update examples

notebooks/09-example-figure-ground.ipynb

@@ -345,7 +345,7 @@
     "point = (37.793897, -122.402189)\n",
     "fp = \"./images/sf_custom.png\"\n",
     "G = ox.graph.graph_from_point(point, dist=1000, network_type=\"all\", truncate_by_edge=True)\n",
-    "fig, ax = ox.plot_figure_ground(\n",
+    "fig, ax = ox.plot.plot_figure_ground(\n",
     "    G=G,\n",
     "    filepath=fp,\n",
     "    street_widths=street_widths,\n",
@@ -383,7 +383,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.9"
+   "version": "3.12.8"
   }
  },
  "nbformat": 4,

notebooks/10-building-footprints.ipynb

@@ -56,10 +56,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "gdf = ox.features_from_place(\"Piedmont, California, USA\", tags)\n",
+    "gdf = ox.features.features_from_place(\"Piedmont, California, USA\", tags)\n",
     "gdf_proj = ox.projection.project_gdf(gdf)\n",
     "fp = f\"./{img_folder}/piedmont_bldgs.{extension}\"\n",
-    "fig, ax = ox.plot_footprints(gdf_proj, filepath=fp, dpi=400, save=True, show=False, close=True)\n",
+    "fig, ax = ox.plot.plot_footprints(gdf_proj, filepath=fp, dpi=400, save=True, show=False, close=True)\n",
     "Image(fp, height=size, width=size)"
    ]
   },
@@ -109,7 +109,7 @@
    "outputs": [],
    "source": [
     "# get the total area within Piedmont's admin boundary in sq meters\n",
-    "place = ox.geocode_to_gdf(\"Piedmont, California, USA\")\n",
+    "place = ox.geocoder.geocode_to_gdf(\"Piedmont, California, USA\")\n",
     "place_proj = ox.projection.project_gdf(place)\n",
     "place_proj.area.iloc[0]"
    ]
@@ -139,11 +139,11 @@
    "source": [
     "point = (48.873446, 2.294255)\n",
     "dist = 612\n",
-    "gdf = ox.features_from_point(point, tags, dist=dist)\n",
+    "gdf = ox.features.features_from_point(point, tags, dist=dist)\n",
     "gdf_proj = ox.projection.project_gdf(gdf)\n",
     "bbox = ox.utils_geo.bbox_from_point(point=point, dist=dist, project_utm=True)\n",
     "fp = f\"./{img_folder}/paris_bldgs.{extension}\"\n",
-    "fig, ax = ox.plot_footprints(\n",
+    "fig, ax = ox.plot.plot_footprints(\n",
     "    gdf_proj,\n",
     "    bbox=bbox,\n",
     "    color=\"w\",\n",
@@ -188,8 +188,8 @@
     "    G = ox.graph.graph_from_point(\n",
     "        point, dist=dist, network_type=network_type, truncate_by_edge=True\n",
     "    )\n",
-    "    gdf = ox.features_from_point(point, tags, dist=dist)\n",
-    "    fig, ax = ox.plot_figure_ground(\n",
+    "    gdf = ox.features.features_from_point(point, tags, dist=dist)\n",
+    "    fig, ax = ox.plot.plot_figure_ground(\n",
     "        G=G,\n",
     "        dist=dist,\n",
     "        default_width=default_width,\n",
@@ -198,7 +198,7 @@
     "        show=False,\n",
     "        close=True,\n",
     "    )\n",
-    "    fig, ax = ox.plot_footprints(\n",
+    "    fig, ax = ox.plot.plot_footprints(\n",
     "        gdf, ax=ax, filepath=fp, dpi=dpi, save=True, show=False, close=True\n",
     "    )\n",
     "\n",
@@ -276,7 +276,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.12.8"
   }
  },
  "nbformat": 4,

