Drawing shapefiles.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "           <script>\n",
       "               \n",
       "                function vct_load_lib(url, callback){\n",
       "                      if(typeof d3 !== 'undefined' &&\n",
       "                         url === 'http://d3js.org/d3.v3.min.js'){\n",
       "                        callback()\n",
       "                      }\n",
       "                      var s = document.createElement('script');\n",
       "                      s.src = url;\n",
       "                      s.async = true;\n",
       "                      s.onreadystatechange = s.onload = callback;\n",
       "                      s.onerror = function(){\n",
       "                        console.warn(\"failed to load library \" + url);\n",
       "                        };\n",
       "                      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "                };\n",
       "                var vincent_event = new CustomEvent(\n",
       "                  \"vincent_libs_loaded\",\n",
       "                  {bubbles: true, cancelable: true}\n",
       "                );\n",
       "                \n",
       "               function load_all_libs(){\n",
       "                  console.log('Loading Vincent libs...')\n",
       "                  vct_load_lib('http://d3js.org/d3.v3.min.js', function(){\n",
       "                  vct_load_lib('http://d3js.org/d3.geo.projection.v0.min.js', function(){\n",
       "                  vct_load_lib('http://wrobstory.github.io/d3-cloud/d3.layout.cloud.js', function(){\n",
       "                  vct_load_lib('http://wrobstory.github.io/vega/vega.v1.3.3.js', function(){\n",
       "                  window.dispatchEvent(vincent_event);\n",
       "                  });\n",
       "                  });\n",
       "                  });\n",
       "                  });\n",
       "               };\n",
       "               if(typeof define === \"function\" && define.amd){\n",
       "                    if (window['d3'] === undefined ||\n",
       "                        window['topojson'] === undefined){\n",
       "                        require.config(\n",
       "                            {paths: {\n",
       "                              d3: 'http://d3js.org/d3.v3.min',\n",
       "                              topojson: 'http://d3js.org/topojson.v1.min'\n",
