Postcodes location.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Australian postcodes location\n",
    "\n",
    "Location of the postcodes of the \"Solar home electricity\" dataset,\n",
    "using [Google Maps Geocoding API](https://developers.google.com/maps/documentation/geocoding/start).\n",
    "\n",
    "The final output of this notebook is saved in `postcodes/postcodes.csv`.\n",
    "\n",
    "PH May 2017"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The post codes to analyze"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pcodes = [2008, 2010, 2018, 2021, 2025, 2026, 2029, 2031, 2034, 2037, 2039, 2041, 2044, 2046, 2047, 2048, 2066, 2074, 2076, 2077, 2079, 2081, 2082, 2084, 2085, 2086, 2087, 2088, 2092, 2093, 2096, 2099, 2100, 2111, 2119, 2120, 2126, 2134, 2135, 2137, 2154, 2159, 2162, 2190, 2196, 2198, 2200, 2203, 2204, 2205, 2207, 2208, 2209, 2211, 2216, 2218, 2219, 2220, 2224, 2227, 2228, 2229, 2230, 2231, 2233, 2250, 2251, 2259, 2260, 2261, 2262, 2263, 2264, 2265, 2278, 2280, 2281, 2282, 2283, 2284, 2285, 2286, 2289, 2290, 2291, 2292, 2293, 2294, 2295, 2296, 2300, 2303, 2305, 2315, 2320, 2321, 2324, 2325, 2326, 2330]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1) API test with one postcode"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using [requests](http://docs.python-requests.org/en/master/) package, \"HTTP for Humans\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import requests"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To use  the Geocoding API, one needs to [request a key](https://developers.google.com/maps/documentation/geocoding/get-api-key). I've put mine in `postcodes/GMaps_geocoding_key.txt` (kept out of the git repo with `.gitignore` file)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "apikey_file = 'postcodes/GMaps_geocoding_key.txt'\n",
    "def apikey():\n",
    "    'returns Geocoding API key as a string'\n",
    "    with open(apikey_file) as f:\n",
    "        return f.readline().strip()\n",
    "#apikey()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Constant parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "geo_url = 'https://maps.googleapis.com/maps/api/geocode/json'\n",
    "\n",
    "params = {\n",
    "    'key': apikey(), \n",
    "    'new_forward_geocoder': 'true'   \n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Forge the request with test postcode:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "params['address'] = '2007, NSW, Australia'\n",
    "r = requests.get(geo_url, params=params)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check response:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Response [200]>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "200"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.status_code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.ok"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "   \"results\" : [\n",
      "      {\n",
      "         \"address_components\" : [\n",
      "            {\n",
      "               \"long_name\" : \"2007\",\n",
      "               \"short_name\" : \"2007\",\n",
      "               \"types\" : [ \"postal_code\" ]\n",
      "            },\n",
      "            {\n",
      "               \"long_name\" : \"Ultimo\",\n",
      "               \"short_name\" : \"Ultimo\",\n",
      "               \"types\" : [ \"locality\", \"political\" ]\n",
      "            },\n",
      "            {\n",
      "               \"long_name\" : \"Council of the City of Sydney\",\n",
      "               \"short_name\" : \"Sydney\",\n",
      "               \"types\" : [ \"administrative_area_level_2\", \"political\" ]\n",
      "            },\n",
      "            {\n",
      "               \"long_name\" : \"New South Wales\",\n",
      "               \"short_name\" : \"NSW\",\n",
      "               \"types\" : [ \"administrative_area_level_1\", \"political\" ]\n",
      "            },\n",
      "            {\n",
      "               \"long_name\" : \"Australia\",\n",
      "               \"short_name\" : \"AU\",\n",
      "               \"types\" : [ \"country\", \"political\" ]\n",
      "            }\n",
      "         ],\n",
      "         \"formatted_address\" : \"Ultimo NSW 2007, Australia\",\n",
      "         \"geometry\" : {\n",
      "            \"bounds\" : {\n",
      "               \"northeast\" : {\n",
      "                  \"lat\" : -33.8745248,\n",
      "                  \"lng\" : 151.2029088\n",
      "               },\n",
      "               \"southwest\" : {\n",
      "                  \"lat\" : -33.8844359,\n",
      "                  \"lng\" : 151.1939931\n",
      "               }\n",
      "            },\n",
      "            \"location\" : {\n",
      "               \"lat\" : -33.8823187,\n",
      "               \"lng\" : 151.197131\n",
      "            },\n",
      "            \"location_type\" : \"APPROXIMATE\",\n",
      "            \"viewport\" : {\n",
      "               \"northeast\" : {\n",
      "                  \"lat\" : -33.8745248,\n",
      "                  \"lng\" : 151.2029088\n",
      "               },\n",
      "               \"southwest\" : {\n",
      "                  \"lat\" : -33.8844359,\n",
      "                  \"lng\" : 151.1939931\n",
      "               }\n",
      "            }\n",
      "         },\n",
      "         \"place_id\" : \"ChIJLV6IoE6uEmsRUIe6P2t9ARw\",\n",
      "         \"types\" : [ \"postal_code\" ]\n",
      "      }\n",
      "   ],\n",
      "   \"status\" : \"OK\"\n",
      "}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(r.text)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Parse response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'results': [{'address_components': [{'long_name': '2007',\n",
       "     'short_name': '2007',\n",
       "     'types': ['postal_code']},\n",
       "    {'long_name': 'Ultimo',\n",
       "     'short_name': 'Ultimo',\n",
       "     'types': ['locality', 'political']},\n",
       "    {'long_name': 'Council of the City of Sydney',\n",
       "     'short_name': 'Sydney',\n",
       "     'types': ['administrative_area_level_2', 'political']},\n",
       "    {'long_name': 'New South Wales',\n",
       "     'short_name': 'NSW',\n",
       "     'types': ['administrative_area_level_1', 'political']},\n",
       "    {'long_name': 'Australia',\n",
       "     'short_name': 'AU',\n",
       "     'types': ['country', 'political']}],\n",
       "   'formatted_address': 'Ultimo NSW 2007, Australia',\n",
       "   'geometry': {'bounds': {'northeast': {'lat': -33.8745248,\n",
       "      'lng': 151.2029088},\n",
       "     'southwest': {'lat': -33.8844359, 'lng': 151.1939931}},\n",
       "    'location': {'lat': -33.8823187, 'lng': 151.197131},\n",
       "    'location_type': 'APPROXIMATE',\n",
       "    'viewport': {'northeast': {'lat': -33.8745248, 'lng': 151.2029088},\n",
       "     'southwest': {'lat': -33.8844359, 'lng': 151.1939931}}},\n",
       "   'place_id': 'ChIJLV6IoE6uEmsRUIe6P2t9ARw',\n",
       "   'types': ['postal_code']}],\n",
       " 'status': 'OK'}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'OK'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()['status']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(r.json()['results'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'northeast': {'lat': -33.8745248, 'lng': 151.2029088},\n",
       " 'southwest': {'lat': -33.8844359, 'lng': 151.1939931}}"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()['results'][0]['geometry']['bounds']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2) Get  all postcodes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Function for one postcode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Geocoding 2007, NSW, Australia...\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'bounds': {'northeast': {'lat': -33.8745248, 'lng': 151.2029088},\n",
       "  'southwest': {'lat': -33.8844359, 'lng': 151.1939931}},\n",
       " 'geoapi status': 'OK',\n",
       " 'http_code': 200,\n",
       " 'json': {'results': [{'address_components': [{'long_name': '2007',\n",
       "      'short_name': '2007',\n",
       "      'types': ['postal_code']},\n",
       "     {'long_name': 'Ultimo',\n",
       "      'short_name': 'Ultimo',\n",
       "      'types': ['locality', 'political']},\n",
       "     {'long_name': 'Council of the City of Sydney',\n",
       "      'short_name': 'Sydney',\n",
       "      'types': ['administrative_area_level_2', 'political']},\n",
       "     {'long_name': 'New South Wales',\n",
       "      'short_name': 'NSW',\n",
       "      'types': ['administrative_area_level_1', 'political']},\n",
       "     {'long_name': 'Australia',\n",
       "      'short_name': 'AU',\n",
       "      'types': ['country', 'political']}],\n",
       "    'formatted_address': 'Ultimo NSW 2007, Australia',\n",
       "    'geometry': {'bounds': {'northeast': {'lat': -33.8745248,\n",
       "       'lng': 151.2029088},\n",
       "      'southwest': {'lat': -33.8844359, 'lng': 151.1939931}},\n",
       "     'location': {'lat': -33.8823187, 'lng': 151.197131},\n",
       "     'location_type': 'APPROXIMATE',\n",
       "     'viewport': {'northeast': {'lat': -33.8745248, 'lng': 151.2029088},\n",
       "      'southwest': {'lat': -33.8844359, 'lng': 151.1939931}}},\n",
       "    'place_id': 'ChIJLV6IoE6uEmsRUIe6P2t9ARw',\n",
       "    'types': ['postal_code']}],\n",
       "  'status': 'OK'},\n",
       " 'location': (-33.8823187, 151.197131),\n",
       " 'nres': 1}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def geo_postcode(c):\n",
    "    '''Geocodes postcode `c` in Australia NSW.\n",
    "    \n",
    "    Returns a dict with 'location', 'bounds', and also the complete json response\n",
    "    '''\n",
    "    addr = '{:d}, NSW, Australia'.format(c)\n",
    "    print('Geocoding {}...'.format(addr))\n",
    "    params = {\n",
    "        'key': apikey(), \n",
    "        'new_forward_geocoder': 'true',\n",
    "        'address': addr\n",
    "    }\n",
    "    r = requests.get(geo_url, params=params)\n",
    "    \n",
    "    out = {\n",
    "        'http_code': r.status_code\n",
    "    }\n",
    "    \n",
    "    if not r.ok:\n",
    "        print('request for postcode {:d} not successful: {}'.format(c, str(r)))\n",
    "        return out\n",
    "    \n",
    "    try:\n",
    "        json = r.json()\n",
    "        out['json'] = json\n",
    "    except Error:\n",
    "        print('unable to decode json response for postcode {:d}: {}'.format(c, r.text))\n",
    "        return out\n",
    "    \n",
    "    out['geoapi status'] = json['status']\n",
    "    \n",
    "    nres = len(json['results'])\n",
    "    out['nres'] = nres\n",
    "    \n",
    "    if nres ==  0:\n",
    "        print('warning: zero result for postcode {:d}'.format(c))\n",
    "    else:\n",
    "        if nres>1:\n",
    "            print('warning: more than one result for postcode {:d}'.format(c))\n",
    "        geom = json['results'][0]['geometry']\n",
    "        bounds = geom ['bounds']\n",
    "        out['bounds'] = bounds\n",
    "        out['location'] = (geom['location']['lat'], geom['location']['lng'])\n",
    "    \n",
    "    return out\n",
    "\n",
    "geo_postcode(2007)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get all postcodes\n",
    "\n",
    "with a bit of throttling to respect the API [usage limits](https://developers.google.com/maps/documentation/geocoding/usage-limits): 50 calls/s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "loc = {}\n",
    "\n",
    "#for c in pcodes:\n",
    "#    loc[c] = geo_postcode(c)\n",
    "#    time.sleep(1/50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Save the data for offline usage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#with open('postcodes.json', 'w') as f:\n",
    "#    json.dump(loc, f, indent=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Reload saved data\n",
    "\n",
    "Caveat about reloading json file: the keys (postcodes) which were ints are now strings. In fact json only supports string keys, cf. [Stack Overflow](http://stackoverflow.com/questions/1450957/pythons-json-module-converts-int-dictionary-keys-to-strings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "with open('postcodes/postcodes.json') as f:\n",
    "    loc = json.load(f)\n",
    "\n",
    "loc_2 = {}\n",
    "for k in loc:\n",
    "    loc_2[int(k)] = loc[k]\n",
    "\n",
    "loc = loc_2 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Example output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'bounds': {'northeast': {'lat': -32.1389092, 'lng': 151.4889105},\n",
       "  'southwest': {'lat': -33.162648, 'lng': 150.3050814}},\n",
       " 'geoapi status': 'OK',\n",
       " 'http_code': 200,\n",
       " 'json': {'results': [{'address_components': [{'long_name': '2330',\n",
       "      'short_name': '2330',\n",
       "      'types': ['postal_code']},\n",
       "     {'long_name': 'New South Wales',\n",
       "      'short_name': 'NSW',\n",
       "      'types': ['administrative_area_level_1', 'political']},\n",
       "     {'long_name': 'Australia',\n",
       "      'short_name': 'AU',\n",
       "      'types': ['country', 'political']}],\n",
       "    'formatted_address': 'New South Wales 2330, Australia',\n",
       "    'geometry': {'bounds': {'northeast': {'lat': -32.1389092,\n",
       "       'lng': 151.4889105},\n",
       "      'southwest': {'lat': -33.162648, 'lng': 150.3050814}},\n",
       "     'location': {'lat': -32.7319195, 'lng': 150.8609358},\n",
       "     'location_type': 'APPROXIMATE',\n",
       "     'viewport': {'northeast': {'lat': -32.1389092, 'lng': 151.4889105},\n",
       "      'southwest': {'lat': -33.162648, 'lng': 150.3050814}}},\n",