notebooks/11-interactive-web-mapping.ipynb

@@ -40,10 +40,10 @@
    "source": [
     "# download a street network then solve a shortest-path route on it\n",
     "weight = \"length\"\n",
-    "G = ox.graph_from_place(\"Piedmont, CA, USA\", network_type=\"drive\")\n",
+    "G = ox.graph.graph_from_place(\"Piedmont, CA, USA\", network_type=\"drive\")\n",
     "orig = list(G.nodes)[0]\n",
     "dest = list(G.nodes)[-1]\n",
-    "route = ox.shortest_path(G, orig, dest, weight=weight)"
+    "route = ox.routing.shortest_path(G, orig, dest, weight=weight)"
    ]
   },
   {
@@ -62,7 +62,7 @@
    "outputs": [],
    "source": [
     "# explore graph edges interactively, with a simple one-liner\n",
-    "ox.graph_to_gdfs(G, nodes=False).explore()"
+    "ox.convert.graph_to_gdfs(G, nodes=False).explore()"
    ]
   },
   {
@@ -81,7 +81,7 @@
    "outputs": [],
    "source": [
     "# explore graph nodes interactively, with different basemap tiles\n",
-    "nodes = ox.graph_to_gdfs(G, edges=False)\n",
+    "nodes = ox.convert.graph_to_gdfs(G, edges=False)\n",
     "nodes.explore(tiles=\"cartodbpositron\", marker_kwds={\"radius\": 8})"
    ]
   },
@@ -94,7 +94,7 @@
    "outputs": [],
    "source": [
     "# explore nodes and edges together in a single map\n",
-    "nodes, edges = ox.graph_to_gdfs(G)\n",
+    "nodes, edges = ox.convert.graph_to_gdfs(G)\n",
     "m = edges.explore(color=\"skyblue\", tiles=\"cartodbdarkmatter\")\n",
     "nodes.explore(m=m, color=\"pink\", marker_kwds={\"radius\": 6})"
    ]
@@ -124,7 +124,7 @@
    "source": [
     "# explore graph nodes interactively, colored by betweenness centrality\n",
     "nx.set_node_attributes(G, nx.betweenness_centrality(G, weight=\"length\"), name=\"bc\")\n",
-    "nodes = ox.graph_to_gdfs(G, edges=False)\n",
+    "nodes = ox.convert.graph_to_gdfs(G, edges=False)\n",
     "nodes.explore(tiles=\"cartodbdarkmatter\", column=\"bc\", marker_kwds={\"radius\": 8})"
    ]
   },
@@ -169,7 +169,7 @@
    "outputs": [],
    "source": [
     "# or explore multiple routes together in a single map\n",
-    "routes = ox.k_shortest_paths(G, orig, dest, k=200, weight=weight)\n",
+    "routes = ox.routing.k_shortest_paths(G, orig, dest, k=200, weight=weight)\n",
     "gdfs = (ox.routing.route_to_gdf(G, route, weight=weight) for route in routes)\n",
     "m = edges.explore(color=\"#222222\", tiles=\"cartodbdarkmatter\")\n",
     "for route_edges in gdfs:\n",
@@ -203,11 +203,11 @@
    "outputs": [],
    "source": [
     "# explore a city's bus stops and rail transit interactively\n",
