osmnx package¶
Users’ reference for the OSMnx API.
This guide covers all public modules and functions. Every function can be accessed via ox.module_name.function_name() and the vast majority of them can also be accessed directly via ox.function_name() as a shortcut. Only a few less-common functions are accessible only via ox.module_name.function_name().
osmnx.bearing module¶
Calculate graph edge bearings.
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osmnx.bearing.
add_edge_bearings
(G, precision=1)¶ Add bearing attributes to all graph edges.
Calculate the compass bearing from origin node to destination node for each edge in the directed graph then add each bearing as a new edge attribute. Bearing represents angle in degrees (clockwise) between north and the direction from the origin node to the destination node.
- Parameters
G (networkx.MultiDiGraph) – input graph
precision (int) – decimal precision to round bearing
- Returns
G – graph with edge bearing attributes
- Return type
networkx.MultiDiGraph
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osmnx.bearing.
get_bearing
(origin_point, destination_point)¶ Calculate the bearing between two lat-lng points.
Each argument tuple should represent (lat, lng) as decimal degrees. Bearing represents angle in degrees (clockwise) between north and the direction from the origin point to the destination point.
- Parameters
origin_point (tuple) – (lat, lng)
destination_point (tuple) – (lat, lng)
- Returns
bearing – the compass bearing in decimal degrees from the origin point to the destination point
- Return type
float
osmnx.distance module¶
Calculate distances and shortest paths and find nearest node/edge(s) to point(s).
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osmnx.distance.
euclidean_dist_vec
(y1, x1, y2, x2)¶ Calculate Euclidean distances between points.
Vectorized function to calculate the Euclidean distance between two points’ coordinates or between arrays of points’ coordinates. For most accurate results, use projected coordinates rather than decimal degrees.
- Parameters
y1 (float or np.array of float) – first point’s y coordinate
x1 (float or np.array of float) – first point’s x coordinate
y2 (float or np.array of float) – second point’s y coordinate
x2 (float or np.array of float) – second point’s x coordinate
- Returns
dist – distance or array of distances from (x1, y1) to (x2, y2) in coordinates’ units
- Return type
float or np.array of float
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osmnx.distance.
get_nearest_edge
(G, point, return_geom=False, return_dist=False)¶ Find the nearest edge to a point by minimum Euclidean distance.
- Parameters
G (networkx.MultiDiGraph) – input graph
point (tuple) – the (lat, lng) or (y, x) point for which we will find the nearest edge in the graph
return_geom (bool) – Optionally return the geometry of the nearest edge
return_dist (bool) – Optionally return the distance in graph’s coordinates’ units between the point and the nearest edge
- Returns
Graph edge unique identifier as a tuple of (u, v, key). Or a tuple of (u, v, key, geom) if return_geom is True. Or a tuple of (u, v, key, dist) if return_dist is True. Or a tuple of (u, v, key, geom, dist) if return_geom and return_dist are True.
- Return type
tuple
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osmnx.distance.
get_nearest_edges
(G, X, Y, method=None, dist=0.0001)¶ Find the nearest edge to each point in a list of points.
Pass in points as separate lists of X and Y coordinates. The ‘kdtree’ method is by far the fastest with large data sets, but only finds approximate nearest edges if working in unprojected coordinates like lat-lng (it precisely finds the nearest edge if working in projected coordinates). The ‘balltree’ method is second fastest with large data sets, but it is precise if working in unprojected coordinates like lat-lng. As a rule of thumb, if you have a small graph just use method=None. If you have a large graph with lat-lng coordinates, use method=’balltree’. If you have a large graph with projected coordinates, use method=’kdtree’. Note that if you are working in units of lat-lng, the X vector corresponds to longitude and the Y vector corresponds to latitude. The method creates equally distanced points along the edges of the network. Then, these points are used in a kdTree or BallTree search to identify which is nearest. Note that this method will not give exact perpendicular point along the edge, but the smaller the dist parameter, the closer (but slower) the solution will be.
- Parameters
G (networkx.MultiDiGraph) – input graph
X (list-like) – the longitudes or x coordinates for which we will find the nearest edge in the graph. For projected graphs use the projected coordinates, usually in meters.