       "                              }\n",
       "                            }\n",
       "                          );\n",
       "                        require([\"d3\"], function(d3){\n",
       "                            console.log('Loading Vincent from require.js...')\n",
       "                            window.d3 = d3;\n",
       "                            require([\"topojson\"], function(topojson){\n",
       "                                window.topojson = topojson;\n",
       "                                load_all_libs();\n",
       "                            });\n",
       "                        });\n",
       "                    } else {\n",
       "                        load_all_libs();\n",
       "                    };\n",
       "               }else{\n",
       "                    console.log('Require.js not found, loading manually...')\n",
       "                    load_all_libs();\n",
       "               };\n",
       "\n",
       "           </script>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import vincent\n",
    "vincent.core.initialize_notebook()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div id=\"vis18a43c03a7084999b3109d2f70605068\"></div>\n",
       "<script>\n",
       "   ( function() {\n",
       "     var _do_plot = function() {\n",
       "       if (typeof vg === 'undefined') {\n",
       "         window.addEventListener('vincent_libs_loaded', _do_plot)\n",
       "         return;\n",
       "       }\n",
       "       vg.parse.spec({\"axes\": [], \"data\": [{\"format\": {\"feature\": \"countries\", \"type\": \"topojson\"}, \"name\": \"countries\", \"transform\": [{\"projection\": \"equirectangular\", \"scale\": 100, \"translate\": [480, 250], \"type\": \"geopath\", \"value\": \"data\"}], \"url\": \"data/countries.topo.small.json\"}], \"height\": 500, \"legends\": [], \"marks\": [{\"from\": {\"data\": \"countries\"}, \"properties\": {\"enter\": {\"path\": {\"field\": \"path\"}, \"stroke\": {\"value\": \"#000000\"}}, \"update\": {\"fill\": {\"value\": \"steelblue\"}}}, \"type\": \"path\"}], \"padding\": \"auto\", \"scales\": [], \"width\": 960}, function(chart) {\n",
       "         chart({el: \"#vis18a43c03a7084999b3109d2f70605068\"}).update();\n",
       "       });\n",
       "     };\n",
       "     _do_plot();\n",
       "   })();\n",
       "</script>\n",