-    "bus = ox.features_from_place(place, tags={\"highway\": \"bus_stop\"})\n",
+    "bus = ox.features.features_from_place(place, tags={\"highway\": \"bus_stop\"})\n",
     "m = bus.explore(tiles=tiles, color=\"red\", tooltip=\"name\", marker_kwds=mk)\n",
-    "rail = ox.features_from_place(place, tags={\"railway\": \"light_rail\"})\n",
+    "rail = ox.features.features_from_place(place, tags={\"railway\": \"light_rail\"})\n",
     "m = rail.explore(m=m, tiles=tiles, color=\"yellow\", tooltip=\"name\")\n",
-    "stations = ox.features_from_place(place, tags={\"railway\": \"station\"})\n",
+    "stations = ox.features.features_from_place(place, tags={\"railway\": \"station\"})\n",
     "stations.explore(m=m, tiles=tiles, color=\"yellow\", tooltip=\"name\", marker_kwds=mk)"
    ]
   },
@@ -218,7 +218,7 @@
    "outputs": [],
    "source": [
     "# explore a city's parks interactively\n",
-    "parks = ox.features_from_place(place, tags={\"leisure\": \"park\"})\n",
+    "parks = ox.features.features_from_place(place, tags={\"leisure\": \"park\"})\n",
     "parks.explore(tiles=tiles, color=\"lime\", tooltip=\"name\")"
    ]
   },
@@ -229,7 +229,7 @@
    "outputs": [],
    "source": [
     "# explore a neighborhood's buildings interactively\n",
-    "gdf = ox.features_from_place(\"SoHo, New York, NY\", tags={\"building\": True})\n",
+    "gdf = ox.features.features_from_place(\"SoHo, New York, NY\", tags={\"building\": True})\n",
     "cols = [\"height\", \"addr:housenumber\", \"addr:street\", \"addr:postcode\"]\n",
     "gdf.explore(tiles=\"cartodbdarkmatter\", tooltip=cols)"
    ]
@@ -243,10 +243,10 @@
     "# explore a neighborhood's buildings + street network interactively\n",
     "place = \"SoHo, New York, NY\"\n",
     "cols = [\"height\", \"addr:housenumber\", \"addr:street\", \"addr:postcode\"]\n",
-    "G = ox.graph_from_place(place, network_type=\"drive\", truncate_by_edge=True)\n",
-    "gdf = ox.features_from_place(place, tags={\"building\": True})\n",
+    "G = ox.graph.graph_from_place(place, network_type=\"drive\", truncate_by_edge=True)\n",
+    "gdf = ox.features.features_from_place(place, tags={\"building\": True})\n",
     "m = gdf.explore(tiles=tiles, tooltip=cols)\n",
-    "ox.graph_to_gdfs(G, nodes=False).explore(m=m, color=\"yellow\")"
+    "ox.convert.graph_to_gdfs(G, nodes=False).explore(m=m, color=\"yellow\")"
    ]
   },
   {
@@ -286,7 +286,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.12.8"
   }
  },
  "nbformat": 4,