Y (list-like) – the latitudes or y coordinates for which we will find the nearest edge in the graph. For projected graphs use the projected coordinates, usually in meters.
method (string {None, 'kdtree', 'balltree'}) – Which method to use for finding nearest edge to each point. If None, we manually find each edge one at a time using get_nearest_edge. If ‘kdtree’ we use scipy.spatial.cKDTree for very fast euclidean search. Recommended for projected graphs. If ‘balltree’, we use sklearn.neighbors.BallTree for fast haversine search. Recommended for unprojected graphs.
dist (float) – spacing length along edges. Units are the same as the graph’s geometries. The smaller the value, the more points are created.
- Returns
ne – array of edge IDs representing the edge nearest to each point in the passed-in list of points. Edge IDs are represented by u, v, key where u and v the node IDs of the nodes the edge links.
- Return type
np.array
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osmnx.distance.
get_nearest_node
(G, point, method='haversine', return_dist=False)¶ Find the nearest node to a point.
Return the graph node nearest to some (lat, lng) or (y, x) point and optionally the distance between the node and the point. This function can use either the haversine formula or Euclidean distance.
- Parameters
G (networkx.MultiDiGraph) – input graph
point (tuple) – The (lat, lng) or (y, x) point for which we will find the nearest node in the graph
method (string {'haversine', 'euclidean'}) – Which method to use for calculating distances to find nearest node. If ‘haversine’, graph nodes’ coordinates must be in units of decimal degrees. If ‘euclidean’, graph nodes’ coordinates must be projected.
return_dist (bool) – Optionally also return the distance (in meters if haversine, or graph node coordinate units if euclidean) between the point and the nearest node
- Returns
Nearest node ID or optionally a tuple of (node ID, dist), where dist is the distance (in meters if haversine, or graph node coordinate units if euclidean) between the point and nearest node
- Return type
int or tuple of (int, float)
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osmnx.distance.
get_nearest_nodes
(G, X, Y, method=None)¶ Find the nearest node to each point in a list of points.
Pass in points as separate lists of X and Y coordinates. The ‘kdtree’ method is by far the fastest with large data sets, but only finds approximate nearest nodes if working in unprojected coordinates like lat-lng (it precisely finds the nearest node if working in projected coordinates). The ‘balltree’ method is second fastest with large data sets but it is precise if working in unprojected coordinates like lat-lng.
- Parameters
G (networkx.MultiDiGraph) – input graph
X (list-like) – the longitudes or x coordinates for which we will find the nearest node in the graph
Y (list-like) – the latitudes or y coordinates for which we will find the nearest node in the graph
method (string {None, 'kdtree', 'balltree'}) – Which method to use for finding the nearest node to each point. If None, we manually find each node one at a time using utils.get_nearest_node and haversine. If ‘kdtree’ we use scipy.spatial.cKDTree for very fast euclidean search. If ‘balltree’, we use sklearn.neighbors.BallTree for fast haversine search.
- Returns
nn – array of node IDs representing the node nearest to each point in the passed-in list of points
- Return type
np.array
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osmnx.distance.
great_circle_vec
(lat1, lng1, lat2, lng2, earth_radius=6371009)¶ Calculate great-circle distances between points.
Vectorized function to calculate the great-circle distance between two points’ coordinates or between arrays of points’ coordinates using the haversine formula. Expects coordinates in decimal degrees.
- Parameters
lat1 (float or np.array of float) – first point’s latitude coordinate
lng1 (float or np.array of float) – first point’s longitude coordinate
lat2 (float or np.array of float) – second point’s latitude coordinate
lng2 (float or np.array of float) – second point’s longitude coordinate
earth_radius (int or float) – radius of earth in units in which distance will be returned (default is meters)
- Returns
dist – distance or array of distances from (lat1, lng1) to (lat2, lng2) in units of earth_radius
- Return type
float or np.array
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osmnx.distance.
k_shortest_paths
(G, orig, dest, k, weight='length')¶ Get k shortest paths from origin node to destination node.
See also shortest_path to get just the one shortest path.
- Parameters
G (networkx.MultiDiGraph) – input graph
orig (int) – origin node ID
dest (int) – destination node ID
k (int) – number of shortest paths to get
weight (string) – edge attribute to minimize when solving shortest paths. default is edge length in meters.
- Returns
a generator of k shortest paths ordered by total weight. each path is a list of node IDs.
- Return type
generator
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osmnx.distance.
shortest_path
(G, orig, dest, weight='length')¶ Get shortest path from origin node to destination node.
See also k_shortest_paths to get multiple shortest paths.
This function is a convenience wrapper around networkx.shortest_path. For more functionality or different algorithms, use networkx directly.
