pico-tracker/sim/geofence/geofence_prefix.ipynb

{
 "metadata": {
  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Import other notebooks\n",
      "import io\n",
      "from IPython.nbformat import current\n",
      "\n",
      "def execute_notebook(nbfile):\n",
      "    with io.open(nbfile) as f:\n",
      "        nb = current.read(f, 'json')\n",
      "    \n",
      "    ip = get_ipython()\n",
      "    for cell in nb.worksheets[0].cells:\n",
      "        if cell.cell_type != 'code':\n",
      "            continue\n",
      "        ip.run_cell(cell.input)\n",
      "\n",
      "execute_notebook(\"country_excludes.ipynb\")\n",
      "execute_notebook(\"geofence_lib.ipynb\")\n",
      "execute_notebook(\"header_files.ipynb\")\n",
      "\n",
      "import matplotlib"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import json\n",
      "json_data = open(\"countries_world.json\").read()\n",
      "countries = json.loads(json_data)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def prepare_simple_grids(grids, tolerance=10*1000): # Approx 10km tolerance\n",
      "    simple = [simplify_points(points, tolerance) for points in grids]\n",
      "    return [s for s in simple if len(s) > 2]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "c_prefix = []\n",
      "\n",
      "for c in countries:\n",
      "    if (c['prefix']):\n",
      "        c_prefix.append(c)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print len(c_prefix)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "224\n"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for c in c_prefix:\n",
      "    c['prefix_grids'] = prepare_simple_grids(c['simple_grids'], tolerance=10*1000) # 10km tolerance\n",
      "    c['prefix_outlines'] = fix_antiprime_outlines(ea_grid_to_lonlat(c['prefix_grids']))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Swap!\n",
        "Swap!\n",
        "Swap!\n",
        "Swap!\n",
        "Swap!\n",
        "Swap!\n",
        "Swap!"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Swap!\n",
        "Swap!\n",
        "Swap!\n",
        "Swap!\n",
        "Swap!\n",
        "Swap!\n",
        "Swap!\n"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Filter out zero-length outlines\n",
      "for c in c_prefix:\n",
      "    \n",
      "    filtered_outlines = []\n",
      "    for outline in c['prefix_outlines']:\n",
      "        if (len(outline) > 0):\n",
      "            filtered_outlines.append(outline)\n",
      "            \n",
      "    c['prefix_outlines'] = filtered_outlines"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "n_outlines = 0\n",
      "n_points = 0\n",
      "\n",
      "for c in c_prefix:\n",
      "    n_outlines = n_outlines + len(c['prefix_outlines'])\n",
      "    \n",
      "    for outline in c['prefix_outlines']:\n",
      "        n_points = n_points + len(outline)\n",
      "        \n",
      "print \"Total number of points {}\".format(n_points)\n",
      "print \"Across {} outlines\".format(n_outlines)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Total number of points 12299\n",
        "Across 486 outlines\n"
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Draw map\n",
      "m = Basemap(projection='mill')\n",
      " \n",
      "m.fillcontinents(color='0.96')\n",
      "m.drawcoastlines()\n",
      "\n",
      "for c in c_prefix:\n",
      "    draw_outlines(m, c['prefix_outlines'], c['colour'])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<matplotlib.figure.Figure at 0x7f95f4074690>"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "write_prefixes(c_prefix)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 20
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 20
    }
   ],
   "metadata": {}
  }
 ]
}