notebooks/12-node-elevations-edge-grades.ipynb

@@ -47,7 +47,7 @@
    "outputs": [],
    "source": [
     "address = \"600 Montgomery St, San Francisco, California, USA\"\n",
-    "G = ox.graph_from_address(address=address, dist=500, dist_type=\"bbox\", network_type=\"bike\")"
+    "G = ox.graph.graph_from_address(address=address, dist=500, dist_type=\"bbox\", network_type=\"bike\")"
    ]
   },
   {
@@ -91,7 +91,7 @@
    "source": [
     "## Elevation from Google Maps Elevation API\n",
     "\n",
-    "You will need a Google Maps Elevation [API key](https://developers.google.com/maps/documentation/elevation/start). Consider your API usage limits. OSMnx rounds coordinates to 5 decimal places (approx 1 meter) to fit 350 locations in a batch. Note that there is some spatial inaccuracy given Google's dataset's resolution. For example, in San Francisco (where the resolution is 19 meters) a couple of edges in hilly parks have a 50+ percent grade because Google assigns one of their nodes the elevation of a hill adjacent to the street."
+    "You will need a Google Maps Elevation [API key](https://developers.google.com/maps/documentation/elevation/start). Remember to track your API usage and costs. If you don't want to set up a Google Maps API key, you could use a free alternative web service that provides the same interface, such as [Open Topo Data](https://www.opentopodata.org/) which doesn't require an API key. Note that there is some spatial inaccuracy in elevation data resolution. For example, in San Francisco (where Google's resolution is ~19 meters) a couple of edges in hilly parks have a 50+ percent grade because Google assigns one of their nodes the elevation of a hill adjacent to the street."
    ]
   },
   {
@@ -100,11 +100,15 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# replace this with your own API key!\n",
-    "try:\n",
-    "    from keys import google_elevation_api_key\n",
-    "except ImportError:\n",
-    "    sys.exit()  # you need an API key to proceed"
+    "# add elevation to each of the nodes, using the Open Topo Data, then calculate edge grades\n",
+    "G = ox.graph.graph_from_place(\"Piedmont, California, USA\", network_type=\"drive\")\n",
+    "original_elevation_url = ox.settings.elevation_url_template\n",
+    "ox.settings.elevation_url_template = (\n",
+    "    \"https://api.opentopodata.org/v1/aster30m?locations={locations}\"\n",
+    ")\n",
+    "G = ox.elevation.add_node_elevations_google(G, batch_size=100, pause=1)\n",
+    "G = ox.elevation.add_edge_grades(G)\n",
+    "ox.settings.elevation_url_template = original_elevation_url"
    ]
   },
   {
@@ -113,19 +117,19 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "# or use the Google Maps Elevation API\n",
+    "# replace this with your own API key!\n",
+    "try:\n",
+    "    from keys import google_elevation_api_key\n",
+    "except ImportError:\n",
+    "    sys.exit()  # you need an API key to proceed\n",
+    "\n",
     "# get the street network for san francisco\n",
     "place = \"San Francisco\"\n",
     "place_query = {\"city\": \"San Francisco\", \"state\": \"California\", \"country\": \"USA\"}\n",
-    "G = ox.graph_from_place(place_query, network_type=\"drive\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# add elevation to each of the nodes, using the google elevation API, then calculate edge grades\n",
+    "G = ox.graph_from_place(place_query, network_type=\"drive\")\n",
+    "\n",
+    "# add elevation to each of the nodes then calculate edge grades\n",
     "G = ox.elevation.add_node_elevations_google(G, api_key=google_elevation_api_key)\n",
     "G = ox.elevation.add_edge_grades(G)"
    ]
@@ -180,7 +184,7 @@
    "source": [
     "# get one color for each node, by elevation, then plot the network\n",
     "nc = ox.plot.get_node_colors_by_attr(G, \"elevation\", cmap=\"plasma\")\n",
-    "fig, ax = ox.plot_graph(G, node_color=nc, node_size=5, edge_color=\"#333333\", bgcolor=\"k\")"
+    "fig, ax = ox.plot.plot_graph(G, node_color=nc, node_size=5, edge_color=\"#333333\", bgcolor=\"k\")"
    ]
   },
   {
@@ -200,7 +204,7 @@
    "source": [
     "# get a color for each edge, by grade, then plot the network\n",
     "ec = ox.plot.get_edge_colors_by_attr(G, \"grade_abs\", cmap=\"plasma\", num_bins=5, equal_size=True)\n",
-    "fig, ax = ox.plot_graph(G, edge_color=ec, edge_linewidth=0.5, node_size=0, bgcolor=\"k\")"
+    "fig, ax = ox.plot.plot_graph(G, edge_color=ec, edge_linewidth=0.5, node_size=0, bgcolor=\"k\")"
    ]
   },
   {
@@ -258,8 +262,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "route_by_length = ox.shortest_path(G, origin, destination, weight=\"length\")\n",
-    "fig, ax = ox.plot_graph_route(G, route_by_length, bbox=bbox, node_size=0)"
+    "route_by_length = ox.routing.shortest_path(G, origin, destination, weight=\"length\")\n",
+    "fig, ax = ox.plot.plot_graph_route(G, route_by_length, bbox=bbox, node_size=0)"
    ]
   },
   {
@@ -275,8 +279,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "route_by_impedance = ox.shortest_path(G, origin, destination, weight=\"impedance\")\n",
-    "fig, ax = ox.plot_graph_route(G, route_by_impedance, bbox=bbox, node_size=0)"
+    "route_by_impedance = ox.routing.shortest_path(G, origin, destination, weight=\"impedance\")\n",
+    "fig, ax = ox.plot.plot_graph_route(G, route_by_impedance, bbox=bbox, node_size=0)"
    ]
   },
   {
@@ -358,7 +362,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.12.8"
   }
  },
  "nbformat": 4,

