Merge pull request #97 from gboeing/new

Update examples and add new examples

.pre-commit-config.yaml

@@ -15,12 +15,6 @@ repos:
         args: [--branch, main]
       - id: trailing-whitespace
 
-  - repo: https://github.com/pre-commit/mirrors-prettier
-    rev: "v4.0.0-alpha.8"
-    hooks:
-      - id: prettier
-        types_or: [markdown, yaml]
-
   - repo: https://github.com/nbQA-dev/nbQA
     rev: "1.9.1"
     hooks:

LICENSE.txt

@@ -1,6 +1,6 @@
 The MIT License (MIT)
 
-Copyright (c) 2016-2024 Geoff Boeing https://geoffboeing.com/
+Copyright (c) 2016-2025 Geoff Boeing https://geoffboeing.com/
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

environment.yml

@@ -5,7 +5,5 @@ channels:
 dependencies:
   - jupyterlab
   - osmnx=2.0.*
-  - pillow
   - pre-commit
-  - python=3.11.*
   - python-igraph

notebooks/00-osmnx-features-demo.ipynb

@@ -54,8 +54,8 @@
    "outputs": [],
    "source": [
     "# download/model a street network for some city then visualize it\n",
-    "G = ox.graph_from_place(\"Piedmont, California, USA\", network_type=\"drive\")\n",
-    "fig, ax = ox.plot_graph(G)"
+    "G = ox.graph.graph_from_place(\"Piedmont, California, USA\", network_type=\"drive\")\n",
+    "fig, ax = ox.plot.plot_graph(G)"
    ]
   },
   {
@@ -67,7 +67,9 @@
     "OSMnx models all networks as NetworkX `MultiDiGraph` objects. You can convert to:\n",
     "  - undirected MultiGraphs\n",
     "  - DiGraphs without (possible) parallel edges\n",
-    "  - GeoPandas node/edge GeoDataFrames"
+    "  - GeoPandas node/edge GeoDataFrames\n",
+    "\n",
+    "Note that converting to an undirected MultiGraph is really only meant for use cases where a function or algorithm only accepts a MultiGraph argument. If you just want a fully bidirectional graph (such as for a walking network), just configure the `settings` module’s `bidirectional_network_types` before creating your graph."
    ]
   },
   {
@@ -76,6 +78,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "# get a fully bidirection network (as a MultiDiGraph)\n",
+    "ox.settings.bidirectional_network_types += \"drive\"\n",
+    "G = ox.graph.graph_from_place(\"Piedmont, California, USA\", network_type=\"drive\")\n",
+    "\n",
     "# convert your MultiDiGraph to an undirected MultiGraph\n",
     "M = ox.convert.to_undirected(G)\n",
     "\n",
@@ -90,7 +96,7 @@
    "outputs": [],
    "source": [
     "# you can convert your graph to node and edge GeoPandas GeoDataFrames\n",
-    "gdf_nodes, gdf_edges = ox.graph_to_gdfs(G)\n",
+    "gdf_nodes, gdf_edges = ox.convert.graph_to_gdfs(G)\n",
     "gdf_nodes.head()"
    ]
   },
@@ -117,7 +123,7 @@
    "outputs": [],
    "source": [
     "# convert node/edge GeoPandas GeoDataFrames to a NetworkX MultiDiGraph\n",
-    "G2 = ox.graph_from_gdfs(gdf_nodes, gdf_edges, graph_attrs=G.graph)"
+    "G2 = ox.convert.graph_from_gdfs(gdf_nodes, gdf_edges, graph_attrs=G.graph)"
    ]
   },
   {
@@ -134,9 +140,9 @@
    "outputs": [],
    "source": [
     "# what sized area does our network cover in square meters?\n",
-    "G_proj = ox.project_graph(G)\n",
-    "nodes_proj = ox.graph_to_gdfs(G_proj, edges=False)\n",
-    "graph_area_m = nodes_proj.unary_union.convex_hull.area\n",
+    "G_proj = ox.projection.project_graph(G)\n",
+    "nodes_proj = ox.convert.graph_to_gdfs(G_proj, edges=False)\n",
+    "graph_area_m = nodes_proj.union_all().convex_hull.area\n",
     "graph_area_m"
    ]
   },
@@ -147,7 +153,7 @@
    "outputs": [],
    "source": [
     "# show some basic stats about the network\n",
-    "ox.basic_stats(G_proj, area=graph_area_m, clean_int_tol=15)"
+    "ox.stats.basic_stats(G_proj, area=graph_area_m, clean_int_tol=15)"
    ]
   },
   {
@@ -164,8 +170,8 @@
    "outputs": [],
    "source": [
     "# save graph to disk as geopackage (for GIS) or graphml file (for gephi etc)\n",
-    "ox.save_graph_geopackage(G, filepath=\"./data/mynetwork.gpkg\")\n",
-    "ox.save_graphml(G, filepath=\"./data/mynetwork.graphml\")"
+    "ox.io.save_graph_geopackage(G, filepath=\"./data/mynetwork.gpkg\")\n",
+    "ox.io.save_graphml(G, filepath=\"./data/mynetwork.graphml\")"
    ]
   },
   {
@@ -196,7 +202,7 @@
    "source": [