       "    'place_id': 'ChIJY02e3iWVDGsRQDjTzLcJBhw',\n",
       "    'types': ['postal_code']}],\n",
       "  'status': 'OK'},\n",
       " 'location': [-32.7319195, 150.8609358],\n",
       " 'nres': 1}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loc[2330]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Quality check on all postcodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for c in pcodes:\n",
    "    assert loc[c]['geoapi status'] == 'OK'\n",
    "    assert loc[c]['nres'] == 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3) Analyze locations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Collect locations in a (postcode × lat_lng) array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ -33.8878872,  151.1964025],\n",
       "       [ -33.8825595,  151.2131584],\n",
       "       [ -33.9219899,  151.20733  ],\n",
       "       [ -33.8921203,  151.2306446],\n",
       "       [ -33.8865002,  151.2437606],\n",
       "       [ -33.8922511,  151.2714535],\n",
       "       [ -33.8754209,  151.265623 ],\n",
       "       [ -33.9122447,  151.2393885],\n",
       "       [ -33.9236193,  151.2539627],\n",
       "       [ -33.8802599,  151.1840188],\n",
       "       [ -33.8661553,  151.1738213],\n",
       "       [ -33.8583166,  151.1781916],\n",
       "       [ -33.921824 ,  151.1665377],\n",
       "       [ -33.8566687,  151.1315813],\n",
       "       [ -33.8523805,  151.1548847],\n",
       "       [ -33.8920561,  151.165081 ],\n",
       "       [ -33.8126017,  151.1694511],\n",
       "       [ -33.6867425,  151.1577979],\n",
       "       [ -33.7085861,  151.1228434],\n",
       "       [ -33.6924088,  151.0995447],\n",
       "       [ -33.6709087,  151.125756 ],\n",
       "       [ -33.5769126,  151.1694511],\n",
       "       [ -33.5988104,  151.134494 ],\n",
       "       [ -33.6363689,  151.2219013],\n",
       "       [ -33.7293236,  151.2044159],\n",
       "       [ -33.7473073,  151.2248157],\n",
       "       [ -33.773259 ,  151.2160726],\n",
       "       [ -33.8303776,  151.2393885],\n",
       "       [ -33.7927181,  151.2423032],\n",
       "       [ -33.8055737,  151.2627078],\n",
       "       [ -33.7738038,  151.2889461],\n",
       "       [ -33.7500081,  151.2860306],\n",
       "       [ -33.7645979,  151.2627078],\n",
       "       [ -33.8296098,  151.125756 ],\n",
       "       [ -33.7551665,  151.0646032],\n",
       "       [ -33.7274311,  151.0762495],\n",
       "       [ -33.7287467,  151.0413133],\n",
       "       [ -33.8799121,  151.1024569],\n",
       "       [ -33.8808808,  151.0762495],\n",
       "       [ -33.8543494,  151.1024569],\n",
       "       [ -33.7270691,  150.9947439],\n",
       "       [ -33.5876386,  151.0704263],\n",
       "       [ -33.883427 ,  151.006385 ],\n",
       "       [ -33.90558  ,  151.0529578],\n",
       "       [ -33.9293131,  151.0558691],\n",
       "       [ -33.9183098,  150.9831038],\n",
       "       [ -33.9200458,  151.0296696],\n",
       "       [ -33.9041707,  151.1374068],\n",
       "       [ -33.9086291,  151.1548847],\n",
       "       [ -33.9378099,  151.1490585],\n",
       "       [ -33.9541086,  151.1228434],\n",
       "       [ -33.9379361,  151.0995447],\n",
       "       [ -33.9454921,  151.0791612],\n",
       "       [ -33.9608964,  151.0296696],\n",
       "       [ -33.9531396,  151.1490585],\n",
       "       [ -33.9712426,  151.1199309],\n",
       "       [ -33.9946489,  151.1315813],\n",
       "       [ -33.9583688,  151.0995447],\n",
       "       [ -34.0094315,  151.0995447],\n",
       "       [ -34.043981 ,  151.0849848],\n",
       "       [ -34.03825  ,  151.1024569],\n",
       "       [ -34.0460194,  151.1228434],\n",
       "       [ -34.0621862,  151.1461455],\n",
       "       [ -34.0194134,  151.1985879],\n",
       "       [ -34.1193032,  151.0704263],\n",
       "       [ -33.3502247,  151.1869325],\n",
       "       [ -33.4721323,  151.38519  ],\n",
       "       [ -33.2059456,  151.3501856],\n",
       "       [ -33.4287117,  151.4377107],\n",
       "       [ -33.3603327,  151.4318742],\n",
       "       [ -33.2075583,  151.5428026],\n",
       "       [ -33.2504355,  151.5077645],\n",
       "       [ -33.1186851,  151.4552213],\n",
       "       [ -33.0641471,  151.4435474],\n",
       "       [ -32.9351373,  151.548643 ],\n",
       "       [ -33.0223311,  151.6713386],\n",
       "       [ -33.1170985,  151.6362736],\n",
       "       [ -32.9648241,  151.6479611],\n",
       "       [ -33.050132 ,  151.5953736],\n",
       "       [ -32.9524472,  151.6187438],\n",
       "       [ -32.9110348,  151.6187438],\n",
       "       [ -32.8995067,  151.5720067],\n",
       "       [ -32.9481404,  151.7064109],\n",
       "       [ -32.9754667,  151.712257 ],\n",
       "       [ -32.9497012,  151.744414 ],\n",
       "       [ -32.9225853,  151.7341816],\n",
       "       [ -32.9153665,  151.7575709],\n",
       "       [ -32.9123334,  151.7663428],\n",
       "       [ -32.8674273,  151.7999723],\n",
       "       [ -32.9125002,  151.7458759],\n",
       "       [ -32.9272155,  151.7795013],\n",
       "       [ -32.9252332,  151.7502614],\n",
       "       [ -32.9274242,  151.7064109],\n",
       "       [ -32.7344109,  152.151274 ],\n",
       "       [ -32.7147232,  151.5369624],\n",
       "       [ -32.6916544,  151.4435474],\n",
       "       [ -32.6400424,  151.9111422],\n",
       "       [ -32.9380528,  151.1869325],\n",
       "       [ -32.787791 ,  151.4552213],\n",
       "       [ -32.7319195,  150.8609358]])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "location = [loc[c]['location'] for c in pcodes]\n",
    "location = np.array(location)\n",
    "location"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mapping the locations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import cartopy.crs as ccrs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Select map projection\n",
    "\n",
    "http://scitools.org.uk/cartopy/docs/latest/crs/projections.html"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plate carrée/equirectangular:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Lr1Ihp6am5nszbt++vUxu2JcqZLFYzHfv3tHX15dnz57lkCFDqKGhQW1tbSooKFBFRYUG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\nqNy2zF3LNgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f50ea3521d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plt.axes(projection=ccrs.PlateCarree(central_longitude=151))\n",
    "ax.gridlines()\n",
    "ax.coastlines();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mercator. Nice property: conformal (preserve the shape of small objects)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JTZs2RUZGhsSTSr969Qp16tRBVFQUOnfujObNm+P27dv45ZdfcPTo0Sqf4pUk8vLyuHv3\nLtzd3eHl5YWYmBjs2rXrS8v65vDy8kJ6ejr69u2LnJwcGBsb48CBA+jfvz92795d5DU1a9aEgoIC\nNDQ00L9/f0ybNg09evQAADx79gza2tqYNWtWAa9j2bJlCAsLQ4cOHYRjXbt2xdy5c3Hnzh0cOnSo\n2PqqPZVhoViEZ/Lu3Tt27tyZ6urq3L59e5ks6eesckpKCs3NzWlsbMxVq1aVqeyK8LGu58+f09XV\nlaqqqrxx44ZE6xk8eDD/+usvJiYmcty4cVRQUKCXlxcDAgJ45cqVz2qrTlRHXXfu3KG2tjZPnTrF\nyMhIGhoaFvh87dq1PHfuXKHrkpOTGRISwh49enDYsGGsW7cuR48ezS1btrB+/fqcM2dOIa943bp1\nBMBJkyYJxx4+fEgZGRmePXu2WI1Sz+QjgoKCcP/+fSQkJOCHH36QaNkqKio4efIkZs6cWalp6Yri\n+vXr8PHxQdu2beHg4ID+/ftj7969Eik7ISEBY8aMwYkTJ9ClSxdhT5WcnBysXLkSFy9ehKurKzZv\n3iyR+v5XmT17NubPn4+cnBz07dsXjRs3xrx585CUlITbt29jwYIFcHV1Fcb7MjMzsXfvXtja2sLF\nxQUvXrzA3bt3MWjQIBgaGmLGjBnIzs7Gs2fPsHXrVvj5+WH06NHYuXMnjIyMoK2tXWD7ClNTU4wZ\nM6ZSs6BVBVVmTEaOHAlzc3MsX768Uso3NjbGmDFjoKmpWSnlf0pycjIePXoEd3d3REVFwcfHB4qK\nijhw4MBn0+eVxO7du9G/f390794d7du3h6KiIry9vQskI46Li8OzZ8+wadMmhIaGYt68eTh37ly5\n6svKysKCBQvQpk0b9O7dGwcOHJD4IHl1JikpCcePH4eMjAwePXqEsWPH4sqVK4iPj4e5uTnOnDkD\nJSUlZGdnY86cOYiOjsa///4LNzc3/P7777hy5QrEYjEmTJgghMKbmJhg2rRpcHJywtGjR3Ht2jVY\nWFjAz88P7u7u2L9/P9q0aVNAx7Jly3Dp0iV0794dTk5OsLCwgLGxMTp06ICLFy9+odYpI5Xh7rCY\nAdiDBw+yV69eZXbLqptr/ODBA5qZmTEwMJA5OTkMDg6mqakpe/bsyf/++69cZR47doxDhgyhqqoq\n//nnH/7222/866+/SnWtr68vBw8eXOBYadssMDCQLVu25JEjR7h9+3ZaWlqyS5cujIqKKlU8S1mp\nbs9SJBJx6tSpdHV15dGjR7lo0SJOnDiR5IfFnvr6+tTU1GSLFi2ooaHBIUOGMDQ0lKampty/fz8j\nIyNpYWHB+/fvc/PmzVRVVeWOHTuoq6vLXbt28dq1axw3bhwdHR3ZsmVL7tmzp1gtL1684Pbt23nh\nwgU+ePCAjx49YlBQELW1tUtccFpWUEndnCo1JoGBgWzdunWZb746fQHDw8Opq6vLgIAAnj17lj/8\n8AMbNGjAY8eOlau81NRU+vv7U19fn+vXr+eDBw/KXMa8efOEH0A+pW2zKVOmcMmSJcLf2dnZ7NGj\nB+3t7ammpsaRI0fy+vXrZdZUHNXpWX5KaGgoraysePLkScbHx/PKlSucPHkyzczM6O/vz82bN9PN\nzY1xcXHs0qULbW1tGRwczBYtWlBLS4vq6uqUk5NjdnY2t27dyt69e9PU1JRz587lv//+y6NHj1JL\nS4vx8fFl0hUeHs6VK1dK7D6/CWNiZWXFESNGlPnmq9MX0M7Ojlu2bKFIJGJAQADd3NyYnp5e7vK+\n++47Ojo68u7du2W+ViwW08fHh/r6+oyOji7wWWnbbMeOHTQzM+O5c+e4ePFi/vnnnzQ1NaW7uzv1\n9PTYsWNHysrKMjExscz6iqI6PctPCQ0N5U8//UR5eXnKyMgQAJ2dnblq1SoOHDiQenp63LJlC0ky\nNjaWKioqtLW1ZevWrenh4cHOnTtTX1+fp0+fLraOdu3a8cSJE2XSlZubSx8fnyIHgctDZRmTKk2O\nNHz4cNy6dasqq5QoOTk5SEtLg6mpKebNmwcjIyMEBgZCUVGxXOWFh4fjyZMnePjwYaEM5J+DJEaN\nGoXw8HBcunQJDRo0KJcGd3d3/Pvvvxg4cCA8PDwAAP369cOiRYvg6+uL7du3Y9myZV/dGqfSkJqa\niitXriAyMhKNGzeGnJwcNmzYAH9/fyxduhT+/v5ITExESEgIBg4ciNmzZ8PW1hbAhzG6sLAwvHz5\nEvr6+nBzc8OjR4+wcOFCDBkyBDY2NnB2dhZCFiIjI6GpqYlHjx4VWL9TGuTl5dGgQQOMHDkS0dHR\npd5itMqpDAvFIjyTXbt2EQC7du1aZktaXd5m06ZNY8+ePXnr1i3q6+szJCSkXOUkJyczKSmJISEh\nrFu3LnNzc8tcRlhYGAFw27ZtPHXqVKHPy9JmYrGYOTk5zMrKYlZWVpm1lIXq8ixJcubMmaxbty6H\nDx9OGxsb/vXXX6xXrx7DwsKEsY49e/YUG2SZmZkp/D8iIoLdu3dnt27d6Ovry8DAQE6bNo0TJkyg\nt7c3T5w4QT8/v1LlPC6K0NBQGhoaMjIyslzXfwy+9m5OWloatbW1i4zu+xzV4QuYnZ1NALx69So9\nPT25ePHicumaPHky69SpQ1VVVaqrq7Nbt26FsmqVBpFIxIMHD9La2poA2KxZM1pbW9Pd3Z2nT59m\naGgoDx48yI4dO/K3335jQEBAiZHHFy5coIqKChs2bMjY2Ngy6ykt1eFZ5nPr1i3WrVtX+Pvs2bM8\nfPgw9fX1mZCQUOj8Xbt2cdKkSUxOTmZcXBw1NDTo5OTEevXq0cbGhnPmzOG+ffuE8a+FCxfSxMSE\na9as4S+//MKePXuyQYMGdHZ25sGDB8ukNTQ0lBMmTCgwvlVeKsuYVMnU8MSJE6GsrAwjIyOYm5tX\nRZUSJzIyEgCgqKiIffv2YeTIkcWem59guCj27NmD8PBwJCcn4+3btzh+/DiUlZXLrEdWVhZ9+vTB\nvXv3UL9+fbRo0QJbt25Fo0aNMHHiRLx79w4nTpxAzZo1kZmZCV9fX8yfP7/Y8oKCgvD+/Xs8fvwY\nK1euLLOer5EnT54U6B7KyMggKysLb9++Rd++ffHy5UuIxWJkZWXB29sbAwcOxPr167Fv3z6sW7cO\nXbp0wciRIxEXF4eYmBgsWrQItra2yM3NRXh4OK5evYr4+HiMHz8eKSkpuHLlCvLy8vDLL79g5MiR\nOH/+fJn09u3bt8zJ0auUyrBQ/Mgzyc7O5s8//8y6deuWeU1OPtXhbdasWTNu2bKFs2fP5pgxY0gW\nrSs2NpYaGhpUU1Njz549OWvWrAKDzg0bNuTDhw8lqu3jdk1NTeW0adO4ceNGNmnSRBgwfPXqFZWV\nlYvd+uPPP/+klZUVu3XrxrVr1/LVq1cS1ZhPdXiW+QwaNIj+/v7C33v37mWNGjXYunVrYa1N165d\nWatWLQJgvXr1KCMjw2vXrgmfnz9/nhoaGlRUVOSDBw9Yv359Llu2jMrKynz9+rVwHkn6+PhQVVWV\ntWvXJgD+9NNPpdYaGhrKvLw8GhgYlMu7/xh8rd2cNWvWCA1anj1syC//BUxNTWWdOnWYmJhIVVVV\nPn78uFhdmzZt4qBBg5iZmUlNTU06OjoSAOfOncuePXsSAI8fP17pmovSZm1tzcuXLxc6Hh0dTXV1\ndR4/fpxLly5lt27dqKqqykaNGnHkyJGMiYmpVF1fgry8PGpqavL58+ckP7TBypUr+d1331EkEnHF\nihW8c+cOW7Vqxf79+xMAd+/ezZo1a/Lu3bsEICT6njlzJlVUVOjk5MSFCxfy4sWLbNq0KUnS39+f\na9euJflhoau6ujpVVVVpbW3N9u3bl7qLm99u3bt357Zt2yp075VlTGQ+lC15ZGRkGBoairy8PMTE\nxCAtLQ1NmzYtV1lpaWnl6gpIipcvXyIjIwOmpqa4desW7OzsICsrW6SumJgYqKioQE1NDREREcJx\nNTU1aGpqIiYmBgoKCmjcuHGlav5UG0ncvHkT9vb2ePv2LRQUFKCgoABZWVnk5eUhOjoaDg4OBWYK\nMjMz8fr1a+Tl5aFhw4YS0ZWamoratWt/8cWXmZmZiI6Oho2NDeTl5REbGwslJSXUrl270DMViUS4\nffs2jI2NkZiYCGNjY2RlZSEuLg7m5uZ49+4d3rx5A5FIBDMzM4hEIiQmJsLMzKxAOdnZ2YiLi4Oe\nnh6UlJTw9OlT5OXlwdjY+LPtkZaWBkVFRdy7dw/W1tYVymnTvn17kJT8lFBlWKj/M1AUi8UEwHv3\n7lFXV7dQLERpqcjbLC0tjcnJyTx58mS5R8LXrl0rZG+zs7Pjjh07itR1+PBhmpiYMD09nQEBAQRA\nS0tLAuDevXtJki9fvuSFCxfKfT+lpag2c3d358KFC6mrq0ttbW0aGBhQW1ub6urqNDAwEDyuj0lN\nTWXDhg35+++/UywWUywW8+3btxSJRGXWdPjwYa5fv54qKio8f/58ma599eoVhwwZInTbKkpeXh5n\nz55NAwMDHjx4kPr6+vTx8aGGhgYdHR0Ldcm9vb2ZkpJCDw8Pbtq0iSS5atUqmpqaUl1dnXXq1OHs\n2bPZpEkT3rhxg3Xq1PlsIGNmZiZlZWUpIyPDoKCgEs8NDQ1lQkICtbW1WbNmTf7777/lvnd8rd0c\nALSwsGC7du2EH1RZKa8xef36NfX09KikpMTmzZtTS0uLK1euLPMPQSwW859//qGRkRF/+OEHAuCT\nJ08K6XJ2dhbuMT4+Xuhnz5w5s9zbfJaXotosJiaGRkZGbNSoEVNTU5mZmcn379/zyZMnJZb18uVL\n2tnZsVGjRlRVVaWysjI1NDS4bt26Mmlq2rQp/f39KSMjwyNHjpTqmpSUFI4aNYoGBgYcNWoUAVBR\nUZGjRo1iampqhdNyTp06lTo6OvT39+e+ffuEcZKwsDCmpaUVOv+vv/5imzZtmJycTJFIxCNHjtDX\n15e9evWiWCxm48aNGRwcTAAcOXLkZ+u/efMmg4ODqauryw0bNhS7hCH/eUZERAjDBuWNTP4qjcnh\nw4eFGwdQZfvmJiQkcNasWXR2di6w1Ds/NiPfsygLeXl59PPz4+TJk+nm5sYXL14U0uXm5sbAwEDh\nb21tbQKQWPRoWSgpb25ERESZy0tNTeW1a9eEOInIyEjWqlWryBgZkUjEixcv8v379wWOh4eH8/Dh\nw6VK7kR+8GR0dHT4008/8fLlyxSLxbx06ZIQ9augoEA9PT3OmDGDO3bs4LFjx0r0ft+/f8+AgADa\n29vTycmJb9684fXr14V9gE+ePEljY+MC39lr164VKCMvL4/jx4+npaUlHzx4wNjYWK5YsYIDBgwg\nSf79998cNGgQJ0+eTBMTE86ZM6fAmFN2dnaRHktYWBjbtGlT5GZe5P9/nr/99htdXFxYr149btiw\noVTt+ClfpTGJjIzk77//XmBEuzyUxZjkZySbOHEiV65cWeAL/d9//1FJSYmWlpbF5gEpC5s3b6a7\nuzu3bdvG7Oxs/vbbb5w+fbrwOYACWbaqksoe6MzJySEAHjt2jEuWLKG3tzevXr3K06dP89ixY1RR\nUaGSkhKtra3ZsGFDjhkzhjExMaXWlZGRQS0trRK7hDk5Obx79y4XLFjArl27snXr1tTU1OTgwYN5\n6tQpoasSHBzMwMBA1q1blw0bNiQA6uvrC9/Lpk2bcvbs2Tx79iwHDhxIVVVVLl26lH5+fkV6Pjk5\nORw4cCB79OjBFi1asHbt2lRVVeWdO3c4ffp0tmnThunp6bx8+TIHDhxIOTk5KioqslmzZrSzsyMA\nDhw4sFDZaWlp1NHR4aNHjwrVmd9u06ZN45IlS7hhwwbKysqWqi0/5as0Junp6RwwYADbtWvHlJSU\nct04WfofxpMnT6irq1tikpm1a9dy/vz51NTU5LBhw7h3795ST1l/fF7+eokxY8awQ4cOtLGx4Y8/\n/ih0gcgPD83a2rrSpllLoipmTRYuXEgHBwdOnz6do0aNoq2tLU1MTNiiRQtaWloyPT2dN2/eZGRk\nJOfMmUMNDY0SV83mk5SURF9fXzo6OpZZ05s3b7hq1SpaWVlx0KBBnDFjBk1NTdm5c2ceOnSIGRkZ\njImJ4Z05T3esAAAgAElEQVQ7d2hlZUUdHR0uWrSI3bp14+rVqzl58mQC4LBhwwosyLt79y5nzJjB\n5cuXc/fu3QTAESNGUElJiWPGjKGKigodHBwYHBxMa2tr6urq8t9//+WOHTvYqVMnLl26lCoqKgwI\nCOCLFy/YrFmzIhN5ubm5cenSpYWO5z/P06dPU01NrUIv6K/SmNjb29PDw0NwI8tLaX4YmZmZbNas\nGZcvX16qMh8+fEg/Pz9aWVlx5MiRwlsiJCSEW7ZsKeDRpKamctKkSQTAJUuW8O+//6aqqipXr14t\nDEz6+flRV1eXzZo1o6enJ8VisfD28/b2Ltd9V4QvNQWbmJhIXV1dWltbFwrNj46O5t9//81WrVoV\nu4QgPDycSkpKtLOzK9cK6nwyMjI4evRoOjk5lcqYi8ViHj58mH369KGioiLV1dXp4ODAQYMG0d7e\nnrVq1aKOjg7Nzc2prKxMQ0ND5uTkcMSIEaxbty719PQoLy/PrKwstmzZkgDYsGHDAvsQjxgxgr6+\nviQ/7EMMgGfOnBE0rFu3jrVq1SoyU9/HzzMuLo6DBw/mkCFDytU2X6UxWb16dbkD1T7mcz8MsVhM\nDw8PDhgwoMz1vX//nn369GHr1q359u1b/vTTTwRAdXV1PnnyhMHBwTQyMmKrVq0IgFpaWnR3d6ef\nnx/XrFkj7KdCkidOnKCysjLHjRtH8sNoPwDu2rWrzPdcUb5kPMfz58+LfYEEBwdTTU2NvXr1KtKg\nbNu2jXp6ekXGw1Q2+W325MkTKisr083NjUuWLGH//v0pKyvLnTt3skmTJuzUqRM3btzIuLg4uri4\nCDN2enp6JD/c4/79+1mzZk26uroKyaM1NTV5584dkh+WVWhoaFBTU5P79u0j+cFItG7dmh06dCi0\n