notebooks/13-isolines-isochrones.ipynb

@@ -60,7 +60,7 @@
    "outputs": [],
    "source": [
     "# download the street network\n",
-    "G = ox.graph_from_place(place, network_type=network_type)"
+    "G = ox.graph.graph_from_place(place, network_type=network_type)"
    ]
   },
   {
@@ -70,10 +70,10 @@
    "outputs": [],
    "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",
+    "gdf_nodes = ox.convert.graph_to_gdfs(G, edges=False)\n",
+    "x, y = gdf_nodes[\"geometry\"].union_all().centroid.xy\n",
     "center_node = ox.distance.nearest_nodes(G, x[0], y[0])\n",
-    "G = ox.project_graph(G)"
+    "G = ox.projection.project_graph(G)"
    ]
   },
   {
@@ -121,7 +121,7 @@
     "        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(\n",
+    "fig, ax = ox.plot.plot_graph(\n",
     "    G,\n",
     "    node_color=nc,\n",
     "    node_size=ns,\n",
@@ -151,7 +151,7 @@
     "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",
+    "    bounding_poly = gpd.GeoSeries(node_points).union_all().convex_hull\n",
     "    isochrone_polys.append(bounding_poly)\n",
     "gdf = gpd.GeoDataFrame(geometry=isochrone_polys)"
    ]
@@ -163,7 +163,7 @@
    "outputs": [],
    "source": [
     "# plot the network then add isochrones as colored polygon patches\n",
-    "fig, ax = ox.plot_graph(\n",
+    "fig, ax = ox.plot.plot_graph(\n",
     "    G, show=False, close=False, edge_color=\"#999999\", edge_alpha=0.2, node_size=0\n",
     ")\n",
     "gdf.plot(ax=ax, color=iso_colors, ec=\"none\", alpha=0.6, zorder=-1)\n",
@@ -202,7 +202,7 @@
     "        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",
+    "        new_iso = gpd.GeoSeries(all_gs).union_all()\n",
     "\n",
     "        # try to fill in surrounded areas so shapes will appear solid and\n",
     "        # blocks without white space inside them\n",
@@ -217,7 +217,7 @@
     "gdf = gpd.GeoDataFrame(geometry=isochrone_polys)\n",
     "\n",
     "# plot the network then add isochrones as colored polygon patches\n",
-    "fig, ax = ox.plot_graph(\n",
+    "fig, ax = ox.plot.plot_graph(\n",
     "    G, show=False, close=False, edge_color=\"#999999\", edge_alpha=0.2, node_size=0\n",
     ")\n",
     "gdf.plot(ax=ax, color=iso_colors, ec=\"none\", alpha=0.6, zorder=-1)\n",
@@ -248,7 +248,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.12.8"
   }
  },
  "nbformat": 4,

notebooks/14-osmnx-to-igraph.ipynb

@@ -51,7 +51,7 @@
    "outputs": [],
    "source": [
     "# create networkx graph\n",
-    "G_nx = ox.graph_from_place(\"Piedmont, CA, USA\", network_type=\"drive\")\n",
+    "G_nx = ox.graph.graph_from_place(\"Piedmont, CA, USA\", network_type=\"drive\")\n",
     "osmids = list(G_nx.nodes)\n",
     "G_nx = nx.relabel.convert_node_labels_to_integers(G_nx)\n",
     "\n",
@@ -223,7 +223,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.12.8"
   }
  },
  "nbformat": 4,

