdforaw0soPC7l6KElJxAqycvL03oIhsGWcthSDlvKYk85bCnnVC1bRn34+p42TPrDAIDcFBvu3VqDskxuEHc8Hpdy9NCS10CoRA/npxkFW8phSzlsKYs95bClnJO1fL13Cl/7/ZHY5KE804kfXlnLycMJ8LiUo4eWXIEgIiIiWoZn28bx3cZuhOc2ediQn4JvbqlCmoM/VtHqwCNdJYWFhVoPwTDYUg5bymFLWewphy3lLNbyfw8M48E/98X+/L7ydOy4uAIOK0/qOBkel3L00JITCJWEw2Gth2AYbCmHLeWwpSz2lMOWco5tGVUU/OSVfvzqwHDssSvWZePG95Vyg7gl4HEpRw8tOV1WycjIyKm/iJaELeWwpRy2lMWecthSznzLcFTB9xq74iYP/985BfjS+zl5WCoel3L00JIrEEREREQnMBOK4J5nOvBarwfA7AZxN7yvFB9en6PxyIi0Y1IURdF6EMsVDofR2NiI+vp6WCwWrYezqHA4fMptwGlp2FIOW8phS1nsKYct5YxN+/GNZ7rQPOIDANgsJuy4uAIfqMjQdmAJiMelHLVaRiIRNDU1oaGh4ZSvz1OYVNLV1aX1EAyDLeWwpRy2lMWecthSxqAngC/9pjk2eUixW3Dv1hpOHk4Tj0s5emjJqaBKAoGA1kMwDLaUw5Zy2FIWe8phyzPXNubD7XvaMD4TBQBkJ9uwa2s1KrOSNB5Z4uJxKUcPLTmBUElycrLWQzAMtpTDlnLYUhZ7ymHLM9PU78FdT7XDF5qdPJSkO3Dv1hrkp9k1Hlli43EpRw8tOYFQiR7u0WsUbCmHLeWwpSz2lMOWp+/5jgl8+9kuhOY2iFubk4SdW2vgcvLHpTPF41KOHlryGgiVtLW1aT0Ew2BLOWwphy1lsacctjw9vz04gp3PdMYmDxeUuvD31RFOHoTwuJSjh5acQBAREdGqpSgKHn6tHw/8qRfzt6W8vDYLd11WBYeFezwQLYbTapXk5+drPQTDYEs5bCmHLWWxpxy2XLpIVMH9L/RgT8tY7LG/rs/HdecVwmQysaUgtpSjh5acQKgkAbfX0C22lMOWcthSFnvKYcul8Yej2LW/Ay93TwEATACu31SCj5yVG/satpTDlnL00JKnMKlkeHj41F9ES8KWcthSDlvKYk85bHlqU/4wbv1Da2zyYDObcNslFXGTB4AtJbGlHD205AoEERERrRrD00HctqcN3ZN+AECyzYy7LqvCOUVpGo+MKHGYFD2sgyxTOBxGY2Mj6uvrYbFYtB7OokKhEGw2m9bDMAS2lMOWcthSFnvKYcsT65yYwW1PtmHUFwIAZCZZsfPyatTkLH5ffbaUw5Zy1GoZiUTQ1NSEhoYGWK0nX2PgKUwq6e3t1XoIhsGWcthSDlvKYk85bLm4twencfPvjsQmD0UuB364vfaEkweALSWxpRw9tOQpTCqZmZnRegiGwZZy2FIOW8piTzlsudCfuiaxa38ngpHZky5qc5Jxz+VVyEw6+W9x2VIOW8rRQ0tOIFTidDq1HoJhsKUctpTDlrLYUw5bxvvD4VH8y4s9mNsfDucWp+HOzZVIsp36FGi2lMOWcvTQkhMIlZSWlmo9BMNgSzlsKYctZbGnHLacpSgK/uvNQfznG4Oxxy6pzsRXLiyDzbK0M7jZUg5bytFDS14DoZIjR45oPQTDYEs5bCmHLWWxpxy2nN0g7kd/6o2bPPyfd+Xhny4qX/LkAWBLSWwpRw8tlzWB2L17NzZu3AiXywWXy4VNmzbhySefjD3f1taGq6++Grm5uXC5XPj4xz+OoaGhk77m888/j+3bt6OoqAgmkwm//vWvT+uNEBEREQXDUezc34EnDo3GHvvs+UX47AXFMJtMGo6MyDiWNYEoKSnBfffdh9dffx2vvfYaLrnkElx11VV455134PV6sWXLFphMJuzfvx8vvvgigsEgtm/fjmg0esLX9Hq9qK+vx49//OMzfjN6kpeXp/UQDIMt5bClHLaUxZ5yVnPL6UAYO/a04YVONwDAYgL+qaEc/2dj/mm93mpuKY0t5eih5bKugdi+fXvcn3fu3Indu3fj5ZdfRl9fHzo7O/Hmm2/C5XIBAB555BFkZmZi//792Lx586KvuW3bNmzbtu00h69fZjPPDpPClnLYUg5bymJPOau15Zg3hNv2tKJjYnaDOKfVjDs3V+K8Etdpv+ZqbakGtpSjh5anPYJIJIJf/OIX8Hq92LRpEwKBAEwmExwOR+xrnE4nzGYzXnjhBZHBHs/j8WBqair2v0AgoMr3OR2Dg4On/iJaEraUw5Zy2FIWe8pZjS27J/340u+aY5OHdKcV3/1QzRlNHoDV2VItbClHDy2XfRemAwcOYNOmTfD7/UhNTcXjjz+Ouro65ObmIiUlBbfccgt27doFRVFw6623IhKJYGBgQI2xY8OGDfD5fLE/X3fddbjxxhtRWFiItrY2AEB+fj4URcHw8DAAYM2aNejt7cXMzAycTidKS0tjF6Pk5eXBbDbH/sFUV1djcHAQXq8XDocDFRUVaG5uBgDk5OTAbrejv78fAFBZWYmRkRFMT0/DZrNBURQcPHgQAJCVlYWkpCT09fUBACoqKjA+Po6pqSlYLBasXbsWhw4dgqIoyMjIQFpaGnp6egAAZWVlmJqawuTkJEwmE9avX4/m5mZEIhG4XC5kZmaiq6sLwOwpZj6fD+Pj4wCAuro6tLS0IBwOIy0tDTk5Oejo6AAAFBUVIRAIYGxsDACwbt06tLe3IxgMIiUlBfn5+WhvbwcAFBYWIhwOY2RkBABQW1uL7u5u+P1+JCUlobi4GK2trbHeAGLXvtTU1KCvry/Wu6ysDC0tLQCA3NxcWK3W2PFRVVWFoaEheL1e2O12VFVV4fDhw/B4PBgaGoLD4YjrPTo6Co/HA6vVitra2rjeycnJsY1WysvLMTExccLeLpcL3d3dAGbvbODxeE7YOysrC52dnQCA4uJizMzMxHqvX78era2tCIVCSE1NRW5ublzvYDCI0dHZc3LXrl2Lzs5OBAIBpKSkoKCgIHbMFhQUIBqNxh2zPT09sd4lJSVxx6zJZIr1rq6uxsDAAHw+HxwOB8rLy+N6h0KhWKeqqioMDw9jeno6rjcAZGdnw+l0LnrMHt87MzMTqampcces2+2G2+2G2WzGunXrcPjwYUSjUaSnpyM9PT2u9/T0NCYmJhYcs4v19vv9ix6zqampyMvLO+kx29XVhUAggOTkZJHPCI/Hg0AgcNqfETU1NTh06FDsmF3tnxEejwft7e2n9Rkxf8zyM2K2dzQajb3X5X5GHN87ET4jnjvQjn8/FII3jNmxOYDPrzdhTXYSWltbz+gzwuPxYGxsTJOfI4z2GREIBGLHxEr/HDF/zBrlM8Lj8SASiYj/HKEoc/c6XgKTspyvBhAMBtHd3Q23243HHnsMDz30EBobG1FXV4d9+/bh+uuvR0dHB8xmM6655hocPHgQ559/Pnbv3n3qwZhMePzxx/GRj3zkpF8XDofR2NiIqqqquGUch8MRtwKipUAgoJuxJDq2lMOWcthSFnvKWU0tX+lx456nOxCY2yCuOjsJOy+vRlbyyTeIW6rV1FJtbClHrZaRSARNTU1oaGiA1XryNYZln8Jkt9tRU1ODc889F/feey/q6+tx//33AwC2bNmCtrY2DA8PY3R0FD/72c/Q19eHqqqq03snp5CWlha7I5TL5dLVgamH5SWjYEs5bCmHLWWxp5zV0nJfyxju3NcemzycXZSK731ojdjkAVg9LVcCW8rRQ8sz3kguGo0uuPYgJycHALB//34MDw/jyiuvPNNvk3C8Xq/WQzAMtpTDlnLYUhZ7yjF6S0VR8Mu3hvDTV4+eHt1QmYGvXVQO+zL2eFgKo7dcSWwpRw8tlzWB2LFjB7Zt24aysjJ4PB48+uijeO6557B3714AwMMPP4z169cjNzcXL730Er70pS/hpptuwtq1a2Ovcemll+Lqq6/GDTfcAACYnp6OnfcGAB0dHfjLX/6CrKwslJWVSbxHTehpNSTRsaUctpTDlrLYU46RW0YVBf/2ch9+/c5I7LGr6nJx/SZ19ngwcsuVxpZy9NByWROI4eFhXHvttRgYGEB6ejo2btyIvXv34rLLLgMANDc3Y8eOHRgfH0dFRQVuv/123HTTTXGv0dbWFrtIDABee+01XHzxxbE/33zzzQCAT33qU/iP//iP031fmquoqNB6CIbBlnLYUg5bymJPOUZtGYxE8d3GLjS2T8Yeu+68Qvx1fT5MKm0QZ9SWWmBLOXpoueyLqPVg/iLq+vp6WCwWrYezqIMHD6Kurk7rYRgCW8phSzlsKYs95RixpTcYwd1Pt+PN/mkAgNkE3PzBMmypzVb1+xqxpVbYUo5aLZdzEfUZXwNBREREpJZxXwhf39uG1rEZAIDDYsLXL63EBWXpGo+MaPXiBEIl8xeS05ljSzlsKYctZbGnHCO17HP7sWNPGwY9QQBAmsOCe7ZUoy4/ZUW+v5Faao0t5eihJScQKrHb7VoPwTDYUg5bymFLWewpxygtW0Z8uH1vG9z+2R3i8lJt2HV5DcoynSs2BqO01AO2lKOHlrL3O6OY+Z0O6cyxpRy2lMOWsthTjhFavtY7ha/+/khs8lCR6cQPt9eu6OQBMEZLvWBLOXpoyRUIIiIi0o1nWsfxvcYuzO0Phw0FKfjmZVVIc/BHFiK94L+NKqmsrNR6CIbBlnLYUg5bymJPOYnc8rEDw/i/f+6L/fn95em49eIKOKzanDCRyC31hi3l6KElT2FSycjIyKm/iJaELeWwpRy2lMWechKxZVRR8H//3Bc3efjQumx8/dJKzSYPQGK21Cu2lKOHllyBUMn09LTWQzAMtpTDlnLYUhZ7ykm0luGogu8/34VnWidij1377gJ88pwC1TaIW6pEa6lnbClHDy05gVCJzWbTegiGwZZy2FIOW8piTzmJ1HImFME9z3TgtV4PgNkN4m54Xyk+vF7721QCidVS79hSjh5acidqlSiKovlvToyCLeWwpRy2lMWechKl5eRMCHfsa0fziA8AYLOYcNvFFXh/RYa2AztGorRMBGwpR62Wy9mJmtdAqOTQoUNaD8Ew2FIOW8phS1nsKScRWg54Arjpd0dik4dUuwX3bavR1eQBSIyWiYIt5eihJU9hIiIiohXTNubD7XvaMD4zu8dDTrINO7dWozIrSeOREdFScQKhkqysLK2HYBhsKYct5bClLPaUo+eWf+n34BtPtcMXigIAStMduHdbDfJStd9ZdzF6bplo2FKOHlpyAqGSpCT+JkUKW8phSzlsKYs95ei15fPtE/j2c10IRWcvvazLS8HdW6rgcur3RxG9tkxEbClHDy15DYRK+vr6Tv1FtCRsKYct5bClLPaUo8eWv3lnBDv3d8YmDxeUunDfFTW6njwA+myZqNhSjh5a6vvfXCIiIkpYiqLgP14bwH83DcUeu7w2C1/+QBksZt6RhyhRcQKhkoqKCq2HYBhsKYct5bClLPaUo5eWkaiCH77Qjb0t47HHrjk7H393bmHC3M5TLy2NgC3l6KElT2FSyfj4+Km/iJaELeWwpRy2lMWecvTQ0h+O4htPtccmDyYAX9hUguvOK0qYyQOgj5ZGwZZy9NCSKxAqmZqa0noIhsGWcthSDlvKYk85Wrec8odx5752HBz2AgBsZhP+6aJyNFRlajqu06F1SyNhSzl6aMkJhEr0ukN2ImJLOWwphy1lsaccLVsOTwex48lW9LgDAIBkmxnfuKwKZxelaTamM8HjUg5bytFDS5OiKIrWg1iucDiMxsZG1NfX6yIiERHRatcxPoPb97Rh1BcCAGQlWbFzazWqs5M1HhkRLUUkEkFTUxMaGhpgtZ58jYHXQKhED9uMGwVbymFLOWwpiz3laNHywOA0vvLEkdjkodjlwD9fWZvwkwcel3LYUo4eWvIUJpUk4MKObrGlHLaUw5ay2FPOSrd8sXMSu57tRCgy+33X5ibjni1VyEiyreg41MDjUg5bytFDS04gVJKRkaH1EAyDLeWwpRy2lMWeclay5ROHRvHAn3owtz8czitJwx2XViLJZozTi3lcymFLOXpoyQmEStLSEvOCMT1iSzlsKYctZbGnnJVoqSgKfv7mIH72xmDssc01mbj5wnJYDbRBHI9LOWwpRw8teQ2ESnp6erQegmGwpRy2lMOWsthTjtotI1EF//JiT9zk4WPvysNXG4w1eQB4XEpiSzl6aMkVCCIiIlqSQDiKe5/txJ+63LHHPntBMf7Pu/I0HBURrTROIFRSVlam9RAMgy3lsKUctpTFnnLUajkdCOPOp9rx9uDsBnFWswlfvbAMl9RkqfL99IDHpRy2lKOHljyFSSV62CXQKNhSDlvKYUtZ7ClHjZaj3iBufuJIbPLgtJpx95YqQ08eAB6XkthSjh5acgKhksnJSa2HYBhsKYct5bClLPaUI92ye8KPL/22BZ0TfgBAutOK731oDc4rcYl+Hz3icSmHLeXooSVPYVKJyWSsC8m0xJZy2FIOW8piTzmSLQ8OeXHHvjZ4AhEAQGGaHbu21qA43SH2PfSMx6UctpSjh5YmRQ+7USxTOBxGY2Mj6uvrYbEY417TREREevLnbje+9UwHAnMbxNVkJ+Fbl1cjKznxN4gjooUikQiamprQ0NAAq/Xkaww8hUklzc3NWg/BMNhSDlvKYUtZ7ClHouXeljHc9VR7bPJwTlEqvvuhNatu8sDjUg5bytFDS57CpJJIJKL1EAyDLeWwpRy2lMWecs6kpaIo+EXTEB5+bSD2WENVBr7WUA67ZfX9zpHHpRy2lKOHlpxAqMTlMv7FZSuFLeWwpRy2lMWeck63ZVRRsPulPvzm4EjssavPysXn3lsMsw7OudYCj0s5bClHDy05gVBJZmam1kMwDLaUw5Zy2FIWe8o5nZbBSBTffa4LjR2Tscf+4T1F+PjGPF1csKkVHpdy2FKOHlquvvXIFdLV1aX1EAyDLeWwpRy2lMWecpbb0huM4PY9bbHJg9kEfPXCMnyiPn9VTx4AHpeS2FKOHlpyBYKIiGiVGveFcPveNrSNzQAAHFYz7ri0AueXpms8MiLSM04gVFJSUqL1EAyDLeWwpRy2lMWecpbass/tx449bRj0BAEALocF91xejfV5KWoOL6HwuJTDlnL00JKnMKnE5/NpPQTDYEs5bCmHLWWxp5yltGwe8eLLvzsSmzzkpdrwz9trOXk4Do9LOWwpRw8tOYFQyfj4uNZDMAy2lMOWcthSFnvKOVXL13qn8LXft8LtDwMAKjOduH/7WpRmOFdieAmFx6UctpSjh5Y8hYmIiGiVePrIOL7/fBfm9ofDuwpS8c3LKpHq4I8DRLR0JkVRFK0HsVzhcBiNjY2or6+HxWLRejhERES699hbQ/i/r/TH/vyBinTcelEF7FaejEBEsxvUNTU1oaGhAVbryX+pwE8NlbS0tGg9BMNgSzlsKYctZbGnnONbRhUFD77cGzd5+PC6HNx+SSUnD6fA41IOW8rRQ0uuWaokHA5rPQTDYEs5bCmHLWWxp5xjW4YiUXz/+W7sb5uIPXbtuYX45Nnc42EpeFzKYUs5emjJCYRK0tLStB6CYbClHLaUw5ay2FPOfMuZUAR3P92B1/s8AGY3iPvi+0txxbocLYeXUHhcymFLOXpoyQmESnJy+AEthS3lsKUctpTFnnJycnIwMRPCHXvb0TI6e7tHu8WE2y6pwPvKM7QdXILhcSmHLeXooSVPflRJR0eH1kMwDLaUw5Zy2FIWe8p59VA7bvrdkdjkIdVuwX3bajh5OA08LuWwpRw9tOQKBBERkUG0jvpw/4EgPKHZP+ek2LBrazUqMpO0HRgRGQonECopKirSegiGwZZy2FIOW8pizzP3Zr8H33yqHb65yUNZhhO7tlYjL9Wu7cASGI9LOWwpRw8tOYFQSSAQ0HoIhsGWcthSDlvKYs8z81zbBL7T2IVwdHZrp7q8FNy9pQouJ/8zfyZ4XMphSzl6aMlrIFQyNjam9RAMgy3lsKUctpTFnqfv8beHce+znbHJw1mZZtx3RQ0nDwJ4XMphSzl6aMlPFyIiogSkKAp++toAftk0FHtsa202Lsv2wMkN4ohIRSZFURStB7Fc4XAYjY2NqK+vh8Vi0Xo4i4pGozCb+QEugS3lsKUctpTFnssTjir44R+7se/IeOyxvzk7H586txCKorClEB6XcthSjlotI5EImpqa0NDQAKv15GsM/Cepkvb2dq2HYBhsKYct5bClLPZcuplQBN94qj02eTABuOF9Jfi784pgMpnYUhBbymFLOXpoyVOYVBIMBrUegmGwpRy2lMOWsthzaab8YXx9bxsOj8zu8WAzm3DLxeW4sDIz9jVsKYct5bClHD205ARCJSkpKVoPwTDYUg5bymFLWex5akOeIHbsaUWve/YOLMk2M755WRXqi9Livo4t5bClHLaUo4eWnECoJD8/X+shGAZbymFLOWwpiz1PrmN8BrftacPY3CYPWUlW7Nxajers5AVfy5Zy2FIOW8rRQ0teA6ESPZyfZhRsKYct5bClLPY8sbcGpnHzE0dik4eSdAd+eGXtopMHgC0lsaUctpSjh5ZcgSAiItKpFzomce9znQhFZm+YuDY3GfdsqUJGkk3jkRHRasYJhEoKCwu1HoJhsKUctpTDlrLYc6EnDo3igT/1YG5/OJxXkoY7Lq1Eku3kty9nSzlsKYct5eihJScQKgmHw1oPwTDYUg5bymFLWex5lKIo+Nkbg/j5m4OxxzavycLNHyyD1Ww65d/PlnLYUg5bytFDS14DoZKRkRGth2AYbCmHLeWwpSz2nBWJKrj/xZ64ycPHN+bhaxcubfIAsKUktpTDlnL00JIrEERERDoQCEdx77Od+FOXO/bY599bjL/akKfhqIiIFjIpiqJoPYjlCofDaGxsRH19PSyWk58LqpVwOHzKbcBpadhSDlvKYUtZq72nJxDGXfva8faQFwBgNZvwtYYyXFydtezXWu0tJbGlHLaUo1bLSCSCpqYmNDQ0nPL1eQqTSrq7u7UegmGwpRy2lMOWslZzzxFvEDc/cSQ2eUiymXHPlqrTmjwAq7ulNLaUw5Zy9NCSU0GV+P1+rYdgGGwphy3lsKWs1dqze8KPHXtaMeKd3eMhw2nFt7ZWozZn8T0elmK1tlQDW8phSzl6aMkJhEqSkpK0HoJhsKUctpTDlrJWY893hqZx5752eAIRAEBhmh33bqtBkctxRq+7GluqhS3lsKUcPbTkBEIlxcXFWg/BMNhSDlvKYUtZq63nS11u7NrfgcDcBnE12UnYeXk1MpPPfIO41dZSTWwphy3l6KElr4FQSWtrq9ZDMAy2lMOWcthS1mrquad5DN98uj02eTinKA3f+9AakckDsLpaqo0t5bClHD205AoEERHRClAUBf/9lyH8x+sDsccuqsrA1xrKYbPw93lElDg4gVBJfn6+1kMwDLaUw5Zy2FKW0XtGogp2v9yL3x4cjT129YZcfO6CYphNS9sgbqmM3nIlsaUctpSjh5bL+pXH7t27sXHjRrhcLrhcLmzatAlPPvlk7Pm2tjZcffXVyM3Nhcvlwsc//nEMDQ2d8nV//OMfo6KiAk6nExdccAFeeeWV5b8TIiIiHQqGo9j1bGfc5OHT7ynC51WYPBARrYRlTSBKSkpw33334fXXX8drr72GSy65BFdddRXeeecdeL1ebNmyBSaTCfv378eLL76IYDCI7du3IxqNnvA1f/nLX+Lmm2/GXXfdhTfeeAP19fW4/PLLMTw8fMZvTktLmTjR0rClHLaUw5ayjNrTG4zg9r1t+GPHJADAbAK+1lCGj9fnw6TS5MGoLbXAlnLYUo4eWi7rFKbt27fH/Xnnzp3YvXs3Xn75ZfT19aGzsxNvvvkmXC4XAOCRRx5BZmYm9u/fj82bNy/6mj/4wQ/wmc98Btdddx0A4N/+7d/w+9//Hj/96U9x6623ns57IiIi0tyYL4Tb97ShfXwGAOCwmnHHpRU4vzRd45EREZ2Z075qKxKJ4Be/+AW8Xi82bdqEQCAAk8kEh+Po/audTifMZjNeeOGFRV8jGAzi9ddfj5tcmM1mbN68GS+99NIpx+DxeDA1NRX7XyAQON23I66mpkbrIRgGW8phSzlsKctoPXvdfnz5ty2xyYPLYcF3rqhZkcmD0VpqiS3lsKUcPbRc9kXUBw4cwKZNm+D3+5GamorHH38cdXV1yM3NRUpKCm655Rbs2rULiqLg1ltvRSQSwcDAwKKvNTo6ikgksuBikPz8fBw+fPiUY9mwYQN8Pl/sz9dddx1uvPFGFBYWoq2tLfZaiqLETolas2YNent7MTMzA6fTidLSUhw5cgQAkJeXB7PZjMHBQQBAdXU1BgcH4fV64XA4UFFRgebmZgBATk4O7HY7+vv7AQCVlZUYGRnB9PQ0bDYbLBZLbKfArKwsJCUloa+vDwBQUVGB8fFxTE1NwWKxYO3atTh06BAURUFGRgbS0tLQ09MDACgrK8PU1BQmJydhMpmwfv16NDc3IxKJwOVyITMzE11dXQBmTzHz+XwYHx8HANTV1aGlpQXhcBhpaWnIyclBR0cHAKCoqAiBQABjY2MAgHXr1qG9vR3BYBApKSnIz89He3s7AKCwsBDhcBgjIyMAgNraWnR3d8Pv9yMpKQnFxcWxW4rN/7OcX16rqalBX19frHdZWRlaWloAALm5ubBarbHjo6qqCkNDQ/B6vbDb7aiqqsLhw4fh8/lQWloKh8MR13t0dBQejwdWqxW1tbU4ePBgrHdycjJ6e3sBAOXl5ZiYmDhhb5fLFdsWvrS0FB6P54S9s7Ky0NnZCWD2PswzMzOx3uvXr0draytCoRBSU1ORm5sb1zsYDGJ0dPYc6LVr16KzsxOBQAApKSkoKCiIHbMFBQWIRqNxx2xPT0+sd0lJSdwxazKZYr2rq6sxMDAAn88Hh8OB8vLyuN6jo6NQFCXWe3h4GNPT03G9ASA7OxtOp3PRY/b43pmZmUhNTY07Zt1uN9xuN8xmM9atW4fDhw8jGo0iPT0d6enpcb2np6cxMTGx4JhdrLff71/0mE1NTUVeXt5Jj9muri4EAgEkJyeLfEb4fD68613vOu3PiJqaGhw6dCh2zK72z4ixsTFkZWWd1mfE/DGrl8+IxgPt+L+HQvCGMfvviAP4fJ0Z63KTceTIEdU/IyKRCILBYOyYXc5nxPG9V/tnhM/nQ2VlpSY/RxjtM6K/vz922t5K/xwxf8zq5TPiTH+O8Pl8OOecc8R/jpj/+WApTMpyvhqzqwbd3d1wu9147LHH8NBDD6GxsRF1dXXYt28frr/+enR0dMBsNuOaa67BwYMHcf7552P37t0LXqu/vx/FxcX405/+hE2bNsUe/6d/+ic0Njbiz3/+86JjCIfDaGxsRFVVFczmo4soDocjbgVESwcPHkRdXZ3WwzAEtpTDlnLYUpZRer7aM4W7n+lAIDx77V9VlhM7L69BdorMHg9LYZSWesCWcthSjlotI5EImpqa0NDQAKv15GsMy16BsNvtsaWTc889F6+++iruv/9+PPjgg9iyZQva2towOjoKq9WKjIwMFBQUoKqqatHXysnJgcViWXAxyNDQEAoKCk45lrS0NFgsluW+hRXhdDq1HoJhsKUctpTDlrKM0PPpI+P4/vNdmNsfDhsLUvGNyyqR6ljZO6YboaVesKUctpSjh5ZnvHNNNBpdcO1BTk4OMjIysH//fgwPD+PKK69c9O+12+0499xz8cwzz8S93jPPPBO3IpGIysrKtB6CYbClHLaUw5ayErmnoij4n7eG8J3Go5OHD1RkYNfW6hWfPACJ3VJv2FIOW8rRQ8tlTSB27NiB559/Hp2dnThw4AB27NiB5557Dp/85CcBAA8//DBefvlltLW14ec//zk+9rGP4aabbsLatWtjr3HppZfigQceiP355ptvxr//+7/jkUcewaFDh3D99dfD6/XG7sqUqObPz6Mzx5Zy2FIOW8pK1J5RRcGDf+7DQ6/0xx7bvj4Ht19SAbtVm92lE7WlHrGlHLaUo4eWy/rVyPDwMK699loMDAwgPT0dGzduxN69e3HZZZcBAJqbm7Fjxw6Mj4+joqICt99+O2666aa415g/xWneJz7xCYyMjODOO+/E4OAgzj77bOzZs0cXu+wRERGdSCgSxfee78azbROxxz51biH+5mz19nggItKDZV9ErQfzF1HX19fr9hqIkZER5Obmaj0MQ2BLOWwphy1lJVpPXzCCu5/pwBt9HgCzG8R96f2l2LYuR+ORJV5LPWNLOWwpR62Wql5ETUtzqvC0dGwphy3lsKWsROo54Qvh6/vacGR0do8Hu8WE2y+pxKZyfWwQl0gt9Y4t5bClHD201OYEzVXgRHtf0PKxpRy2lMOWshKlZ/9UADc90RKbPKQ5LPj2thrdTB6AxGmZCNhSDlvK0UNL7acwRERECeDIqA+372nDpH92h7icFBt2ba1GRWaSxiMjIlpZnECo5ER7X9DysaUctpTDlrL03vONvil88+kOzIRmN4grz3Bi59Zq5KXaNR7ZQnpvmUjYUg5bytFDS57CpJLjN8ej08eWcthSDlvK0nPPZ9sm8PW97bHJw1n5Kfj+h9focvIA6LtlomFLOWwpRw8tuQKhEq/Xq/UQDIMt5bClHLaUpdeej789jN0v98X+vKksHbddUgGHRns8LIVeWyYitpTDlnL00JITCJXY7fr8zVQiYks5bCmHLWXpraeiKPjpq/345VvDsce2rc3GF99fCotZ33s86K1lImNLOWwpRw8tuQ+ESqLRKMxm/f6GKpGwpRy2lMOWsvTUMxxV8IM/duPpI+Oxxz55TgGufXdBQmwQp6eWiY4t5bClHLVaLmcfCP6TVMnhw4e1HoJhsKUctpTDlrL00nMmFMFd+9pjkwcTgBvfV4JPnVuYEJMHQD8tjYAt5bClHD205ClMREREANz+MO7Y24bDIz4AgM1swq0XV+CDlRnaDoyISGc4gVBJdna21kMwDLaUw5Zy2FKW1j0HPQHctqcNve4AACDZZsbdW6qwsTBN03GdDq1bGglbymFLOXpoyQmEShwOh9ZDMAy2lMOWcthSlpY928dmcNveVoz7ZjeIy0q2YtflNajKTswN4nhsymFLOWwpRw8teQ2ESvr7+7UegmGwpRy2lMOWsrTq+daAB1/5/ZHY5KEk3YEfbq9N2MkDwGNTElvKYUs5emjJFQgiIlqV/tgxifue60QoMnszwrW5yfjW5dVId/I/jUREJ8NPSZVUVlZqPQTDYEs5bCmHLWWtdM/fHRzBA3/qxfx9zN9T4sLXL61Akk2ftwZfDh6bcthSDlvK0UNLnsKkktHRUa2HYBhsKYct5bClrJXqqSgKHnl9AD86ZvJw2ZosfHNLlSEmDwCPTUlsKYct5eihJVcgVOLxeLQegmGwpRy2lMOWslaiZySq4F9e7MGTzWOxxz6xMQ9//56ihNnjYSl4bMphSzlsKUcPLTmBUMmpdvCjpWNLOWwphy1lqd0zEI5i1/5OvNTtjj12/XuLcfWGPFW/rxZ4bMphSzlsKUcPLU2Koiin/jJ9CYfDaGxsRH19PSwWYyw5ExGROqb8Ydz1VDveGfICAKxmE77WUI6LqzM1HhkRkX5EIhE0NTWhoaHhlJMUXgOhkoMHD2o9BMNgSzlsKYctZanVc3g6iK88cSQ2eUiymfGty6sMPXngsSmHLeWwpRw9tNR+DYSIiEgFXRMz2LGnDaPeEAAgw2nFzq3VWJOTrPHIiIgSGycQKsnKytJ6CIbBlnLYUg5bypLu+c7gNO58qh2eQAQAUOSyY9fWGhS5tN/BVW08NuWwpRy2lKOHlpxAqCQ5mb/hksKWcthSDlvKkuz5UpcbO/d3IDi3QVxNdhJ2Xl6NzGSb2PfQMx6bcthSDlvK0UNLXgOhkt7eXq2HYBhsKYct5bClLKmeTx4exTefbo9NHs4pSsP3PrRm1UweAB6bkthSDlvK0UNLrkAQEVHCUxQFj/5lCI+8PhB77OLqTHz1wjLYLPxdGRGRJE4gVFJeXq71EAyDLeWwpRy2lHUmPSNRBf/6Ui9+d+jo7qx/tSEXn72gGGYDbRC3VDw25bClHLaUo4eW/LWMSiYmJrQegmGwpRy2lMOWsk63ZzAcxc79nXGTh8+cX4TPv7dkVU4eAB6bkthSDlvK0UNLrkCoZGpqSushGAZbymFLOWwp63R6eoMR3LWvHW8NTgMALCbgKxeWY/Ma7e9QoiUem3LYUg5bytFDS04gVMIdsuWwpRy2lMOWspbbc8wbwu17W9E+7gcAOKxm3HlpJd5T6lJjeAmFx6YctpTDlnL00NKkKIqi9SCWKxwOo7GxEfX19bqISEREK6dn0o/b9rRhaDoIAEh3WnHPliqsy0vReGRERIkrEomgqakJDQ0NsFpPvsbAayBUcujQIa2HYBhsKYct5bClrKX2PDTsxU2/a4lNHvJT7fjn7Ws4eTgGj005bCmHLeXooSVPYVJJAi7s6BZbymFLOWwpayk9X+lx455nOhEIRwEAVVlJ2Lm1GtmraI+HpeCxKYct5bClHD205ARCJRkZGVoPwTDYUg5bymFLWafqua9lDD/4Yzeic//drC9MxTcuq0KKnaexHo/Hphy2lMOWcvTQkhMIlbhcvJBPClvKYUs5bCnrRD0VRcGv3hrGQ6/2xx77YGUGbrmoHHZuELcoHpty2FIOW8rRQ0t++qqku7tb6yEYBlvKYUs5bClrsZ5RRcG//bkvbvJwZV0Obru4gpOHk+CxKYct5bClHD205AoEERHpTjASxfcau/Bc+2TssevOK8Rf1+fDtEo3iCMi0gtOIFRSWlqq9RAMgy3lsKUctpR1bE9fMIJvPt2BN/s9AACzCfjSB8qwbW22VsNLKDw25bClHLaUo4eWXANWicfj0XoIhsGWcthSDlvKmu854Qvhq78/Eps82C0m3LW5ipOHZeCxKYct5bClHD205ARCJZOTk1oPwTDYUg5bymFLWZOTk+hzB/Dl37WgdWwGAJDmsODbV9RgU3m6xqNLLDw25bClHLaUo4eWPIVJJTxHVw5bymFLOWwpq9er4Bu/a8GkPwwAyE2x4d6tNSjLdGo8ssTDY1MOW8phSzl6aGlS9LAbxTKFw2E0Njaivr4eFgvvAU5ElMhe753C3c90YCY0u0FceaYTu7ZWIzfFrvHIiIhWj0gkgqamJjQ0NMBqPfkaA09hUklzc7PWQzAMtpTDlnLYUsazbeO4Y197bPKwIT8FP/jwGk4ezgCPTTlsKYct5eihJU9hUkkkEtF6CIbBlnLYUg5bnrn/PTCMB//cF/vzpvJ03HZxBRxW/m7rTPDYlMOWcthSjh5acgKhEj3sEmgUbCmHLeWw5elTFAU/ebUf//PWcOyxhhInbr20Ehaz9uf2Jjoem3LYUg5bytFDS04gVJKVlaX1EAyDLeWwpRy2PD3hqIIf/LEbTx8Zjz32/51TgI+uc3HyIITHphy2lMOWcvTQkuvEKuns7NR6CIbBlnLYUg5bLt9MKII797XFJg8mAF98fymuPbcQXV1d2g7OQHhsymFLOWwpRw8tuQJBRESqm5wJ4Y597Wge8QEAbBYTdlxUgQ9UZmg7MCIiWjZOIFRSXFys9RAMgy3lsKUctly6QU8AO55sQ99UAACQYrfgm5dVYWNhauxr2FMOW8phSzlsKUcPLXkKk0pmZma0HoJhsKUctpTDlkvTNubDl3/bEps8ZCfb8IMPr4mbPADsKYkt5bClHLaUo4eWnECoZHx8/NRfREvClnLYUg5bnlpTvwdfeeIIxmdmd5cuSXfgh9trUZmVtOBr2VMOW8phSzlsKUcPLXkKExERiXu+YwLffrYLoagCAFiXm4x7Lq9GupP/2SEiSnQmRVEUrQexXOFwGI2Njaivr4fFYtF6OItSFAUmE29JKIEt5bClHLY8sd8eHMGP/9SL+f+4nF/qwu2XVCDJduLPa/aUw5Zy2FIOW8pRq2UkEkFTUxMaGhpgtZ78lz08hUklra2tWg/BMNhSDlvKYcuFFEXBw6/144FjJg9b1mThG5dVnXTyALCnJLaUw5Zy2FKOHlpyLVkloVBI6yEYBlvKYUs5bBkvElVw/ws92NMyFnvsr+vzcd15hUv6TRl7ymFLOWwphy3l6KElJxAqSU1NPfUX0ZKwpRy2lMOWR/nDUeza34GXu6cAzG4Q9/n3FuPqDXlLfg32lMOWcthSDlvK0UNLTiBUkpubq/UQDIMt5bClHLacNeUP48597Tg47AUAWM0m/FNDOS6qzlzW67CnHLaUw5Zy2FKOHlryGgiVdHR0aD0Ew2BLOWwphy2B4ekgbn7iSGzykGwzY+fW6mVPHgD2lMSWcthSDlvK0UNLrkAQEdGydU7M4LYn2zDqmz0XNzPJip2XV6MmJ1njkRERkdo4gVBJUVGR1kMwDLaUw5ZyVnPLtwencee+dkwHIwCAIpcD926tRqHLcdqvuZp7SmNLOWwphy3l6KElJxAqCQaDWg/BMNhSDlvKWa0t/9Q1iV37OxGMzN6odU1OEr51eTUyk2xn9Lqrtaca2FIOW8phSzl6aMlrIFQyOjqq9RAMgy3lsKWc1djyD4dHcffTHbHJw7nFafjeh9ac8eQBWJ091cKWcthSDlvK0UNLrkAQEdFJKYqC/3pzEP/5xmDssUuqM/GVC8tgs/D3UEREq41JURTl1F+mL+FwGI2Njaivr4fFcvLdTbUSiUR0O7ZEw5Zy2FLOamkZiSr48Uu9eOLQ0d94fXRDLj5zQTHMS9ggbsnfZ5X0XAlsKYct5bClHLVaRiIRNDU1oaGhAVbrydcY+KsjlXR2dmo9BMNgSzlsKWc1tAyGo9i5vyNu8vDZ84vwufeWiE4egNXRc6WwpRy2lMOWcvTQkqcwqSQQCGg9BMNgSzlsKcfoLacDYdz1VAcODE4DACwm4CsXlmPzmixVvp/Re64ktpTDlnLYUo4eWnICoZKUlBSth2AYbCmHLeUYueWYN4Tb9rSiY8IPAHBazbjj0kq8p9Sl2vc0cs+VxpZy2FIOW8rRQ0tOIFRSUFCg9RAMgy3lsKUco7bsnvTjtj2tGJ6e3SAu3WnFty6vwtpcdf+DZdSeWmBLOWwphy3l6KElr4FQSVtbm9ZDMAy2lMOWcozY8tCwFzf/riU2eShIs+OH29eoPnkAjNlTK2wphy3lsKUcPbTkCgQREeGVHjfueboDgbk9HqqykrBrazWyks98jwciIjIWTiBUooflJaNgSzlsKcdoLV/v88QmD/WFqfjGZVVIsa/cLReN1lNLbCmHLeWwpRw9tOQEQiXRaFTrIRgGW8phSzlGa/m5C4ox7p09delrF5XDvsIbxBmtp5bYUg5bymFLOXpoyWsgVDI8PKz1EAyDLeWwpRyjtTSbTPini8px68UVKz55AIzXU0tsKYct5bClHD20XNZ/JXbv3o2NGzfC5XLB5XJh06ZNePLJJ2PPDw4O4m//9m9RUFCAlJQUvPvd78b//u//nvQ1PR4PvvzlL6O8vBxJSUl43/veh1dfffX03g0REZ02m8UMi1l2gzgiIjKeZU0gSkpKcN999+H111/Ha6+9hksuuQRXXXUV3nnnHQDAtddei+bmZvz2t7/FgQMH8Fd/9Vf4+Mc/jjfffPOEr/npT38aTz31FH72s5/hwIED2LJlCzZv3oy+vr4ze2caW7NmjdZDMAy2lMOWcthSFnvKYUs5bCmHLeXooeWyJhDbt2/HFVdcgTVr1qC2thY7d+5EamoqXn75ZQDAn/70J9x44404//zzUVVVha9//evIyMjA66+/vujrzczM4H//93/xne98BxdeeCFqamrwjW98AzU1Ndi9e/eZvzsN9fT0aD0Ew2BLOWwphy1lsacctpTDlnLYUo4eWp72ia6RSAS/+MUv4PV6sWnTJgDA+973Pvzyl7/E+Pg4otEofvGLX8Dv9+Oiiy5a9DXC4TAikQicTmfc40lJSXjhhRdOOQaPx4OpqanY//Swtfc8v9+v9RAMgy3lsKUctpTFnnLYUg5bymFLOXpouey7MB04cACbNm2C3+9HamoqHn/8cdTV1QEA/ud//gef+MQnkJ2dDavViuTkZDz++OOoqalZ9LXS0tKwadMm3HPPPVi/fj3y8/Px3//933jppZdO+Pcca8OGDfD5fLE/X3fddbjxxhtRWFgY22QjPz8fiqLELjhZs2YNent7MTMzA6fTidLSUhw5cgQAkJeXB7PZjMHBQQBAdXU1BgcH4fV64XA4UFFRgebmZgBATk4O7HY7+vv7AQCVlZUYGRnB9PQ0bDYbnE4nDh48CADIyspCUlJS7LSsiooKjI+PY2pqChaLBWvXrsWhQ4egKAoyMjKQlpYWm12WlZVhamoKk5OTMJlMWL9+PZqbmxGJROByuZCZmYmuri4As6eY+Xw+jI+PAwDq6urQ0tKCcDiMtLQ05OTkoKOjAwBQVFSEQCCAsbExAMC6devQ3t6OYDCIlJQU5Ofno729HQBQWFiIcDiMkZERAEBtbS26u7vh9/uRlJSE4uJitLa2xnoDwNDQEACgpqYGfX19sd5lZWVoaWkBAOTm5sJqtWJgYAAAUFVVhaGhIXi9XtjtdlRVVeHw4cPw+XwYGhqCw+GI6z06OgqPxwOr1Yra2tq43snJyejt7QUAlJeXY2Ji4oS9XS4Xuru7AQClpaXweDwn7J2VlYXOzk4AQHFxMWZmZmK9169fj9bWVoRCIaSmpiI3NzeudzAYxOjoKABg7dq16OzsRCAQQEpKCgoKCmLHbEFBAaLRaNwx29PTE+tdUlISd8yaTKZY7+rqagwMDMDn88HhcKC8vDyut8lkinWqqqrC8PAwpqen43oDQHZ2NpxO56LH7PG9MzMzkZqaGnfMut1uuN1umM1mrFu3DocPH0Y0GkV6ejrS09Pjek9PT2NiYmLBMbtYb7/fv+gxm5qairy8vJMes11dXQgEAkhOThb5jPD5fAgEAqf9GVFTU4NDhw7FjtnV/hnh8/nQ3t5+Wp8R88csPyNme9vt9th7Xe5nxPG9V/tnhM/nw9jYmCY/RxjtM0JRlNgxsdI/R8wfs0b5jPD5fIhEIuI/RyjK7K28l8KkLOerAQSDQXR3d8PtduOxxx7DQw89hMbGRtTV1eHGG2/EK6+8gl27diEnJwe//vWv8c///M/44x//iHe9612Lvl5bWxv+/u//Hs8//zwsFgve/e53o7a2Fq+//nrsX5zjhcNhNDY2oqqqCmbz0UUUh8MBh8OxnLejmlAoBJuNGzBJYEs5bCmHLWWxpxy2lMOWcthSjlotI5EImpqa0NDQAKv15GsMyz6FyW63o6amBueeey7uvfde1NfX4/7770dbWxseeOAB/PSnP8Wll16K+vp63HXXXTjvvPPw4x//+ISvV11djcbGRkxPT6OnpwevvPIKQqEQqqqqTjmWtLS02B2hXC6XbiYPAGIzOzpzbCmHLeWwpSz2lMOWcthSDlvK0UPLM77ZdzQaRSAQiJ1KdOyKAABYLJYlbXiRkpKCwsJCTExMYO/evbjqqqvOdGhERERERCRsWddA7NixA9u2bUNZWRk8Hg8effRRPPfcc9i7dy/WrVuHmpoafO5zn8P3vvc9ZGdn49e//jWeeuopPPHEE7HXuPTSS3H11VfjhhtuAADs3bsXiqJg7dq1aG1txde+9jWsW7cO1113new7XWF5eXlaD8Ew2FIOW8phS1nsKYct5bClHLaUo4eWy5pADA8P49prr8XAwADS09OxceNG7N27F5dddhkA4A9/+ANuvfVWbN++HdPT06ipqcEjjzyCK664IvYabW1tsYvEAMDtdmPHjh3o7e1FVlYWPvrRj2Lnzp0Jf56cycTNmKSwpRy2lMOWsthTDlvKYUs5bClHDy2XNYH4yU9+ctLn16xZc8qdp+evPJ/38Y9/HB//+MeXM4yEMDQ0hOzsbK2HYQhsKYct5bClLPaUw5Zy2FIOW8rRQ8szvgaCiIiIiIhWD04gVFJdXa31EAyDLeWwpRy2lMWecthSDlvKYUs5emjJCYRK5jc1oTPHlnLYUg5bymJPOWwphy3lsKUcPbTkBEIFgUAAP/rRjxAIBLQeSsJjSzlsKYctZbGnHLaUw5Zy2FKOXlpyAqGCQCCAhx9+WPN/uEbAlnLYUg5bymJPOWwphy3lsKUcvbTkBIKIiIiIiJaMEwgiIiIiIlqyZe0DoReKogAAIpGIxiNZXDQaRXJyMqLRqG7HmCjYUg5bymFLWewphy3lsKUctpSjZsv515v/OftkTMpSvkpn/H4/XnzxRa2HQURERERkKO9///vhdDpP+jUJOYGIRqMIBoOwWCy62M6biIiIiCiRKYqCSCQCu90Os/nkVzkk5ASCiIiIiIi0wYuoiYiIiIhoyTiBICIiIiKiJeMEgoiIiIiIlowTCCIiIiIiWjJOIJbpueeeg8lkWvR/r776KgDgG9/4xqLPp6SkLOl7jI2NoaSkBCaTCZOTkyq+G22p1XJsbAxbt25FUVERHA4HSktLccMNN2Bqamql3pom1OrZ1NSEa665BqWlpUhKSsL69etx//33