       "<style>.vega canvas {width: 100%;}</style>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "world_topo = 'data/countries.topo.small.json'\n",
    "geo_data = [{'name': 'countries',\n",
    "             'url': world_topo,\n",
    "             'feature': 'countries', \n",
    "             }]\n",
    "\n",
    "vis = vincent.Map(geo_data=geo_data, scale=100, projection='equirectangular')\n",
    "vis.display()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div id=\"vis6e1e01a24ad6476bbc1df8a8ab8735e3\"></div>\n",
       "<script>\n",
       "   ( function() {\n",
       "     var _do_plot = function() {\n",
       "       if (typeof vg === 'undefined') {\n",
       "         window.addEventListener('vincent_libs_loaded', _do_plot)\n",
       "         return;\n",
       "       }\n",
       "       vg.parse.spec({\"axes\": [], \"data\": [{\"format\": {\"feature\": \"countries\", \"type\": \"topojson\"}, \"name\": \"countries\", \"transform\": [{\"projection\": \"winkel3\", \"scale\": 100, \"translate\": [480, 250], \"type\": \"geopath\", \"value\": \"data\"}], \"url\": \"data/countries.topo.small.json\"}], \"height\": 500, \"legends\": [], \"marks\": [{\"from\": {\"data\": \"countries\"}, \"properties\": {\"enter\": {\"path\": {\"field\": \"path\"}, \"stroke\": {\"value\": \"#000000\"}}, \"update\": {\"fill\": {\"value\": \"steelblue\"}}}, \"type\": \"path\"}], \"padding\": \"auto\", \"scales\": [], \"width\": 960}, function(chart) {\n",
       "         chart({el: \"#vis6e1e01a24ad6476bbc1df8a8ab8735e3\"}).update();\n",
       "       });\n",
       "     };\n",
       "     _do_plot();\n",
       "   })();\n",
       "</script>\n",
       "<style>.vega canvas {width: 100%;}</style>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vis = vincent.Map(geo_data=geo_data, scale=100, projection='winkel3')\n",
    "vis.display()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div id=\"visc394d2732bc84444889a43f863bae232\"></div>\n",
       "<script>\n",
       "   ( function() {\n",
       "     var _do_plot = function() {\n",
       "       if (typeof vg === 'undefined') {\n",
       "         window.addEventListener('vincent_libs_loaded', _do_plot)\n",
       "         return;\n",
       "       }\n",