8vjj5/nrr7/SxcWFb968KfW9paen88cffxSWX/BrMyaS4nM/jCNHjtDKyqrcqQBEIhE9PT05duxY\n+vn50cTEhEpKSrSysqKxsTGDg4NJfljL8fGajeIiYPO7dN27dxe8maqmugSHfUpoaCgzMjLYuXNn\nDho0qEiDcujQIerp6ZV7UVxFtJEfvCNHR0cqKSnR3NycCgoKlJOT440bN/j8+XOuX7+elpaW1NTU\npK2tLf39/YXxo3zS0tKoqalJTU1N4T7at28vvFjq1KlDCwsLzpw5k82aNROuy83N5bp166ijo8Pw\n8PBC2kjSxsaGly5dKtO9jR8/nv3792d4ePi3Z0xSU1NLvQVFST8MsVjMZs2alaovnk92djYDAgIK\nxJ1cuHCBzZs359atWwmANjY2rFu3boEHWhZdFy5cIADKy8sXmtWoCqqzMSE/dEPy+/3Ozs6FQsS7\ndevGFi1alDtquiLaPuXp06eFopbFYrEQYpCWlsapU6cWui4gIEAYxI2NjWWDBg148uRJkmTLli3p\n6OjI3bt3s0mTJoWu3bRpE42MjPjbb78V0CYSiaiuri54OKXh8ePH1NDQELp7X7UxWbBgAW1sbLhr\n1y5OnTqV06dPF9Y7lGb5fUk/jODgYFpZWRUZO5KSklJkDEVUVJTwRe7QoQP9/f0FVxUAZWRkOGvW\nLPr7+5fYbSpJl7OzMwFUabb8j6muxuTUqVNCkh8lJSU2bdqUfn5+NDQ0ZHx8PO/fv88uXboIz2L2\n7NlVpq0y2ix/QFdTU7PI70KTJk144MABkh9ecm5ubvzhhx+Yl5fHlStX0snJqZC2tm3blpiAKR+R\nSMQzZ87Q0NCwQN1frTF5+vQpZWRkhJFvNzc3enh48P79+6xRo0apYjCKe8hisZjNmzcvMm7k0KFD\nVFNTo7q6uvCwPsbPz4/Ozs4MCgoS1l54eHjw5MmTQh+2vLpI8t69e+WKZ5EU1dWYrFixggC4Zs0a\nJiUlMTExkX5+ftTT0xMWyPn4+PDAgQMcNWpUlbahpNssJyeHGhoaNDY25r1794Tjubm5vHXrlhCH\nlR+o9vjxY6qqqrJ58+ZcuXIlO3XqJKRr/Fhbv379uHjx4hLrXrduHS0tLWlmZlYoWPSrNSaZmZnC\nW+b+/fsF3vTu7u6cM2dOiY1CFv+Qd+3axSZNmhTplRgbG/Ps2bP09PQslGyZ/LDoyt7enl27duWE\nCRNYq1Yt3r9//7NaSqOrOlDdtGVnZwszaK1ataKTkxN//PFHXrhwgXp6egwMDGRycjIbN27MdevW\nUSwW8/3799yyZUuVdXUk3Wb79+8XpnHt7OyE4LXZs2ezfv36bNKkCV1dXQVjIhKJ2L17d7Zo0YKa\nmpq0s7MTPPePtcXGxlJZWbnY6N/g4GA2bNiQ586dK9Kz/mqNCUkOHz6cABgWFkbyQxRhQEAAtbS0\nSjX9V9RDfvXqFQ0NDQtMreXz9u1bYQd6MzMzYWXox0RFRVFJSYkA2KlTJxoaGpY5D2t1+8F+THXT\nNn78+AIzW8+ePWPnzp2ppaVFZ2dn4bybN29SX19feDZFRaFWFpJqM5FIxJCQEFpaWtLQ0JDXr18X\nlmFcvHiRnTp1YqdOnYRUBB+vU0pLS2Pv3r3p4eHBly9fFqtNW1ubL168KLL+2bNnc9GiRcXq+6qN\nycuXLwmAurq69PT0pJWVFdu1a1fi4ObHfNqQKSkpbN26NefOnVvo3PT0dDo7O7Nx48bFLl7LJz+V\nZHkzi1W3H+zHVDdtr169Yp06dQr09fPy8hgUFMRp06YJiyFFIhFzc3MZHx/PP//8k8rKysKgZWUj\nqTbz8vKiubk5f/75ZyFvycch+g8ePKC/vz+PHz/OnTt3CmkpfH19aWFhwYiICBoYGBTwKj7V1qNH\njwL7FX9M165dS0xT8FUbE/KDtb5z5w59fX154sSJMsWDfNyQly5dYoMGDThu3LhC3Zvs7Gy2b9+e\nHh4etLS05OHDh0tdR3mobj/Yj6lKbTk5OXz9+nWJ52RkZLBfv35FjoHMnTtX+KFFR0fz+fPnlJWV\nJQAuWrSoXDlyy4Mk2uz69ets0KABDxw4wBcvXggeSb9+/disWTNhUP/t27fCNRMmTGCjRo0YGBgo\ntIOiomKBbsyn2sLCwmhgYFAgzokkly9fTisrqyIXKebz1RuTipDfkPk70xeXP/PUqVN0dHRkWloa\na9So8T+VHPlTKltbfhJqksJ6k6JeENnZ2fT29qaGhgYBFJtCICMjg8+ePSNJjh49mhMnTqzQEozy\nUNE2S05OppGREVeuXCkkmxaJRLx+/ToB0MDAgK6urnR1dWV+hLipqSkXL15Mb29vamlpCVtsLFy4\n8LPaRo4cyVmzZhU4Zmtr+9n7qCxjUmXbg0qCs2fPwsXFBX369Cny8wsXLqBz585QUlKCmZkZHjx4\nUMUKv31yc3MxduxY6Ovro1u3bti3bx/u3LmD9u3bF9qCITQ0FAYGBjh58iQuXryIxMRE1KtXr8hy\na9Wqhfr16yM3NxebNm3CrFmzoKKiUqyO9PR0nD59WqL3VlHWrFmDNm3aYMqUKcL2J7KysrC1tcXO\nnTtx//59HDx4EG/fvsWMGTPg6+uLNWvWYNeuXYiPj8elS5ewceNGfP/995gzZ85n65swYQJ27NiB\n7Oxs4ZimpibS09Mr7R5LpDIsFCvJM9m3bx9dXV2LPe/vv/9mjx49KBaLaWxszNDQUIrFYoaHh3Pb\ntm18+vSpxDR9rKs6UlnaZsyYwa5duzIyMpIqKiqCW75582aSH7a4DAwM5J49e6ilpVVo0eXndL17\n947t2rUT1rAURW5urlDvgQMH2KRJE27cuLHUQZDFUZE2y1+L9blB/KysLK5fv77Aupro6Gg6ODjQ\nyMhIOPapV1aUNrFYzP79+1NfX5/Ozs6Mi4ujsrJyoa7Pp0DazfmwFcHHI/+ffnkyMjJoaWnJ/fv3\nc/PmzdTV1RXyUzRv3pz6+voS3T/3f8GYvHnzhpcuXWJmZibPnDnDevXqCeMjvr6+wnjA9OnThTVN\nBgYGBMCbN2+WWVf+LI6GhgY9PDyKXPS2bNkyAh9ysNarV48DBgxgq1ataGRkRAcHBy5cuLDUOVPK\noq0kHj58SENDw1Kde/36dVpZWRU49vLlS+ro6JD8kCoDQIEd/IrTlpeXx//++4/Tp0+nurp6qbbf\nrSxjUqU7+pWWD/eLQm6zvr4+4uLiAAD//vsvevXqhQsXLsDa2hoA8PbtWyQlJcHa2hrm5ubYvXs3\njh8/DgsLC0RFRWHatGkVyp35rfPkyRP8+eefiIiIwIsXL6Cnp4enT5+iRo0aaNq0KWRkZKCvrw8t\nLS3k5uZi586dmD9/PkJCQlCjRg1Mnz4dnp6e0NPTQ2RkJBwcHMqs4fr16zh48CDs7e3h7e2NH3/8\nEb169YKrqysUFRWRlZWFBQsWAADGjh2LpUuXYvjw4dDT00NERARSU1OxY8cONGnSBEeOHEHz5s0l\n3UxFkpKSAjk5Obx8+RIGBgYlnhsSEgILC4sCx3R0dJCSkoLY2Fj8+eef0NfXh5eXF5ydnUssS05O\nDmZmZvDy8sKwYcNQv379Ct9LuakMC8UKeCZZWVnU0dERpgrJ/2+Vc3JyqK6uzpkzZ1JXV5fdu3fn\nhAkThGubNm1aYEBq1qxZ1NTUlKg38jHfkmfy5s0bmpubc/r06Tx79iwfPnzIsLAw3rhxg8eOHWOH\nDh04YcIEHjt2jMnJyZw0aRK7dOnCoKAg2tralrqNy6IrP29I/r/27dszLCyMqqqqDA0NLXHV7JEj\nR6ilpcUpU6bQy8tLGNyVlLZPSUpKYt++fUuVg8Xd3Z2TJ08udHzRokVUU1OjgYEB4+LiaGRkJCSH\nkuR3Df8r3Zzdu3ezUaNGwhcoJSWlQENGRkZy4sSJnDNnDgGwVq1aQqLjj/uLvr6+QvRhZU0tfivG\nJCMjg05OTgWyxBWHWCxm/fr16ezszMTERP79999UVlYudQKo8rRZYmIi7e3t2bp1a6Eb9HF3tzii\noqL4+++/09XVtVS5Pyr6PLOzs6miosLAwMAS8+q+fv2aWlpaRe6ftGvXLmFl+qZNm9i+fXuJaPuY\n/xljMn/+fE6ZMkVYt5Cbm1uoIc+cOcM6deoIBicsLIy3bt0SUiRmZGQI+5g4ODiUS0dp+BaMSW5u\nLl1dXenu7l6qRNtbtmxh06ZNhfEqsVhMIyOjUi9FKGubpaenC1OptWvX5qBBgwjgs9ncPyZ/PKKo\naOmKaCuKWbNmsWvXrtTQ0OC4ceOK9dhGjBgh7KdTHDk5OaxVqxbj4+OlxqQ8nDhxggA4ZswYAh82\n7vq0IdeuXVtgZWnDhg0pLy8vJI9+/fo11dXVy1V/WfjajYlYLOZPP/1EFxeXUmd59/DwKBB5mT8Y\nWtrcI2Vpsx07dgjPWFNTk0+ePGFmZuZns+kXRVBQkPCWl4S2z/Hu3Tu6uLjQycmJoaGhBYLIUlNT\naW5u/lnjlpeXx0aNGnHSpElfhTGpNnEmJPHLL79g8ODBAP7/XrqrVq0qdK6xsTFOnjwJIyMjAB82\nN9q/fz/atm2LuXPnYvr06cjMzIRIJKrSe/jamDJlCjZu3Ijdu3dDQUEBACAWi0u8Ji4uThjky87O\nhre3NzZs2AANDQ2J6UpLS0Pjxo0xaNAgAB/iKS5fvgwjIyMoKioKz70sdOvWDfHx8Vi0aJHEdJaE\nmpoajh49irFjx+Knn36ClpYWhgwZgsuXL6N58+Zo27Yt2rdvX2IZcnJyuHLlCq5cuYLIyEgcOnSo\nSrSXl2pjTObNm4ewsDCMHTsW7dq1w969e+Hg4ICVK1ciMzNTOC8lJQXR0dEAgFevXgnHxo8fDy8v\nL0RGRuLMmTOIior64rvGVXfs7Oygra2Nbt26oX79+li3bh3k5OSQmppa7DUNGjRAbGwsAGDSpEkw\nNzf/7IxDWXn48CHu3buHSZMmITU1Fb6+voV2xysr7dq1g6KiIvz8/PDy5UsJKS0ZBQUFeHh44NGj\nRwgKCkJycjIuXbqE58+fY/369YVmK4tCVVUVly5dQr169TB8+HAkJCRUgfLyUenbg5aWR48eQUND\nAxkZGUhLS0N6ejoaNGiAzMxM1KxZE2pqakhJScHz588hKysLVVVV6OvrC7vUAx/eBlXJl962tCRK\nqy0nJwdv3rxB7dq1ERsbC7FYDHNzc9SpU6fI8xMSEpCXl4datWoJ22PWqlVL4rokzY0bNwAAurq6\nEIvFMDQ0LHROZWrLysrCw4cPYWVlhYiIiDJPm6elpSEpKQk5OTkVNqxf5fagZaF169YcPHgwdXR0\nWKdOHWHKNyEhgb6+vvTx8aGxsfEXSTRcHF/7mMnH5M+GKSgolLi50+HDh9mpUyfq6OiUele+iuiS\nFPm77O3du5f6+vrcuXNnoXMqU5tYLKalpSX37t3L2rVrfzZK9VNCQ0N59OhRWltbV1gLvvUxEwsL\nCyQmJmLr1q1ITU3F6tWrcf36ddy7dw/Z2dnYtm0b9PT00KJFiy8t9Zvk2rVrkJeXR05OjtB9LApH\nR0ecPn0a9vb26NGjRxUqrBhdunTBrVu30KNHD/Tp0wchISHIy8ursvplZGTg7++P/v37o1mzZmXy\nohMTExEbG4vevXsjMjKyElVWjGpjTAICAhASElJgcK1Zs2aYO3cuatSogQ4dOuDMmTOl6mdKKTuP\nHz+GjY0N5OXlcfTo0WLP09fXx969e3HgwIGv7lnY29tDUVERQUFBCAgIgKqqKm7fvl1l9bdt2xYP\nHz7EsWPHij3nzZs36N27NywtLWFra4uhQ4fCyckJeXl5EIvFUFRUzPf8qx3VxpjkY2BggMWLF2Px\n4sUAgKtXr0JdXR2//vorateu/YXVfbvExsZCWVkZeXl5uHz5Mh4/flzsuf369fuqn8WePXtQs2ZN\nZGRkoEWLFjhw4ECV1W1qagolJaUiP7t+/Tq0tbVx5MgRvHr1Cnfv3sX58+fh7++P3NxcAB/GXmRl\nZXHv3r0q01xaqp0xqVOnDlJTU+Hl5YXmzZsjNDQU9evXL9Mgn5SyIRaLcfToUWhpaQEAFi1aBFVV\n1S+sqvLo3Lkznj17hkaNGiEnJwd9+/b90pKQnJyMZs2aAfjQ/u/fv4e/vz/Wrl2LM2fOIDMzE/fu\n3UNUVBQAYPny5V9SbpFUO2MCAB4eHmjatClq1KgBJycniZYdExOD+/fvAwCePn2KxYsXQ0ZGBkFB\nQUWe//LlS8yfPx9eXl549OiRRLVUF3x9fSEnJyfMMNja2kJTU/MLq6pcdHR0sGbNGuHvL911UFdX\nBwDEx8dj+PDhUFZWhqOjI0xNTSESiSArKwtHR0c0atQIAKrnFHFljOqyAhGw+YhEIvbo0YNeXl4l\njrK/fv2aGzZsKFVWtfj4eCGislOnTgUWkRWVBzYoKIhqamocNWoU1dXVC2W1+hZmc16/fs26devy\n+vXrnDdvHgGwf//+X1xXVZCSksLatWsLSc2/pLZJkyYJm8KJxWLWrFmzwPfzzJkzTEhI4Lhx49i9\ne/cit28pLfhfCaf/mFWrVnHChAlFPuT4+HiKxWIhxyaAEpPjZGRk0MTEhNOmTWOzZs0KPChnZ+dC\n61KOHj1KXV1d7tmzR0hL6OfnV+Cc6vTD+JTSaMvOzqazszNnzpxJkvT09CQAxsTEFMhRWtW6qoq8\nvDzKysoKz/5LaxOLxQXy4X78/fw0yVRFqCxjUm3ymWRmZmLFihXIycmBmpoadHV1ce7cOdjb2wOA\nMDCoqKiIHTt2wNvbGx07doSFhQV0dHTw6tUrzJo1C15eXpCVLdx7u3z5MmJiYvDrr78iPT0dffr0\nwZAhQ1CzZk2MHTsWjo6OuH79unBteno6lJWVYWpqijt37uDixYto06ZNlbZJZZGYmAgVFRVMmjQJ\nderUwZIlS5CcnCzkIDExMYGurm71dKUlyKtXr6CpqVnk96WquXbtGiZMmICUlBTh2PDhwzFx4kQ4\nODjg/PnzX1Bd6fjyrfh/LFy4EKtXr4asrCyePn2K48ePQ1VVFSNHjgQATJ48GYMHD8ZPP/2EJ0+e\noGHDhggPD0fXrl3RsGFDDB8+HKdOnULnzp0RExNTqPwVK1Zg1apVUFJSgra2Nvbs2YPvv/8enp6e\nePToEWRkZODk5CSs53FxccHLly9haGiI8ePHw8PDA3fu3KnSNqkM/Pz8oKenBzU1NURHR2P79u2Q\nk5PD6NGjceXKFbRp0wa1atVCp06dvrTUSufatWuwtbX90jIAAEOHDoWbmxvu37+PwMBA7N27F5s2\nbUKTJk2+nin4ynB3WI5uzrp16zhs2LAiPzt8+DDr1avHkJAQkh/6+QA4dOhQamlpCfuS1K5dm56e\nnmzcuLFw7fPnz/ny5Uva2dkJ0Z22trbU1tammpoaBwwYwCNHjnD37t2Ul5cvkCd20qRJdHNzo1gs\nFlzOj5PsfGm3uCROnz5daMP0y5cvU1lZmSEhIbx3716BbPLNmzcnALZq1arEPVcqSnVqs2vXrtHW\n1lb4+0tou3XrFu3t7YXvV3FIVw2XAT09vSLd6qNHj+LRo0eYO3cuOnbsCODDGwX4EFUYEhKCmJgY\nGBoaIiMjAwEBAYiMjERmZibU1NRQv359GBgY4M6dO8jJycG5c+cwc+ZMJCYmIi4uDs2bN8fKlSux\nZcsW/P333wXWbCxbtgx79uzBrFmzhGOXLl2q5JaoOCdOnMDt27fh4uKCU6dO4f3794iOjsa4ceMw\nZswYdOrUCdbW1gXeeEpKSqhTpw5GjRolrNz+1snNzc1/8X0R8vLy4ODggNu3b2PUqFFCStKvlsqw\nUCyHZ/Ljjz8WuaVhp06duGfPngLH8vchGTp0KMkPA1e9e/cmAKqoqNDIyIh//fUXAbBBgwasWbMm\nLSwsypwHIy0tjbKysjxw4AA7depECwuLAp9Xp7cs+aEdPD09qampKWwQrq2tTQsLC3bu3JmWlpbF\nDlK3b9+eOjo6XLFiRaVqrE5tlpKSQhUVFcbHx5OsWm2HDh0SvJHSZAKUeiZlQE5ODpGRkQXeFM+e\nPcP58+cLBKyJRCJYWFjAy8sL48aNw5o1ayArK4vDhw8D+LB8/ejRo0IEbWxsLAYOHAgXF5cy58H4\n77//oKqqCkdHR2zcuBEPHz6UwJ1WHnl5eQgICECrVq0gLy+PefPmYfr06YiOjkafPn2QmJiIxMTE\nAte8fv0aBw8exOXLl/HmzRv06tXrC6mvelRUVDB48GBMnjy5yuvO3/vp999/h7x8tZkHqRiVYaFY\nDs8kJCSEACgvL8+ff/6ZvXv3Zt26denp6clt27axY8eOtLGxoaamJuXl5amgoEAAHDVqlGDhjx8/\nLpSXP/07cOBAPn78mGpqavT09OTQoUM5Y8YMrl69mmZmZjx06FCxmkQiEX/++WdqamqyefPmrFGj\nRon7v1YHbty4QTs7O8EzyY+tMTQ05NixY7l06VLh3PT0dKHttm7dynr16lW6vurWZu/fv6empiaj\noqKqVFv+/sql3evna/BMqk0+E+BDbo3Y2FikpaUBAOTl5SEWi2FkZAR5eXnUqFEDMjIyQlawu3fv\nol69esIuZh+vecjJyUFcXBzevXsHGRkZNGrUCMnJycjNzUVOTg7ev38PANDS0vqsx5KTk4OcnBzU\nqlWrQMKl6prP5L///oOGhgZUVFSgoKCAV69eITk5GfLy8lBUVEStWrWQkJCArKws1KlTB/Xr18fb\nt2+RlpZW4VwZn6M6tlliYiLevXuHevXqVZm2rKwsREVFCaEPn0OS7fbN5zMhP7xV9fT0uH37dm7d\nupXe3t58//59kVY5OzubAHjy5Mliy4uOjhb2uP04CCs/+rVr16709vYus858qttblvyQhLhu3boF\nZmQ2b95MAOzduzf79OlTICBKXV2dGhoabNu2bZEbXkma6thmIpGINjY2XL16dbH7WEsKsVjMFStW\nUE1NjX/99Vepr/saPJNqY0wOHDhAHR2dIje2LqohxWIxhwwZQj09Pfbp04f//POPEMkYERFBd3d3\nTpw4sdgtQRMTE6mqqsrk5OQy6fycrurA48eP6ePjI+wrIxKJmJKSwvXr1xcwJMbGxvz5558rvK1m\nWaiubZadnc29e/dSR0eHV69erZQ68vLyOHHiRDZq1IgRERFluvZrMCbVZgDWx8cH69atw9ChQ0t1\nvoyMDAIDAxESEgI3NzesWLECEydOxIMHDzBs2DA0bNgQ6enpMDMzg42NDUaPHo01a9agZ8+esLa2\nxty5c+Hk5PRNro5t0KAB1NXVMX/+fAAfknOrqKjAzc0NwIfB7gsXLuDx48dYtWqVNFcuPuRr1dTU\nxKRJk/Drr79CW1sbK1eulGgdXl5euHPnDsLCwtC4cWOJll0dqDbG5Pnz5zA3Ny/zdTY2Nhg8eDAO\nHToEBQUFfPfdd4iIiMDo0aMREBCApKQkrF69GiYmJjh16hT69OkDFRUVvHnzBvPmzSux7A0bNqB5\n8+bYvn17eW/riyESiYTl6vmoqanB29sbp06dQtu2bb+eyMoqZNSoUThx4gTevHmDqVOn4s2bN6W6\nTiwW48SJE9i+fTvCw8PRt29fGBoawsrKCqNHj4a3tzeuXr2K8ePHf7srsivD3WEZujlJSUmcOXMm\nTUxMiu1ylMXFS09PFzbWLg585OqXRMuWLVmzZk2qqakVqa26uuzkhz1nXFxcvrSMQlTnNsvX5uPj\nI3w/Ro4cWWAGryji4uLYp08f2tra8vvvv6eenh4BcNOmTbxw4QJHjhxJExMTtmnThgMGDKiQNkmA\nb7GbEx8fD0tLSzx48ABXrlyRSJejdu3aQpKf4vjjjz+E/5e03mbKlCmoW7cuOnXqBHt7ewQHB+PA\ngQPF5j6pLiQkJCAhIQGjR4/+0lK+Sjp06CD8f8OGDZg0aVL+C7JIevXqBTMzM1y5cgX79+/Hs2fP\nkJ2djeHDh6Nt27ZYv349evXqBSsrKwQHByM0NBTnzp2rgjupYirDQrEUnklOTg5tbGz466+/ftaS\nSm+1FewAACAASURBVPptJhKJWK9ePbq7u7N58+bFRiCKxWIOGzaMADhjxgxaWVkJb6xVq1bx2LFj\nfP36NR89esSIiAheu3ZNojrLi6enJwMDA5mRkfGlpRTia/BMRCKRsJc1AMrIyHDdunXFXqeurs7n\nz5+XWPbt27epo6NDeXl5odyypHmQeiYlcOTIEeTl5WHhwoVVXresrCy8vb1x8+ZNvH37FgEBAUWe\nJyMjg6lTpwIANm3ahFatWgmfXbhwAU+ePIGpqSk6deoEd3d3uLq6YvXq1VVyD8WxZcsWnDx5Eq9e\nvZJ6JuVEVlYWS5Ysgbe3N4AP34O5c+eiqLip9+/fIy8vDyoqKiWWaWdnh3HjxsHQ0BD9+/eHhoZG\nle/zVNl8EWOSlZWF0aNHY+3atV+iegAfkiKnpKSgY8eOWLBgAW7evFnkeY0bN4a/vz+cnJxQo0YN\nPHnyBK6urjh16hQMDQ2RnJyM2NhYREZGCmH806dPL9EtLoqHDx9i48aNQuLgsvDq1Sts27YNgwYN\nwtKlS4UZsaZNm5a5rOrIl9rmdeTIkXB0dIRYLMYvv/yCAQMGCItM83n69Cnq169fojFJSEiAq6sr\n/vzzT7i4uEBfXx8tWrT49gbAK8Pd4We6OevXr6ejo2Op3bLKco33799PDQ0NDh06lEuWLCnTtePG\njeP69esLHY+KiiIAnj9/njt37vzs4F1QUBBbtmwpuL4bN278bN23b9/m4MGD+fPPP3PChAmUk5Oj\nvr4+Fy9ezPT0dF69epUrVqxgQkJCme6pKijP5mDdunXjrFmzuH379kIZ8SRJUdpycnLo7e3NtLQ0\nBgYGsnnz5gU+v3nzJo2MjAroyszM5ObNmzlz5kxu3769UOY0ALSxsSlT9rSvoZvzRYzJ33//TScn\np1LffGX2sxs2bMj58+ezXr16Qg7Oz3HkyBHKyMjw2LFjRX7u4+NDHR0dAihxpfKVK1eora3NadOm\nMTg4mIGBgbSxsSnxmvPnz1NLS4sDBw4Uonjv379f6DxJpvmTJOV5lklJSRw4cCAVFBT4888/f9ZA\nl5fPabt48WKhGcD8nfr2798vHFu2bBmbNGlCCwsLOjk5MSoqiu/evaNIJOKVK1doYmIiGBUHBwd6\nenpy2bJljImJKbe2svBNGZP4+Hh27ty51DdfmcbE1dWVXl5e9Pb2ZsuWLT/7RX38+DG1tLQ4b968\nz+qysbHhzZs3i/xsz5491NXVZUBAgHBMLBazQ4cO7Nu3b7Fl9uvXj4sXL6aNjQ0BFJm2IScnhzt3\n7iyVl1PVVORZjh07lgCYlJQkOUEf8TltqampbNCgAQcNGsRHjx4Jx0NCQqirq8s5c+bwl19+oZ6e\nHg8ePEgA9Pf3L1TOvn372KBBAw4ZMqSQxzJu3DiOGTOmQBKu0mgrC5VlTL7IQj+xWIzbt2+jSZMm\npSqrMheHZWZm4r///oOpqSmePn0KTU1N6OrqFjovJycHb9++xYsXL6CtrY369esLeWKLIzY2Fioq\nKoWClPJTAZiZmRXaD0gsFuPOnTuwtrZGVlZWob54amoqYmNjoa+vD5FIBB0dnUI5TFNTU5GRkYG4\nuLhqN25SkWcpFotBstIidkujjSTi4uKQlJQENTU1/L/2zjye6vT9/y+EsmTLVpLQnl17MooWiUqR\nmj7TVNprtpZp04JWmWpK07SYakS0TJNS2qhICzNDEUKFqBDH7uRcvz/6Od85Y+kcznEOvZ+Ph8eD\n9/t+X/frvM85l/t93/d1XZqamlBUVERpaSkKCwvRsWNHboDlP//8AzMzs3opBuoSc+nq6uLt27fc\nOSFlZWXIy8ujoKCgXvF4JtCvES5fvkwWFhZ8e1JRLyd6e3uTs7MzXbt2jXR1dXnOsdlsioiIIHl5\neZo9ezb9+eeffOvav38/zZgxg/t3eXk52dnZcUPeG6KkpIQAkIqKCgGgkpKSem22bNlChoaG3Nib\n/9KnTx/y8/MjHR2dVo274Ye2sDTMD8XFxbRlyxbq06cP9enTh4YMGUK6urrckcjBgwe5meWtra3J\n39+fZ9T739+rq6uFpu1ToD095qipqXGzpPGDqD+ApaWlNGXKFFJTUyMAVF1dTa9fv6YDBw6QoaEh\nmZub06lTpwTWVVxcTLq6utygrqSkJNLS0vpkjZ9Hjx7RX3/9RVZWVnT37l3Kzs6u9/jl4eFBBw8e\nbPD6TZs2cfOZNNZGXLQXZ1JHbW0t3b9/ny5fvkyJiYlkZGRECxcupKCgINq3bx/98ccfdOXKFQJA\nqampraqtMUTlTMSyNOzl5SW25b6GUFJSwrlz5zB79mwAgJ6eHnr37o2rV69i7969CAoKwsyZMwW2\nq6KiAicnJ9y4cYP7d21tLeTl5Zu8ztraGubm5hg3bhzc3d3RvXt3uLu7o6Kigttm6NChePr0aYPX\njxs3jvv70qVLxbKX53NBWloaQ4cOhaOjI0xMTBATEwMtLS3s3LkT33zzDX799VfY2NgAAAwNDRu0\nkZCQgODg4CbrO7cJROGh6BMjk+TkZOrUqRPf+Rxa679ZcXExASBzc3PauXMnubq6Uo8ePQhAgxOp\n/OiKiYmhrl27Unl5OZ0+fZrGjRvHt57ff/+dAJCNjQ3Z29vT4sWLqaysjF69ekW2trYNLmfX1tbS\nhAkT6Pjx4zwTe5+KV2ot2tvIpCmio6MJAH399dekpaVV7/zZs2dp2LBhPO/TypUr6dq1a/T333+T\nv78/bd68mZKTk9vEyEQszoSIKCMjg7p06UInT5785ItvzQ/gH3/8QUOHDqW5c+fS0aNHKSEhgRQV\nFRv8MvKra+zYsXTq1Cnq0KED9ejRg968ecPXdYGBgQSA/vzzT8rOzqaBAweSgoIC6ejokJeXF9XU\n1PC053A43C3/ly5d4vmQ1pXAFDefkzMh+r8VKADk6+tL3t7eNGbMGLpx4wYBoAMHDlDPnj0JAF2/\nfp1Gjx5NJiYmPO/dDz/8wDiTT/H333+ThobGJ2NIxPkBPHnyZKPRt/zqOnv2LM+k6qxZs/i6ri4j\nnK2tLRERPX/+nAA0mg3s9u3bBIDCw8Pp1q1bpKioyP1Arl69mq8+Rc3n5kxqampo9erVBIBkZWW5\n74eVlRV5e3sTEVFUVFS9UeaHDx+IzWaTj48PAaDQ0FChaWqXzoSIaO7cudSzZ0969OhRg+fZbDZd\nvHiRtm3bRr6+vo2uYIiCmpoa6tevH0VERDR4XpAPX2RkJAUGBpKMjAwZGxvzdc3Tp0+5gWFz586l\nysrKRtvW1taSh4cHOTg4UFVVFV2+fJnnv9u/C5OJk8/NmdTx7NkzmjRpEgGg7777jjw8PPi+Nj09\nnfz8/MjHx4fCwsIoKSmpRRv32q0zISIKDQ0lTU1N8vHxoe3bt5OdnR2NGjWK5s2bR926daNDhw7R\nypUraerUqWRra0shISF05MgRAW+h4Gzbto3s7e0bfeME/fCVl5fTvHnzeJaXG+LChQvc3ZHBwcGk\nrq5OLi4utHDhwgbbl5aW0vjx47nb8jt06EC3b9+m6upq2r59OwFodCm6tflcncm/SU1NJTU1NYGu\niYiIoIkTJ5K9vT316NGDRowYQTk5Oc3qv107E6