r9Tb0oSa/55/8YtfxLnnnguHw4Gzzz57Bd6NttRs2d3djQ996ENITk5GXl4evva1ryEcDq/E29LEUloCs3dS+d73vofa2lo4HA4UFxdj586dJ33tN954A5dddhkyMjKQnZ2Nz372s5ienlb7LWlGzZYtLS246qqrkJOTA5fLhQ984AN49tln1X5LmlKr51Jf10jUPDYB4Pe//z0uuOACJCUlITMzEx/5yEdOb6AKLUsgEFAGBgbi/vfpT39aqaysVKLRqKIoiuLxeBZ8TV1dnfKpT31qSd/jqquuUrZt26YAUCYmJtR7MxpTq+X4+Ljyr//6r8qrr76qdHZ2Kk8//bSydu1a5Zprrlmhd6YNtXr+5Cc/Ub74xS8qzz33nNLW1qb87Gc/U5KSkpQf/ehHK/TOVp6a/57feOONygMPPKD87d/+rVJfX6/+m9GYWi3D4bCyYcMGZfPmzcqbb76p/OEPf1BycnKUHTt2rNA7W3lLaakos8fY2rVrld/85jdKe3u78tprryn79u074ev29fUpmZmZyuc//3nl8OHDyiuvvKK8733vUz760Y+uxNvShFotFUVR1qxZo1xxxRVKU1OT0tLSovzjP/6jkpycrAwMDKj9tjSjVs+lvq6RqHlsPvbYY0pmZqaye/dupbm5WXnnnXeUX/7yl6c1Tk4gzlAwGFRyc3OVu++++4Rf85e//EUBoDz//POnfL1//dd/VRoaGpRnnnnG8BOI40m3PNb999+vlJSUnOkQE4qaPf/xH/9Rufjii890iAlDjZZ33XXXqphAHE+q5R/+8AfFbDYrg4ODscd2796tuFwuJRAIiI5ZrxZrefDgQcVqtSqHDx9e8us8+OCDSl5enhKJRGKPvfXWWwoA5ciRI6Jj1iupliMjIwuO3ampKQWA8tRTT4mOWc+kei7ldY1OqmUoFFKKi4uVhx56SGRcPIXpDP32t7/F2NgYrrvuuhN+zUMPPYTa2lp88IMfPOlrHTx4EHfffTf+8z//85QbeBiRZMtj9ff34//9v/+HhoYGiWEmDLV6AoDb7UZWVtaZDjFhqNlytZFq+dJLL+Fd73oX8vPzY49dfvnlmJqawjvvvCM6Zr1arOXvfvc7VFVV4YknnkBlZSUqKirw6U9/GuPj4yd8nUAgsGDjqKSkJADACy+8oN4b0BGpltnZ2Vi7di3+8z//E16vF+FwGA8++CDy8vJw7rnnrsRb0QWpnkt5XaOTavnGG2+gr68PZrMZ55xzDgoLC7Ft2za8/fbbpzcwkWnIKrZt2zZl27ZtJ3x+ZmZGyczMVL797W+f9HX8fr+yceNG5Wc/+5miKIry7LPPrroVCKmW8/76r/9aSUpKUgAo27dvV2ZmZqSGmhCke8578cUXFavVquzdu/dMh5gw1Gi5WlcgpFp+5jOfUbZs2RL3mNfrVQAof/jDH0TGqneLtfzc5z6nOBwO5YILLlCef/555dlnn1XOPvvsk64Yvv3224rValW+853vKIFAQBkfH1c++tGPKgCUXbt2qf02dEGqpaIoSk9Pj3LuuecqJpNJsVgsSmFhofLGG2+oOXzdkex5qtc1OqmW//3f/60AUMrKypTHHntMee2115RrrrlGyc7OVsbGxpY9Lk4g5txyyy0KgJP+79ChQ3F/T09Pj2I2m5XHHnvshK/76KOPKlarNW6ZfTE33XST8olPfCL250SeQGjdct7AwIBy6NAh5Te/+Y1SV1enXH/99Wf0vrSil56KoigHDhxQcnJylHvuuee034+W9NQy0ScQWrc00gRCsuVnPvMZBYDS3Nwce+z1119XAJz0dIf/+q//UvLz8xWLxaLY7Xblq1/9qpKfn6/cd999sm9WZVq3jEajypVXXqls27ZNeeGFF5TXX39duf7665Xi4mKlv79f/g2rTOueS3ndRKF1y//6r/9SACgPPvhg7DG/36/k5OQo//Zv/7bs92Nd+lqFsX3lK1/B3/3d3530a6qqquL+/PDDDyP7/2/vfkKa/OM4gH8mmk3bhLk9bhaEQZvr0KFLaaiHdCBEh90aBkFQxw4rEltEh65BFEGQkzqHB53gUAZeAu3PBs+IhqNF1GEFRXSJ2Xr/Dv02HE19HM/Tnq33C7x8nz2P3++bZ9OP3+f7tbtbzpw5s+U5jx49ktOnT1dMs1eTSCREVVV5+vSpiPxeXS8i4nQ65fr163Lr1i0NozCHemdZ4na7xe12S39/vzgcDhkaGpIbN26Ix+PRdL5ZmCXP169fy6lTp+TixYsSiUQ0nWM2ZsmyGdQ7S7fbLWtraxVt+Xy+fKyR6Jmlx+OR1tZW8Xq95Ta/3y8iv3et8vl8Va8fCoUkFApJPp+Xzs5OsVgscufOnT++r9nVO8tEIiGxWEy+fv0qdrtdREQePHggS0tL8vjxY5mcnKxlWHVT7zy1XLdR1DvL0u8+R44cKbe1t7fLoUOH5P3797sai4jwEaZa/fr1C319fQiHw1u+5u3bt7BYLJifn9/xetlsFqqqlr+i0ShEBM+ePUM+n9ez66ajd5bVrKysQESQy+Vq7GXjMCLPdDoNRVFw9epVvbrZEIy8Nxt9BmK39M6ytIh68+fjw4cPYbfb8ePHD136bFbbZRmPxyEiyGaz5bbSovTNf63cyfT0NDo6OhpyFnw39M5ybm4OLS0t+P79e0W71+vF7du39e28CRl1b2r5/Gg2emf57ds3tLe3VyyiLhQKUBSlYlZCKxYQNVpeXq463bRZJBJBb28vfv78+cex2dlZ+Hy+Lc9t5EeYdkvvLBcWFhCNRqGqKnK5HGKxGPx+P06ePGlI/81G7zxVVYXL5cLExETFtnKfPn0ypP9mYsT7fH19HclkEpcuXYLX60UymUQymWz6nYP0zrK0jWsgEEAqlcLi4iJcLldTb+Nasl2WxWIRx44dw/DwMF69eoUXL17g+PHjGBsbK79mdXUVPp8PHz58KLfdu3cPL1++RCaTwf3792G1WnH37t2/Mp560jvLz58/o7u7G8FgEKlUCplMBleuXEFbWxtSqdRfG1e9GHFv7nTdZmVElpcvX8b+/fsRj8fx5s0bXLhwAYqi4MuXL7vuHwuIGp09exaDg4NbHi8Wizhw4ACmpqaqHp+ZmcF2E0D/UgGhd5aJRAIDAwPo6urC3r17cfjwYVy7du2fyBLQP8+bN29WfVbz4MGDenfddIx4n4+MjFTNs9lnx4zI8t27dxgfH4fVaoXT6UQ4HMbGxoau/TajnbL8+PEjgsEg9u3bh56eHpw/f75ikWTp58vme+7cuXNwOBzYs2cPjh49iidPnhg5BNMwIsvnz58jEAjA4XDAZrPhxIkTDbcup1ZG5Knlus3IiCwLhQLC4TAURYHNZsPo6CjS6XRN/bMA/z9sT0REREREtIN/758NEBERERFRzVhAEBERERGRZiwgiIiIiIhIMxYQRERERESkGQsIIiIiIiLSjAUEERERERFpxgKCiIiIiIg0YwFBRERERESasYAgIiIiIiLNWEAQEREREZFmLCCIiIiIiEiz/wBUX1ivf9jAQQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 6))\n",
    "l.plot(ax=ax);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    POLYGON ((-77.03687 38.90719, -76.61219 39.290...\n",
       "dtype: geometry"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from shapely.geometry import Polygon\n",
    "p= gpd.GeoSeries([Polygon([Point(-77.036873,38.907192),\n",
    "                           Point(-76.612190,39.290386),\n",
    "                           Point(-77.408456,39.412006)])])\n",
    "p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 6))\n",
    "p.plot(ax=ax);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "注意，`GeoSeries` 中的所有条目不需要具有相同的几何类型，但如果不是这样，某些导出操作将失败。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### GeoDataFrame\n",
    "\n",
    "`GeoDataFrame` 是包含 `GeoSeries` 的表格式数据结构。\n",
    "\n",
    "`GeoDataFrame` 最重要的属性是它总是有一个 `GeoSeries` 列，它持有一个特殊的状态。这个 `GeoSeries` 被称为 `GeoDataFrame` 的“几何”。当将空间方法应用到 `GeoDataFrame` （或调用类似 `area` 的空间属性）时，此命令将始终作用于“几何”列。\n",
    "\n",
    "“几何”列——不管它的名字是什么——都可以通过几何属性（`gdf.geometry`）访问，并且可以通过键入 [`gdf.geometry.name`](http://gdf.geometry.name/) 找到几何列的名称。\n",
    "\n",
    "```{note}\n",
    "`GeoDataFrame` 还可以包含具有几何（形状）对象的其他列，但一次只能有一列是活动几何。要更改哪个列是活动几何列，请使用 {meth}`GeoDataFrame.set_geometry` 方法。\n",
    "```\n",
    "\n",
    "使用世界 `GeoDataFrame` 的例子："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pop_est</th>\n",
       "      <th>continent</th>\n",
       "      <th>name</th>\n",
       "      <th>iso_a3</th>\n",
       "      <th>gdp_md_est</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>889953.0</td>\n",