       "       vg.parse.spec({\"axes\": [], \"data\": [{\"format\": {\"feature\": \"countries\", \"type\": \"topojson\"}, \"name\": \"countries\", \"transform\": [{\"projection\": \"mercator\", \"scale\": 100, \"translate\": [480, 250], \"type\": \"geopath\", \"value\": \"data\"}], \"url\": \"data/countries.topo.small.json\"}], \"height\": 500, \"legends\": [], \"marks\": [{\"from\": {\"data\": \"countries\"}, \"properties\": {\"enter\": {\"path\": {\"field\": \"path\"}, \"stroke\": {\"value\": \"#000000\"}}, \"update\": {\"fill\": {\"value\": \"steelblue\"}}}, \"type\": \"path\"}], \"padding\": \"auto\", \"scales\": [], \"width\": 960}, function(chart) {\n",
       "         chart({el: \"#visc394d2732bc84444889a43f863bae232\"}).update();\n",
       "       });\n",
       "     };\n",
       "     _do_plot();\n",
       "   })();\n",
       "</script>\n",
       "<style>.vega canvas {width: 100%;}</style>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vis = vincent.Map(geo_data=geo_data, scale=100, projection='mercator')\n",
    "vis.display()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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SBFu3itnjmDHwzTfCiBQVJU6ptWsHLVs6JLDqA/u58/GHWd8mhMhA2ymcr03kCqMRNm8W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\nqUmpyvg8mzYJTZuS4kSzPkh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ZCQWg8HrOG5mKOJ/qUsbt+G3fRtLn8zn91LOYWrWm/oRx\n/Eo6jaMcP1ebVaRj5eEMejaMZ2VmCWd0kKNQofULpNAvAK1fAKn9B5PXf6BjFZ88SdTTT9Ek/Shb\n7mnl0W2r/zLWws3IQnsNUaUeJWDvXoriaonYW5GR4ic8nKhlS5i14QuG1Xfcar362EXe3X6cM3nF\nNIoOYXynhvRpUtHjK7dYT8uQDlx4ZYbtCk+eJGHJAhod3U93cx6PJYfY9NqRcQ3356eVcRnV4UP0\nmzSOqXVV5JQYuWhWcMGo5JJRItso0SxYzbDGzgnshHUHSMsV6TROaopIyxWO/GWCK0kSa85qKOpu\nJTF2Whp1P59Pw2MH6GnO59HkEOKbBYLDgW9k3I0stNcARdoJbp/0OCs6RP2bpdxdzP4r7V+BLSMt\nV8ucv09ya/1YZp3I4zt1NEcGPUdR/3sq3nziBHU/n0+j4wfpJeUzJjmUWs0CkAW1eiELrbc5c4Ye\nE0bxXftItwssgM5kOSH2Ho2O9nnxnHj1baTmLa5cOHaMxCXzaXT8EL0pYHRyKHGyoFZrZKH1Jpcu\n0fXx4fzcLsLupNG2MJkl9Cbzvz9VmSAy211P5kfzK35oNnPLyMGs7JxAbHNZUH0FWWi9RXY2N455\nkDVtQitF1y9j8ZkClujDMKlUmJRKTAql+Lf87xX+VWFWqzEHBGAOCsQcEEBRr3iUP/yMuXwmiIYN\n4ZlnKjeoVBKXEEdssLzX6kvIQusN8vO5ftQDrGsRaDXB0ldafzZ+/Z3r7Q1YDe+9B6dPQ+PG8NRT\n0KePxaIF/s6HaZW5NshC62m0WtqOHMK6JmqrWc0NJjPpsVasuY7Qp484Uvn11zBunNWiQmj17mlX\nxivIO+OeRKej5cihrEuRbKb12JqRx9nbLWtDpzCb7coEX+hgPCuZa4+saT2FwUCzkQ+wslYR4Mex\n7ELySgzk6k1cMivJNCnINECO0UyRQsXhfAMlPXu5r32lEoJthzAtDAjCZM5zKZidjHeRhdZTHDtG\nUVQ0t4WnYIiKQRcdQ3F0DLqYOHE2Nzz8yo+fBxIllwUot0Z2NuGn0jC1DUZl0zlOprogC62naNmS\nMx/ZH/vY7SgUVtO4qPftpdvLz7CyZYjbtp9kvIMstDUVK5o24usvuf/reXzcPkqeFvsgstDWVCyt\naSWJutMm81L6Dp7wQpwqGc8gC62PUff2Hvi1bs3ph0YgtW1XdWC2q63HWi1Nxz3C/JAcusjJnH0a\nWWh9jOikOmxRp7Hsnaf5wRDE8eTGnH5gBOYOHSoKcDlNq0g/SacJY/muiR+13Rn7SuaaIFsgfIyT\nvftyIFvL402i+aVlEPv80/n4vWe4fdAdNHjmCZQ7d4r1bOmaNnj9L9w7YQSb2gTLZ2BrCPIheF+j\nuJiHHryLL9pUnuIW6o0sP53HSl0gR2ISyT6bwXPhJUxrGilHS/Qx5EPwNYmgIA5ExCNJJZUEMdRf\nzejGMYwGzuadZ07eSaZ3bHVt+injMeTpsQ9yssed7LqYb7VMWICaehFyUueaiCy0PkjBgHv5JMv6\nssUsYTU/rYzvIgttdeLcOWJmv0/daTZSi4aGsic0DsmKvcFS3GOZmoG8pr2WlJQQsOF3ktb+QErm\neW6WCni4diA78gw8tupbCgfeV+WtJ7v04PCeb2hZy3Iy6rK4xzI1D1lovYkkwdGj1Fn1NcmpB2lW\nmM0DkWZurRuJf4w/ZeFeGkbDosUf8/sdd1V5Uiev/0Bmr/2KebUsN6VQQIisaWskstB6kZj+fRhl\nzOSZFnHUbhAIVO2ZtKCBH51fmkjGgEFEHT5A+IljRBTmE1lcSFRJIbVMOu6JrfqMrqxpay6y0HqR\n7K9X8u2kp2lw6RiP2nB0qBcZzOKMVIyLXqFxRBDJEUH4hZeZIEJKf6pG5KeVNW1NRBZab5Kfj+rM\naaaeyuSn45f4oXcTq6dsbkuwvF61B5EJXta0NRFZaL1JrVo0U5v4/p7GZBSU4MlTcbKmrbnIWz7e\nRKHgZEwdABLDgzzqWighVZkJXsa3kYXWy5zu3pvdF/I83o4CRZWZ4GV8G1lovUxhn368nlbIpcIS\nj7Yja9qaiyy03iY8nB/mfE77qE50TFczdL+GFSezKdAZ3NqMvKatucjzp2tBixZcaDGdC8BOg4Fv\n/tpB3Z+/JyktnWbaHIZEQteEcAKqSB9iD7L1uOYiC+21xs8PU5eunOnSlTPANq2WpRs3kPjbaupl\nnqeNIZ/JKSHEhTiWb0fWtDUXWWirGyEh6O7uS9rdfUkDNly6RPa4ISxp45jQyh5RNRd5TVvdiY9n\nT1QCJrNjEURk3+Oaiyy0PsCJAUP45ZzGoXtkTVtzkYXWByi5404+1Ti2kpHP09ZcZKH1BdRqDtVt\nQLEDmlOOXFFzkYXWR0gfNpqlp+z3pJI1bc1FFlofwXT9DawwWD+OVx4J0OplTVsTkYXWV1AoONqk\nFX7QPaEAABniSURBVFlFOvuKAyH+sqZ1B2ZJYl7q5WrjFioLrQ9xbtQ4/nfCvimyrGndw6FsLV33\naZlw+yjes/PZexpZaH2JlBQ+6fcINx2H6YezySnWV1lU9ohyDb3JzNMHcugd25Ht36xBN2Ik3/nH\nYa4GGTdkofUxckeMYsey73j17c9pr2zGA/st79/KvsfOs+FCAZ1Szcx5fR4Z02aCnx8AR0Y8xnIL\nxsC0HC06o/eetSy0vkpKCmfefI8zYTEWL8ua1nHydQYe2JvL/e36s/frHzE3a1bhuq7nbczVVozt\nZTCZGXBKYuh+jdU41O5EFlofJ67IcnoQSZLQGqqH4cQX2HZZS6eMUL6a9zVZ456ynPdXoeDgHf35\nq1xKlhmpGo7M+D/WTpzBxMOOea05iyy0vkxuLg0ky9ZkhUJBiJ98HsReTDoDZ/reC/HxVstpho9i\nxiXxe6ZWx7LazTG2bUfJLd1YfPfDfHrS88YqWWh9GMXBA3SrYutW1rSO0aVuBPXX/WC7oJ8fe9rd\nxLn8Yh4/UczJ197691LO8FG8Vr8Tmy8UeLCnstD6NLE7/6J9tOX4yfKa1jGUCgXNcy6A0fZAlzH+\nOR7Yfp7NPfpDZMWA8+dffYPRhnhOa4o81VVZaH0ZfZ06bM+zHKZG3qd1nOHhRvx/X2+7YFQUOydO\nJeuJ8ZWvKRScmLuQAWeU5Ls5hFAZstD6MHlDH+J9reX5sewR5Th3JEVS//uv7Spbct9gUFYhPgEB\n7PnkcwYcKMRoNruxhwJZaH2cWCxrU1nTOo6fSkmTzHPgDkGrVYs/3pzNqH25rtd1FbLQ+jIFBaQY\ntRYvyZrWOe4P1qP680+31GVs3YZVYyYy86h7BVcWWh9GuWcPvUKrvl4oa1qHGZgcTr0VS91WX+Hd\n/Zhzcz++OWt5P90ZZKH1YeK2/0GnOMv5awFCZU3rMMF+ahplpIt4PW4ic/yzPB/RjL1ZlmdFjiIL\nrQ8Tm36ceCspM2VN6xz91EWoNm92a52n/282D+SEkam172ilNWSh9WFqF1btNlfTozGaJcljvr5j\nG0Ux7eNptBw5BOXBg+6pVKXiyKef0y9VT4mLhwtkPzdfxWgkoSgPiLJ4uSZHY7xYWMLdxwyYo2No\nVZDJqCiJLgmRVnP9OoKfSsnUFtFMMhbx9mtPsCIkgSMTX8bcsqVrFYeG