KPQ/ivvvqKPD09KSIigiIjI2nv3r306NEj7ptc\nVVVF7u7uNHz4cALQYGyMsLh06RLp6Og0mkOWSHQfvoKCAurRowd16tSJunXrRmpqarRnzx4aOHBg\nvbY3b96k0aNH05w5cygnJ4fk5ORo69atEvullVRdRK2n7d69ewTwX+aCiFdbbW0tLV26lEaNGtWs\n/tu9M2mKht7kHTt2kKenp9D6qIPNZtO2bdtIS0uL4uLiBNYlLN6/f0/GxsZkampKCgoKJC0tTQC4\ne1YSEhJo7Nix1KlTJ/L29iY2m03FxcUkKytLt27dovDwcMrNzaW4uDg6e/YsbdiwgTZs2CAyvfzy\nuTuT9+/fcydjBeG/2qqrq0lZWZnu3LkjsAZROROJyQErKP/88w/69u0rVJuVlZVwdHTEjRs38PDh\nQwwZMkSo9gVBVVUV9+7dw4sXLxAZGQk7OztoaGjUOWocOnQIsrKyuHfvHjZs2IAOHTpAWloabDYb\nM2fOxLNnz9CtWzcMHToUx44dg4+PD3x8fMBms5Gbm4sXL16I7bV9zgwfPhy9evXiqV/dHOTk5CAv\nL48ffvhBYmoUS1QRrsZoKC4hMTERRkZGPIW3WgIRcb9gPXv2bLYuYfPmzRsUFRXByMgISUlJ6N+/\nP7eIVmlpKU/RrLdv36KwsBAVFRXQ09NDTk4O5OTkMHDgQGRmZqK4uBgaGhooLCwEAHTv3h0qKioo\nLS3lxoWIGkkswlWHqLWVlpbi+fPnMDc3FziXSUPa3r17h1evXgH4mK5US0uLr2TV7So2R1AaGn4u\nX76cpkyZwlfRZ36YNWsWDRkyRKA6Oq0xLOZwODRixAjavXs3HTlyhKSlpSkiIoIqKipISUmJPDw8\naOfOnZSQkECGhoZ0+PBhAsDdTl9cXExRUVH07bffkqKiIg0YMIBnlUddXZ1mzpxJXbp0IUtLS9q5\ncydlZmbyaPDw8CB5eXkqLS1t8ev5nB9z6iKJo6OjBb62MW15eXlUWFhIN2/eJACkpaVFU6ZMoQUL\nFjQ66Q7mMYeXXbt2oby8HEuWLGmxrfj4eISHh+PKlSsSV0dHSkoKv//+O/z9/VFWVoavv/4aKSkp\n6NSpEy5evAgNDQ3Ex8fD0tISmZmZsLe357k+NjYW8fHx+PXXX8HhcPD06VMsWLCAe97CwgK7d+9G\nTk4O9uzZg/T0dAwZMgQrVqwAEeHDhw/Q0dFBdXU1evXqhezs7Na+Be2GtLQ0qKqq8l0SlB90dHSg\nrq6O0aNHIyMjA7GxsXB3d4e+vj5GjhyJI0eOIDc3V2j9NYkoPBS1wsiE6GPRaW1tbfrrr79aZH/W\nrFl8JbbmV5coSE1NJWtra5KTkyMzMzMKCQmhBw8e0O3bt6myspJYLBZ3dUBOTo47MgkICGjQ3smT\nJ0lFRYWWLl1KGhoaPAmRS0pKyNDQkJvgqe5nzZo13E1xzeVzHpl4enrShAkTmnVtc7QlJCSQo6Mj\nqaio8OxRArOa0zDr1q2jefPmtcj+ihUraNq0aQJf19pfjLKyMm5k839/Nm3aRPn5+RQdHU1paWl0\n5coVio+Pp/LyciovL6esrCweW5GRkeTm5ka1tbUEgObMmUNVVVX05s0b8vLyoqVLlxLwsW7Mpk2b\nqKioiKqqqqhr164EgIyNjWnTpk30/v17gV7D5+xMHj9+TF27dqXTp08LfG1LtFlYWNC9e/e4fzPO\npBHCw8PJ1NS0RfaPHTtGTk5OAl8nji8Gh8Oha9eukb+/Py1YsIDMzMy4DmX06NHcbdt1I5O6LfkA\niMVi1bOXnZ1NAKhLly5kZmZGenp6NGTIEBo8eDABIHl5ebp69SrPNbm5ubRixQquXUHmrT5nZ0L0\nMfBTW1ubysvLBbquudpYLBZ16dKFJxUo40waIT09nbp06SJQDZL/wmKxSF1dnWJjY4Wmq7VhsVj0\n6tUrbu4MPz8/7oSfm5sbvX79mtv2zp079Sbnamtr6eTJkzRhwgTKz8+n/Px8srKy4jqM/+YnZbPZ\npKCgQAAoKCiIb52SdM/+S2tpc3Fxob179wp0TXO0lZeXk42NDS1ZsoTnuKicSZudgK1DX18f8vLy\nLZpkUlZWhpOTE1JSUniOl5SUYO7cuWCxWC2VKXKUlZXRvXt3TJgwARwOB5aWlnB2dkZhYSHOnDkD\nXV1dAB/rFY0aNQp9+/aFtbU1+vbti5cvX0JaWhr5+fmIiIjA06dPoa2tjUePHuHly5eIiIiAgYEB\nT38dOnRAeXk5AgIC6p1jaJrNmzdjx44dIv9cbd26FRoaGvj5559F2k8dbd6ZbNu2DZaWlhgwYECL\n7Kirq6O4uJjnmKenJwIDA3Ho0KEW2W5tpKSkuD/q6uo4c+YMNm7ciPv378PZ2Rl79uzBkydPMGHC\nBKSmpuLDhw8APhYWMzY2xjfffIOKigpISUlBX18f48ePr5dnto7Fixdj+PDhrfny2jzm5uYYNWoU\n/Pz8RNZHZGQkjh49ioMHDzb63gmbNu1MiAjBwcHw8vJqcUEjIuI6k4qKCuzZswdhYWEYNmwYjh8/\nLgy5YuH48eOYMWMG4uLiMHz4cLi6uuL777/HgAEDUFlZCQsLC25tZhkZGUyfPh1PnjzBt99+K3Bf\ns2bN+uSmKQ6H06zX0d5YtmwZDh8+jMjISJHYf/nyJaZMmYKuXbuKxH5DtGln8ubNG7x7947vLPcN\nUVlZicOHD+P06dNwd3dHfn4+FBUVceXKFTx79gyZmZnNqrInCQwaNAjz5s3D3bt3cf36deTl5eG3\n337jnl+1ahX69+8PU1NTBAcH49GjR/jyyy/x+PFjXL16FTU1NQL1N2vWLBQVFaGoqKjeudLSUlha\nWiIpKQmlpaUtfWltHhsbG/z+++9YuHAhpk6divT0dKHaLy0trVf5QOSIYiKGWmkCtri4mDp27Cjw\n8mQdOTk5ZGZmRo6OjnT//n0iIgoODubZC6Cvr99o7RtJnkyMiIggALRixYpPtr106RIZGRnR5MmT\niejjilHv3r2bFUTW2K7L6dOnEwC6cOGCwDZbC3G8nxUVFbRhwwbq0qULJSUlNdpOUG0uLi6NpumA\niCZg22xsTh0vX76EjIwM9PT0BLLJZrPx7NkzdOnShTs5CXwcqWRkZGDgwIGoqqpCeno6TExMBNYl\nLurq+8jIyKC2thY6OjrNspOXl4d3796hR48en9wVzOFwUFJSAlVV1UYfN6urq1FdXQ1paWmJu2d1\niPP9zM7ORocOHXg+i/9GEG0cDocbxyUrK1vvPBOb0wjp6emkqakpUEwN0cdUeV27dq2X+MjLy4tb\nbXDz5s307bffNktXa8Jmsyk0NJR69epFcnJyNGfOHDp//nyLy2jWpYFsqlwpEdGLFy8IAElLS38y\ncbWk3LOGEKc2f3//JkeRgmjz8vIid3f3Rs+DWRpuGGNjY7i4uGD79u0CXTdq1Ci8fv0ajx8/5jke\nHh7OnXy8dOkSXFxchKZVVHz55Zdwc3PDzp07UV1djcDAQKipqbV4UvqLL77AkiVLYGBg0GSYe48e\nPXD58mVwOJwWh9Z/rpSVlbU4Av7vv//G5s2bsW/fPnz//fdCUsY/bd6ZAICtrS03FJtfiouLoaKi\nUm9y1dzcHOnp6Xj37h3S0tLaxLInEWH9+vWYMmWK0G3/9NNPGDhwINavX99krSNHR0eUlpa22p6G\n9kZWVhbfqS/+S2xsLOzs7ODs7IycnBycPn0agwcPFrLCT9MunEnv3r3x5MkTvtuHhoZCX18f06dP\nx6BBg3jOjR07Fj4+PjAzM8PMmTMhJycnbLlCJywsDA8fPhSJbTk5Ody/fx8vX77Erl27mmyrpKTU\n+isI7YT09HSe3DT8EhcXBxcXF8ybNw+pqak4evQoHB0dRaDw07QLZ2JhYYEXL16goKCAr/ZnzpzB\n/PnzceTIkXoTVO7u7rhy5QrCwsLazGY1IsL169dFZl9JSQlr164VaR+fOzk5OQIvIgDAb7/9hlWr\nVuHLL78UuyNvF85EVlYWzs7O8Pb25qt9YWEhxowZ0+h5a2trjBgxosVzDq3F77//LvJhraGhIRIT\nE+sm1xmESGFhIQoLCxtdyWkKFosFVVVVEagSnHbhTADgwIEDCAkJabT+bh07duzA27dvYWtr20rK\nRM/06dPx6tUrJCYmiqwPZWVl7rZ7BuHy8OFDDBo0SOAJ2MuXL+PevXtwdnYWkTLBaDfORFVVFd9/\n/z02btzYaJunT5/Cz88PkZGRUFZWbkV1okVOTg42NjZ48OBBk+0KCwsRFRUl0PxSHY8fP8bgwYPb\nzGitLfH+/XuBM/yxWCz88MMPOHToULP3EgmbduNMAGDp0qW4cOFCg3Mn6enpGD9+PPbv39+sZ1NJ\nx93dHefPn693PCsrC+vXr8fIkSNhaGiIjRs3wsHBAf369UN0dDSICG/fvv2k/atXr7YobIGhcaSl\npSEjI8N3+9raWjg4OGDMmDFim2xtiA7iFiBM6lZeysrKkJeXh/DwcNTU1ODBgwd48OABdu/ejZkz\nZ4pZpWh4/PgxNzo0Pj4e+fn58Pf3h7e3N9zd3bFu3TrY2tpCUVERNTU18PX1xcSJEzFt2jScOHGi\nybmQmzdvIjw8HLGxsQJpIiJmJMMHeXl5nwyQZLFY3F2w+/fvh4yMDA4cOCBR97ddjUzk5ORgaWmJ\nnj17Yvz48cjJyUFpaSnMzc2RlJSEuXPniluiyJCVlcWtW7cwdepUDB8+HGw2G5mZmdizZw9++eUX\nODo6cp/J5eTksGXLFgwcOBAnTpwAACQkJDRqe//+/Vi/fr3AEaju7u48pTUYGubPP//EuHHjmmyT\nnp4OZWVlWFtbY/v27QgKCpIoRwKg7W+nb4h//vmHqqurhdZ/Y0ja1vAbN25QQEAAFRYW8qWNxWLR\njh07CAApKCg0WBg9JyeH1NXVBQ5XIPoYQAiA+vbty03tKGn37N+IQ1teXh6pqqpSVVVVk+0uXrxI\nAOiPP/6g/Pz8FvUJJtBP8oLDJFUXILi2Z8+eQVtbG2pqaqipqYG0tDQ4HA7y8/O5ZS6aw7Nnz1Be\nXg4tLS3IyclBUVGx3dwzYfDq1SvU1NTA2Ni4yXalpaVIS0uDmZkZOnRo2eyEqAL9RDpn8sUXXwjF\nTlRUlNBsCRNJ1QUIro3NZmPWrFlQVVXl5tZQV1eHk5MTFi1ahGHDhjVLR0REBK5evYr8/Hy8ffsW\nt2/fbjf3TBgsWLAA/fv3b7Df1NRUnDhxAmVlZejVqxeKiorq1UWSJNrVBCxD83FwcEBeXh7i4uJA\nRHj48CGsra0xatSoZtssKyvDL7/8AhcXF6SlpcHX11eIitsH0tLSqKioaPDc/fv3sX37dvj7+8PI\nyAjLly9vZXWC0a4mYBlahoyMDEaMGIHTp09j3bp1mD9/Pnbs2NEsWywWC8rKymCxWDh16hRMTU2x\ndu1aIStu+8TFxWHs2LE8x968eQNra2ts27YNS5YswXfffQcFBQUxKeQfxpkw1KNXr17Q0dHhroI1\nh927d3PLYPbp0wdHjhyRvNUHMUNE+OeffxAUFMRzvKysDPHx8aiqqsLOnTvFpE5wGGfCUA9XV1e8\nffsWYWFh9aKqPwWHw8Evv/yCI0eOQF5eHsOHD0dKSgpMTU1FpLbtUrdZcO/evTzH6wL2Jk6cKLGT\n1Q3BzJkw1ENfXx9BQUGoqqrC9OnT+b6OzWbD1dUVubm5cHV1RUBAAM6fP8+MSBqhvLwcADB16lTu\nMSLCiRMn4Ozs3Gai1utgnAlDgzQn0dL+/fuRl5eHu3fvwtraGnfu3IGNjY0I1LUPEhISYGVlxeM0\n/Pz8sHfvXgQEBIhRWfNgHnMYhIa0tDQeP36MAQMGwNjYGCNHjhS3JInG29sbvXr1gpaWFvdYdHQ0\n5syZAycnJzEqax7MyIRBaHz33XeYM2cOEhMTMXLkSObx5hP07t0bJSUlPMd+/vlnGBoaon///vjq\nq6/EpKx5MCMTIZOcnIxJkyYhPj5e3FLEgpqaGmxtbQWKgv1ciYmJqZcz9/r169DT02syeZekwjgT\nIXPx4kWEh4fjwIED4pbCIOHU1NTw5DF58+YNduzYgbCwsDaZJoN5zBEyCxcuxJAhQwReUmX4/Oja\ntSuSk5O5u4wXLVqESZMmYciQITztXr58CRaLBQ6H02pFyJuD5Cpro6irq2P06NHtKpMbg2jo3bs3\nMjMzuX+/ffsWBgYGPHNNoaGhMDAwQHp6Oo4ePSoOmXzDOBMGBjExY8YMrFq1ComJiViwYAFiY2Nx\n7NgxnjZEBGVlZWhqamLy5MliUsofjDNhYBATdnZ2KCgogJmZGY4cOQIPDw8UFhbyrPC4u7uDxWJB\nX1+fZwlZEmHymbQASdUFSK42SdUFiEdbSUkJnj9/DikpKZibmyM7OxsFBQXQ19eHpqamSLQxhcsl\nEEnVRSS52iRVF5H4tMXExFC/fv2oT58+ZGRkRABo0aJFItMGEWVaY1ZzGBjEzPDhw5GcnIxr164h\nPz8f06dPF3t1vubAOBMGBgnhU0mlJR1mApaBgUEoMM6EgYFBKDDOhIGBQSgwzoSBgUEoMM6EgYFB\nKDDOhIGBQSgwzoSBgUEoMM6EgUHCKSkpQUZGBvbv3y9uKU3COBMGBgnm8OHDUFVVRXFxMeLi4sQt\np0mYHbAMDBJIQUEBRo4cidTUVHTq1AlaWlo4fvy4uGU1CTMyEQD6vyDGVicpKQmJiYlCtTlr1izE\nxsYK1SaDcFi2bBlSU1OxePFiVFRUoHv37ujYsaO4ZTUJ40z4oKCgAIsWLYKamho0NTWxevVqoTkV\nDofzyS90UVER7OzsYGlpiStXrnCPExEOHjyI0aNHY/ny5XxpYrPZyMnJwaNHj3D69Ok2VX7yc8HP\nzw/x8fGYPHkydHV1xS2Hb5jHnE/A4XAwevRo2NnZISUlBbW1tbCyssKMGTOEYj86OhqjR49GcnIy\n+vXr12D/rq6umDt3LqZMmQIXFxecOnUKRITAwEBkZGRg0aJFOHDgACZOnIhvv/0WY8eORXV1Nfr3\n7w9ZWVloa2ujoKAA/fv3x9WrVyEnJwcNDQ24ubkhOjoa169fB4vFQn5+PmpqaqCoqIhhw4bBxMRE\nKK+RgX9iYmLg5+eHFStWYMOGDW0q+I9xJo1QUVGBiIgIfP3117CyssLevXu5uTl9fX0xefJk+Pv7\ng4iQkpKCgoICbmLgpmCz2di0aRMSExORnJyMvLw8mJqawtbWFoqKilBSUsL79+8xePBgFBUVIS0t\nDUZGRtixYwekpaWxb98+bNy4EQoKChg3bhyOHTsGJSUlODs74/z585g7dy66d+8ODw8PrFixSyIf\ndQAAD9dJREFUAgMHDkR+fj709PSQkJCArVu3wtDQkKtn165d8PHxgYaGBrS1tSEnJ4eysjKsW7cO\nsbGx6N27t8juMUN91qxZgx9++AG7du1CYmIiBg4cKG5JfCPSTGvCsh0VFYUvvvhCKLb44dy5c1iw\nYAEA4MqVKxg8eHC9glIRERHIyspCXFwcbt26BSkpKSgpKcHW1haTJk3CxIkT69mtqqrCsmXLkJWV\nBU9PTwwYMADdunWDuro6srKyUFVVhaqqKsjKyiIqKgq9evWCrq4uevbsyXeC6srKSsTFxaGqqgoT\nJkxo9j2wt7eHlZUVvL29IScn12w7/6W130tBkARt/fr1g4mJCbp27cpT0FyY2qSkpESSae2zHZns\n27cPQ4YMwdChQ7nHoqOjsWPHDqSmpuLq1auwtLRstJjUhAkTcPPmTbx79w7Tpk3DpEmT8OjRI1y6\ndAnr1q2r50xqamrwxRdfoFu3bggNDYWGhgbP+Z49e/L83dz/SJ06dYKdnR2ioqKadX0dgYGBWLRo\nEUxMTLBw4UJMnz4dBQUFICJYWlq2yDZD42hqaoLNZiM3NxdE1LaqIooifRtJeNrG6Oho0tPTI3V1\ndQoJCaGSkhLy9fUlHR0dCgwMpMrKymbr+vDhA6mpqVFeXh7P8dDQULKxsSEOhyOMl9AsbYLC4XDo\n9u3bNHfuXFJXVycABIBu3bolVl2iQlzaWCwW2djYkI+PD3Xu3JlevnxJAwcOpNWrV4tEG0SUtrFN\nOpPa2toG23348IHevn3bpDOIi4uj4cOH008//URHjhwhKysrsrW1JRUVFcrOzm6RLiKimpoa0tLS\n4tqKj4+ngIAAMjIyolOnTglkvyUI+4tRWVlJhYWFdPPmTdLU1CQLCwsKCwsTuy5hIi5tv/76Kxka\nGpKKigpNnjyZiIiKiopIW1ubUlNTha5NVM6kzS0N19TUYMCAATA0NMTBgwcRHR2Nvn37omPHjtDS\n0kLfvn2hqakJOzs75Obmcq978eIFlixZAjc3Nzg7O2P58uWYP38+YmJiYGpqipCQEKGUZJw9ezas\nra2hq6uLmJgY2Nvb48GDB9i7dy9mzZrVYvviomPHjtwCYzk5Odi6dSsWL16MyMhIcUtr8xQUFGDa\ntGno0KEDt2KfmpoaJkyYgFu3bolZHf9I3JwJm82GrKxsveMcDgcXLlzA2rVrYWBggBkzZmD16tXo\n3LkzfHx8sHXrVpw4cQJDhgxBSUkJ1q9fD1tbW5SUlKCiogIdO3aEu7s7/vrrL6irq3PtysvLCy3m\ngc1m48yZMwgMDISMjAyCg4OxcuVKrFu3Tij2JQU5OTk4OTkhJCQEM2bMwMKFC6GhoQFFRUWYmJhg\n6NChbetZX8xwOBzIyMhg5MiRePjwIfe4vb09Tp48iUWLFolRHf9IhDNhsVi4dOkSevfuDRsbGyxZ\nsgSurq64ePEit/iQsbExlJSUcOjQIYwePRpSUlIoKiqCjIwMPDw8MHPmTK49FRUV+Pn5wdraGmPH\njkXnzp2hoKAg8jqtsrKycHBwQEhICGxsbBASEoLHjx+LtE9xMmbMGFy7dg3nz59HZmYmKioqsHfv\nXnTu3BlHjx5tU8ua4iIsLAxBQUH45ptvYGBggCtXruDdu3fQ1NSEq6srFi5ciNLSUnHL5A9RPDuR\ngHMms2fPpn79+pGsrCyNGDGCDAwMqG/fvrR582YCQAcOHKCHDx+22uQlvzT0HDtu3Dg6deoUrVq1\nin788cfWF/X/EdfzP4fDoUOHDlGXLl0oLS2t3vn2Mmdy4cIFunz5MhUWFja7v6CgINLV1aWDBw/S\nu3fvKCwsjHR0dOjMmTPcNgYGBpSZmdkm5kzEPjLJz8/Hn3/+ibS0NERERKBfv34YPHgw97ybmxvy\n8vIwaNAgMarkn5ycHMTHxyMoKAjCqmjYlpCSksKiRYsQFhaG1NRU9OrVS9yShE5tbS2mTJkCCwsL\nPH/+HAoKCli7di2++eYbgez89ddfsLe3x9WrV9GnTx9cvHgRenp6ePHiBbdN586dUVRUJORXIBrE\nWh6Uw+Hg+fPnUFRURLdu3RptJ6klJRvSVVVVhXfv3kFZWRmqqqpiUibee/bhwwc8efIEpqam9R4t\nJfW9BPjXlp+fj7KyMrBYrLpROOTk5HjCD968eQNlZWUoKCg0aqe6uhovX77kPsaoqamBzWZDS0sL\nampqAICsrCx07twZ8vLyTHnQxnjw4AH17NmTlixZQh8+fGiyraQOjSVVF5F4tR09epTc3NwaPCcp\n9yw3N5e7haDu8ZlfbQDIyMiIBg0aRFpaWhQdHU0FBQVUUlJCZ8+epdzcXAJAWlpa5OXlRUlJSdxr\ng4ODic1m89jLycmhw4cPk6OjI5mbm/NsbVi7di15eXm1icccsSwNExE8PDzg6+uLgwcPNrrLlKHt\nUVtbi7Nnz8LJyUncUhqFiNCtWzfo6uoiKysL0tLSmDdvHjIyMpCWlgbg4yiFzWY3eP2wYcNw/Phx\nPHz4EFu3bsWKFSuwbds2GBoa4qeffoK+vj6mTp0Kb29vpKamwtnZGStXrkRYWBg8PDxgYWEBT09P\nVFVVISQkBCYmJrhw4QKmTJmC2NhYnlQDenp6ePPmTavcl5YiljmT3Nxc5OXlwc7OThzdM4gQR0dH\nlJaWwsXFRdxSGkVKSgo7d+7EmjVruEGPQUFB6N+/PyIjI1FVVQVzc3O4u7sjODi43vWWlpYIDw/H\n0KFD8fXXX6O4uBjl5eV48OABjIyMeB6XPD09cf36ddy7dw/z5s3D5s2bMXjwYOzfvx9WVlaoqKhA\nVFQUTE1NG9T65MmTeqEWkopYnEm3bt1gZ2eHc+fOYenSpeKQwCACZs+ejfz8fMTHx6NDB7HP7YOI\ncPjwYZw7dw5aWlqoqamBjY0N7ty5Ax0dHfz2228oKipCeXk5oqKiICcnhzNnzmDt2rVYtmwZfvvt\nNxw+fBju7u4881/Lly+Hq6srCgoKcPz4caxZs4an33/PbUhJSWHs2LEYO3YsVq1aBSUlJUhJScHS\n0hIxMTFwcHBoNIgzPj4eoaGhSEhIQGZmpmhukhARyzv+5MkTPHz4EHv27BFH9wwiIDk5Gbdu3UJG\nRoZEOJJXr15h2bJlyMvLw4oVK1BSUgIpKSk8ffoUjo6OKCgoQHh4ODp16oTKykooKytDW1sbd+7c\n4W64y83NxY8//oiTJ09i+/btGDVqFJ4/f44PHz7g1q1b6Nu3L3x8fNC1a1e+NP3baWhra2Pq1KmN\nts3MzISDgwN27doFfX19xpk0RF5eHtzd3bFr1y707du3tbtnEBG7d+/GvHnzxJJasLa2FidOnEDX\nrl0RExODQ4cOgcPhYMmSJQgLC4O8vDxfdqKionh27p46dQrAxwhqDw8P9OjRAxkZGVBWVgaHw0GH\nDh1QUFDAtzMRhICAAMyePRvz588Xum1R0arOJCkpCZMmTYKnpyfmzJnTml0ziJCsrCyEh4cjPT1d\nLP2fP38eGzduxOvXr+Hg4IDHjx+je/fuLZ7Yr1vWXbp0KVxcXJCSkoJhw4ZBUVERcXFxuHLlitCz\n0VVWVsLf3x9hYWFtLj9vqziTmpoaHD9+HBs3bsS+fft4tr4ztH2ioqLg4OAgtn01+fn5cHJywurV\nq2FkZCSSPvT09HgCQYcNG4Zhw4YJtY/79+/jf//7H/r374/o6Ogm915JIiJ1JoGBgTh69CiSk5Nh\nYWGB27dvM/Ea7ZCUlJRGVyNaAwMDA5w/f15kjqQ1uHPnDqZPn46AgAC4urqKW06zEIkzkZKS6gQA\nwcHBWLduHQYNGgQtLS1RdMUgAbx//x7GxsYi7aOxaPLQ0FB4enpi+fLlIu1f2KxZswavX7/Gs2fP\noKCggPT0dOzYsUPkjqSxvTPCQCTOhIgqpaSkmFwXnwm1tbUiTTnw/v17qKurIzo6GgUFBcjMzMTK\nlStx8+ZNLF26FFFRUbCwsBBZ/6LgxIkTmDFjBvbt24fq6mqoqqrC3Nxc5P3+8ssvIrMt/jU8hjaP\niYkJHjx4AE9PT5HYrxuRjBs3DsOGDcOTJ0+QkpKC8PBwnDt3rs05EgDYtm0b1qxZg6FDhwqtbMqn\nuHr1Knx9fUVmv81lWmOQPGxtbfHo0SOR2VdUVISMjAyKi4tx69Yt/Pzzz+jRowfi4+P5Ki8iicyd\nOxc3b97E4sWLUVZW1iJbb968QUpKSqPniQjHjh3D7NmzceHChRb11RSMM2FoMb1790ZGRobQQ+VZ\nLBaAj7tIVVVVUVBQAABwd3eHl5eXUNJsiouEhASkpqZCVlYWGRkZzbZz4sQJmJiYYNSoUQgICKh3\n/sOHD5g5cyYOHDiAmzdvCn0F6t8wzoShxSgpKWH+/PkwNDTEjRs3hGIzLi4OampqmDJlCioqKuDs\n7IxDhw4Jxba4uXv3LsaPH4+jR49iwYIFMDMza5YdDoeDH3/8EYGBgXj48CG8vLzw6tUrnjbXrl1D\neno6YmNjRb7ixjgTBqGwd+9eLFy4EBEREUKx9+TJE9jb20NGRgbe3t7YsmULjh8/jujoaKHYFycx\nMTGYM2cOrl27Bh8fn2bbuX//PtTV1TFx4kT07NkTrq6uOHv2LE+b7OxsWFlZoVOnTi2V/UkYZ8LQ\nImpqavDs2TNMmzYNISEhQpvDsLa2RkpKCvz9/XH48GGoqalhy5Yt2LZtG0/VgbZITU0N31v8m+Ly\n5cs88T39+/ev98hUUVHRKo4EYJwJQwuZPHkyxo0bBwMDA6SlpQkt9YCZmRlkZWWRn58PY2NjJCYm\nws3NDerq6jA1NYWDgwN8fX3x9OlTofTXmsjLyyM7O7vFdu7cucPjvLt3717P0crKyqK8vBxZWVnY\nsmULpk2b1uJ+G4NxJgzNprS0FHfv3kVKSgr8/PyE8t+2DikpKaxduxZfffUVsrOzUVRUBBUVFQQH\nB+P169fw9PREUVERxowZg+TkZKH12xosWLAAkZGRfDnC4uJixMfH1zvOYrHw999/Y8SIEdxjnTt3\nrpfJ3sLCAiEhIRg8eDAKCgpEmoiM2WfC0GweP34MMzOzJvOctoR58+bh/fv3MDMzg729Pfe4vLw8\n3Nzc4ObmBjMzMzg5OeHRo0f16jdLKmpqahg+fDiSkpIwYMCAJtt6e3vD39+/XjGuwMBAjB07lufe\ny8rK1tvhOnLkSB4Hc+zYMYSGhgrhVdRHpAmlRWKYgYGhpbwlIm1hGxWZM2FgYPi8YOZMGBgYhALj\nTBgYGIQC40wYGBiEAuNMGBgYhALjTBgYGIQC40wYGBiEAuNMGBgYhALjTBgYGIQC40wYGBiEAuNM\nGBgYhALjTBgYGIQC40wYGBiEAuNMGBgYhALjTBgYGIQC40wYGBiEAuNMGBgYhALjTBgYGIQC40wY\nGBiEAuNMGBgYhML/A3VCeOjn7B6+AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f50df791d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plt.axes(projection=ccrs.Mercator(central_longitude=151))\n",
    "ax.gridlines()\n",
    "ax.coastlines();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JTZs2RUZGhsSTSr969Qp16tRBVFQUOnfujObNm+P27dv45ZdfcPTo0Sqf4pUk8vLyuHv3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\nGBiEAuNMGBgYhML/A3VCeOjn7B6+AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f50df6caf28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plt.axes(projection=ccrs.Mercator(central_longitude=151, latitude_true_scale=-50))\n",
    "ax.gridlines()\n",
