13-isolines-isochrones.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Draw an isochrone map with OSMnx\n",
    "\n",
    "Author: [Geoff Boeing](https://geoffboeing.com/)\n",
    "\n",
    "How far can you travel on foot in 15 minutes?\n",
    "\n",
    "  - [Overview of OSMnx](http://geoffboeing.com/2016/11/osmnx-python-street-networks/)\n",
    "  - [GitHub repo](https://github.com/gboeing/osmnx)\n",
    "  - [Examples, demos, tutorials](https://github.com/gboeing/osmnx-examples)\n",
    "  - [Documentation](https://osmnx.readthedocs.io/en/stable/)\n",
    "  - [Journal article/citation](http://geoffboeing.com/publications/osmnx-complex-street-networks/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\tstrub\\AppData\\Local\\Temp\\ipykernel_13672\\3012662632.py:7: FutureWarning: The `utils.config` function is deprecated and will be removed in the v2.0.0 release. Instead, use the `settings` module directly to configure a global setting's value. For example, `ox.settings.log_console=True`. See the OSMnx v2 migration guide: https://github.com/gboeing/osmnx/issues/1123\n",
      "  ox.config(log_console=True, use_cache=True)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'1.9.3'"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "import networkx as nx\n",
    "import osmnx as ox\n",
    "from descartes import PolygonPatch\n",
    "from shapely.geometry import Point, LineString, Polygon\n",
    "ox.config(log_console=True, use_cache=True)\n",
    "ox.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# configure the place, network type, trip times, and travel speed\n",
    "place = 'Freiburg, BW, Deutschland'\n",
    "network_type = 'walk'\n",
    "trip_times = [5, 10, 15, 20, 25] #in minutes\n",
    "travel_speed = 4.5 #walking speed in km/hour"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Download and prep the street network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# download the street network\n",
    "G = ox.graph_from_place(place, network_type=network_type)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "ename": "ImportError",
     "evalue": "scipy must be installed to search a projected graph",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mImportError\u001b[0m                               Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[35], line 2\u001b[0m\n\u001b[0;32m      1\u001b[0m center_node\u001b[38;5;241m=\u001b[39m(y[\u001b[38;5;241m0\u001b[39m], x[\u001b[38;5;241m0\u001b[39m])\n\u001b[1;32m----> 2\u001b[0m \u001b[43mox\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnearest_nodes\u001b[49m\u001b[43m(\u001b[49m\u001b[43mG\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mx\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\osmnx\\distance.py:291\u001b[0m, in \u001b[0;36mnearest_nodes\u001b[1;34m(G, X, Y, return_dist)\u001b[0m\n\u001b[0;32m    289\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m cKDTree \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:  \u001b[38;5;66;03m# pragma: no cover\u001b[39;00m\n\u001b[0;32m    290\u001b[0m     msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mscipy must be installed to search a projected graph\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m--> 291\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m(msg)\n\u001b[0;32m    292\u001b[0m dist, pos \u001b[38;5;241m=\u001b[39m cKDTree(nodes)\u001b[38;5;241m.\u001b[39mquery(np\u001b[38;5;241m.\u001b[39marray([X, Y])\u001b[38;5;241m.\u001b[39mT, k\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m)\n\u001b[0;32m    293\u001b[0m nn \u001b[38;5;241m=\u001b[39m nodes\u001b[38;5;241m.\u001b[39mindex[pos]\n",
      "\u001b[1;31mImportError\u001b[0m: scipy must be installed to search a projected graph"
     ]
    }
   ],
   "source": [
    "center_node=(y[0], x[0])\n",
    "ox.nearest_nodes(G, y[0], x[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\tstrub\\AppData\\Local\\Temp\\ipykernel_13672\\2617934978.py:3: DeprecationWarning: The 'unary_union' attribute is deprecated, use the 'union_all()' method instead.\n",
      "  x, y = gdf_nodes['geometry'].unary_union.centroid.xy\n"
     ]
    }
   ],
   "source": [
    "# find the centermost node and then project the graph to UTM\n",
    "gdf_nodes = ox.graph_to_gdfs(G, edges=False)\n",
    "x, y = gdf_nodes['geometry'].unary_union.centroid.xy\n",
    "#center_node = ox.get_nearest_node(G, (y[0], x[0]))\n",