8teHC+kxeigpIX6U+PlT\novKjRO1PiZ8/eqOJfrrLvNQ00mo1stD6KkeP0iW46q2JmqppU3OKGJgZxOHlKyE4mD3FxXy7djUp\n636kcVYGQ0IN9E+KIMgN3z1AreKVFtG8YNTy1quP801oXSG8LVo4X2lyMn+u28KfVezx7t3zD6ve\nmm61CltDk+TOBbmM+4icP48de7+haWyYxetFBiPvbT/B1G7NLF73Rf68VMgwfTwnPln07xnXCphM\nqLZto97Kr2iYkc6dqmKG1wslOsjfLe2XGE28fSzPPcJrDUkqc9ywKJ+y0PoojZ4ay9GozCqnhEUG\nI/N2neKZmxp5uWee4cdz+YwPb8Hpdz+o2hPpao4coe1LT/N360D8Ve4z35QYTUw5lMP8B58i/777\n3VYvIBw7kpIgIwOqkE/ZEOWj1CrItbmGK6wmgchcZUF6Ho+ldOX0/+bYL7AAzZtz4PX/MfWoe8+5\nBqpVvNc2jvuXfYx67x631o1SCefOWS/i3hZlvIIkWbUcQ83JBP96qoYXb76XC1OmO3W/uWVLvk5q\nTUZBsXs7BsxtHUX3l5+GzEz3VmzpAH45ZKG9Gkki+OcfiZn38bXuSdVkZNBGbf0Eia9ngpckiQkH\ncnjn3sfIevQJl+o6/eqbjD3h+v7o1aiUCla2DqP9uBGgc3/9VSELbRmSROi3X3PToLtY/O37LPh7\nJSmPjwZ91REPrxUBO/+itxX3RfBtTWsySzy8J4fPnprunjVjWBjb7nmINefcH1UiLMCPlUlmGj05\nxq1eVNaQhdZsJuKLxXS5706Wr5nHtpYBDKofSf+kcNb5naXt0AHun/64SK0d22gbb9lqXB5fXNPq\njCb6/ZPD1zNmU3xrd7fVqxnxCC/nBWMwuf+oXEpkEJ8oL5Dw+nS3122J/6712GgkauFntF33HVNj\nTPSoG26xWIHOwH0HC9l3c0+K4+tQVLsOxtg4iI6GqCgRuUDl3f3Q60Y/wK5E62u0YoOJubvSedaH\nrMf5OgN3H9SyZc4iqF/f7fWr9u/jxZnjmdki2u11A8w5kcfUfmPIGzzU9crEutaifPrm/MkV9Hpi\n5n1Eh41reDXOzE1tLAtrGWEBfqzrEMml7O3knjOQW6InQw/nTQoyDAouG81olX4Uq/0p9vOnRO1P\nsbr0Xz8/9BFR6GLjKIqvQ1GteKTYOCHs0dEQEmLT6GCJ+EINYDszvDc07Z+XCph8SUmQUkFPdTFD\nEoKpGx7kcD2XCkvok2Zm98IVEBfngZ6CqU1bvkxoyZOF6dS24rPtLE81iuDQ8k9Y2LAJhuuuc3v9\nZfx3NK0kUet/73Dd1l+ZWVtBBzuml643KaE1mMgt1pNTbPj/9s48vMkq++OfNEnb0CWl+0YtFAoF\nhAoFGWAUKbI5ioOKyyiK6PwcHMURl1EZF0QZBEefQQRFf4yIigVlRwQdEBCQHSq0pWVtS9O92Zql\nSd7549JRx260SZuk+TxPnrd9ktzctO/3nnPvPfccKs11FNv9KK6TUVInUeWQXRa4EpPy52L3x+wf\niDU8AnNUDMaYWCzRsULoAQE8+vQ03rm6aWthttlZfOAss4b3csl3K9aZePSshT2Zt1A543GxVZGf\nT8yXWSTlnKCXvpw7Qx2MTVQTqGjaEymoMXGrJoCTH34qBjJXotNxy32TWH9N06GCrcUhSUw8Us3X\nyz6H2NjWN9SEpe08orXZuG5SJt8NcY1r5GzsDgmtpY5qk7DuZWY7hXY/LtXJ+EOCilR105bCVGdn\nwd58XnRyRJTZZufpHC0bUwZx4W9zIKSRwc9qRbnrO7ptXkuyppAMm477oxWkRYYg+5l3cbDcwD2m\naAre+1fDUU4uIHzZUlYdWM2NjUyJ2orBauP6XBtHPl0Lga206D7RCkI/+4SPtn/IrUnqju6Ky3GV\npX3kRBXvzXsfeve+sjeWlqLesJak/bvpUV3K71RWQhV+PNO135UHTbQVSWLwHTexv68ShYs+t1Bb\nS6YuivwPPm7VFMgn2nokiUFTbuaHNLnL/lnugtlmZ/6efF4a5TxLe1Fby0jVAApfX9C2hhwOZMeO\nEpx/Gv2Uu1p3U7cRxZHDzP77k7zkokUpgJ0aA3eHDaD0xgkElZagKtUQUF5KgE6Hym5FVWdFZbNS\nXGPkzLqvfvlmn2h/QnH4EC8vmMULfTzDTW4trrC0Nx/TsumTja6fd7YTPR77I3sDCptMJNBWDml0\nGM1WwlVKwlX+hKv8f3UCaUKela2fbf7lG5sQrXebmwawDc5ghbo7WrNrctK6E87MXLFLo2fv+Mle\nI1iAs68t5LemRP6YXY3GYHbJZ2TEhnJ9ciRXx6hJCFU1eGRQF9B4yqCG6HSiBTj9yt/5y2lDR3fD\npTg7G