    "ax.coastlines();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Orthographic: nice globe projection effect, but incompatible with x/yticks (cf below)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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29lELFiwI/u677/gsyyItLQ0ODg4YPny4UescmUyGr776Clu3bsXbb7+NNWvWgGEYFBUV\ngYjg7+/fZ8/AsiwUCkWHnkLXu+V1FWNeQgAMboIADG5+HSUbG5suWTb1FrlcjqysLKM24F1B77Dv\n7e2NwYMHQyqVYv78+YrLly8fl8lky+kfEgv61rZwvw69aO++++7g7777jl9RUYGCggIEBwfD2dm5\nw2sUCgUOHTqEN954A9OnT0dUVFSbGePa2lqMGDHC5GXV6XQduvGp1WpwOBzY2toanBE8PDwgFAph\nZWXVLj6yqSCiNrGWVSoVZDIZ6urqDP/vSOA2NjYQCASGv13xDOoMoVAIhUJxrUXpYT7u7u5wcXHB\nlStXcO7cOYwcORJnz561nTVr1sKsrKyDDMP8I8T7j2hxrxftV199xc/MzISVlRWCg4ONusaVl5fj\n/vvvR01NDb799ltMmzatzecsyyIyMhIXL17EX3/9haampjahZm6GVqvtUJwajQYcDqdDNz5zOrCb\nAr3AO3L1UyqVUCgUEAgEBmcCsVjcbe+nlJQUBAQEQCwW97q8LS0tyMzMBJfLhZ+fHxYuXKjIysr6\nR7S8t7xwrxfttm3b+Lm5uRg+fDg8PDw6PJ+I8O2332LdunV48cUXsWHDhg7F0tDQgO+//x5//vkn\n6urqUFtbi6KiIqPluNE7yJiP7T/ZppmIoFQqDZ5BjY2NYBgGjo6OkEgkcHR0vKmZaElJCTQaDYYM\nGWKyclVXVyM7OxuOjo546qmn/hHd5ltauHrRLly4MOTVV1+10Wq1GDVqFIw5C2RmZmL16tXQarX4\n5ptvMGrUKKN5JyYm4p133sHhw4exdetWFBcX4+DBg4bP9Yby13sHubi4wNXVFWKx2OId9D80Gg0a\nGxsN3kFqtRoikcjQKotEojYVp1wux+XLlxEWFmbScuh0OhQUFKCwsBBvv/22Mjs7+/dbWby3rHD1\nop0/f37oU089xRsyZAi8vb3btZ5NTU346KOPsGnTJgDAJ598gueee65TYel0Onz66afIysqCs7Mz\nfvvtN5w6dQouLi6oqalBTU0NWlpa4OjoCBcXF4t3UDcgIjQ3Nxta5ebmZtjY2BiE7OjoiLi4OMyY\nMcMs929qakJ8fDzeeecdVXZ29m+3qnhvSeEyDCMUiUTRM2bMuG3t2rXcsWPHwtbWtt15RUVFmDt3\nLkJDQ3H06FEAgEqlMtoi68nIyEBUVBRGjRqFjRs3Yv369VCr1eDxeAgMDIS7uzvs7OwG9Hj0VkKl\nUrXpXkulUgwZMsQQbM/UtLS0ICYmBm+99ZY6Nzf32K0o3ltOuAzDcMVicdSECRMm7dq1i6OPR3wj\nly5dwvz58/Hoo4/i+++/R2lpKe644w6cPn3aqOD0rUFGRgZKSkpQVVWFrKwspKWlITs7GxqNBr/+\n+itCQkIQEBBg7kf915Kamgo+n4+GhgZYWVnBx8cH7u7uJh1+qNVqREdHY/369a15eXl7ZDLZGpNl\n3hf090Jyd5NEIvm/UaNG6YqKisgYxcXF5OnpSQcPHiQ3Nzfy8PCgYcOGUUtLS4fnKxQKysrKooiI\nCEpOTqZLly7Rq6++SgBo8ODB5OTk1C4OcnJystH7W+gdBQUFpP99m5ubKTMzkyIiIujSpUtGTVR7\ngkajob/++os8PT1braysHqUB8H53NfV7AbqT3NzcnnB1ddVdunTJ6I+hUqkoODiYduzYQcXFxQSA\nFixYQLW1te3ObWpqopSUFIqOjqbS0lKDvWtmZiZNnjyZANDOnTtJJpNRY2MjffTRRwbhvvnmm0bL\nYKF31NbWUkZGRptjOp2OKioq6Pz58xQTE0NFRUXU2tra7bw/++wzOn78eJt8f/rpJ7K3t9fY2NiE\n0wB4z7uS+r0AXU2hoaG329vb686ePdvpD7Nnzx66/fbbDXbFejHqYVmWKisrKS4ujs6fP0+1tbXt\nbJCTkpIoMTGRbrvtNoNQ3dzcDP92dHSkrKysTsthoecoFApKSEgw+rlSqaS8vDyKjIyk5OTkDn9D\nY3z//fe0devWNrbqLMvS7t27SSwWq4cPH+5LA+B9v1nq9wJ0qZCAi52dXd2ePXtu+sNkZWWRs7Nz\nuygVGo2GioqKKDIyktLT00kmk3V4fWVlJUVGRpJOp6OCgoIOtwsZMWIEbdy4sV2lYME0sCxLkZGR\nXTqvvr6eUlNTKTIyknJyckihUHTpHgBo5cqVbY69/PLLWpFIlAHAhgbAe99Z6vcC3LSAgLW9vX3y\nf/7zny73iz788EOytbWl9957j5RKJV2+fJkiIiIoNzeX1Gq10euam5sJAP38889ERFRTU0PBwcEG\nwSYkJNDSpUtpyJAhJJFI6OrVq10tkoVu0hXhXo9Go6Hi4mI6d+4cxcfHU3l5eaet8OnTpyk0NJTu\nvffeNr2z//nzHsAA38Oo3wtws2Rvb79n1qxZLd1t3XJzc+mll15qN37tjEmTJpGNjQ2dOHHCcGzP\nnj0EgO68806aOXMmLV26lK5evUrh4eHd8h+10D1iYmLIWEywmyGTySgjI4POnTtHjY2NRs9LT08n\nAPTGG28YjjU3N5O/v38Lj8d7jgbA+28s9XsBOks8Hu9JHx+flqamJqNf/vWwLEtVVVUUFxdHCQkJ\nFBwc3OXu7JYtWwgA7dmzhy5cuGDI74svviArKysCQE888QTJZDJ65plnaOjQoXTq1Kku5W2h+1y4\ncKHTQHFdQSqVUmxsLKWnpxvtaSUlJZGLiwsdOHDAcOzKlStkb2+vwAAOQNfvBTBasGshZxQXL17s\nkvhqa2spKiqK0tPTqbm5maqrq0kkEnVp0uKzzz4jAPTggw9SVVWVYeLp77//NnSTuVwuLV261HCu\ns7Nzl8dTFrpPZmYmVVdX9zoflmXp6tWrFBERQUVFRR2+D/qJx/z8fMOxv//+m/4XPVJCA0APN6YB\naVDLMAzX3t7+8Lp16/ihoaE4edJ4zGudTofMzEzk5eUhLCwMo0aNgr29Pc6ePYuZM2fe1LopPj4e\nzz77LObNm4dDhw5BqVQarHU++eQTANdi+K5ZswbNzc3IyclBYGAgfv/9d0tcZTPC4/EMuwb2BoZh\n4OXlhSlTpqClpQWxsbFobGxsc865c+cwdOhQXLlyxXBs9uzZePzxxwUikeiLXhfCHPR3zdFR4vP5\nr4WHh8vnz59PAAxd1xtpbGykqKgoKigoaFOTqtVqmjZtGn3++ecdXnc9P/30Ey1cuNDw/9zcXCov\nLyciopKSEsMEVF1dHW3evJlWrFhBERERN83XQu8oKiqizoxsekpzczPFxcVRWlpam0BzHSGXy8nd\n3b2Fw+HMpwGgi+tTvxegXYGAIba2tooHH3yQRo8eTQDoySefpOLiYsrMzCSia7N/ubm5FBMT024c\npNPpaMWKFbRw4cKbhmZhWZZSU1PbWFSZqotmoXdcvXqV8vLyzJI3y7JUXl5OERERVFhYeNPZZ6FQ\nWAtARANAH/o0oCJgMAzDiESiQ3fccQc/IyMD8fHxWLduHXx8fODn54eQkBDEx8cbdnmbPHlyG/tV\nlmWxevVqlJSU4OTJkzcNt6L3GuLxePj+++8hEonA5/P7fV/a62FZFq2trR3uLN+V3emN/SWiduFq\n+ipETVewtrZGc7N59vRiGAaenp5wdXVFXl4ezp07h+DgYNwYbxu4tkn54sWL7X799dcdAFaZpUA9\nYEA5GfB4vKcGDRq0U6lU8uPj4+Hv74/x48fjypUrBve8kJAQfPjhh7jvvvswffr0NqFl3nzzTURH\nR+PPP/+86daWubm5mDx5MmJjY/Hmm28avIeSkpIQFBTU4YbLHXHx4kUMGzbsph5HnaHT6TqMM6VW\nq8EwDGxsbLq0+3x3dqcH0CZcjT6qRWchavT/5vP5Zhd4fX09ysvLERoaatb7ANd8gC9dugQ+n48R\nI0a0+y2bmprg7++vbGxsnEtE58xeoC4wYITLMMwggUCQKxKJhD/++CNmzJiBM2fOYPbs2Zg+fTqW\nLl0KR0dH7Ny5E4mJiRg2bBjs7OywY8cODB48GFeuXMGyZcuQlpYGNze3Tu9VV1eHiRMnYt26dVi1\nahWqqqrg4eGB3377DS4uLhgzZkyXhPjXX39h3rx5sLW1RVRUFMaPH2/0XK1W206ccrncEMrm+jhT\n+mRjY9MvroNE/z8GlVqthlKpbBeu5kaB68UtFovh4ODQa2E3NzcjPz8fY8eONcUj3RQiMgSau+22\n2+Do6Njm82PHjmHFihXlcrl8KA2AzbUHRFf5f13kfWFhYQIrKyuDE/XVq1dx77334plnnsHJkydh\nb2+PrKwsJCUl4bbbbkNwcDAeeOABVFdXw93dHfv27bupaGtrazFr1iwsXboUq1atglwux5QpU/D6\n669j4cKFOHfunNGuckxMDM6ePYt33nkHAPDHH39g7dq1uHDhAjIzMzFu3DjIZDLI5XLI5XIUFRVB\nLpeDy+XCxsYGrq6uBlE6OTnBzs4O1tbWZhOnTqfrkYD0rfzNKi8igkajaRN36urVq7h06RI4HE6b\nzay72yPhcrnQ6frORZZhGHh4eMDBwQFJSUntggzec889uP32253Onj37PoBX+6xgxujvQTYRgcvl\nPuTt7a1wcnIyTEio1Wq6cOECpaSkUGtrKy1btowCAwNp+fLlbSYZdu/eTQDoo48+MjrBoKe1tZWm\nTp1K//nPfwwTEm+99RYtW7bMcE5HpnY6nY5++eUXAkAODg6G45s2bSKxWExz586lkydPUkREBF24\ncIFOnTpFb7zxBk2YMIFWrlxJd999NwkEgjYeLzqdjr7++msaO3YsOTs707hx4+i1116js2fPUlZW\nVqcWP11hx44dBIDmzp1LFRUVvcqrJ7S2tlJVVRVdvnyZYmNjKTIyklJSUqioqIikUulN19dbWloo\nMTGxj0rbFqVSSVFRUVRVVdXmeFVVld4wYwz19yRuvxcA4Nva2taPGjWKtm/fTkTXvEMiIyMNyzJE\nROPHjzfYC19PTU0NffLJJ10ytNi2bRvNnDmzjUHH6tWrafbs2QYXscjISMrIyKAff/yRdu/eTY8+\n+ig5OjoaDDEKCgqopqaGMjMz6eTJk/Tuu+/Sm2++SY2NjcSyLG3cuJEA0JAhQyg+Pp6IrtnRPvHE\nE7Rz504iIqqurqbw8HCaOHEiRUREUEVFBcXExNCbb75JkyZNouHDh5NQKKSQkBB66aWX6Ndff6Wy\nsrJu7aRQWFhIDz30kKHcR48e7fK15kCn01FjYyMVFBTQhQsXKCIighISEignJ4dqa2vbmTe2tLTQ\n+fPn+6m01xqOmJgYKisra3P866+/JgcHh2T0sy1zvwvX2tr6heHDh6vCw8NJq9VSa2srRUVFUX19\nveHLkslkBIBcXFx6vA1ITk4OSSSSdpHyVSoVWVtbk95d8OTJkyQWi0koFBpeei8vL3rllVfo1KlT\nBmFXVlaSRqOh9evX0/r16w35NTU10WuvvUaPPPIIubi4GPIQCoU0Z84cqquro9tvv51ee+21Ti3C\nNBoNJSQk0KZNm2jevHnk7OxM7u7udP/999Ply5e79MwtLS302GOPEYfDIQBt/FAHAgqFgq5evUoZ\nGRkUHR1N0dHRdPHiRSorK6OGhoZ+FS7RtV5DbGwsFRcXG45pNBry9PSUA7id/q3CBSCwtbVtdHZ2\npvPnz5NWq6XY2Nh2Xbu4uDgCQCEhId3/9unarnuhoaG0e/fudp+xLEtLliwhALR371766KOPyM7O\njh599FHav38//fzzz/Tpp59SYWGh0QgaHVFbW2sQ7bZt2yg2NpYWL15MAoGA7rjjjm5v/8GyLJWU\nlNCOHTvI2dmZPv74Y6PnZmdnU11dHcXExBCXyyWRSEQA6P333yciMmkUCVOi0WiopqaGcnJy6Ny5\nc3TixIluueqZA61WSwkJCW0q/AMHDpCDg0N6f7a6/SpcHo/3akBAQOtDDz1ELMtSUlJSh9Yy77//\nvkEE19d+XeHjjz8mZ2dn+vTTTztsrSMiIsjDw4O+/PJLOnLkCP3www/0yy+/0PHjx2nBggWG1spY\nS19dXW1oFf38/CgkJIRiYmJIq9XSBx98QDwej5YuXUrOzs706quvUkxMDF26dIm66jjREUVFReTm\n5kbHjx+7T3fNAAAgAElEQVQ3VABnzpyhtWvX0vbt2wkAhYaGEgBydXUlT09POnv2LGk0GtLpdASA\n/vvf//b4/n2BUqmk+Ph4KikpMbjqlZWV9ct+RzqdjpKSkignJ4dYliWtVks+Pj5yAHPp3yZcAEKB\nQNAsEomosLCQLl68aLQLCIC+++47mjRpEr311lsUHx/fpS5zSUkJOTk5tXOq16NQKOiDDz6gI0eO\nUFpaGm3YsIF27NhBQUFBZGtrSzY2NjRv3rx291IoFHTixAk6fPgw6c0yb0x6Vq5cSePHj6eUlBRa\nt24dDRkyhAIDA8nOzo7CwsJo/fr11FkoHmMcPHiQQkNDSSKR0MMPP0wvvPCC4d6jR482tLLPPPMM\npaamtrnW09OTANAvv/zS7fv2FXrh6pHJZIa4YBcvXuxVxdcT9FZ2mZmZxLIs/fjjjyQSibL6q9Xt\nz9Z2nbe3t2bt2rWUn59PqampHYpR30Lou5zz5s0jNzc3WrlypVHxarVaSklJoccff5yWLFnS7vPG\nxkZKTk6m6OhoevXVV2nv3r3Esiy5urrSn3/+ST/88ANNmDCBRo4c2WH3eO7cuYYyffnll7Rt2zbK\nysoinU5HMpmMCgsL213DsiwdO3bMMK5VKpUUGRlJ69evJzc3N6qsrOzwWW7GM888Q1wulzZv3kwp\nKSm0YcMGuvPOO+m5555rF7dJT0JCgqH869at6/eJq45QKBQdjnF1Oh1VVlZSYmIiRUdHU2FhYY9i\nT/UElmXp4sWLlJaWRlqtlvz9/eUAFtC/RbgA7Pl8vtzR0ZFycnIoISGh04maI0eO0Nq1aw3OAAqF\ngtzd3Y3asr7++uvk7e1NjzzyCDU0NBi+9IqKCoqNjaXExESqq6uj7777jnx8fKiiooIqKipIIpFQ\nZGQkffPNN/TDDz9QUFBQh2PJ1NRUev311406Pxh7BlwXXeN6XnnlFXrxxRe7nNf1jB49mlatWtVh\nMLzOOH78OM2aNYueeeYZAkCzZs2ikpISKi0t7VE5TI1MJrvp96tSqSg/P98Qe6qmpsbsexizLEvZ\n2dl04cIF+umnn0gkEuX2R6vbL8Ll8/lvDR48WLN58+YuRzo4e/YsTZw40fB/T0/PDlu22tpaEovF\nhhZMo9FQYWGhYTb4+lhTDg4OhlZp8+bNtGzZMjp69CgxDEPvvfce7dmzh8LCwkxSo69YsYIAUGxs\nbIfPFhAQ0On11dXVtGHDBvL396fw8HBav349FRUVUXR0NHl5edHTTz/doxhYLMvSrl27aNq0afTg\ngw8SAHrhhRe6NRFnDpqamtp18Y2hjz2VlpZGERERlJOTY/byZ2VlUU5ODg0bNkzG4XDuoX+6cAE4\n2NjYtIwYMYJOnz59U9cqPXl5eeTg4GCoUfVj4xtJSEig8ePHt4mVnJeX1y4CAsuyZGNjY/iBn3/+\neZowYQJ99913ZGNjQ87Ozgan+SlTpnSpjJ1x5swZeumll9odLykpIYlEQi+//DLt37+ffv3113YL\n/9XV1SSRSGjNmjWUmppKZ8+epWeffZZCQ0NJrVaTVCqlCRMm0K5du3pVxpaWFrrzzjsN3eg///yT\nzp0716s8e0p9fb3Rrn5naDQaKikpodjYWMOEljmC+ul0OoqMjKQjR46Qvb19IQAO/ZOFa21t/R9v\nb2/d4cOHjUZa1FNfX9/GesbJyclg2bR8+fI2VlR64uLi6J133qHo6Gi6evWq0R9N3zXWVwQ1NTXk\n7+9P27dvpwULFtD69evbRL8wF6+88gqJxWIaNGgQTZkyhRYsWEBubm509OhRSktLo4yMDDp+/DgJ\nBII23UCWZemee+6h++67j+RyuaFiA9DOaKC7nDlzhsaMGWMwernZ72QO9EYuvUEmk1FmZiZFRUV1\neyjRFWprayk+Pp6GDRsm6+uxbl+3toydnV3l888/365VuR6WZembb74hV1dXcnZ2ppdffpnKyspo\n37595OvrS5s2baJDhw4ZzA/1sZJjY2MpLi6OpkyZQgcOHOhwvMOyLOl0Opo7dy65uLi0+Wznzp20\ndetWmjZtGimVSvr666/J3t7erMHPk5OT6ffff6fs7GxDeaOjo2n06NEUGhpKQUFBNGzYMPr222/b\nXatSqeiRRx6hoKAgOn36NOXk5NCYMWMIAH388cdd7s3ciH48PmHCBAJA999/f28esUdUVlZSdna2\nSfKSy+V0/vx5Sk5ONvmacGpqKn3wwQckFov/on+wcCc5Oztrtm7d2umX8fvvv5Ofnx+lpaVRZWUl\nPfPMMySRSOjZZ58lR0dHCgkJoWHDhtHevXuprKys3fj17Nmz5ObmRnFxcSSVSqmhoYEeeeQRCg4O\nJpFIZGhJbizHo48+Shs2bKC77rrLcMzckx29hWVZ2rdvH4WFhZG7uztxuVxDT+Hdd9/tUZ45OTk0\nYsQIAkB33XUXeXh4mLjUN6esrIxyc3NNmmdVVRVFRkZSfn6+ybrPKpWKjh8/Tnw+XwXAlf6JwnVy\ncjqyePFiOnz4cKdfRk5ODrm7u9NLL71kMLZPTU2lp59+ms6fP0933HEHTZkyhU6dOkUpKSkdRvBb\nvnw5TZs2jezt7cna2ppWrVpFCQkJlJiYSBs3buywNSotLaXDhw+3sZHuCP2ywF133UXHjh3r9Nze\nsnnz5g7HxsZobW2lw4cP086dO3vdPWxtbaWnn36aANBjjz3Wq7y6S2FhoVlC12i1WsrJyaGoqCiq\nqakxSZ4lJSV05513aqysrNbSP024AOwEAoFmzpw5XXqhSkpK6N5776U5c+a0m10sLS2lXbt2dVoB\nnDlzhrZs2UKFhYXdWrbJyspq043XaDRtlkhiY2MN+woBoF9//bXLeXeX5uZmsra2JkdHR6NGJOam\nubmZpkyZQnw+v8dxjntCTk7OTSvQ3qD3PkpKSup195llWfr000/J0dGxsq+WhvpMuB4eHi+NHTuW\nveOOO7r8hchkMtq4cSMFBASQTqcjjUZD6enpdP78eZo4cSIBoMTERJNOnly5coVKSkpIq9VSQUEB\n8fl8gyXU6dOnDYINCgrq8nJFTzl8+DDdcccdtHjx4nbbZfzTycjIoLq6OrPfp7q6miIjIyk3N7dX\n3WepVEoeHh66vto4rM+E6+vrW33fffd1aOjfGSzL0tChQ+nEiRMUGRlJxcXFhnHnu+++S1wul7y8\nvDqd7OoqSqWSkpOT6cUXX2xjvrh79246dOgQSSQSwv926uvKxI/erW7SpEn0888/0+XLlykuLo5i\nYmLo4Ycfprlz57bxgrqRBx98kLZt20aFhYXk7Ozc61nWWwlTBETvKjqdzrCJWG8CBb744ovssGHD\nYuifIlwAU3g8niYgIKDbdrk6nY6OHTtGW7dubTee1Ol0VFVVRbfddhslJSV1K9/r2bx5s2FS5+23\n36ZHH32U7O3t6dlnnzXsQePg4EC+vr60ePHiLue7a9cuAkAPP/wwzZw5k3x8fCgwMJA8PT3pvffe\nIzc3N9q/f7/R66dOnUoHDx4komvLRps2berxM95qxMXFdbrPkzlQKBSGnRp7YsBRWlpKfD6/BYAt\n/ROEa2VldcrZ2Zm1t7fv1jhJKpVSdHQ05efn09mzZ8nX15fkcnm789zd3Ttcu7xy5Qq9/fbbtGzZ\nMlq0aBElJyfTZ599Rhs2bKA9e/ZQU1MTrVmzxtCyTpw4kR566CHauHFjG0FptVpydXWlNWvWGEwo\nOyMvL49Gjx5NQqGQZs6c2aEZ4c6dO8nd3b3T/AICAgyOFx9++CE98sgj9O233/Y6OsatQGRkZL/N\n6NfU1FBkZGQ73+2uMGPGDBnDMCvoVhcuACsul6sWCAQEoEvO0SzLUn5+PkVHR7fxHV25ciXddddd\n7fxJJRIJVVdXG9Zoia5t6BQWFkbLli2j7777jl544QVydHSkmTNn0pgxY4jP51NSUhIB13adj4mJ\noddff50kEgm9+eab5O/vf9NydoRarabAwEDatWuXUVGyLNslx/aZM2caNiCrrq4mOzs78vPzowkT\nJrSbuNE/uz4YgVqtJqVSSQqFguRyOTU3N5NUKqXGxkZqaGighoYGamlpGbBbhXZ3tz5To9PpKDk5\nmbKysrpVgfz0008kFotTyMy6MnuUR4ZhJvJ4vHOtra1cAPj7778xe/Zso+e3tLQgPT0djo6OGD58\neJu4ySqVCi+++CISExPx/vvvY9KkSXBycoKPjw/Cw8Nx/PhxqFQq2NnZQSwW46mnnsJrr72Gy5cv\nY9++fdi/fz/s7OwgkUiwd+9ejB49GlKpFA4ODoZ7NDc3Iy4uDuPHj28TLKyrHDt2DPfeey86+14j\nIiLw5JNPIicnB1ZW/z9eHxFBrVYbokAePHgQgwcPhqenJ1iWhVarhZWVFQoLC2Frawt3d/cbv2uj\n4Vhv/Ku/l1qtNkRs1IdevT4M6/Xp+t9CD8uyUKlUsLW17fZ3ZQwiQnR0tCFoYH9BRLh48SIYhkFI\nSEiXgvqp1Wo4ODi0qtVqDyJqMFfZzB7lkcfjzdOLFgBcXFyMnltWVoYrV64gNDS0w+DUfD4fX3zx\nBT799FPs2rULjz32GKZMmYLa2loIhUKUlpaCYRi8+OKLUKvVOHPmDHbt2gU7Ozs89NBDyMjIgLe3\nd5s8rxctAIhEIggEgh6Jlojw3//+F59//nmn5xw4cABLlixBWVmZQaQKhQLANfHoI0Hm5OQgJCQE\nU6ZMaSOa8+fPo6KiArt27ep2GTsr1/VxllUqFWQyGWpraw1hWm8UuI2NDfLz87F161bs3r0bo0aN\nalMR9RSVSjUg9mViGAahoaHIzs5GWloabrvttg4rr+uxsbFBeHi4Kjo6+nYAP5utbOZucZ2cnC42\nNjaG6DdxUqlUHYbqrKioQHFxMcLCwrr84+fl5eHIkSPYuHEjXF1dcf/99yMmJgYCgQBr1qyBj48P\nAgIC4OPj060yx8TEYNKkSZ2WQ6fT4fPPP8fXX3+NOXPmYMOGDSgqKsK9996LgoKCNi2nPimV18Lx\nqtVqREZGoqamBsOGDcMDDzwAPz+/Ni+FWq2GWCxGY2Mj+Hx+m3tnZGRg4cKFyM/P71Ug9p5wo8Cj\no6Px888/4/bbbzcEp3d0dDSEZe2JAPsyGHpXycvLQ1NTE8aOHXvTkLc7duzAf//7331SqfQxc5XH\nrMJlGMaex+PVt7a2WgPA4sWL8fPP7Suh+vp6ZGVlYeLEid3e/qOpqQnbtm3TR5vHlClTMG7cuF5t\nI5KcnIxhw4bB3t6+w891Oh18fHzA5XKxZ88eHD161BCL18/PDzNnzoSdnV2b4OZ2dnbg8/mG7hbL\nsjh//jx++uknHDhwAOvXr8fChQsRGBgIADh+/Di2bt2KuLi4dvcnIsyePRujRo3C9u3be/ycpqC5\nuRlz584Fh8NBXFwctFotGhsb0dDQgIaGBqhUKtjb2xuELBKJbtpqlZWVQalUYujQoX30FF2jsLAQ\n1dXVGD9+fKeV+qVLlzB58uSa5ubmzoN89wZzDqABLAgLC5NGR0fThg0bOjRhk0qlFBkZOaD2mr3R\neupGVq1aRb6+vpSamkrp6ekUERFBp06d6jDQXVfIzs6mu+++m9zd3enZZ5+lpKQkmjFjBn3yySdG\nr7l8+TINGjSo2/cyB9u2bSMAFB0d3e4zlmVJKpVSUVERJScnU2RkJMXFxVF2djZVV1d36Oucm5vb\naw8nc6F3GezMR/t/y4cKAP50K84qC4XCz99//32jU3L6+Ml9tdDeVYqLi6mgoKDNMZZlqaGhgSIi\nIuiDDz6gyMhIunz5MtXV1ZlsZraiooJWrVpFw4cPpxdeeKHTyuzq1avk6Og4IGaF9cHUurrUp1Qq\nqby8nC5dukQxMTGGDclLS0tJLpdTWlpap4Yp/U15eTlFR0d3aoRz//33tzAM8yTdirPKYrG49PTp\n094d7amj0WgQHx+P4OBgSCQSs5WhJ9TU1KC2thb+/v6oqalBTU0N5HI5xGIxvv32W4SGhmL16tX9\nWkYiwoQJEzBx4kSsX7++3QzzrYROp0NTU5Ohe11XVwdPT0/4+/u3mzwcKNTU1CA7OxthYWEdjuP3\n7duHl19++c+Ghob55ri/2XakZxjGU6PRuI4ZM6bdZzqdDklJSQgMDBxQotVqtaiurkZZWRlKSkqQ\nlpYGjUaDYcOGYfLkyUhISMCnn36KoKCg/i4qGIbB0aNHodVqMWLECLzzzjsm2cG9P+ByuZBIJBgy\nZIhh5tbNzQ25ubmIiYlBUVHRgHs2V1dXBAcHIzExES0tLe0+nzVrFpRK5VSGYcyzraG5mnIAj9x5\n553trP9ZlqULFy50GHamv5BKpZSamkqRkZF06dIlqqysbGcAsHjxYgJAq1ev7lMvma5w9epVuvPO\nO2nEiBEm92HtK4qKiggAcTgc2rlzJ128eJGI2gaEu3DhQp8EhOsO+uFTRxZ9Pj4+zQDGkRn0ZbYW\nVywW371o0aJ2m8xmZWXB1tYWgwcPNtetuwQRoaamBgkJCbh8+TK8vLwwffp0BAcHG7qd9L9hxKVL\nlxAXFwcvLy/Y29ubZK3SlHh5eeHEiRMQiUTYsWOH2e4jl8vxwAMP4Pjx4ybLMyMjAy4uLggJCUFQ\nUBCWL18ONzc3BAcHA7i2LjpkyBBMnz4dAQEBKC8vR1RUFHJzcw1r3/2Jo6MjQkJCkJmZ2e6zu+66\ny8bKymquWW5sjtqAiODg4FB2Y7Cv/Px8SklJ6dcaU6vVUnFxMUVFRVFaWprRibGkpCSDu+ChQ4do\n8eLFpFAoBlRtfyOlpaXk4eFhNndDpVJpsOvubWA6PUePHiUvLy8KCQmhVatWUUVFxU33RtL7SOtD\nFfXXDgfXc+HChXaeRT/++CNJJJLTZAZ9maXpYBjGmsvluunXJIFra3O1tbWYMGFCv2zWrFarUVRU\nhMrKSnh6eiI8PLxT4wV7e3vIZDLY2dmBiNDS0jIgrHk6w9vbG6tXr8bChQvx448/YuLEiSbdOZ7P\n5+PIkSNYvnw51q9fD4lEgmXLlvUqz3vuuQdqtRrp6el46qmnIJfLja6f67GysoK3tze8vb0hl8tx\n9epV5OXlQSKRwNfXt18mtEaOHInExEQ4Ozsb1qmDgoKg1WqHm+WG5qgNAAx3d3c3jG9bWlooMjKy\nX8aGUqmU0tLSKCoqioqLi7tcM5eVlRn2ivH396eTJ0+auaSmoaCggGbOnGnwGzYHr732GtnZ2ZG1\ntbXBCcJUpKSk9Mj7iWVZqqqqoqSkJMMOB33dCufk5LTxKFIoFGRlZaUBYEWm1pipM6Rrwr1n5syZ\nBheezMzMPl1QZ1mWqqurKT4+nuLj4w2eQ91BKpXShQsXKDk5mby9vc1UUvOxa9cueuCBB8ySt06n\no1dffdXQbTblRGN0dHSvK3iVSkW5ubm9dozvLlqtliIiItqs77q5uckABNKtMDnF4XBGjB492ha4\ntsRSU1MDDw8Pc9yqDTqdDiUlJYiJiUF5eTlGjhyJiRMnwtXVtdvdczs7O9TX1+ORRx7Bm2++aaYS\nm49FixYhOjoaR44cMXneHA4HH330Efbt24clS5ZAKBSaJF8iAsuyvZ78s7GxQWBgICZMmIDS0lIk\nJib2yUQWl8tFYGAgsrOzDceGDx/OAjD5+qFZhOvg4DBm5MiRVgBQWloKb2/vm9qn9paKigrExMRA\nqVRiwoQJGD16NEQiUY/yamxsxMMPP4ycnBw899xzeOKJJ0xcWvPj6+uL06dP4+WXX8aePXvMco9H\nHnkEhw8fhqurq0nyU6lU7RwqeoNAIMC4cePg7++PCxcuIDc3FzqdzmT5d4SnpydaWlrQ1NQEABg9\nerQth8O5NYTLMExIUFAQiAilpaXw9fU1x20AXLPASklJQWVlJSZPnozhw4f36sevqqrCPffcA41G\ng3HjxmHZsmX9MplmCkJDQxEdHY2NGzfijz/+6O/i3JSmpiazTCy5uLhg6tSp4HK5OHfuHKqqqkx+\nDz0MwyA4OBhZWVkgIgQHB1s5ODiMNfV9TC5chmEYuVzuO3z4cFRVVcHJyalXnjqdUVNTg9jYWLi7\nu2Ps2LHg8Xg9zotlWezduxeTJ0/GxIkTcfDgQbi7uxtqzluVIUOG4MiRI3jqqacM69IDlRuDGpgS\nDoeDIUOGIDw8HOXl5UYtnkyBg4MD7OzsUF5ejuHDhwNAiMlvYupBM4BBIpFIQXQtBrE59p3RaDSU\nkZFBCQkJJvMqWrt2LY0ePbrN1iX19fWUnp5ukvz7m54E6utrzp8/32e7BNbV1VFUVBRlZ2ebZfZZ\npVJRREQEVVdXE4/HU8LE8ZbNsY4bFBgY2CqVSgVWVlaws2tnPNUrGhsbkZGRAT8/vy6HE7kZ0dHR\n+Omnn5Camtom8oZIJIJUKu11/gMBDw8PNDSYLZKKSVAoFH22Vi6RSDB16lQUFRXh3LlzGDZsGNzd\n3U02LLKxsYGvry8aGhrA5/OptbXVA0CFSTKHeca4foGBgVYFBQXw9/c3WaYsyyInJwdZWVkYN24c\n/Pz8TPIlJyYm4uGHH8bHH3/cLlyOlZUViMjsExp9QUNDg8krUVOiVqvB4/H6dD6Bw+EgICAA4eHh\nqKysRGJiIuRyucny9/PzQ1VVFby9vVsB+JksY5hHuCIHBweeTCbrUdymjpDJZIiNjQWHw8GkSZNM\n9gKmp6cjPDwcixcvxn333dfhOSKRCM3NzSa5X38ye/ZsHDx4sL+LYRSpVAqxWNwv9+bz+RgzZgwC\nAwORnJyMmpoak+TL4XBgbW0NkUjEAOjZEoexvE2ZGQBwOBwRAOvBgwf3uvYkIhQUFCA1NRWjRo1C\nYGCgSZeV8vPzAQBz5swxeo6joyMaGxtNds/+YunSpYiKiurvYhjFXDPK3cHJyQkTJ05Ebm4uKipM\n06uVSCQQCoXWADq34+wmJheuQCBwZlkWgwYN6lU+CoUCCQkJUKlUmDJlill+1MmTJ8Pe3h7z5xv3\nddYHbLvVqa+vN1kPyBw0NDR0GNmzr/lflEYUFRWhtLS01/lJJBIIBAJrDPQWVywW+zg6OvbKuF0m\nkyExMRGBgYEYOXKkSQ3lr8fBwaFN2FFj5/wTusqnTp3q9zjFxiAiKJXKAePEYW1tjQkTJqC8vByF\nhYW9ysvR0RE8Ho8LE7e4Jp9VFggEnr2JaqFSqZCSkoKxY8f22PKpO/eysbGBWq02GtCbYRjw+Xwo\nFAqTBv3uCizLQqFQGMK7qlQqg1ngzf7eeGzEiBHw9/c3dJf1z3Vjuj5mcl9NFMnlctjZ2Q0oQxcr\nKyuEhYUhJSUFWq0W13u6dTcfoVDICAQCk4Z6MblwGYZx6SzoeWdoNBpDmFNzixa4NqaZP38+nn32\nWXz77bdGXxxnZ2fU19ebRbg6na5d/OWWlhao1WpwOBzY2toaQrxKJJIu7VJw418Oh4MZM2ZAp9MZ\n5ghYloVarYZSqTQEPNeHU9X/H+hY4DfueNBbwQ2UbvKNcLlcjBs3Dunp6bh8+TKCgoJ69KwSiQRe\nXl4jTVk2kwtXoVCwPXEoYFkWFy5cQEBAQJ+NxRiGwYYNG3DbbbfB09MTmzdv7vA8iUSCkpKSdrsg\ndBWtVtuhODUaDTgcTpv4y05OThAKhSZdGikqKoKbm1ub/DgcDgQCwU27p9cLXK1WQ6VSobGxsc2O\nB7a2toa4yWKxuNtDm4aGBvj5+fXk0cwOh8PB6NGjcenSJVy8eBGhoaHd/l28vLzQ2trac7O+DjCH\ncKm7wiMipKWlwc3NrdeTWt2lvLwcALBlyxajwhWLxbh48WKX89TpdGhoaEBNTQ3q6urAMEybAOnO\nzs4GcfYFR48exbx583pUEdxM4EQEhUKBhoYGlJWVITMzExwOB05OToYdDW5mO25OU0dToN87KDs7\nG6mpqRg9enS3Vjfc3Nwgl8uNT6T0AJMLV6vVCrvbzb18+TL4fD4CAgJMXZybMnHiRADA3XffbfQc\nDocDHo9n1HuFiCCXyw1hXVUqFZycnODq6ophw4b1a4yqsrIy7Nq1C0ePHjVL/gzDGCokfY9Eo9Gg\nsbER9fX1KCoqgkajgUgkMrTK9vb2hkpErVbD2tra7N5jvYVhGIwYMQL5+flITk7u0lYkekQiERiG\nMekitcnfKJ1Ox+/OWLCgoAAqlQodhXHtCxwdHZGXl4fp06cjMTEREyZM6PA8iUSCuro6eHl5AQBa\nW1tRW1uL2tpaNDY2QigUwtXVFaGhoW3Gwvn5+Th58iT+/vtvWFtb44EHHgCXy8WsWbPMPiRoaGhA\nWFgYXnjhBXQU29pcWFtbw9XV1eDux7Ismpub0dDQgLy8PMhkMvD5fDg5OYGI+s3woicMHToURUVF\nSEpKQlhYWJfEyzAM7O3tTdoqmVy4XC63VaVSdenciooKVFdXIzw8vF9nFIcOHYrXX38da9aswS+/\n/NLhJmESiQRXrlyBXC5HbW0tgGvuYj4+PggNDW3XYjQ2NuKNN97A0aNHsWjRIjz22GOQy+X46aef\nQERYuXIlFi1ahMOHDxuuqaysxKhRo1BeXm4Sj6r9+/dj5syZWLduXa/z6g0cDgdisRhisdhgBqtU\nKg1C1mq10Ol0/RYvqrsMHjwYOp0O+fn5eu+fTmFZFkqlstykhTClx8L/as/irnjU1NbWUnR0dKd7\nsPQlWq2Wnn/+eZo1a5ahTFqtlkpKSigxMZEiIiLojz/+oLKyMlKr1UbzqayspEOHDpGnpyc9/fTT\nRje3zszMJAC0ZcsWw7EVK1YQAJN4JCmVSvLw8KALFy70Oi9zEhkZSa2trVRVVUWJiYkUHR1NBQUF\nnX7HAwGdTkdRUVFd8mY6dOgQSSSSP2ggewdxuVzZzQwWmpubkZmZiQkTJpjNV7e7cLlcbN++HXPn\nzsXevXsxffp0VFZWwsPDA0FBQbCzs0NycjLs7e2NTipt2bIFmzZtQlhYGH788UdMnTrV6P1GjhyJ\nitTu2hEAACAASURBVIoK3H777XBwcEBDQwNOnDgBhmFQWlqKUaNG9ep5YmJiMHjwYIwbN65X+ZgT\npVIJGxsbWFtbw83NDW5ublCr1SgrK0NCQgKEQiF8fHzg4uIyoNZ4gWu9iKCgIGRlZd10GCKTyaDT\n6UxqfmeOdVyZTCYz+jnLskhNTcXYsWMHjKWMHqVSieeffx7V1dXg8/mYNm1amzGMq6srampq2q0x\nK5VKbNiwAX/88Qfy8/O7HF/Lw8MD27dvx9q1a1FXV4dNmzbh2WefxaJFi1BZWdmr/YA+//xz3Hvv\nvT2+vi+ora1tt9G5jY0NAgIC4O/vj6amJpSWliIrKwseHh7w8fHpcyOYznB1dUVRURHq6uo6na9o\nbm5Ga2urSX0qTT6VR0TSzoRbWVkJFxeXm8bO7SuI/v+OBllZWZg0aRIOHDiA/fv3t5t4cHV1RXV1\ndbs89u7di+TkZMTHx3c7KN6cOXOwYsUKhIeHt1mO+uqrr3rsYlZSUoK4uDg8//zzPbq+txQXF0Oj\n0dz0vI6Eq4dhGDg6OmLUqFGYOnUqhEIh0tLSEB8fj7KysgHjanl9mBpjVFVVwdXV1aStlDlmlRs7\n6yoXFhYOiO6bTqdDWVkZiouL4eDggJEjRxpa0p9//hlhYWGYNm1aG/tegUAArVYLrVZrWOKRyWSI\ni4vDXXfd1aNZYisrK6xfvx4AkJ2dDQ8PD6xbtw5///03Dh8+jPj4+G5P2MTExGDGjBl9vls9cO17\nHTx4MB5//HF88803Rs8jIjQ3N3fJQq6jAOj5+fmQSCTw9/fvVz9joVAIFxcXFBcXG91Wp7q6Wmdq\nS0CTt7gajabRWIvb0NDQJWsdc6JWqw27wCmVSoSHh+O2225r8wJ5eHjg3Xffxccff9zuemdnZ1y5\ncgXr16/HkiVL4OfnB6lUikcffbTXZQsKCoJYLMYXX3yB2NhYjB49Gp999lm388nLy+uxbW1v4XK5\n8PT0xN69ezstu36XiJ6EzQ0KCsKMGTPg5uaGtLQ0ZGVlQavV9rboPSYwMBDFxcVGdxSUSqWkUqlM\nFv0CMINwlUplvTHhmjoqRneQyWTIyMhAQkKCYfw6fPhwo63SrFmzcP78+XZdstzcXHz22WeQy+W4\n5557kJKSgj/++MMs+9M++eSTOHjwYIfdTrVajatXrxr+39LSgs2bN2PFihX48ssvERoaavLydJU1\na9ZgzJgx2LZtm9FzampqehXWlWEYuLm5YcqUKRAKhTh37hzKy8v7JSCelZUVhgwZgtzc3A4/l8lk\nTFNTU+99BK/HlFPURARfX9/tTzzxRLtQ9C0tLRQTE9Pl6XZTodVqKTMzk86dO0dVVVVd3tGgvr6e\nbG1tqaioyHAsNzeX3N3d6dixY32y+ZdWq6UFCxbQ3Llz6bfffqO8vDzS6XRUXV1NAIjH41FrayuV\nlpbS4MGD6cEHH6R9+/b1+xJQRUUFASCGYYyeExsbS0ql0mT3VKvVlJ6eTnFxcSSVSm9+gYlhWZbO\nnTvX4b3Hjh2rA3AnDeTlIDs7O01HoT+Kior6vLWVSqVIT0+Hl5cXJk+e3K1uWUJCAtzd3dHY2Ahf\nX1/IZDKsXLkSTz31FLy9vdHY2Pj/2jvz+KbrPP+/vkmPJL1PKEdLoYBQ7lpaKOAouuqgoz6GEQFn\nXS9cZscdj9WZ1XV/DI6ozCpeC67MeMwwzigqoDszopK2NG2h95HSIz2TXqTN0TR38v2+f39gvkvb\npGfStJrn4/F5QJPv8c73+3l/zvfhc48WoVCIzz77DG+++SbeeustNDU1wWq1IioqCjt37oRSqUR6\n+hWnk3/5l3/Bk08+6VN5xktSUhKuu+465Ofng2EYOJ3OIQt9drsdHMd5Nfh5SEgI1q5dywcTjImJ\nwfLly6dtu5FhGKSnp6Ourm6IQdG3DhocAM8rtpPBm60AESE+Pv7HGzZsGBLv0uFwkFQqJZZlp960\njQOO46ixsZHy8/M9ptEcC5PJRA8//DAtXryYFi1aRBEREXTPPfcQy7LU3d1Ncrncy1KPD4VCQZ98\n8gn/LL/44gs6fvy4X2QZjf379/O5hdRq9ZDvlEolNTQ0+OzeHMdRe3s7SaVSUqlU05oataKignp7\ne/m/1Wo1xcXFOQAsIi/qmdcVF8DihIQE9uqH1dLSQgqFwqsPyBNGo5EKCgqovr7eKw0Fx3FUWVlJ\ner2e/8zpdFJubu6MzpXrb370ox/R73//e4qNjaUTJ05QdXU1NTY2EtGVXLJXP09fYbPZqLq6mmQy\n2bQNny9fvjykUa+qqqKQkBAnAAHNcMUVhoSEcK4saRzH8WZtvoTjOGpra6Pc3FyPZobepKSkZFoq\nnycGBwfp97//PZWVlRHLsiSTyejjjz8mjUbjN5mIrryHwsJCiomJIa1WS5WVlbRixQoKDg4mAPzo\nazobPZ1ORwUFBVRTU+Pzemg2m6m4uJj/+49//CPFx8d3kpf1zOtzXCJi582bN1BZWRl98803+zwN\nCXAlBE1VVRUkEgm2bNkyLW508+bNQ09Pj9+M4qurq/HYY48hPj4eOp0O8+fPh16vx7PPPov9+/f7\nRSbgiu/vz3/+c7z66quIiYlBTEwM5HI5HnvsMTidTn5tYDpNGKOjo5GTkwOVSgWZTIYNGzb47L2J\nRCJc7WTzbea+am/fxydOkBKJpK22thbAFUd1Xyb96urqQnFxMRYvXow1a9ZMm++rJyuq6WL9+vWI\njo7Ge++9h4qKCtTW1uKf/umf0N/f7zeZ7HY7UlJSwHEcXHHHXnnlFURGRuKzzz7DgQMH0Nvb65Ot\ns7FgGAbJycnIzMxERUWFz7I6MAwDoVDIG+p0dHRAr9eXevs+PlFci8VSdOnSJQKuOFV7c/XQhStL\nX29vL7Zs2eK1VI/jJTg4GCKRCKOZd/oSiUSC//zP/8Qbb7wBVwzr4uLiaY8gAlxxYdy0aRMiIyOx\nYcMGvP766zh27Bi0Wi1ef/11nDx5ElVVVUhISEB/f79HM8fpIDw8HFlZWaipqeHdM31xj8HBQWg0\nGqhUKrvT6azz9j18oriXL1+WNTU1ERENCVDmLRwOB79dk5GR4TcPowULFqCzs9Mv9waAW265Bfn5\n+VCr1Th58iSkUiluv/32aZXB6XTiqaeeQnx8PGw2G4KCgvDyyy9j7dq12LFjB3bu3IlbbrmFH9JH\nRUX5PdqFRCJBdnY26uvrfZJyMyIiAoODg1Cr1WhtbWUBNHj9Jt6eNNOVBao1CxcudAwMDFBeXp5X\nt4FYlqWioiLq7Oz02jUni9PpnPaFluE88cQTtHr1agJAt912m08yz43GM888Qzk5OdTb20uffPIJ\nhYaGEgBKSEig+++/f8izqampGbJV4m9sNhudP3+eVCqVV6/rWln++uuvKSgoyAlARDN9cepbFL29\nvYLu7m4QkddaWCJCVVUVEhMT/TIkHI5QKER0dDS0Wi2mEkt6Krzwwgv8VCEnJ2fa7ms2m3HgwAGc\nPHkSFy9ehEQiwdGjR3HPPffg5ptvRnR0NG6++WZ+EYqI0N/fzxuMzARCQkKQnZ2N0tJSOJ1Or0Wa\njIiIgEKhQF9fHyQSSf/AwMD4QsJMAJ8oLhFZoqKitJWVlfGTCdXqifr6eoSEhPglqJwnXMNlfymu\nSCTi/W5drbErCPrV/3cFSQfAO69PZmW3u7sbp0+fxosvvojs7GyUlJTAYrHg1ltvxbp16/DOO++4\njcOk1WoRHR3t92HycFxZC8rKyuB0OpGWljbla4pEIhiNRuj1egQHBzd5QcwR+GwJNigoqFIul9/k\nrRXEtrY2mM1mZGRkeOV63iI+Ph5yuRwsy3o9VYrD4XAbj3k0T5irg6C7C5DOMAxsNhvvySIQCNxm\nNHAFO3fFdyYivPLKKzh06BC2b9+OTz/9FOvWrcOHH36Ihx56CNnZ2fjd737nsTHo6uqaEaMkdwiF\nQn61uaGhAcuXL5/SdhXDMGBZFk1NTazJZCr0oqg8PlNcnU53qrq6+vrrr79+yvfo7u5GT08PsrKy\nZlwIE4Zh+MgYEx1dEBEcDgeMRuMI5eQ4zpW+gi+JiYkICwvz6mIcy7JDshdYLBYYjUb+M7vdDiJC\na2sr7HY7zp49i7S0NERFReGXv/wlCgsLcejQIaxatcrjuyEiaDQarFq1ymtyexuBQICMjAxUV1ej\nrq4O6enpk65rdrsdDMPg73//u9VqtX7pZVEB+FBxiejroqIi9mc/+9mU7qHRaKBQKLB582afJf+a\nKgsXLkRDQ8OYiktE0Ol0fFhXp9OJ4OBgPlh6VFQU5s2bB4lEMm370UKhkG8YPHHkyBF89tlnOH36\nNIxGI9rb2/lIJq+99hqSk5NHdbjo7+9HTEzMjBsmD4dhGKxduxZVVVVQqVRuo32Oh87OTjidTrS3\nt4cAKPaulFfwZe1ocTgcg21tbaGTHUYODg6itrZ2RgWVc0dkZCTfYw3377VYLFCr1VCr1TAajYiO\njkZiYiJSU1OnLZPBVOno6EB/fz8+//xz3H///VCr1Xj88cdx4MABJCcnQ6vVorm5GU6nE1FRUXzg\nc5ejvFKp9BgdYqbBMAxWrVoFmUyGpKSkSdW7zs5OVFdXIyoqqvLy5cvuveuniC97XIqNjf1GLpff\n09vbO+H5jcViQXl5OTZs2DDjgsq5Izk5ma+gGo0GarUaGo0GoaGhfEaDqyP4zyYOHz6MO++8E/ff\nfz8OHz4Mg8GAAwcOYPfu3QDAW0JxHIeBgQFotVrU19fDZDJBJBLBYDBg5cqV/vwJEyI4OBipqalo\namqa8Cr4wMAARCIRLly4wGk0mo/GPmNyMES+ixgQGxt737Jly35/5MgRoSvVx3i5ePEiFi9e7Fcr\nm/FAdCV2Um9vL5qbmxEeHo64uDgkJiYiLi5uxg7vJ4PVaoVcLseKFStGHVq7ICIoFArodDrY7XaE\nhIQgJSUFiYmJM37YTEQoKCjAhg0bJhTTqra2FgkJCVi3bh13+fLltUQk94V8Pp1Imc3mv9bU1Ajs\ndvuE8ssajUY4nc4ZrbQcx6G7uxutra0Qi8V8XOCUlJQZLfdUEIlEEwr0xzAM1Go1H4rXYDCgo6MD\n9fX1SExMRHJy8oyJ9jmcqx3jPaWlGQ7Lsujv70dQUBCsVisHwOumji58qrhWq7U/Jiampb+/P02l\nUmH58uXjOq+1tdVvsanGwm63o6OjA52dnZgzZw4yMzP5oXxkZCQUCsV3VnEnitFohFAoHPJ8Vq9e\nDY7j0Nvbywd5W7hwIebPn+/X5GjuiIuLQ1tb27jjY3V1dWHu3LkoKCgAwzBfkA+Hsz4fr9hsti8q\nKipYlxXVWDgcDmi1Wr94kIyGyWRCTU0NioqKIBQKsXXrVqxcuXLI/Ds6OppPFB0AUKlUbnMKCwQC\nzJs3D9nZ2cjIyIDVaoVMJkNlZSW0Wu246sl0kZ6ejkuXLvHGK57gOI7vcD7//HOjXq8/40u5fDrH\nBQCGYW5cvXr1p3/6058iY2Njx1ykam5uhkAgmBE9LhFBq9WipaUFDocDixcvxty5c0ddYHIFA1+6\ndOk0SjrzICLk5eWNyAYx2vEajQYdHR0YHBzE8uXLx3zW00VjYyOCgoJGtdhTqVQwGAy45pprEBUV\nZTOZTEuIyLuJvq5iOlYIZAqFIkgkEqG5uXnU1pTjuCntn3kLjuPQ1dUFmUyG9vZ2LF26FDk5OUhK\nShqzIs2fPx+dnZ0zqtfwB2q1ekKLcwzDID4+HhkZGcjOzkZPTw8uXLgw6WwO3iQtLQ0qlQo2m83t\n90SElpYWpKWlITc3F0FBQZ2+VFpgGhSXiKzBwcEf//nPf2ZjYmLQ09Pj8dienh4kJib6da7T39+P\n8+fPQ6/X49prr0VGRgZiYmLGfX5wcDASEhJG/Z3fB9ra2iZttC8SibBhwwYsX74cFRUVuHTpkl8D\nnguFQixbtgwNDe6987q7uxEfH4/Q0FAcO3bMbDQa3/C1TNOyJj84OHj02LFj1iVLlkChUHjsjdra\n2vy2Uc+yLORyOZqampCVlYX09PRJ7x8vXrwYra2tXpZw9mAymcCy7LjSi4xGbGwstm7dCrFYjIKC\nAox3ncQXJCUlQacbmXCPiNDc3Iy0tDTodDr87W9/E7Is+ydfyzNdm2llZrO5r6SkBNHR0W57I51O\nh9DQUL9kY9Pr9ZDJZBCLxdi0adOUDT4kEglCQ0PdvujvA+3t7V5zkWMYBqmpqdi8eTOfnM0fUUdc\njhrDM1t0dXUhNjYWIpEIH374IUQi0ddEpPG1PNOiuEREJpPpjWPHjpmXLVvmdq7b0tIy7e56HMeh\nqakJtbW12LBhA5YsWeK1xZAlS5agpaXFK9eaTbAsOymHi7EIDQ3FunXrsGLFClRVVaGurm5cGQG9\nSXh4+JA5t8PhgEKh4Lc533zzzUG9Xv/mdMgybeYrLMue+OKLL4R2ux3R0dEjQr4YjUafZwYYfr+i\noiJwHIecnByvGwLExsbCYrHAbDZ79bozne7ubiQlJfnMMiomJobPFySTyaDR+Lxz43GFpHHR0NCA\nxYsXIyQkBFVVVejs7LQDODcdskyb4hJRn0gkyv3LX/6CFStWoLm52WN2Mx/Lgba2NpSVlSE9PR3X\nXHONzyrZ4sWL0dbW5pNrz1Ta29t9GtUTuDJsXbRoEbKzsyGXy6ct2ubVijswMICBgQF+B+T48eN2\nlmXfIaJpSdw7rQajer3+jTfffHMwODgYS5cudcWcnTbsdjsuXrwIo9GIrVu3Tmi1eDIkJSVBrVZP\n+5DOX2i1WohEomlzChGLxcjOzkZTUxO6u72axdItLsUlItTW1mL16tV8YII//OEPnNVqPe5zIb5l\nui29v2pra3PK5XLMnz8fJpOJt5Tx9UY7y7IoKSlBSkoKVq9ePS3G/wKBACkpKd+bXte1ujqdhIaG\nIjs7G21tbVAqvZvJcjgSiQRmsxlKpRLR0dF8UPUzZ84gKCioloim7UVPq+ISEetwOL546KGHWIZh\nsGbNGsjlcjgcDp96ixARysvLsXDhQq8vmoxFSkoKurq6/LoPOR0YjUY4HA6fj2Lc4Yob1dXV5dNt\nOFfn0tLSMsTu/o033jAODAz4fO/2aqbdt8rhcLxSVVXF9vT0IDw8HImJiWhra/NZD0hEqKmpQVRU\nlM/nXu4QCoVITk7+zve6/tgVuJqgoCBkZWVBo9Ggqckn8dlARLBarVi8eDHvYF9cXIyqqiorEZ30\nyU09MO2KS0Q1wcHBv3/hhRfsALB06VJ0d3ePacQ9WVwGH8uWLfPJ9cdDSkoKH87ku4jNZoNer8ec\nOXP8KocrbpTRaERdXZ3XjTUUCgXCw8OHRMV4+umnjVar9Vkicm8P6SP84s1sNBoPvvvuu2xnZyeE\nQiFWrFgBg8Hg9YqtVCqh0+mwZs0avxqrBwUFYcGCBejo6PCbDL7EZd44ExwCBAIB1q9fD5ZlUVfn\nPXdYV1STqKgoXnELCgpQVVVlZln2Pa/daJz4RXGJqFcgELxz8OBBG3Bl0h8eHg5XojBvoFaroVQq\nkZGRMSOiLaSmpkKpVI6wvJntOJ1O9PT0YMGCBf4WhYdhGKxevRpGo9Eryb3sdjtqamqwYcMG6HQ6\nfh7/1FNPGS0Wy6+IaNq3DXzu1ufxxgyTIBaL2+vr6yWRkZHo6OgAy7JITEx068M5EfR6PaqqqrBp\n06YRwdv8SVNTE4KCgibtsshxHMxm85AwrhaLZUjQ8+HBz4fjSlbmKY7yRB08WlpaQETTvpo8HoxG\nIyorK7Fly5ZJjwaICKWlpViwYAESExNRWFiI6667DlKpFHfccUeP0WhMJqJpnwP5zQ2HiPrCwsKO\nHjhw4OdvvfWWyGq1IiMjA4WFhYiOjp60JZMrTUlmZuaMUlrgikFGQUEBFi5cOGr0QIvFgoGBgSEK\narPZwDAMJBIJP0JJSkqCWCweNQD61bjiOLtiJlutVphMJmg0GthsNlitVn5EEBkZibi4OMTExHgM\ncud0OqFUKrF161bvPigvER4ejpiYGCiVykkvTCoUCojFYsybNw99fX2IjY0FEeGpp54ymkymp/2h\ntIAfe1wAYBgmViwWq+RyuaSrqwuZmZmw2WyoqqpCTk7OpNz7uru7odVqZ2zw7ba2NthsNlxzzTX8\nZyzLDokMGRwcjJiYmCHB0ENDQ6dtDnl1tEatVguj0QixWMyHXY2OjkZQUBCam5sBYEb2ti4cDgdk\nMhm2bNky4VCrKpUK3d3dyMzMhEAgQGNjI8LDwyGXy/GTn/xENTg4mDpdllLD8aviAoBYLH4xJyfn\n8ePHj4dyHIclS5ZApVKhq6sLGzdunPD8VCaTYf369eOKQugPOI5Dfn4+Vq1ahYGBAajVatjt9iGR\nIWda7CUigsVi4RXZ5fVkNpuRlZU1rTbmk6GjowNGo3FCoVb7+vpQX1+PzZs38++jqKgI69atQ1ZW\nlrGuru4hjuN8Fn51LPyuuAzDJAuFwpaysrIgg8GAbdu2AbgyHzSbzVi7du24exqdTgeFQoGNGzf6\nUuRJo9Pp0N7ejr6+PggEAixduhSJiYmzIm70cBobG2EymeBwOGC327FgwQIsWLBgRgaun2ioVYPB\ngIqKCmRnZ/NJ2V0NrtFoxN69e9sHBweXEJFv9jDHgd+XW4lIGRwc/O/79+83hYaGYmBgAMCV/V2B\nQDChzfTW1tYZlckPuFJpenp6UFhYCIVCgYULF+LGG29EaGgo4uPjZ6XSOp1OdHd3Y82aNcjKykJm\nZiZYlkVhYSHKy8vR19c3o0L3uLITyOVjhzi2Wq2oqKhARkYGr7TAFWUOCQnBvn37zCaTab8/lRaY\nAYoLAFar9cilS5faz58/Ty53P9eS/sDAwLj2Py0WC0wm04wZtjmdTrS2tiI/Px/9/f1Yt24dNm7c\niPj4eAgEAlxzzTXT7mThLdra2rBw4UJ+CCkSiZCWlobrrrsOqamp6OrqQl5eHhobG2dMxMvY2FgE\nBQWhv7/f4zF2ux0lJSVYtWrViMVRjUaD48ePO81m899YlvVJIq8J4e1M2ZMtAFaFh4ebP/rooyEZ\n7J1OJxUUFIyZybyuro6USuWox0wHZrOZ5HI5SaVSUigUZLfbPR5bXFxMGo1mGqWbOjabjaRSKTmd\no2e+dzgc1N7eTrm5udTU1DTknfqLzs5OamxsdPudzWaj/Px86u7udvv97373OwoLCxsEEEczQV/8\nLcDVRSKRvLBlyxZHT0/PiIeal5fnUXkdDgdJpVK/Vg6WZamuro7y8/NJpVKNS5bBwUHKz88njuPG\ndQ+z2Uz9/f1TFXVK1NbWTqiBdDqd1NjYSLm5uXT58mUfSjY2AwMDVFZWNuJzi8Uyav3SaDS0cOFC\nlmGYu2kG6AkRzYyhsguz2fzruro69bvvvjvk85CQEGzatMmj32V/f79f89EYDAbIZDKEhIRg69at\nWLBgwbhkceUZGq8p5JkzZxAfH+8x2qCvcblhTsRKyhUhcePGjWhvb0dpaSksFosPpfTM8NAzwJUp\n1sWLF7Fy5UqPttZPP/00EVElTbMjwaj4u+UY0ZIIBBujo6M5d0MWu91OMplsRIuvUqmoqanJbWvp\nSziOI4VCQfn5+TQwMDCpa7hGCzabzeMxvb29dOLECdq8eTMBoJycHLpw4QK999579Itf/ILuuusu\nuv766+mOO+6g8vLyyf6cMSktLSW1Wj2la1y+fJlyc3OpsbFxzOG2L8jNzeVHOGazmXJzc0cdxRQW\nFlJERIQzODh4Hs0A/XCVGdXjAgDLsiUpKSl5DzzwwAiLFJffZWdn5xA3OU/5d30ZDdBkMqGoqAgO\nhwNbtmyZdCjSoKAgt9FAFAoFjh07hv/4j/9Aeno6Tp06hb1790Kj0SAzMxP79u3DN998g3nz5mH3\n7t149tlnkZKSgn379sFkMnnjJw5Bq9V6JRFbYmIitm3bBoZhUFhYOO2LVy5neKPRiIsXL2LNmjWI\ni4tze6zT6cSDDz5oW7JkyW/tdrvvQ2xMBH+3HO7KvHnzwhMSEmx/+ctf3LaCTqeTLly4QAqFgoiI\nWltbqb29fcgxn3/+OQGgY8eOeWxNJ0tHRwfl5uZ6bWGJ4ziSyWSk1Wppz549NHfuXIqOjqYHH3yQ\nfvGLX4x7NDEwMEB33303xcXF0aOPPkr/+7//SyaTib744gtyOBxTlm+yowpP9PX1UW5uLplMJq9e\ndzQuXbpEDQ0NlJubS3q9ftRjX3rpJWdkZOQFfGvvMJOK3wXwVK699tp/jIuLc3ha0GBZlsrLy6mq\nqoqamppIpVIN+f6///u/CQAlJCR4fjOToKOjgy5cuDAlRSAievPNN+nuu++mU6dO0YkTJ6i4uJg+\n/fRTWrRoEalUKhocHJz0tZubm+mFF16g6667joKCgggA3X777ZMe5qpUKqqqqpq0PKOh1WpJKpVO\n6feOF47jqLy8nL766iuyWCyjHltTU0NhYWFWAItpBujD8OJ3AUYrYWFhv924caPJ05aKa4751Vdf\njehxiYhOnTpF77//vttzJ0Nvby8VFBRMWWk//vhjSkhIoOeff562bt1Kt912G61du5Z+9atf0V//\n+lcvSXsFu91OVquV9u/fT5GRkbRnz55xr2K7zh9rDj5VBgYGSCqVjtkDTgWWZamqqoouXLhApaWl\nox7b399PSUlJJqFQeC/NAD1wV/wuwKjCAYLIyMhz+/bts472oEtLS+ns2bOk0+lGO2xKaLVays3N\nnXAF7urqotOnT/MNi81mo+3bt9Obb7454lin00l5eXlkNBq9IvNwLBYLrV+/nh5++OExexwXNTU1\n1NHR4RN5rmZwcJCkUqlP9rWtVivJZDJSKBSkVquppqbG47EOh4NycnJMYWFhr9MM0AFPxe8CjCkg\nEBUeHq585513PHYTrr3FvLw8nxhhGI1Gkkqlk5qLvfTSS/yQffXq1bR8+XL68Y9/7NEwQ6PRx18q\n7QAAGJBJREFUkEwmm1CvOBEMBgPddNNNFBISQsuXL6cHHniAmpub3R6r1+upoKDAZ7IMx2w2k1Qq\n9WrDpdFoKDc3l9+jbWhooM7OTo/HP/roo7bIyMgCAEKaAfXfU/G7AOMSElgukUgGCwsL3T7smpoa\nUqvV5HA46OLFi1RTU+O1rQar1TquhQxPfP3117Rt2zZyOp1UWFg4LoOL2tpaamtrm9T9xovdbqea\nmho6ePAgzZkzZ4RhAsdxVFBQ4NPhqzv6+vro4sWLU74Oy7JUX19PBQUFQxqCwsJCMpvNbs95//33\nufDw8C4AMTQD6v1oxe8CjLcIBIIfxsTEmIcvQhFdmXu6hj+ueW9eXp5XKl1ZWRkNt+SaCNXV1QRg\nQkNsh8NBubm5HiuYt9m5cyf927/925DP2tvbqba2dlruP5ySkpIp7RcPDg5SQUEBNTQ0DLFgY1mW\npFKp23MuXrxIEonECCCdZkB9H6v4XYCJFLFY/B/p6emm4RXa9UKufkkDAwOUn58/4uVNBLPZPCGT\nxOFUVFTQ0qVL6R//8R8nPALo6+ujwsJCnw9T33jjDVq+fDl1dXXxn7mGrKPZWfsSk8lEeXl5E35v\nHMfx9tFarXbE9zqdzq2BSnd3N8XFxZkFAsEdNAPq+XiK3wWYkLAAExkZeeaee+6xDK/QtbW1IwzE\nXcOl8+fPT2q7YbKOCxzH0WuvvUbh4eH0q1/9atLKJ5fLfWYR1tDQQLt27aJ58+YNGZZzHEfFxcV+\ntyuur6+nlpaWcR9vsVjowoULVFVV5XHVv7m5ecQUxGq10vr1600SieQ3NAPq+HiL3wWYsMBAWERE\nRNPBgweHvB29Xu9xbqTT6SgvL49aWlrGrUSTcVz4zW9+QwDo3nvvpUWLFpFcLh/3ue5gWZbOnz/v\ntvcguqJkFouF+vv7qaOjgy5dukQ1NTVUXV1NlZWVVFFRQWVlZVReXk5yuZyam5ups7OTPvjgA1q+\nfDn9+te/HrFQ097e7rM924kwHlNQoivPqLm5ecgClCdKSkrIYDAMOfeee+6xREZGfglAQDOgfo+3\n+D0CxmRgGGZeWFhYyTPPPDPnmWee4eO85OfnY9OmTQgJCRlxDsuyaGxsRH9/P1auXIn4+PhR79He\n3g673T6hQOrd3d2YP38+7rzzTrz++ut8JrepYDQaUVZWhpycHDAMw8emcuVcCg0NHRKbKigoaETA\nOCLig8EVFRWhpKQEO3bsgEAggEgk4mNJiUQilJWVTSo+ky9oamqCRCLx6NTQ19eHS5cuYe7cuUhL\nSxs1GwYRIS8vDz/4wQ/AMAw4jsN9991nPXPmjHxwcPAHROR9O1EfMisVF3CvvM3NzRAKhUhNTfV4\nnivKvUAgQHp6OiQSyYhjiAj5+fnYvHmz20bAE5WVlbjxxhvR3NzstRw6NpsNNTU10Gg0EIvFQ2JT\nTTRti9VqRXJyMr755husWbMGAPhYUhqNBiqVCuHh4Vi6dCnmzp3r93jUvb290Ol0WLFixZDPLRYL\n5HI5iAirVq1y+w6H09HRAYPBgNWrV896pQX8GJ51qhBRN8MwGw8dOlQCYM4zzzwTtGDBApSWlo6q\nuOHh4cjKykJfXx9KS0uRmJiIpUuXDgnQRkQQCAQTUloAeP/993Hrrbd6RWkHBwfR2toKnU6HlJQU\nEBGSkpKmFHP6woULSE1N5ZUWuJKqcv78+bDb7Vi4cCEfuL2xsREJCQlISUnxetLv8RIRETEkA58r\nqkh3dzdWrlyJxMTEcV3HYrGgra0NW7Zs+U4oLYDZN8cdXgDMCwsL63zhhRccRFeiSniaEw6HZVlq\nbW0lqVRK7e3t/HzW5T44UUpLSykuLm5Kq7EDAwNUXFxMhYWF1Nvby8/J7Xb7lLe4zp49S0uXLh2x\nwq3X6ykvL2/I5yzLUk9PD8lkMqqurvapyaMnOI6j3Nxccjgc1NTURFKplJqbmye0Qn/1YhvLsnTv\nvfdaIiIiSgGE0Qyov5MtfhfAKz/iKuU1Go2Um5tLVuuoVpJDsNlsVFdXR1KplFpbW8lkMlFRUdG4\nz7+abdu20cGDBye8kny1b68n083BwcEJ/zYXJSUl9MQTTxAAKigo4D+32+2Um5s7ZNFmuFxKpZJv\n3KbLioroygLVl19+SefOnZuwwrpQKpVUWVn5nVJa+q4oLg1T3suXL5NMJpvwPqDdbqeGhgb65ptv\n6Ny5c5NyJlAqlbR27Vp67rnnxn2OyWQimUxGdXV1Y8rc29tLhYWFE/ptBoOBEhMT6fHHH6dPPvmE\nHxFwHEdlZWXj2vJyWVpduHDB5w7wdrudGhsbSSqVetyTHQ8Wi4WkUilZrdbvlNLSd0lx6SrlPXjw\noKOpqWnS2xouhwKpVEoNDQ0THiZKpVLKzs4e17Emk2nCxvWNjY0Tsmp65ZVX6I477hjxeXt7O1VU\nVIz4/Ny5c6RUKunSpUsEgIqLi4ecI5PJfGKcYTAYqKamZsiQuLCwcNwOEcMpKSkhpVJJe/bssX6X\nlJa+a4pL3ypvRERE065duywymcytu99Y6PV6Ki8vJ6fTSW1tbZSbm0tlZWXU19fndqjIcRzdeOON\ndMstt9Brr71GJSUlFBsbS7/5zW9G7RltNtukehSO46ikpGTcXjtPPfUUPfnkkyN+Y15e3ohRxfvv\nv08AaNeuXRQfH08ACAA/Cjl8+DDl5OTQu+++6xWTTJZlqauri2QyGRUVFVF3dzf/zFiWpdzc3Eld\nt6uri77++mvKzs42RUZG5n6XlJa+i4pLV5RXEhERcSY9Pd108uTJCbuKOZ1OkkqlvJJyHEcajYYq\nKir4cKNX9wJ79uyh1NRU+vDDD2nv3r2UmJhIZ86codWrV9Mdd9zhNuQny7JUUFAwaTtoh8NB58+f\nH5eF08cff0zbt2/n/7ZYLJSbm+vWmiw1NZUA0Nq1a+m3v/0t9fT00G233UZbtmyh9evX0z/8wz/Q\nI488QjfddBM999xz9N57703KndJsNlN9fT1JpVKSy+VuPYI8mSiOhclkonfeeYcSExPNYWFh/4UZ\n7ukzmeJ3AXz2wwBGLBY/GxMTY3njjTcm3DtUVVW5NXS32+3U1tZG58+fp4sXL1JPTw9lZ2fTDTfc\nwB/z3nvv8T0VAAoODh5RMVUq1ZQtq1yeS2P12BaLhebOnUsXL17k41S7+21ms5l6enpIpVLR1q1b\n6ejRox6vabfb6eTJk3T99dfTj370o3HJa7FYqKWlhWQyGRUUFJBSqRx1vtzc3DzhEdPAwAA999xz\nFBYWZhEKhbtoBtRFXxS/C+DrIhAIfhgWFmZ+6qmnJrSootFoRm3tLRYLvfjii3T06FE6cuQIHT16\nlFQqFT/3GxgYoMbGRrr77rvplltuGbISzHEcnT9/3itDTdcceSxb7F27dlFycjI/fxxOWVkZAaAf\n/vCH9NVXX1FmZia9+uqro15Tq9XSl19+SUKhkCorK+mf//mfR/gsm81mamlpoYKCAiooKKCWlpZx\n/+6LFy96XO12h1qtpt27d3MREREaAOtoBtQ/XxW/CzAtPxJYFhsbq7nzzjvZ8TobXL2H6I6vvvqK\nYmJi6Je//CUfSK2hoYHy8/OpsLCQWltbPVZQjUYzZviUiaDX6yk3N3fURZy8vDzauXMnPfjggwSA\n7031ej299dZblJSURHfddRcBoOuvv54OHjw4rkW5vLw8WrRoEUVFRREA0mq1pNVqqampiQoKCkgm\nk01IWV04HA46d+7cuLefmpqaaOPGjWxsbGwVgASaAfXOl2XWmjxOFIZhoubPn58XGxu75tSpU4Lx\nJAdrbGyEWCx2a3NsMpmwbt067N+/H48//viQjIJmsxm9vb3o6emBw+FATEwMYmNjERcXB7FYDKVS\nCZZlJ52Z3h39/f2oq6tDVlbWkGRVLpRKJVpbW2Gz2XDnnXfiyy+/RHx8PLKysrBjxw78/Oc/n1SC\n6rKyMrzzzju4fPkyVq9ejR/84AeIjY1FfHw8EhMT3coyHmpqahAVFTWuhNS5ubn46U9/ylmt1hMa\njeYhInJM6qaziO+N4gIAwzCC5OTk4yaT6Z9ef/11wd69e0c93mw2o7S0FFu2bHFrF9ze3o6dO3eC\nYRh89dVXbk0dWZaFXq/n7YEtFgsYhuFtgsPDwydsc+yJvr4+XnmvzgLY3d2NtrY2ZGVlISgoiG9k\nEhISsHv3brz++uvjuj4RwWq1YmBgAAaDATqdjv9dH3zwAZKSkvDBBx9MOQG3RqNBY2MjNm3aNOq1\nOI7DoUOH6PDhwyQQCP5Vr9f/95RuPIv4Ximui8WLF9+l1+s/2L59e9DRo0fFowX5bm9vh0ajwYYN\nG9xWIiLCI488gqKiIpw6dQpLly4d9d5EhLq6OtjtdhARjEYjiAgSiQQRERF8maxCazQa1NbW8sp7\n+fJlNDU1ITs7m/f4KSgowN69e7Fs2TK8+uqrQ2yXXTLa7XaYzWYYDAa+2O12iMViREZGIjIyEtHR\n0WhtbcWHH36Il19+GSdOnMBYjeFYsCyLgoICbNy4cVTngebmZtx7770mlUplMplMN+v1+qop3XiW\n8b1UXABgGEYSHh5+WCAQPPA///M/4l27dnls3aurqxEWFoa0tDS33xMR/v3f/x1//vOfcfr0aaxf\nv37Ue6vVavT09GDt2rX8+WazGYODg3wxGo3gOA5CoRChoaEIDQ2FSCTi/+8qAoFgRNHpdKipqUFa\nWhpaWlqQlZUFgUAAlmXhdDr5f51OJ6xWKywWC18cjiujzJCQkCFKGhUVNcLpgojw0Ucf4f7778cH\nH3yAn/zkJ1Pubevq6iAWiz1OI5xOJ1599VX217/+tY1l2f9ns9mOEBE7pZvOQr63iuuCYZis8PDw\nv2zatCnx3Xfflbjz/eQ4DsXFxXwGeXcQEf70pz/hiSeewOHDh3Hfffd5rMREV3xDt23bNmavyrIs\n70t79b+uwnHciAJccQd09ZAhISEQCoUICgoa8a9YLIZIJIJYLIZYLEZwcPC4le/vf/87Ll26hMzM\nTH64vG/fPmzdunVSHkVarRb19fXYvHmzWxlqa2uxZ88ek1KplBsMhr1E1DLhm3xX8Pfq2EwoAEIk\nEslvwsLCzG+//TbnztrJarWOK3RobW0tpaen0/bt2+n06dMeV0V9mc+3s7OT8vPz+dCknnK+TgWD\nwUD79u2jG264gSIjI4fsW//xj3+c8PVc6UjcPV+r1UrPPvusQywWG4OCgh7GDEwJMt3F7wLMpAJg\nVWRkpDw7O9vU0NBAw3GFwBlra8PhcNDzzz9PANzmYyX6P+MJb6feaG1tpcLCQn4/2W63U1FRETU1\nNXnVs6elpYVeffVVuu+++wgAxcTEEAD6NiXlhFCpVJSfn+92O0smk1FqaqoxMjLyawDzaQbUk5lQ\n/C7ATCsAhCKR6N/EYrFx9+7dluEBy/r6+kgqlY4Z3+izzz4jAPT88897tP5xNQTeMNjnOI7q6+up\npKRkhKGJK/1GeXn5lNOnEP1fekqj0UgPPvgg7d27l4qLi+mjjz6aUOPAcRw1NDRQcXHxCLlKS0vp\nhhtuMIaFhfUzDLMr0MsOq6f+FmCmFgDRYrH4BbFYbLzvvvssVyuf1WqloqIiksvlHp0InE4nnTx5\nkh5++GGKi4ujJ554wq0Cq1QqKiwsnJSPrQu73U4XLlyg2traURVntNCl40Wv15NUKqX+/n4+sdoj\njzwy4euwLEsVFRVUVVU15BmePn2abr75ZpNEItEGBwc/CiCUZkB9mGnF7wLM9AIgViKRHBaLxaaH\nHnrI6grIznEcbx00VmqSzs5OevLJJyk2NpYOHDgwokfs6enhlWGiuKymro6LPBonT56kF198kV5+\n+WV65pln6O6776YdO3bQ9u3bKSEhgebOnUsLFiygxx57jKxW6xBZXUmpP/30U1q7di3NmTOHjh07\nNuGGwNXwKRQK4jiOzGYzHTlyhGJiYliGYbjg4ODnAIhpBrz/mVr8LsBsKQASwsLCXhOLxeaf/exn\nVteCz0QWgDo7O2n79u0UGhpKra2tQ74zm80kk8mooaFhXDbVHMdRW1sb5eXljWuefOTIEXryyScp\nNTWV7rrrLnr77bfp4MGDNH/+fAJAX375JSmVSlIqlXTzzTfzC02LFi0is9lM5eXl9M0339Djjz9O\nACYV5cPpdPIO8j09PdTU1HT1whYnEAj+CCCaZsD7nunF7wLMtgJgTnh4+FGxWGzZv3+/raamhmw2\nG5++cayYUE6nkwDQXXfdNcKlj2VZPrZSU1OTx7mvwWDgY0F5mrNyHEdnz56lp59+mhYtWsTfMyoq\nil9IOnr0KB06dIjOnTs3xC7ZarUSAMrMzKSysjLKy8ujkydPUkxMDGVmZtKePXvGnOMPl8UV/kah\nUFBhYeGQVWiGYYoBRHh65oHiph76W4DZWgDME4lEL0skEu3KlSsNx44do5aWFiouLqYLFy6M6gOs\n0+no0Ucf5Svu2bNnhwQmdzgc1NzcTFKplOrr6/ke1el0Un19PeXn5485PO3p6eGvn5OTQxaLhXbs\n2EHXXXcdvfzyy7RmzRoiGqpULS0t5HA46MMPP6Snn36avvnmG2pra6MzZ85QRETEEGW79957x5Vl\nQa1WU35+PlVVVdGBAwcoLCzs6usoAET5+13OxuJ3AWZ7ASAEcGt0dPTfRCKRdefOnabPP/+cj9So\nVqs9Din7+/vpkUceoc2bNxMAOnHiBPX19fHfO51O6ujooKKiIjp79iz97W9/o6qqqnG7J7700ks0\nd+5cAkClpaXU09NDt99+O0VGRtLx48f54xwOB12+fJnOnz9Pn3/+OR0/fpx+/OMf843JoUOHhiit\nqwxPFHY1rmiV+fn5tGrVKv4cgUDQCyAnsEo8tfK9t5zyJgzDxAuFwnvDwsL+VSwWJz7wwAOinJwc\nYVRUFNLS0jBnzhy3FkEsy+K//uu/cOrUKdTX1yM2NhbXXnstMjIysGzZMsTExCApKQnh4eHo7++H\nTqdDcHAwb9PMcRwUCgUaGhrQ3NzMG/+XlZXh1ltvxe7du3HrrbfC4XDAbrfDZrNhcHAQOp0OBoMB\nAoEAUVFRSEhIQHx8PMrLyyGXy9Ha2oqGhgbYbDYEBQWhp6cHVVVVcDqdAICwsDAYjUb+d1gsFnR1\ndaG7uxudnZ04f/688w9/+ANnsVhCAFQCuImINNP0Or7TBBTXBzBXtDMjIiLiZw6HY9eSJUu4zZs3\nh6WnpzM5OTlYuHAh4uPj3Zo7Go1GyOVydHV1wWAw4JNPPkFtbS0SEhJwyy23YPHixdixYwdqamqg\nVqtRWVkJjUaDdevWISYmBhKJBEKhEEKhEBKJhHcsYBgGISEhfImIiEB0dDQiIyPdZiwgImi1Wsjl\ncgwMDMDpdF5p6RkGTz/9NNRqNZYsWYLi4mJ0dXWhpaUFFRUVqK+vZwsKCiyXL192EtHvLBbLO0Sk\n8PUz/74RUFwfwzCMCECOWCz+oUgk+pHFYklZs2aNcO3atYLMzEysXLkSoaGhsFgsYFkWoaGhmDNn\nDpKSkiAWi0FE6OzsxNtvv43y8nIMDg6irq4O69atQ3JyMkJDQ7Ft2zb89Kc/9envsFqtaGlpwYED\nBzBnzhykp6fDYrGgsrIS1dXVnEKhYJKSkvoBnGpra3sPQBkROX0q1PeYgOJOMwzDxK9cuXLv4ODg\nPwwODm5lGEackZEh2Lhxo2DLli249tprERMTMyQlij8huuJ62NPTg4qKCpw7dw6XLl3iqqurKTQ0\nVG2z2U6ZTKa/AjhPRMYxLxjAKwQU1498O6RezDDMTQkJCXc7nc4Mg8EQMXfuXC45OZlJS0sTrFix\nAunp6Vi7di2SkpJ8mkXP1btXVFSguroaly5dora2Nuro6OA0Go0gKipKA6BYo9F8AuAbIurxmTAB\nRiWguDOMb4fWSxmGWREbG5sVERGRY7Va07RabUxkZCQWLlxI8+bNY6KjoxEVFSUIDw9HREQEoqKi\nEBERwfvORkZGIiwsDDabDQaDAXq9HjqdDnq9HgMDA3wUC4PBwBkMBnR3d5NSqRTY7XaKi4vThoSE\n1Pf39+cZDIZyAA0AWul7EBJmthBQ3FkCwzACACkAromLi1sRFxe3iGGYWIZhYnHF2ijC6XSGO51O\nsd1uF9nt9hCHwyEMDQ3lQkNDncHBwdagoCCTQCAYAKBzOBx9Foul12q1qgcHB3udTmcrgHoAPRSo\nFDOegOIGCDAL8W/m4gABAkyKgOIGCDALCShugACzkIDiBggwCwkoboAAs5CA4gYIMAsJKG6AALOQ\ngOIGCDALCShugACzkIDiBggwCwkoboAAs5CA4gYIMAsJKG6AALOQgOIGCDALCShugACzkIDiBggw\nCwkoboAAs5CA4gYIMAsJKG6AALOQ/w+SMZIZyVAwKQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f50df64a2e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plt.axes(projection=ccrs.Orthographic(central_longitude=151, central_latitude=-33))\n",
    "ax.gridlines()\n",
    "ax.coastlines();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plotting lands\n",
    "\n",
    "from Natural Earth dataset (public domain)\n",
    "\n",
    "http://scitools.org.uk/cartopy/docs/latest/matplotlib/feature_interface.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import cartopy.feature as cfeature"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Low resolution: \"110m\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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5/f8y5OTJkzFq1CiHY8eOfQHgvXarWHN0tM8lEYFhmJUMw5BEYkMZGRlERKTT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\nOeaYhcwZ7hxzzEL+H0xeBedgw0K5AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f50df5770b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plt.axes(projection=ccrs.Orthographic(central_longitude=151, central_latitude=-33))\n",
    "ax.gridlines()\n",
    "\n",
    "land = cfeature.NaturalEarthFeature('physical', 'land', '110m', facecolor='#FFEEBB', edgecolor='black')\n",
    "ax.add_feature(land);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "High resolution: \"10m\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Z0NraitjY2GG3bW1thdlsHlBDdzxAkiTa29tRU1ODadOmYdq0aYN2YocOHcKy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\nZD1w11nnLGQ9cNdZ5yxkPXDXWecs5P8HSexDybt3zzsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f50ea3c2fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plt.axes(projection=ccrs.Orthographic(central_longitude=151, central_latitude=-33))\n",
    "ax.gridlines()\n",
    "\n",
    "land = cfeature.NaturalEarthFeature('physical', 'land', '10m', facecolor='#EEEEEE', edgecolor='#777777')\n",
    "ax.add_feature(land);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  Nearby cities, for a bit of context"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cities = {\n",
    "    'Newcastle': (-32.933, 151.733),\n",
    "    'Cessnock': (-32.834, 151.3555),\n",
    "    'Gosford': (-33.433, 151.33),\n",
    "    'Sydney':  (-33.856, 151.1925),\n",
    "    #'Wollongong': (-34.417, 150.883),\n",
    "    #'Nowra-Bomaderry': (-34.883, 150.6)\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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GDBiATqcjKipKBvwhZ/Uht7W1ZceOHRw9epQ1a9bcs21cXBwdOnSgU6dODBs2jO3bt+Pi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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f50deadef28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "proj = ccrs.Mercator(central_longitude=151, latitude_true_scale=-50)\n",
    "\n",
    "ax = plt.axes(projection=proj)\n",
    "ax.coastlines('10m')\n",
    "\n",
    "def plot_cities(ax):\n",
    "    for cit in cities:\n",
    "        lat, lng = cities[cit]\n",
    "        ax.plot(lng, lat, 'o',transform=ccrs.Geodetic(), color='tab:red', fillstyle='none');\n",
    "\n",
    "        ax.text(lng + 0.15, lat, cit,\n",
    "             horizontalalignment='left', verticalalignment='center',\n",
    "             color='tab:red',\n",
    "             transform=ccrs.Geodetic())\n",
    "\n",
    "plot_cities(ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Add a scale reference (length in km) \n",
    "\n",
    "Inspireed by Wikipedia's section [Great-circle distance/Radius for spherical Earth](https://en.wikipedia.org/wiki/Great-circle_distance#Radius_for_spherical_Earth).\n",
    "\n",
    "A different code for scale bar: http://stackoverflow.com/questions/32333870/how-can-i-show-a-km-ruler-on-a-cartopy-matplotlib-plot (but using UTM, so is it applicable to the Mercator map??)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def scale_square(ax, length, lng0, lat0):\n",
    "    'scale square'\n",
    "    R = 6371\n",
    "    \n",
    "    cos_lat = np.cos(np.deg2rad(lat0))\n",
    "    d_lng = np.rad2deg(30/(R*cos_lat))\n",
    "    d_lat = np.rad2deg(30/R)\n",
    "    \n",
    "    lng = [lng0-d_lng, lng0, lng0]\n",
    "    lat = [lat0, lat0, lat0+d_lat]\n",
    "\n",
    "    ax.plot(lng, lat, '-',transform=ccrs.Geodetic(), color='black', lw=3)\n",
    "    ax.text(lng0-d_lng/2, lat0+d_lat/2, '{:.0f} km'.format(length), transform=ccrs.Geodetic(),\n",
    "           horizontalalignment='center', verticalalignment='center')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Map of postcode locations\n",
    "\n",