       "      <td>Oceania</td>\n",
       "      <td>Fiji</td>\n",
       "      <td>FJI</td>\n",
       "      <td>5496</td>\n",
       "      <td>MULTIPOLYGON (((180.00000 -16.06713, 180.00000...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>58005463.0</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Tanzania</td>\n",
       "      <td>TZA</td>\n",
       "      <td>63177</td>\n",
       "      <td>POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>603253.0</td>\n",
       "      <td>Africa</td>\n",
       "      <td>W. Sahara</td>\n",
       "      <td>ESH</td>\n",
       "      <td>907</td>\n",
       "      <td>POLYGON ((-8.66559 27.65643, -8.66512 27.58948...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>37589262.0</td>\n",
       "      <td>North America</td>\n",
       "      <td>Canada</td>\n",
       "      <td>CAN</td>\n",
       "      <td>1736425</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -122.9742...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>328239523.0</td>\n",
       "      <td>North America</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>USA</td>\n",
       "      <td>21433226</td>\n",
       "      <td>MULTIPOLYGON (((-122.84000 49.00000, -120.0000...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       pop_est      continent                      name iso_a3  gdp_md_est  \\\n",
       "0     889953.0        Oceania                      Fiji    FJI        5496   \n",
       "1   58005463.0         Africa                  Tanzania    TZA       63177   \n",
       "2     603253.0         Africa                 W. Sahara    ESH         907   \n",
       "3   37589262.0  North America                    Canada    CAN     1736425   \n",
       "4  328239523.0  North America  United States of America    USA    21433226   \n",
       "\n",
       "                                            geometry  \n",
       "0  MULTIPOLYGON (((180.00000 -16.06713, 180.00000...  \n",
       "1  POLYGON ((33.90371 -0.95000, 34.07262 -1.05982...  \n",
       "2  POLYGON ((-8.66559 27.65643, -8.66512 27.58948...  \n",
       "3  MULTIPOLYGON (((-122.84000 49.00000, -122.9742...  \n",
       "4  MULTIPOLYGON (((-122.84000 49.00000, -120.0000...  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))\n",
    "world.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "world.plot();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 空间点线多边形\n",
    "\n",
    "经常发现处于这样一种情况：需要从头生成新的空间数据，或者需要更好地理解数据是如何构造的。这节课将带您了解一些最常见的数据生成形式。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import geopandas as gpd\n",
    "from shapely.geometry import Point, LineString, Polygon\n",
    "# import fiona\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('bmh') # 更适合绘制几何图形。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 创建 GeoDataFrame 几何\n",
    "\n",
    "`GeoDataFrame` 对象是 `pandas.DataFrame`，具有几何列的数据帧。空的 `GeoDataFrame` 就是空的，本质上就像 pandas 的那个一样。\n",
    "\n",
    "创建空的 `GeoDataFrame`，并创建名为 `geometry` 的新列，它将包含 Shapely 对象："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Empty GeoDataFrame\n",
      "Columns: []\n",
      "Index: []\n"
     ]
    }
   ],
   "source": [
    "# 创建空白的 geopandas GeoDataFrame\n",
    "newdata = gpd.GeoDataFrame()\n",
    "print(newdata)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "为了有工作的空间数据框架，需要定义一些东西：\n",
    "\n",
    "### GeoDataFrame 组件\n",
    "\n",
    "- ``data``：包含所需属性数据的 `pandas.DataFrame`、字典或空列表 `[]`。如果没有数据，则使用 `[]`。\n",
    "- `crs`：几何对象的坐标参考系（Coordinate Reference System）。可以是 `pyproj.CRS.from_user_input()` 所接受的任何内容，例如权限字符串（例如  “EPSG:4326”）或 WKT 字符串。\n",
    "- `geometry`：DataFrame 中的列名称，用作几何或 Shapely 点、线或多边形对象。\n",
    "\n",
    "因为 geopandas 利用了 Shapely 的几何对象，所以可以通过将 Shapely 的几何对象传递到 GeoDataFrame 来从头创建 Shapefile。这是非常有用的，因为它可以很容易地将包含坐标的文本文件转换为 Shapefile。\n",
    "\n",
    "现在在 GeoDataFrame 中有一个几何列，但是还没有任何数据。\n",
    "\n",
    "### 从坐标列表中创建点\n",
    "\n",
    "创建 geopandas 点对象是一个快照！所需要的是坐标对，从中生成 Shapely 点几何对象，然后创建字典，保存该几何和想要的任何属性，以及坐标参考系统。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# GW department of geography 的十进制坐标\n",
    "coordinate = [-77.04639494419096,  38.89934963421794]\n",
    "\n",
    "# 从坐标对中创建 Shapely\n",
    "point_coord = Point(coordinate)\n",
    "\n",
    "# 创建具有所需属性和所需几何列的数据帧\n",
    "df = {'GWU': ['Dept Geography'], 'geometry': [point_coord]}\n",
    "\n",
    "# 将 shapely 对象转换为  geodataframe \n",
    "point = gpd.GeoDataFrame(df, geometry='geometry', crs =\"EPSG:4326\")\n",
    "\n",
    "# 渲染\n",
    "point.plot();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以对存储在 pandas 数据框架中的点集应用相同的过程。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 属性和坐标列表\n",
    "df = pd.DataFrame(\n",
    "    {'City': ['Buenos Aires', 'Brasilia', 'Santiago', 'Bogota', 'Caracas'],\n",
    "     'Country': ['Argentina', 'Brazil', 'Chile', 'Colombia', 'Venezuela'],\n",
    "     'lat': [-34.58, -15.78, -33.45, 4.60, 10.48],\n",
    "     'lon': [-58.66, -47.91, -70.66, -74.08, -66.86]})\n",
    "\n",
    "# 从坐标元组列表中创建 Shapely points\n",
    "ply_coord = [Point(x, y) for x, y in zip(df.lat, df.lon)]\n",
    "\n",
    "# 用 crs 转换 shapely 对象到 geodataframe\n",