     "# color edges in original graph with closeness centralities from line graph\n",
     "ec = ox.plot.get_edge_colors_by_attr(G, \"edge_centrality\", cmap=\"inferno\")\n",
-    "fig, ax = ox.plot_graph(G, edge_color=ec, edge_linewidth=2, node_size=0)"
+    "fig, ax = ox.plot.plot_graph(G, edge_color=ec, edge_linewidth=2, node_size=0)"
    ]
   },
   {
@@ -235,8 +241,8 @@
    "outputs": [],
    "source": [
     "# find the shortest path between nodes, minimizing travel time, then plot it\n",
-    "route = ox.shortest_path(G, orig, dest, weight=\"travel_time\")\n",
-    "fig, ax = ox.plot_graph_route(G, route, node_size=0)"
+    "route = ox.routing.shortest_path(G, orig, dest, weight=\"travel_time\")\n",
+    "fig, ax = ox.plot.plot_graph_route(G, route, node_size=0)"
    ]
   },
   {
@@ -286,7 +292,9 @@
     "    G = ox.elevation.add_node_elevations_google(G, api_key=google_elevation_api_key)\n",
     "    G = ox.elevation.add_edge_grades(G)\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=20, edge_linewidth=2, edge_color=\"#333\")\n",
+    "    fig, ax = ox.plot.plot_graph(\n",
+    "        G, node_color=nc, node_size=20, edge_linewidth=2, edge_color=\"#333\"\n",
+    "    )\n",
     "except ImportError:\n",
     "    print(\"You need a google_elevation_api_key to run this cell.\")"
    ]
@@ -317,8 +325,8 @@
    "source": [
     "# you can make query an unambiguous dict to help the geocoder find it\n",
     "place = {\"city\": \"San Francisco\", \"state\": \"California\", \"country\": \"USA\"}\n",
-    "G = ox.graph_from_place(place, network_type=\"drive\", truncate_by_edge=True)\n",
-    "fig, ax = ox.plot_graph(G, figsize=(10, 10), node_size=0, edge_color=\"y\", edge_linewidth=0.2)"
+    "G = ox.graph.graph_from_place(place, network_type=\"drive\", truncate_by_edge=True)\n",
+    "fig, ax = ox.plot.plot_graph(G, figsize=(10, 10), node_size=0, edge_color=\"y\", edge_linewidth=0.2)"
    ]
   },
   {
@@ -328,8 +336,8 @@
    "outputs": [],
    "source": [
     "# you can get networks anywhere in the world\n",
-    "G = ox.graph_from_place(\"Sinalunga, Italy\", network_type=\"all\")\n",
-    "fig, ax = ox.plot_graph(G, node_size=0, edge_linewidth=0.5)"
+    "G = ox.graph.graph_from_place(\"Sinalunga, Italy\", network_type=\"all\")\n",
+    "fig, ax = ox.plot.plot_graph(G, node_size=0, edge_linewidth=0.5)"
    ]
   },
   {
@@ -342,8 +350,8 @@
     "# ...useful when OSM just doesn't already have a polygon for the place you want\n",
     "wurster_hall = (37.870605, -122.254830)\n",
     "one_mile = 1609  # meters\n",
-    "G = ox.graph_from_point(wurster_hall, dist=one_mile, network_type=\"drive\")\n",
-    "fig, ax = ox.plot_graph(G, node_size=0)"
+    "G = ox.graph.graph_from_point(wurster_hall, dist=one_mile, network_type=\"drive\")\n",
+    "fig, ax = ox.plot.plot_graph(G, node_size=0)"
    ]
   },
   {
@@ -369,15 +377,15 @@
    "outputs": [],
    "source": [
     "# get NY subway rail network\n",
-    "G = ox.graph_from_place(\n",
+    "G = ox.graph.graph_from_place(\n",
     "    \"New York, New York, USA\",\n",
     "    retain_all=False,\n",
     "    truncate_by_edge=True,\n",
     "    simplify=True,\n",
     "    custom_filter='[\"railway\"~\"subway\"]',\n",
     ")\n",
     "\n",
-    "fig, ax = ox.plot_graph(G, node_size=0, edge_color=\"w\", edge_linewidth=0.2)"
+    "fig, ax = ox.plot.plot_graph(G, node_size=0, edge_color=\"w\", edge_linewidth=0.2)"
    ]
   },
   {
@@ -398,7 +406,7 @@
     "# get all building footprints in some neighborhood\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"
    ]
   },
@@ -408,7 +416,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig, ax = ox.plot_footprints(gdf, figsize=(3, 3))"
+    "fig, ax = ox.plot.plot_footprints(gdf, figsize=(3, 3))"
    ]
   },
   {
@@ -426,7 +434,7 @@
    "source": [
     "# get all parks and bus stops in some neighborhood\n",
     "tags = {\"leisure\": \"park\", \"highway\": \"bus_stop\"}\n",
-    "gdf = ox.features_from_place(place, tags)\n",
+    "gdf = ox.features.features_from_place(place, tags)\n",
     "gdf.shape"
    ]
   },
@@ -454,7 +462,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.12.8"
   }
  },
  "nbformat": 4,