- Parameters
G (networkx.MultiDiGraph) – input graph
orig (int) – origin node ID
dest (int) – destination node ID
weight (string) – edge attribute to minimize when solving shortest path. default is edge length in meters.
- Returns
path – list of node IDs consituting the shortest path
- Return type
list
osmnx.downloader module¶
Interact with the OSM APIs.
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osmnx.downloader.
nominatim_request
(params, request_type='search', pause=1, error_pause=60)¶ Send a HTTP GET request to the Nominatim API and return JSON response.
- Parameters
params (OrderedDict) – key-value pairs of parameters
request_type (string) – Type of Nominatim query. One of: search, reverse, or lookup
pause (int) – how long to pause before request, in seconds. per the nominatim usage policy: “an absolute maximum of 1 request per second” is allowed
error_pause (int) – how long to pause in seconds before re-trying request if error
- Returns
response_json
- Return type
dict
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osmnx.downloader.
overpass_request
(data, pause=None, error_pause=60)¶ Send a HTTP POST request to the Overpass API and return JSON response.
- Parameters
data (OrderedDict) – key-value pairs of parameters
pause (int) – how long to pause in seconds before request, if None, will query API status endpoint to find when next slot is available
error_pause (int) – how long to pause in seconds (in addition to pause) before re-trying request if error
- Returns
response_json
- Return type
dict
osmnx.elevation module¶
Get node elevations and calculate edge grades.
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osmnx.elevation.
add_edge_grades
(G, add_absolute=True, precision=3)¶ Add grade attribute to each graph edge.
Get the directed grade (ie, rise over run) for each edge in the graph and add it to the edge as an attribute. Nodes must have elevation attributes to use this function.
See also the add_node_elevations function.
- Parameters
G (networkx.MultiDiGraph) – input graph
add_absolute (bool) – if True, also add absolute value of grade as grade_abs attribute
precision (int) – decimal precision to round grade values
- Returns
G – graph with edge grade (and optionally grade_abs) attributes
- Return type
networkx.MultiDiGraph
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osmnx.elevation.
add_node_elevations
(G, api_key, max_locations_per_batch=350, pause_duration=0.02, precision=3)¶ Add elevation (meters) attribute to each node.
Uses the Google Maps Elevation API by default, but you can configure this to a different provider via ox.config()
See also the add_edge_grades function.
- Parameters
G (networkx.MultiDiGraph) – input graph
api_key (string) – your google maps elevation API key, or equivalent if using a different provider
max_locations_per_batch (int) – max number of coordinate pairs to submit in each API call (if this is too high, the server will reject the request because its character limit exceeds the max)
pause_duration (float) – time to pause between API calls
precision (int) – decimal precision to round elevation
- Returns
G – graph with node elevation attributes
- Return type
networkx.MultiDiGraph
osmnx.folium module¶
Create leaflet web maps via folium.
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osmnx.folium.
plot_graph_folium
(G, graph_map=None, popup_attribute=None, tiles='cartodbpositron', zoom=1, fit_bounds=True, edge_color='#333333', edge_width=5, edge_opacity=1, **kwargs)¶ Plot a graph on an interactive folium web map.
Note that anything larger than a small city can take a long time to plot and create a large web map file that is very slow to load as JavaScript.
- Parameters
G (networkx.MultiDiGraph) – input graph
graph_map (folium.folium.Map or folium.FeatureGroup) – if not None, plot the graph on this preexisting folium map object
popup_attribute (string) – edge attribute to display in a pop-up when an edge is clicked
tiles (string) – name of a folium tileset
zoom (int) – initial zoom level for the map
fit_bounds (bool) – if True, fit the map to the boundaries of the route’s edges
edge_color (string) – color of the edge lines
edge_width (numeric) – width of the edge lines
edge_opacity (numeric) – opacity of the edge lines
kwargs (dict) – Extra keyword arguments passed through to folium
- Returns
graph_map
- Return type
folium.folium.Map
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osmnx.folium.
plot_route_folium
(G, route, route_map=None, popup_attribute=None, tiles='cartodbpositron', zoom=1, fit_bounds=True, route_color='#cc0000', route_width=5, route_opacity=1, **kwargs)¶ Plot a route on an interactive folium web map.