    "G = ox.project_graph(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add an edge attribute for time in minutes required to traverse each edge\n",
    "meters_per_minute = travel_speed * 1000 / 60 #km per hour to m per minute\n",
    "for u, v, k, data in G.edges(data=True, keys=True):\n",
    "    data['time'] = data['length'] / meters_per_minute"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plots nodes you can reach on foot within each time\n",
    "\n",
    "How far can you walk in 5, 10, 15, 20, and 25 minutes from the origin node? We'll use NetworkX to induce a subgraph of G within each distance, based on trip time and travel speed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\tstrub\\AppData\\Local\\Temp\\ipykernel_13672\\2843268174.py:2: FutureWarning: The `return_hex` parameter has been deprecated and will be removed in the v2.0.0 release. See the OSMnx v2 migration guide: https://github.com/gboeing/osmnx/issues/1123\n",
      "  iso_colors = ox.plot.get_colors(n=len(trip_times), cmap='plasma', start=0, return_hex=True)\n"
     ]
    }
   ],
   "source": [
    "# get one color for each isochrone\n",
    "iso_colors = ox.plot.get_colors(n=len(trip_times), cmap='plasma', start=0, return_hex=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "ename": "NodeNotFound",
     "evalue": "Node (47.998286223266, 7.81789149749992) not found in graph",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNodeNotFound\u001b[0m                              Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[29], line 4\u001b[0m\n\u001b[0;32m      2\u001b[0m node_colors \u001b[38;5;241m=\u001b[39m {}\n\u001b[0;32m      3\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m trip_time, color \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(\u001b[38;5;28msorted\u001b[39m(trip_times, reverse\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m), iso_colors):\n\u001b[1;32m----> 4\u001b[0m     subgraph \u001b[38;5;241m=\u001b[39m \u001b[43mnx\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mego_graph\u001b[49m\u001b[43m(\u001b[49m\u001b[43mG\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcenter_node\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mradius\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtrip_time\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdistance\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mtime\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m      5\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m node \u001b[38;5;129;01min\u001b[39;00m subgraph\u001b[38;5;241m.\u001b[39mnodes():\n\u001b[0;32m      6\u001b[0m         node_colors[node] \u001b[38;5;241m=\u001b[39m color\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\networkx\\utils\\decorators.py:789\u001b[0m, in \u001b[0;36margmap.__call__.<locals>.func\u001b[1;34m(_argmap__wrapper, *args, **kwargs)\u001b[0m\n\u001b[0;32m    788\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mfunc\u001b[39m(\u001b[38;5;241m*\u001b[39margs, __wrapper\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m--> 789\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m argmap\u001b[38;5;241m.\u001b[39m_lazy_compile(__wrapper)(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32m<class 'networkx.utils.decorators.argmap'> compilation 26:3\u001b[0m, in \u001b[0;36margmap_ego_graph_23\u001b[1;34m(G, n, radius, center, undirected, distance, backend, **backend_kwargs)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mbz2\u001b[39;00m\n\u001b[0;32m      2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mcollections\u001b[39;00m\n\u001b[1;32m----> 3\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mgzip\u001b[39;00m\n\u001b[0;32m      4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01minspect\u001b[39;00m\n\u001b[0;32m      5\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mitertools\u001b[39;00m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\networkx\\utils\\backends.py:633\u001b[0m, in \u001b[0;36m_dispatchable.__call__\u001b[1;34m(self, backend, *args, **kwargs)\u001b[0m\n\u001b[0;32m    628\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Returns the result of the original function, or the backend function if\u001b[39;00m\n\u001b[0;32m    629\u001b[0m \u001b[38;5;124;03mthe backend is specified and that backend implements `func`.