    "poly = gpd.GeoDataFrame(df, geometry=ply_coord, crs =\"EPSG:4326\")\n",
    "poly.plot();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 从经纬度（lat, lon） CSV 创建点\n",
    "\n",
    "最常见的数据创建任务之一是从点列表或 `.csv` 文件创建 shapefile。幸运的是，将这些数据转换成可用的格式非常容易。\n",
    "\n",
    "首先，必须创建示例 `.csv` 数据集来工作："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "# 创建 Washington DC 的轮廓，并写入 csv\n",
    "path_to_csv = 'points.csv'\n",
    "points = {'Corner':['N','E','S','W'],\n",
    "          'lon': [-77.0412826538086, -77.11681365966797, -77.01896667480469, -77.0412826538086], \n",
    "          'lat': [38.99570671505043, 38.936713143230044, 38.807610542357594, 38.99570671505043]}\n",
    "points = pd.DataFrame.from_dict(points)\n",
    "points.to_csv(path_to_csv)              "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "要从我们的数据创建 `geodataframe`，您只需要将其读入，并使用 `points_from_xy` 将其指向 `df` 的正确列，即 `df` 指定几何列值 `df.lon` 和 `df.lat`。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Corner</th>\n",
       "      <th>lon</th>\n",
       "      <th>lat</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>N</td>\n",
       "      <td>-77.041283</td>\n",
       "      <td>38.995707</td>\n",
       "      <td>POINT (-77.04128 38.99571)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>E</td>\n",
       "      <td>-77.116814</td>\n",
       "      <td>38.936713</td>\n",
       "      <td>POINT (-77.11681 38.93671)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>S</td>\n",
       "      <td>-77.018967</td>\n",
       "      <td>38.807611</td>\n",
       "      <td>POINT (-77.01897 38.80761)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>W</td>\n",
       "      <td>-77.041283</td>\n",
       "      <td>38.995707</td>\n",
       "      <td>POINT (-77.04128 38.99571)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0 Corner        lon        lat                    geometry\n",
       "0           0      N -77.041283  38.995707  POINT (-77.04128 38.99571)\n",
       "1           1      E -77.116814  38.936713  POINT (-77.11681 38.93671)\n",
       "2           2      S -77.018967  38.807611  POINT (-77.01897 38.80761)\n",
       "3           3      W -77.041283  38.995707  POINT (-77.04128 38.99571)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 读取点数据\n",
    "df = pd.read_csv(path_to_csv)\n",
    "\n",
    "# 从使用 'EPSG' 代码的数据创建 geodataframe，以分配 WGS84 坐标系\n",
    "points= gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(x=df.lon, y=df.lat), crs = 'EPSG:4326')\n",
    "points"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在本例中，`points_from_xy()` 用于将 `lat` 和 `lon` 转换为  `shapely.Point` 对象列表。这将被用作 GeoDataFrame 的几何图形。（`points_from_xy()` 只是 `[Point(x, y) for x, y in zip(df.lon, df.lat)]` 的增强包装器。\n",
    "\n",
    "```{tip}\n",
    "- 虽然我们说 \"lat lon\"，但 python 使用 \"lon lat\" 代替，这遵循了使用 x, y 作为符号的偏好。\n",
    "- 通常，像上面的数据一样，这些数据存储在 WGS84 经纬度中，但一定要检查这一点，另一种常见的格式是 UTM 坐标（寻找从东到西约 $500\\,000$ 的值，以米为单位）。\n",
    "```\n",
    "\n",
    "### 创建空间线条\n",
    "\n",
    "按照上面的例子，可以很容易地指定线条。在这种情况下，假设有追踪三个骑自行车穿过城镇的人的线。跟踪他们的唯一 id `ID`，他们的位置 X, Y 和他们的速度，并读取以下数据："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from io import StringIO \n",
    "data = \"\"\"\n",
    "ID,X,Y,Speed\n",
    "1,  -87.789,  41.976,  16\n",
    "1,  -87.482,  41.677,  17\n",
    "2,  -87.739,  41.876,  16\n",
    "2,  -87.681,  41.798,  16\n",
    "2,  -87.599,  41.708,  16\n",
    "3,  -87.599,  41.908,  17\n",
    "3,  -87.598,  41.708,  17\n",
    "3,  -87.643,  41.675,  17\n",
    "\"\"\"\n",
    "# 使用 StringIO 读取文本块\n",
    "df = pd.read_table(StringIO(data), sep=',')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "让我们把这些转换成点来看看。注意，在本例中点不能很好地替代线，我们有三个个体，它们需要分别处理。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# zip 坐标到点对象，并转换为 GeoDataFrame\n",
    "points = [Point(xy) for xy in zip(df.X, df.Y)]\n",
    "geo_df = gpd.GeoDataFrame(df, geometry=points, crs = 'EPSG:4326')\n",
    "geo_df.plot();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "现在让将这些数据作为线处理，可以利用列 ID 到 `.groupby`。幸运的是，geopanda `.groupby` 与 pandas 的用法一致。所以这里 `.groupby(['ID'])`，对于每个 ID 组，将值转换为一个列表，并将其存储在 Fiona `LineString` 对象中。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 把每个点的 `ID` 组看作一条线\n",
    "lines = geo_df.groupby(['ID'])['geometry'].apply(lambda x:  LineString(x.tolist()))\n",
    "\n",
    "# 存储为 GeodataFrame 并添加 'ID' 作为列（当前存储为 'index'）\n",
    "lines = gpd.GeoDataFrame(lines, geometry='geometry', crs=\"EPSG:4326\") \n",
    "lines.reset_index(inplace=True)\n",
    "lines.plot(column='ID');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "现可以看到，每条线都是由 ID 单独处理的，并使用 `.plot(column='ID')` 绘制它们。\n",
    "\n",
    "### 创建空间多边形\n",
    "\n",
    "在 geopandas 中创建多边形与其他练习非常相似。首先，从坐标中创建 Fiona 几何对象，将其添加到具有任何属性的数据帧中，然后使用指定的坐标参考系统（coordinate reference system，简称 CRS）创建 GeoDataFrame。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# list of coordindate pairs\n",
    "coordinates = [[ -77.0412826538086, 38.99570671505043 ], [ -77.11681365966797, 38.936713143230044 ], [ -77.01896667480469, 38.807610542357594],\n",
    "               [-76.90910339355469,  38.892636142310295]]           \n",
    "\n",