+OqMitV90x1WntuQWgo+YuXsey9NQz1789tJ3Scqmj/+0IfcGVbZJ1StMTG8vWAES4t3eAO\nOHOf9vdqGcq9e5zWnlsRGUnh6wv48pNNjEoZx5jjBr4p0rZL6UpJkrCcOQd5eS1+T+cULVCbkIjF\nBSFt7kSwE2OPR8arSfhmq9Pac0tUKsr/8hTfrtnK5DHTGZ5r4//PVGN3uE68MpmMw0PDmPviw2Tc\ncyvBWZ81W0+o04o24sQxUrp6z/ysIZxpaVVKOQmlTZ/z9BrkcvR3/YH9n2/iTw+9zOBzCuacqqLW\nRVUIg/0VvJAWwYFesG7bMiZOGd/k6zutaKMMzR8i92RcUZ82xVjtlqeeXIn1+lEc/3gNL89ZyqDK\nSGZkV1PuhDSoDSGTychMVLN5QNPRep1WtNFG52V8d0dcUZ/2lmAH8h/2O7VNT0Hqk0be0uUsefdz\nhvj1ZsrxGvIrO2Yxs3OKVqulu935mQzcCVdY2sz4YOK+3uTUNj2OmBguzH+L1Ss3MfKqTMadMLCz\nuH0NQKcUrSz7BDcEe1fQSEM4+5RPWKA/CUXnndqmxxIURNlTf2Xb6q1Muu4+Rpy0sPJsNY52WHHu\nlKKNPLCPwRFXtqHtiThz9RjgcJkBvVbv1DY9Hrkc3X0PsDdrMw/dP5uMM3Lm5VS2uYpAU3RK0YYX\n5JIQ4rrQNXfBWZa2UFvL749rmZA6jlOrNzqlTa9DJsOSOYajK79g9uzFXFMWxuPZVVTWOn/hrlOK\nNtqg/cXxMG+lrZZWa67j4RNVjAgayLqPN1D+xFOgcO+8CYpDB1Ht+75D++C4+mpy31/BokWfkeFI\n4e7jNZyrdk7FPOiMmSskiSijFnD9IfiOprWW1mp3MDevhlURKeQvXgZxcU7umQs4c4a0uX9jqqmY\no7USq99ejtQjpWP7FB/P+YX/5Lxez8533iL94C5ejJL4TVzbzvF2PtGWlZEm9/7DAiL2+Mr+vZIk\nsexMDYuJ5MeX3m17wan2oKKCHnNmc+ulHF7tHUoXZTgWm50LT/wfP6zaAF3cYO0iJATNcy+y1WZj\n/4rl9N/yJX8OMnFHchh+rfD4mnePi4rg1Cmv2VRXHD/G6CDvXzmGK7O0W4t0DPvRwsxpszmxco37\nC7a2loQXn+O+h2/nh8CLvNk/nC6Xt7gCFHLW9lKSOmN6u6U1bREKBTUPPsye1Vt44K5nGJIvY2Fu\nFZbLi1YVtRYuamvZmFfSZDPNizY0FJ54AiorYfx4qKiATz8Fs7nZGEl3JGr/HgZGeb9rDC2b02ZX\nGBhzTM/d193LgTVbMGeOaYeetZ2+997OHt1hVgzsSmSXXye5iwsJZGlgOXGvv9IBvWsGmQzz2HEc\nmbOAZ8dOpccODU9u+5ENeRrW5pQQ18wiactEu22bSFI1Z47IJLhzpxjB4uLAZBKidjjg4EH3Gtka\nIKL4IhFdnFNFzd1pytKW6M3ccbyGG7uN4tusLdRMndYhGSRaizwiguSwpmPHb4gN4S8nvyNkw9p2\n6lUjaLWQnQ3Hj8M//wnr1sG990JpKQ6HxKXP1rAvOIZp6UnMHJZCRnzDNYfrafnqsUwGQ4eKHL/v\nvw8qFVy8KJ7r10907PnnRWLvESNAp4O334a6uvoKYG6BWITqHDRmaTcU6RhmS2bNv9ZR+uwL4O95\ng1hpal+Kdc1HtT2dGsaED94SHqKrsduhuFjc78uWwdGjMHky5OeL38PDITUVJk6ElSuFTh56CJKS\nyH7saT4637J7s21bPiqVeDz8sLDA27dDRAR8/LGobSKTwblzMHUq5ObCgw+CRgNr1gj3urq6TR9/\nxTgcxNR2HtE2ZGl1ljqes4Rz8e13Qe25Ce7KbriRf5e3LBR1dIgMysud9+EOhxCnVivEWFwsxHn2\nrLCgcrm4v9PS4J13ICNDWNhu3cQU09//VwnujTdPYqEjskUniZy/T6tQQI8eIuH0zJliZPnmG0hM\nhMcfB71eWOjDh2H6dNi7F558EgoKYO1a8bwz/8A/58IFBgV49xnaehqrBD89x8CpNxd7lCvcIAMH\nst3Qsu/gkGjd95UkYXQsFiE6gwFuuEF4kWPHinv9wgWIjhZeZq9esGMHxMTAY4+J9Knx8S3+uJOv\nLuDp3OYjztpvyyc4GNLTxc9PPimuI0aI0SosTIxMWi3s3g2bNokR6Ycf4NZb4fx5GD4cjEbo2bPV\n6TZVRw4zKtjDb9Yr4H8t7aoLWrbf8aC4yTwdpZKLwU3P/eqRZLLGRetwiOd27oTrr4dnn4XXX4fB\ng8X9N3EiHDsmrKlKBfPnCw/l5Enx/rlzxTUjo+3fKTmZ9f1+wxNVh5t8Wcfv06rVP7lp/fuL68SJ\nUFMDAwaIUS0oCI4cESk5VCox+o0cCVVVcM01QvD1Yo6IaPSjIg/tp28nWTmGX85pq01WXpZi0P7B\ne/I8XQqNxO4ob/ZctIQkXNfu3cVccsoU4fUtXAiDBglxLlok7qXu3cWuyBdfQEAA5OSIRubPF9eh\nQ136nYpfeJlHpkxs8jUdL9rGCAsTDxDiBbj5ZuGyWCxi5KuthZIS4bZkZwvXuq5OzBcSE4X7Eh8v\nMtfHxRF56gRd0t1gs72d+LmlnZZjJG/5ig7sjfPRDB3OyX0r6B+jJq/CQJJaxbrcEsb1jObV7/KY\nNbwnU1YfZEx6CrzxhphjFhWJHY877/xJlCoVfPmlaHTGDHHt5ZpyKs0SEMCBB2bAhn83+hLvy3ts\nNotAkKLLqVHOngV/f/yzVvFg7l6CHXaS1CrskkR8iAo/GUR1CSBQ4Yc6UEmIv4IgfznqAKVHxyfb\nHA7e3FvAsyNT+ehcDY/f/Ihzar22F5IkHsXFYtX1++9h4EARIzBpEsybB5Mnc9XUu/h8UjqLDpzl\nuZGpbMkv5c7+CeRXGhkcr0aSYMVFPU/M+bDjhNgaOlXVvMBA8ejbV/zety/Y7QxdspB3M/vgkMQN\nfUlvRin3o6DKgDpQwXGNjviQQPYVVdEzPIhdFyq5NqErhToTA2JCKTNaSY0IQm+x0U2tos4uER0U\ngNxPRoi/ApVSjtJP5lZCN1htVNRaeE2Z2PGCtVjE9OXSJbHTcPKkcEV37IAhQ8SOwoQJsGSJ2G14\n9VWYNUvsRPzpTyIGIDERkpKEhZw5E5KSGDhyMNcmqrk2USSf7xct4nqT1D/zqJqa03og3ifaBohY\nupg3Yh3IZDLkMpD7yel+Oalb4uWyjOmxwhW/MUUs0tzZLxG7JFGiN9NFKaegykhUkD/HNVrsDthf\nVEX/6FC2nSnj2sSurM/TMDo5kn1F1YzpEcXRkhpGJkWQU6FncFwYF7Qm+kaFUGqwkBIeRJnRQmJo\nIFqzjeigAGrr7HRVKbE5JIKUcmQy8Jf7tbp8SX0l+PtzTeSvWNTyNzour66bzWJ6YTCIQVCjEWI7\nf14E1eTkiF2Co0fFwLhvn1i82boVrrsOVq+Gm26C5cuFK7p8OUybBps3wx13wJ49MG6cmM7YbDBs\nmNhxeOYZsVC2YYOY1oy5HKE1bJi41g/GCQkAaMKigKZDbB3gVaL1Pvf4f6mt5aZ7fsemdNfvSUqS\nhM5iQymXUaK3oA5UcKbKSFxIINmlOlLCg9hfVMWAGDXfX6wkI74rO86XM7xbOFsLyhjdPYoNeSWM\nS4lmTc4lbkmNJevUJW5Pi2d9XgmT0+LZdFrDpN5xbC0o5ab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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ce74510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "from mpl_toolkits.basemap import Basemap\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "width = 2800000; lon_0 = -0.1; lat_0 = 51\n",
    "m = Basemap(width=width,height=width,projection='aeqd',\n",
    "            lat_0=lat_0,lon_0=lon_0)\n",
    "# fill background.\n",
    "m.drawmapboundary(fill_color='aqua')\n",
    "# draw coasts and fill continents.\n",
    "m.drawcoastlines(linewidth=0.5)\n",
    "m.fillcontinents(color='coral',lake_color='aqua')\n",
    "# 20 degree graticule.\n",
    "m.drawparallels(np.arange(-80,81,20))\n",
    "m.drawmeridians(np.arange(-180,180,20))\n",
    "# draw a black dot at the center.\n",
    "xpt, ypt = m(lon_0, lat_0)\n",
    "m.plot([xpt],[ypt],'ko')\n",
    "# draw the title.\n",
    "plt.title('Azimuthal Equidistant Projection')\n",
    "plt.show()"
   ]
  }
 ],
 "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": "2.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}