    "Ref about grid and ticks: http://scitools.org.uk/cartopy/docs/latest/matplotlib/gridliner.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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tl53/a55//nlGjhxJjx49mDhxIp999hm//vWvvRitEO1LEoXo9nJycvj444+Z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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f50deb01908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#proj = ccrs.Orthographic(central_longitude=151-60, central_latitude=-33) # cannot label gridlines\n",
    "proj = ccrs.Mercator(central_longitude=151, latitude_true_scale=-50)\n",
    "\n",
    "ax = plt.axes(projection=proj)\n",
    "\n",
    "ax.add_feature(land)\n",
    "\n",
    "\n",
    "lat, lng = location.T\n",
    "ax.plot(lng, lat, '.', transform=ccrs.Geodetic());\n",
    "\n",
    "ax.set(xlabel='lng', ylabel='lat', title='Postcode locations');\n",
    "\n",
    "plot_cities(ax)\n",
    "\n",
    "from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER\n",
    "\n",
    "gl = ax.gridlines(draw_labels=True)\n",
    "gl.xlocator.set_params(nbins=2)\n",
    "gl.xlabels_top = False\n",
    "#gl.ylabels_left = False\n",
    "gl.xformatter = LONGITUDE_FORMATTER\n",
    "gl.yformatter = LATITUDE_FORMATTER\n",
    "\n",
    "\n",
    "ax.set_extent([150, 153, -34.2, -32.5])\n",
    "\n",
    "scale_square(ax, 30, 152.5, -34)\n",
    "plt.savefig('postcode_locations.png', dpi=150)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bounds of post codes areas\n",
    "\n",
    "Drawing boxes with [matplotlib.patches.Rectangle](http://matplotlib.org/api/patches_api.html#matplotlib.patches.Rectangle) doesn't seem to work.\n",
    "\n",
    "Using instead `shapely.geometry ` works (http://stackoverflow.com/questions/13856123/setting-up-a-map-which-crosses-the-dateline-in-cartopy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import shapely.geometry as sgeom\n",
    "#from matplotlib.patches import Rectangle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'northeast': {'lat': -32.1389092, 'lng': 151.4889105},\n",
       " 'southwest': {'lat': -33.162648, 'lng': 150.3050814}}"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loc[2330]['bounds']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create the dict of rectangles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(150.3050814, 151.4889105, -33.162648, -32.1389092)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rects = {}\n",
    "for c in pcodes:\n",
    "    bounds = loc[c]['bounds'] \n",
    "    sw = bounds['southwest']['lng'], bounds['southwest']['lat']\n",
    "    ne = bounds['northeast']['lng'], bounds['northeast']['lat']\n",
    "    rects[c] = sgeom.box(minx=sw[0], maxx=ne[0], miny=sw[1], maxy=ne[1])#Rectangle(sw, ne[0]-sw[0], ne[1]-sw[1], fill=True, color='b')\n",
    "\n",
    "sw[0], ne[0], sw[1], ne[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(150.3050814, -33.162648, 151.4889105, -32.1389092)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r = rects[2330]\n",
    "r.bounds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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T8dbXk/jLn+Mpr6DuF78h6errad+wAc/+/SQ88wxGQwN1t96GLTcXz/79tH/0MQmPP4YK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\n/wKBevejWLuddQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f50df2dae80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "proj = ccrs.Mercator(central_longitude=151, latitude_true_scale=-50)\n",
    "\n",
    "#box = sgeom.box(minx=100, maxx=160, miny=-50, maxy=-10)\n",
    "\n",
    "ax = plt.axes(projection=proj)\n",
    "\n",
    "ax.add_feature(land)\n",
    "\n",
    "lat, lng = location.T\n",
    "ax.plot(lng, lat, '.', transform=ccrs.Geodetic());\n",
    "\n",
    "ax.add_geometries(rects.values(), ccrs.PlateCarree(), facecolor='coral', \n",
    "                   edgecolor='', alpha=0.2)\n",
    "\n",
    "    \n",
    "ax.set(xlabel='lng', ylabel='lat', title='Postcode areas');\n",
    "\n",
    "plot_cities(ax)\n",
    "\n",
    "from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER\n",
    "\n",
    "gl = ax.gridlines(draw_labels=True)\n",
    "gl.xlocator.set_params(nbins=2)\n",
    "gl.xlabels_top = False\n",
    "#gl.ylabels_left = False\n",
    "gl.xformatter = LONGITUDE_FORMATTER\n",
    "gl.yformatter = LATITUDE_FORMATTER\n",
    "\n",
    "ax.set_extent([150, 153, -34.2, -32.5])\n",
    "\n",
    "scale_square(ax, 30, 152.5, -34)\n",
    "plt.savefig('postcode_bounds.png', dpi=150)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Save clean location data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2008,\n",
       " -33.8878872,\n",
       " 151.1964025,\n",
       " 1.1789553292422299,\n",
       " 1.7666126699185636,\n",
       " 2.0827574219073348]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loc_array = []\n",
    "for c in pcodes:\n",
    "    lat, lng = loc[c]['location']\n",
    "    bounds = loc[c]['bounds'] \n",
    "    delta_lat = bounds['northeast']['lat'] - bounds['southwest']['lat']\n",
    "    delta_lng = bounds['northeast']['lng'] - bounds['southwest']['lng']\n",
    "    \n",
    "    R = 6371\n",
    "    cos_lat = np.cos(np.deg2rad(lat))\n",
    "    dlng_km = R*cos_lat * np.deg2rad(delta_lng)\n",
    "    dlat_km = R         * np.deg2rad(delta_lat)\n",
    "    loc_array.append([c, lat, lng, dlat_km, dlng_km, dlat_km*dlng_km])\n",
    "\n",
    "loc_array[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>postcode</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>dlat_km</th>\n",
       "      <th>dlng_km</th>\n",
       "      <th>area_km2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008</td>\n",
       "      <td>-33.887887</td>\n",
       "      <td>151.196403</td>\n",
       "      <td>1.178955</td>\n",
       "      <td>1.766613</td>\n",
       "      <td>2.082757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010</td>\n",
       "      <td>-33.882559</td>\n",
       "      <td>151.213158</td>\n",
       "      <td>2.039637</td>\n",
       "      <td>2.559093</td>\n",
       "      <td>5.219621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018</td>\n",
       "      <td>-33.921990</td>\n",
       "      <td>151.207330</td>\n",
       "      <td>3.230835</td>\n",
       "      <td>2.408996</td>\n",
       "      <td>7.783069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021</td>\n",
       "      <td>-33.892120</td>\n",
       "      <td>151.230645</td>\n",
       "      <td>3.256143</td>\n",
       "      <td>2.567510</td>\n",
       "      <td>8.360180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2025</td>\n",
       "      <td>-33.886500</td>\n",
       "      <td>151.243761</td>\n",
       "      <td>1.142317</td>\n",
       "      <td>2.256786</td>\n",
       "      <td>2.577965</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   postcode        lat         lng   dlat_km   dlng_km  area_km2\n",
       "0      2008 -33.887887  151.196403  1.178955  1.766613  2.082757\n",
       "1      2010 -33.882559  151.213158  2.039637  2.559093  5.219621\n",
       "2      2018 -33.921990  151.207330  3.230835  2.408996  7.783069\n",
       "3      2021 -33.892120  151.230645  3.256143  2.567510  8.360180\n",
       "4      2025 -33.886500  151.243761  1.142317  2.256786  2.577965"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loc_df = pd.DataFrame(loc_array, columns=['postcode', 'lat', 'lng', 'dlat_km', 'dlng_km', 'area_km2'])\n",
    "loc_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>postcode</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>dlat_km</th>\n",
       "      <th>dlng_km</th>\n",
       "      <th>area_km2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2181.150000</td>\n",
       "      <td>-33.555777</td>\n",
       "      <td>151.299839</td>\n",
       "      <td>8.751208</td>\n",
       "      <td>8.940664</td>\n",
       "      <td>275.172006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>100.089392</td>\n",
       "      <td>0.443103</td>\n",
       "      <td>0.255943</td>\n",
       "      <td>13.757440</td>\n",
       "      <td>15.264920</td>\n",
       "      <td>1318.676000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2008.000000</td>\n",
       "      <td>-34.119303</td>\n",
       "      <td>150.860936</td>\n",
       "      <td>1.142317</td>\n",
       "      <td>1.230935</td>\n",
       "      <td>1.898558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2206.000000</td>\n",
       "      <td>-33.759882</td>\n",
       "      <td>151.201502</td>\n",
       "      <td>4.120445</td>\n",
       "      <td>4.096955</td>\n",
       "      <td>16.953859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2330.000000</td>\n",
       "      <td>-32.640042</td>\n",
       "      <td>152.151274</td>\n",
       "      <td>113.834561</td>\n",
       "      <td>110.733301</td>\n",
       "      <td>12605.276700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          postcode         lat         lng     dlat_km     dlng_km  \\\n",
       "count   100.000000  100.000000  100.000000  100.000000  100.000000   \n",
       "mean   2181.150000  -33.555777  151.299839    8.751208    8.940664   \n",
       "std     100.089392    0.443103    0.255943   13.757440   15.264920   \n",
       "min    2008.000000  -34.119303  150.860936    1.142317    1.230935   \n",
       "50%    2206.000000  -33.759882  151.201502    4.120445    4.096955   \n",
       "max    2330.000000  -32.640042  152.151274  113.834561  110.733301   \n",
       "\n",
       "           area_km2  \n",
       "count    100.000000  \n",
       "mean     275.172006  \n",
       "std     1318.676000  \n",
       "min        1.898558  \n",
       "50%       16.953859  \n",
       "max    12605.276700  "
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loc_df.describe(percentiles=[])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Save to CSV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "comment = '''# Australian postcodes of the \"Solar home electricity\" dataset\n",
    "# located with [Google Maps Geocoding API](https://developers.google.com/maps/documentation/geocoding/start)\n",
    "# Pierre Haessig, May 2017\n",
    "'''\n",
    "with open('postcodes.csv', 'w') as out:\n",
    "    out.write(comment)\n",
    "    loc_df.to_csv(out, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# Australian postcodes of the \"Solar home electricity\" dataset\r\n",
      "# located with [Google Maps Geocoding API](https://developers.google.com/maps/documentation/geocoding/start)\r\n",
      "# Pierre Haessig, May 2017\r\n",
      "postcode,lat,lng,dlat_km,dlng_km,area_km2\r\n",
      "2008,-33.8878872,151.1964025,1.17895532924223,1.7666126699185636,2.082757421907335\r\n",
      "2010,-33.8825595,151.2131584,2.039637419948519,2.5590925282735424,5.219620881777381\r\n",
      "2018,-33.9219899,151.20733,3.230835310613587,2.408995764206797,7.7830685781178826\r\n",
      "2021,-33.8921203,151.2306446,3.2561432759173567,2.5675097783137186,8.360179700508278\r\n",
      "2025,-33.8865002,151.2437606,1.1423166009121215,2.2567863956392284,2.577964564451322\r\n",
      "2026,-33.8922511,151.2714535,2.556738306816677,2.59023971059348,6.622565091912094\r\n"
     ]
    }
   ],
   "source": [
    "!head postcodes.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Stats on the extremely large post code areas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    100.000000\n",
       "mean      10.042000\n",
       "std       15.696012\n",
       "min        1.390969\n",
       "50%        5.006065\n",
       "80%       10.727598\n",
       "90%       17.770985\n",
       "95%       46.070113\n",
       "max      113.834561\n",
       "dtype: float64"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max_dim = loc_df[['dlat_km', 'dlng_km']].max(axis=1)\n",
    "max_dim.describe(percentiles=[0.8, 0.9, 0.95])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7ff3eed35240>"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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D+y90bcuRmfdl5uWZOcLs9+fzmXkn3e/rJeA7EXFVs2sb8E063hezSy03RMQ7mp/Jbcxe\nz+l6X3Mt1MsB4PaIeFtEXAlsAb4ygPoujMxcdR/ALcB/AP8JfHjQ9Syjj99i9k+/bwBPNh+3AD/P\n7JX448DngI2DrnUZPY4BB5vtzvcFXAscab5nnwI2FOnrI8CzwFPAPwJv62pfwMPMXgv4EbN/Vd39\nVr0AH26y5DngPYOuv58fvlJUkopYjUsukqQlMNAlqQgDXZKKMNAlqQgDXZKKMNAlqQgDXZKKMNAl\nqYj/B3WXVlBLhNQ+AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff3eed27ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "max_dim.hist(bins=30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7ff3eeec8be0>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Uu12nPyn1L+N8Xw3ka2XcjZGvtbFXJF+bY6+3Hz4h6aPnmKf18df/leKUSwz5GALbv9x7\n/M8kfUTSD0j6U9uStBbrH6bTkfTJ3rQNkv46Ij7bcLY7Jf2K7TVJJyXtjPVRMfGPVyiYT5J+TtLn\nI+L1vsUnuu8kyfYjWn8lxhbbr0i6T9LFfdme1PorDV6U9D+SPniu76vObAXztTLuxsjX2tgrmE9q\naexJukXS3ZJWbB/sTftdrf8nPRXjbxDvFAWAJLKcQweACx6FDgBJUOgAkASFDgBJUOgAkASFDgBJ\nUOgAkASFDgBJ/D/3rKZSyNyvbAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff3eeefbda0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.log10(max_dim).hist(bins=30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count      100.000000\n",
       "mean       275.172006\n",
       "std       1318.676000\n",
       "min          1.898558\n",
       "50%         16.953859\n",
       "80%         85.150811\n",
       "90%        230.102730\n",
       "95%       1604.434592\n",
       "max      12605.276700\n",
       "Name: area_km2, dtype: float64"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loc_df.area_km2.describe(percentiles=[0.8, 0.9, 0.95])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7ff3ef21d7f0>"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff3ef347080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.log10(loc_df.area).hist(bins=20)\n",
    "plt.xlabel('log10 of area (km²)')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}