\"\"\"\u001b[39;00m\n\u001b[0;32m    631\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m backends:\n\u001b[0;32m    632\u001b[0m     \u001b[38;5;66;03m# Fast path if no backends are installed\u001b[39;00m\n\u001b[1;32m--> 633\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39morig_func(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m    635\u001b[0m \u001b[38;5;66;03m# Use `backend_name` in this function instead of `backend`\u001b[39;00m\n\u001b[0;32m    636\u001b[0m backend_name \u001b[38;5;241m=\u001b[39m backend\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\networkx\\generators\\ego.py:58\u001b[0m, in \u001b[0;36mego_graph\u001b[1;34m(G, n, radius, center, undirected, distance)\u001b[0m\n\u001b[0;32m     56\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m     57\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m distance \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m---> 58\u001b[0m         sp, _ \u001b[38;5;241m=\u001b[39m \u001b[43mnx\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msingle_source_dijkstra\u001b[49m\u001b[43m(\u001b[49m\u001b[43mG\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcutoff\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mradius\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mweight\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdistance\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     59\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m     60\u001b[0m         sp \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mdict\u001b[39m(nx\u001b[38;5;241m.\u001b[39msingle_source_shortest_path_length(G, n, cutoff\u001b[38;5;241m=\u001b[39mradius))\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\networkx\\utils\\decorators.py:789\u001b[0m, in \u001b[0;36margmap.__call__.<locals>.func\u001b[1;34m(_argmap__wrapper, *args, **kwargs)\u001b[0m\n\u001b[0;32m    788\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mfunc\u001b[39m(\u001b[38;5;241m*\u001b[39margs, __wrapper\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m--> 789\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m argmap\u001b[38;5;241m.\u001b[39m_lazy_compile(__wrapper)(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32m<class 'networkx.utils.decorators.argmap'> compilation 30:3\u001b[0m, in \u001b[0;36margmap_single_source_dijkstra_27\u001b[1;34m(G, source, target, cutoff, weight, backend, **backend_kwargs)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mbz2\u001b[39;00m\n\u001b[0;32m      2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mcollections\u001b[39;00m\n\u001b[1;32m----> 3\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mgzip\u001b[39;00m\n\u001b[0;32m      4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01minspect\u001b[39;00m\n\u001b[0;32m      5\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mitertools\u001b[39;00m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\networkx\\utils\\backends.py:633\u001b[0m, in \u001b[0;36m_dispatchable.__call__\u001b[1;34m(self, backend, *args, **kwargs)\u001b[0m\n\u001b[0;32m    628\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Returns the result of the original function, or the backend function if\u001b[39;00m\n\u001b[0;32m    629\u001b[0m \u001b[38;5;124;03mthe backend is specified and that backend implements `func`.\"\"\"\u001b[39;00m\n\u001b[0;32m    631\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m backends:\n\u001b[0;32m    632\u001b[0m     \u001b[38;5;66;03m# Fast path if no backends are installed\u001b[39;00m\n\u001b[1;32m--> 633\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39morig_func(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m    635\u001b[0m \u001b[38;5;66;03m# Use `backend_name` in this function instead of `backend`\u001b[39;00m\n\u001b[0;32m    636\u001b[0m backend_name \u001b[38;5;241m=\u001b[39m backend\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\networkx\\algorithms\\shortest_paths\\weighted.py:489\u001b[0m, in \u001b[0;36msingle_source_dijkstra\u001b[1;34m(G, source, target, cutoff, weight)\u001b[0m\n\u001b[0;32m    392\u001b[0m \u001b[38;5;129m@nx\u001b[39m\u001b[38;5;241m.\u001b[39m_dispatchable(edge_attrs\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mweight\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m    393\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msingle_source_dijkstra\u001b[39m(G, source, target\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, cutoff\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, weight\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mweight\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[0;32m    394\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Find shortest weighted paths and lengths from a source node.