notebooks/15-advanced-plotting.ipynb

@@ -33,7 +33,7 @@
    "outputs": [],
    "source": [
     "place = \"Piedmont, California, USA\"\n",
-    "G = ox.graph_from_place(place, network_type=\"drive\")"
+    "G = ox.graph.graph_from_place(place, network_type=\"drive\")"
    ]
   },
   {
@@ -63,7 +63,7 @@
    "source": [
     "# get node colors by linearly mapping an attribute's values to a colormap\n",
     "nc = ox.plot.get_node_colors_by_attr(G, attr=\"y\", cmap=\"plasma\")\n",
-    "fig, ax = ox.plot_graph(G, node_color=nc, edge_linewidth=0.3)"
+    "fig, ax = ox.plot.plot_graph(G, node_color=nc, edge_linewidth=0.3)"
    ]
   },
   {
@@ -80,7 +80,7 @@
     "ec = ox.plot.get_edge_colors_by_attr(G, attr=\"length\")\n",
     "\n",
     "# plot the graph with colored edges\n",
-    "fig, ax = ox.plot_graph(G, node_size=5, edge_color=ec, bgcolor=\"k\")"
+    "fig, ax = ox.plot.plot_graph(G, node_size=5, edge_color=ec, bgcolor=\"k\")"
    ]
   },
   {
@@ -98,7 +98,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig, ax = ox.plot_graph(\n",
+    "fig, ax = ox.plot.plot_graph(\n",
     "    G,\n",
     "    ax=None,  # optionally draw on pre-existing axis\n",
     "    figsize=(8, 8),  # figure size to create if ax is None\n",
@@ -135,10 +135,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "Gc = ox.consolidate_intersections(ox.project_graph(G), dead_ends=True)\n",
-    "c = ox.graph_to_gdfs(G, edges=False).unary_union.centroid\n",
+    "Gc = ox.simplification.consolidate_intersections(ox.projection.project_graph(G), dead_ends=True)\n",
+    "c = ox.convert.graph_to_gdfs(G, edges=False).union_all().centroid\n",
     "bbox = ox.utils_geo.bbox_from_point(point=(c.y, c.x), dist=200, project_utm=True)\n",
-    "fig, ax = ox.plot_graph(\n",
+    "fig, ax = ox.plot.plot_graph(\n",
     "    Gc,\n",
     "    figsize=(5, 5),\n",
     "    bbox=bbox,\n",
@@ -157,7 +157,7 @@
    "outputs": [],
    "source": [
     "# or save a figure to disk instead of showing it\n",
-    "fig, ax = ox.plot_graph(G, filepath=\"./images/image.png\", save=True, show=False, close=True)"
+    "fig, ax = ox.plot.plot_graph(G, filepath=\"./images/image.png\", save=True, show=False, close=True)"
    ]
   },
   {
@@ -174,17 +174,17 @@
    "outputs": [],
    "source": [
     "# impute missing edge speeds and calculate free-flow travel times\n",
-    "G = ox.add_edge_speeds(G)\n",
-    "G = ox.add_edge_travel_times(G)\n",
+    "G = ox.routing.add_edge_speeds(G)\n",
+    "G = ox.routing.add_edge_travel_times(G)\n",
     "\n",
     "# calculate 3 shortest paths, minimizing travel time\n",
     "w = \"travel_time\"\n",
     "orig, dest = list(G)[10], list(G)[-10]\n",
-    "route1 = ox.shortest_path(G, orig, dest, weight=w)\n",
+    "route1 = ox.routing.shortest_path(G, orig, dest, weight=w)\n",
     "orig, dest = list(G)[0], list(G)[-1]\n",
-    "route2 = ox.shortest_path(G, orig, dest, weight=w)\n",
+    "route2 = ox.routing.shortest_path(G, orig, dest, weight=w)\n",
     "orig, dest = list(G)[-100], list(G)[100]\n",