    "# Create a Shapely polygon from the coordinate-tuple list\n",
    "ply_coord = Polygon(coordinates)\n",
    "\n",
    "# create a dictionary with needed attributes and required geometry column\n",
    "df = {'Attribute': ['name1'], 'geometry': ply_coord}\n",
    "\n",
    "# Convert shapely object to a geodataframe \n",
    "poly = gpd.GeoDataFrame(df, geometry='geometry', crs =\"EPSG:4326\")\n",
    "\n",
    "# Let's see what we have\n",
    "poly.plot();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 创建空间点（必须承认这是漫长的过程）\n",
    "\n",
    "因为 geopandas 利用了 Shapely 的几何对象，所以可以通过将 Shapely 的几何对象传递到 GeoDataFrame 来从头创建 Shapefile。这是非常有用的，因为它可以很容易地将包含坐标的文本文件转换为 Shapefile。\n",
    "\n",
    "让我们创建空的 GeoDataFrame，并创建名为 geometr 的新列，它将包含我们的 Shapely 对象："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Empty GeoDataFrame\n",
      "Columns: [geometry]\n",
      "Index: []\n"
     ]
    }
   ],
   "source": [
    "# Create an empty geopandas GeoDataFrame\n",
    "newdata = gpd.GeoDataFrame()\n",
    "# Create a new column called 'geometry' to the GeoDataFrame\n",
    "newdata['geometry'] = None\n",
    "\n",
    "print(newdata)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "创建表示 GWU 地理学系的 Shapely Point，可以将它插入到 GeoDataFrame 中："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/svg+xml": "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"100.0\" height=\"100.0\" viewBox=\"-78.04639494419096 37.89934963421794 2.0 2.0\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,77.79869926843588)\"><circle cx=\"-77.04639494419096\" cy=\"38.89934963421794\" r=\"0.06\" stroke=\"#555555\" stroke-width=\"0.02\" fill=\"#66cc99\" opacity=\"0.6\" /></g></svg>",
      "text/plain": [
       "<shapely.geometry.point.Point at 0x7f49ac952e90>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Coordinates of the GW department of geography in Decimal Degrees\n",
    "coordinates = (-77.04639494419096,  38.89934963421794)\n",
    "\n",
    "# Create a Shapely polygon from the coordinate-tuple list\n",
    "point = Point(coordinates)\n",
    "\n",
    "# Let's see what we have\n",
    "point"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "现在有了合适的 Polygon -object。\n",
    "\n",
    "将多边形插入到 GeoDataFrame 的“geometry”列中："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POINT (-77.04639 38.89935)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     geometry\n",
       "0  POINT (-77.04639 38.89935)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Insert the polygon into 'geometry' -column at index 0\n",
    "newdata.loc[0, 'geometry'] = point\n",
    "\n",
    "# Let's see what we have now\n",
    "newdata"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "现在有了带 Point 的 GeoDataFrame，可以将它导出到 Shapefile中。在 GeoDataFrame 中添加另一列，名为 Location，文本为 GWU Geography。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "      <th>Location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POINT (-77.04639 38.89935)</td>\n",
       "      <td>GWU Geography</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     geometry       Location\n",
       "0  POINT (-77.04639 38.89935)  GWU Geography"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Add a new column and insert data\n",
    "newdata.loc[0, 'Location'] = 'GWU Geography'\n",
    "\n",
    "# Let's check the data\n",
    "newdata"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "好了，现在有了额外的有用的信息能够识别特征代表什么。\n",
    "\n",
    "在导出数据之前，确定 GeoDataFrame 的坐标参考系统（CRS，“投影”）是很有用的。\n",
    "\n",
    "GeoDataFrame 有叫做 `.crs` 的属性，它显示了在例子中为空（`None`）的数据坐标系统，因为是从头创建数据（例如 `newdata.crs` 返回 `None`）。\n",
    "\n",
    "为 GeoDataFrame 添加 `crs`。Python 模块 fiona 有很好的 `from_epsg()` 函数，用于传递 GeoDataFrame 的坐标系统。接下来，将使用它，并确定投影到 WGS84 (epsg code:4326)，这是最常见的选择，lat lon CRSs："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/media/pc/data/4tb/lxw/libs/anaconda3/envs/tvmx/lib/python3.10/site-packages/pyproj/crs/crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Geographic 2D CRS: +init=epsg:4326 +no_defs +type=crs>\n",
       "Name: WGS 84\n",
       "Axis Info [ellipsoidal]:\n",
       "- lon[east]: Longitude (degree)\n",
       "- lat[north]: Latitude (degree)\n",
       "Area of Use:\n",
       "- name: World.\n",
       "- bounds: (-180.0, -90.0, 180.0, 90.0)\n",
       "Datum: World Geodetic System 1984 ensemble\n",
       "- Ellipsoid: WGS 84\n",
       "- Prime Meridian: Greenwich"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Import specific function 'from_epsg' from fiona module\n",
    "from fiona.crs import from_epsg\n",
    "\n",
    "# Set the GeoDataFrame's coordinate system to WGS84\n",
    "newdata.crs = from_epsg(code = 4326)\n",
    "\n",
    "# Let's see how the crs definition looks like\n",
    "newdata.crs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "最后，可以使用 `GeoDataFrames.to_file()` 导出数据。该函数的工作原理与 numpy 或 pandas 类似，但这里只需要为 Shapefile 提供输出路径。\n",
    "\n",
    "```python\n",
    "# Determine the output path for the Shapefile\n",
    "outfp = r\"../temp/gwu_geog.shp\"\n",
    "\n",
    "# Write the data into that Shapefile\n",
    "newdata.to_file(outfp)\n",
    "```"
   ]
  }
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