\u001b[39;00m\n\u001b[0;32m    395\u001b[0m \n\u001b[0;32m    396\u001b[0m \u001b[38;5;124;03m    Compute the shortest path length between source and all other\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    487\u001b[0m \u001b[38;5;124;03m    single_source_bellman_ford\u001b[39;00m\n\u001b[0;32m    488\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m--> 489\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mmulti_source_dijkstra\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    490\u001b[0m \u001b[43m        \u001b[49m\u001b[43mG\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m{\u001b[49m\u001b[43msource\u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcutoff\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcutoff\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtarget\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtarget\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mweight\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mweight\u001b[49m\n\u001b[0;32m    491\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\networkx\\utils\\decorators.py:789\u001b[0m, in \u001b[0;36margmap.__call__.<locals>.func\u001b[1;34m(_argmap__wrapper, *args, **kwargs)\u001b[0m\n\u001b[0;32m    788\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mfunc\u001b[39m(\u001b[38;5;241m*\u001b[39margs, __wrapper\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m--> 789\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m argmap\u001b[38;5;241m.\u001b[39m_lazy_compile(__wrapper)(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32m<class 'networkx.utils.decorators.argmap'> compilation 34:3\u001b[0m, in \u001b[0;36margmap_multi_source_dijkstra_31\u001b[1;34m(G, sources, target, cutoff, weight, backend, **backend_kwargs)\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mbz2\u001b[39;00m\n\u001b[0;32m      2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mcollections\u001b[39;00m\n\u001b[1;32m----> 3\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mgzip\u001b[39;00m\n\u001b[0;32m      4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01minspect\u001b[39;00m\n\u001b[0;32m      5\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mitertools\u001b[39;00m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\networkx\\utils\\backends.py:633\u001b[0m, in \u001b[0;36m_dispatchable.__call__\u001b[1;34m(self, backend, *args, **kwargs)\u001b[0m\n\u001b[0;32m    628\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Returns the result of the original function, or the backend function if\u001b[39;00m\n\u001b[0;32m    629\u001b[0m \u001b[38;5;124;03mthe backend is specified and that backend implements `func`.\"\"\"\u001b[39;00m\n\u001b[0;32m    631\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m backends:\n\u001b[0;32m    632\u001b[0m     \u001b[38;5;66;03m# Fast path if no backends are installed\u001b[39;00m\n\u001b[1;32m--> 633\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39morig_func(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m    635\u001b[0m \u001b[38;5;66;03m# Use `backend_name` in this function instead of `backend`\u001b[39;00m\n\u001b[0;32m    636\u001b[0m backend_name \u001b[38;5;241m=\u001b[39m backend\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\networkx\\algorithms\\shortest_paths\\weighted.py:754\u001b[0m, in \u001b[0;36mmulti_source_dijkstra\u001b[1;34m(G, sources, target, cutoff, weight)\u001b[0m\n\u001b[0;32m    752\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m s \u001b[38;5;129;01min\u001b[39;00m sources:\n\u001b[0;32m    753\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m s \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m G:\n\u001b[1;32m--> 754\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m nx\u001b[38;5;241m.\u001b[39mNodeNotFound(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNode \u001b[39m\u001b[38;5;132;01m{\u001b[39;00ms\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m not found in graph\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m    755\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m target \u001b[38;5;129;01min\u001b[39;00m sources:\n\u001b[0;32m    756\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m (\u001b[38;5;241m0\u001b[39m, [target])\n",