-    "route3 = ox.shortest_path(G, orig, dest, weight=w)"
+    "route3 = ox.routing.shortest_path(G, orig, dest, weight=w)"
    ]
   },
   {
@@ -200,7 +200,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig, ax = ox.plot_graph_route(G, route1, orig_dest_size=0, node_size=0)"
+    "fig, ax = ox.plot.plot_graph_route(G, route1, orig_dest_size=0, node_size=0)"
    ]
   },
   {
@@ -210,7 +210,7 @@
    "outputs": [],
    "source": [
     "# you can also pass any ox.plot_graph parameters as additional keyword args\n",
-    "fig, ax = ox.plot_graph_route(G, route1, save=True, show=False, close=True)"
+    "fig, ax = ox.plot.plot_graph_route(G, route1, save=True, show=False, close=True)"
    ]
   },
   {
@@ -230,7 +230,7 @@
    "source": [
     "routes = [route1, route2, route3]\n",
     "rc = [\"r\", \"y\", \"c\"]\n",
-    "fig, ax = ox.plot_graph_routes(G, routes, route_colors=rc, route_linewidth=6, node_size=0)"
+    "fig, ax = ox.plot.plot_graph_routes(G, routes, route_colors=rc, route_linewidth=6, node_size=0)"
    ]
   },
   {
@@ -248,7 +248,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "G2 = ox.graph_from_address(\"Piedmont, CA, USA\", dist=200, network_type=\"drive\")\n",
+    "G2 = ox.graph.graph_from_address(\"Piedmont, CA, USA\", dist=200, network_type=\"drive\")\n",
     "G2 = ox.convert.to_undirected(G2)"
    ]
   },
@@ -258,8 +258,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig, ax = ox.plot_graph(G2, edge_linewidth=3, node_size=0, show=False, close=False)\n",
-    "for _, edge in ox.graph_to_gdfs(G2, nodes=False).fillna(\"\").iterrows():\n",
+    "fig, ax = ox.plot.plot_graph(G2, edge_linewidth=3, node_size=0, show=False, close=False)\n",
+    "for _, edge in ox.convert.graph_to_gdfs(G2, nodes=False).fillna(\"\").iterrows():\n",
     "    text = edge[\"name\"]\n",
     "    c = edge[\"geometry\"].centroid\n",
     "    ax.annotate(text, (c.x, c.y), c=\"y\")\n",
@@ -282,7 +282,7 @@
    "outputs": [],
    "source": [
     "# get all the building footprints in a city\n",
-    "gdf = ox.features_from_place(\"Piedmont, California, USA\", {\"building\": True})\n",
+    "gdf = ox.features.features_from_place(\"Piedmont, California, USA\", {\"building\": True})\n",
     "gdf.shape"
    ]
   },
@@ -292,7 +292,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig, ax = ox.plot_footprints(gdf)"
+    "fig, ax = ox.plot.plot_footprints(gdf)"
    ]
   },
   {
@@ -302,8 +302,8 @@
    "outputs": [],
    "source": [
     "# or plot street network and the geospatial features' footprints together\n",
-    "fig, ax = ox.plot_footprints(gdf, alpha=0.4, show=False)\n",
-    "fig, ax = ox.plot_graph(G, ax=ax, node_size=0, edge_color=\"w\", edge_linewidth=0.7)"
+    "fig, ax = ox.plot.plot_footprints(gdf, alpha=0.4, show=False)\n",
+    "fig, ax = ox.plot.plot_graph(G, ax=ax, node_size=0, edge_color=\"w\", edge_linewidth=0.7)"
    ]
   },
   {
@@ -330,7 +330,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.12.8"
   }
  },
  "nbformat": 4,

notebooks/16-download-osm-geospatial-features.ipynb

@@ -25,6 +25,7 @@
    "outputs": [],
    "source": [
     "import osmnx as ox\n",
+    "import pandas as pd\n",
     "\n",
     "ox.__version__"
    ]
@@ -53,7 +54,7 @@
     "# `True` means retrieve any object with this tag, regardless of value\n",
     "place = \"SoHo, New York, NY\"\n",
     "tags = {\"building\": True}\n",
-    "gdf = ox.features_from_place(place, tags)\n",
+    "gdf = ox.features.features_from_place(place, tags)\n",
     "gdf.shape"
    ]
   },
@@ -63,7 +64,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig, ax = ox.plot_footprints(gdf, figsize=(3, 3))"
+    "fig, ax = ox.plot.plot_footprints(gdf, figsize=(3, 3))"
    ]
   },
   {
@@ -75,7 +76,7 @@
     "# get all the parks in some neighborhood\n",
     "# constrain acceptable `leisure` tag values to `park`\n",
     "tags = {\"leisure\": \"park\"}\n",
-    "gdf = ox.features_from_place(place, tags)\n",
+    "gdf = ox.features.features_from_place(place, tags)\n",
     "gdf.shape"
    ]
   },
@@ -89,7 +90,7 @@
     "# and everything tagged landuse = retail or commercial,\n",
     "# and everything tagged highway = bus_stop\n",
     "tags = {\"amenity\": True, \"landuse\": [\"retail\", \"commercial\"], \"highway\": \"bus_stop\"}\n",
-    "gdf = ox.features_from_place(\"Piedmont, California, USA\", tags)\n",
+    "gdf = ox.features.features_from_place(\"Piedmont, California, USA\", tags)\n",
     "gdf.shape"
    ]
   },
@@ -113,6 +114,42 @@
     "gdf[gdf[\"highway\"] == \"bus_stop\"].dropna(axis=1, how=\"any\").head()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Attach features to nearest nodes\n",
+    "\n",
+    "For example, attach parking information to nearest network nodes."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# first create the graph and the features\n",
+    "place = \"Piedmont, CA, USA\"\n",
+    "G = ox.graph.graph_from_place(place, network_type=\"drive\")\n",
+    "features = ox.features.features_from_place(place, {\"amenity\": \"parking\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# then attach your features to your graph's nearest nodes as attributes\n",
+    "feature_points = features.representative_point()\n",
+    "nn = ox.distance.nearest_nodes(G, feature_points.x, feature_points.y)\n",
+    "useful_tags = [\"access\", \"parking\", \"surface\", \"capacity\", \"fee\"]\n",
+    "for node, feature in zip(nn, features[useful_tags].to_dict(orient=\"records\")):\n",
+    "    feature = {k: v for k, v in feature.items() if pd.notna(v)}\n",
+    "    G.nodes[node].update({\"parking\": feature})"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -137,7 +174,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.12.8"
   }
  },
  "nbformat": 4,

notebooks/17-street-network-orientations.ipynb

@@ -74,7 +74,7 @@
    "outputs": [],
    "source": [
     "# verify OSMnx geocodes each query to what you expect (i.e., a [multi]polygon geometry)\n",
-    "gdf = ox.geocode_to_gdf(list(places.values()))\n",
+    "gdf = ox.geocoder.geocode_to_gdf(list(places.values()))\n",
     "gdf"
    ]
   },
@@ -96,9 +96,9 @@
     "    print(ox.utils.ts(), place)\n",
     "\n",
     "    # get undirected graphs with edge bearing attributes\n",
-    "    G = ox.graph_from_place(place, network_type=\"drive\")\n",
-    "    Gu = ox.add_edge_bearings(ox.convert.to_undirected(G))\n",
-    "    fig, ax = ox.plot_orientation(Gu, ax=ax, title=place, area=True)\n",
+    "    G = ox.graph.graph_from_place(place, network_type=\"drive\")\n",
+    "    Gu = ox.bearing.add_edge_bearings(ox.convert.to_undirected(G))\n",
+    "    fig, ax = ox.plot.plot_orientation(Gu, ax=ax, title=place, area=True)\n",
     "\n",
     "# add figure title and save image\n",
     "suptitle_font = {\n",
@@ -145,7 +145,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.12.8"
   }
  },
  "nbformat": 4,