      "\u001b[1;31mNodeNotFound\u001b[0m: Node (47.998286223266, 7.81789149749992) not found in graph"
     ]
    }
   ],
   "source": [
    "# color the nodes according to isochrone then plot the street network\n",
    "node_colors = {}\n",
    "for trip_time, color in zip(sorted(trip_times, reverse=True), iso_colors):\n",
    "    subgraph = nx.ego_graph(G, center_node, radius=trip_time, distance='time')\n",
    "    for node in subgraph.nodes():\n",
    "        node_colors[node] = color\n",
    "nc = [node_colors[node] if node in node_colors else 'none' for node in G.nodes()]\n",
    "ns = [15 if node in node_colors else 0 for node in G.nodes()]\n",
    "fig, ax = ox.plot_graph(G, node_color=nc, node_size=ns, node_alpha=0.8, node_zorder=2,\n",
    "                        bgcolor='k', edge_linewidth=0.2, edge_color='#999999')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot the time-distances as isochrones\n",
    "\n",
    "How far can you walk in 5, 10, 15, 20, and 25 minutes from the origin node? We'll use a convex hull, which isn't perfectly accurate. A concave hull would be better, but shapely doesn't offer that."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# make the isochrone polygons\n",
    "isochrone_polys = []\n",
    "for trip_time in sorted(trip_times, reverse=True):\n",
    "    subgraph = nx.ego_graph(G, center_node, radius=trip_time, distance='time')\n",
    "    node_points = [Point((data['x'], data['y'])) for node, data in subgraph.nodes(data=True)]\n",
    "    bounding_poly = gpd.GeoSeries(node_points).unary_union.convex_hull\n",
    "    isochrone_polys.append(bounding_poly)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot the network then add isochrones as colored descartes polygon patches\n",
    "fig, ax = ox.plot_graph(G, show=False, close=False, edge_color='#999999', edge_alpha=0.2,\n",
    "                        node_size=0, bgcolor='k')\n",
    "for polygon, fc in zip(isochrone_polys, iso_colors):\n",
    "    patch = PolygonPatch(polygon, fc=fc, ec='none', alpha=0.6, zorder=-1)\n",
    "    ax.add_patch(patch)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Or, plot isochrones as buffers to get more faithful isochrones than convex hulls can offer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_iso_polys(G, edge_buff=25, node_buff=50, infill=False):\n",
    "    isochrone_polys = []\n",
    "    for trip_time in sorted(trip_times, reverse=True):\n",
    "        subgraph = nx.ego_graph(G, center_node, radius=trip_time, distance='time')\n",
    "\n",
    "        node_points = [Point((data['x'], data['y'])) for node, data in subgraph.nodes(data=True)]\n",
    "        nodes_gdf = gpd.GeoDataFrame({'id': subgraph.nodes()}, geometry=node_points)\n",
    "        nodes_gdf = nodes_gdf.set_index('id')\n",
    "\n",
    "        edge_lines = []\n",
    "        for n_fr, n_to in subgraph.edges():\n",
    "            f = nodes_gdf.loc[n_fr].geometry\n",
    "            t = nodes_gdf.loc[n_to].geometry\n",
    "            edge_lookup = G.get_edge_data(n_fr, n_to)[0].get('geometry',  LineString([f,t]))\n",
    "            edge_lines.append(edge_lookup)\n",
    "\n",
    "        n = nodes_gdf.buffer(node_buff).geometry\n",
    "        e = gpd.GeoSeries(edge_lines).buffer(edge_buff).geometry\n",
    "        all_gs = list(n) + list(e)\n",
    "        new_iso = gpd.GeoSeries(all_gs).unary_union\n",
    "        \n",
    "        # try to fill in surrounded areas so shapes will appear solid and blocks without white space inside them\n",
    "        if infill:\n",
    "            new_iso = Polygon(new_iso.exterior)\n",
    "        isochrone_polys.append(new_iso)\n",
    "    return isochrone_polys\n",
    "\n",
    "isochrone_polys = make_iso_polys(G, edge_buff=25, node_buff=0, infill=True)\n",
    "fig, ax = ox.plot_graph(G, show=False, close=False, edge_color='#999999', edge_alpha=0.2,\n",
    "                        node_size=0, bgcolor='k')\n",
    "for polygon, fc in zip(isochrone_polys, iso_colors):\n",
    "    patch = PolygonPatch(polygon, fc=fc, ec='none', alpha=0.6, zorder=-1)\n",
    "    ax.add_patch(patch)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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