- Parameters
G (networkx.MultiDiGraph) – input graph
route (list) – the route as a list of nodes
route_map (folium.folium.Map) – if not None, plot the route on this preexisting folium map object
popup_attribute (string) – edge attribute to display in a pop-up when an edge is clicked
tiles (string) – name of a folium tileset
zoom (int) – initial zoom level for the map
fit_bounds (bool) – if True, fit the map to the boundaries of the route’s edges
route_color (string) – color of the route’s line
route_width (numeric) – width of the route’s line
route_opacity (numeric) – opacity of the route lines
kwargs (dict) – Extra parameters passed through to folium
- Returns
route_map
- Return type
folium.folium.Map
osmnx.footprints module¶
Download footprints from OpenStreetMap.
Deprecated: use the new geometries module instead.
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osmnx.footprints.
footprints_from_address
(address, dist=1000, footprint_type='building', retain_invalid=False)¶ Get footprints within some distance N, S, E, W of an address.
Deprecated: use geometries module instead.
- Parameters
address (string) – the address to geocode to a lat-lng point
dist (numeric) – distance in meters
footprint_type (string) – type of footprint to be downloaded. OSM tag key e.g. ‘building’, ‘landuse’, ‘place’, etc.
retain_invalid (bool) – deprecated, is ignored
- Returns
- Return type
geopandas.GeoDataFrame
Notes
You can configure the Overpass server timeout, memory allocation, and other custom settings via ox.config().
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osmnx.footprints.
footprints_from_place
(place, footprint_type='building', retain_invalid=False, which_result=None)¶ Get footprints within the boundaries of some place.
Deprecated: use geometries module instead.
The query must be geocodable and OSM must have polygon boundaries for the geocode result. If OSM does not have a polygon for this place, you can instead get its footprints using the footprints_from_address function, which geocodes the place name to a point and gets the footprints within some distance of that point.
- Parameters
place (string) – the query to geocode to get place boundary polygon
footprint_type (string) – type of footprint to be downloaded. OSM tag key e.g. ‘building’, ‘landuse’, ‘place’, etc.
retain_invalid (bool) – deprecated, is ignored
which_result (int) – which geocoding result to use. if None, auto-select the first multi/polygon or raise an error if OSM doesn’t return one.
- Returns
- Return type
geopandas.GeoDataFrame
Notes
You can configure the Overpass server timeout, memory allocation, and other custom settings via ox.config().
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osmnx.footprints.
footprints_from_point
(point, dist=1000, footprint_type='building', retain_invalid=False)¶ Get footprints within some distance N, S, E, W of a lat-lng point.
Deprecated: use geometries module instead.
- Parameters
point (tuple) – a lat-lng point
dist (numeric) – distance in meters
footprint_type (string) – type of footprint to be downloaded. OSM tag key e.g. ‘building’, ‘landuse’, ‘place’, etc.
retain_invalid (bool) – deprecated, is ignored
- Returns
- Return type
geopandas.GeoDataFrame
Notes
You can configure the Overpass server timeout, memory allocation, and other custom settings via ox.config().
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osmnx.footprints.
footprints_from_polygon
(polygon, footprint_type='building', retain_invalid=False)¶ Get footprints within some polygon.
Deprecated: use geometries module instead.
- Parameters
polygon (shapely.geometry.Polygon or shapely.geometry.MultiPolygon) – the shape to get data within. coordinates should be in units of latitude-longitude degrees.
footprint_type (string) – type of footprint to be downloaded. OSM tag key e.g. ‘building’, ‘landuse’, ‘place’, etc.
retain_invalid (bool) – deprecated, is ignored
- Returns
- Return type
geopandas.GeoDataFrame
Notes
You can configure the Overpass server timeout, memory allocation, and other custom settings via ox.config().
osmnx.geocoder module¶
Geocode queries and create GeoDataFrames of place boundaries.
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osmnx.geocoder.
geocode
(query)¶ Geocode a query string to (lat, lng) with the Nominatim geocoder.
- Parameters
query (string) – the query string to geocode
- Returns
point – the (lat, lng) coordinates returned by the geocoder
- Return type
tuple
-
osmnx.geocoder.
geocode_to_gdf
(query, which_result=None, buffer_dist=None)¶ Geocode a query or queries to a GeoDataFrame with the Nominatim geocoder.
Geometry column contains place boundaries if they exist in OpenStreetMap. Query can be a string or dict, or a list of strings/dicts to send to the geocoder. If query is a list, then which_result should be either a single value or a list of the same length as query.
- Parameters
query (string or dict or list) – query string(s) or structured dict(s) to geocode
which_result (int) – which geocoding result to use. if None, auto-select the first multi/polygon or raise an error if OSM doesn’t return one.
buffer_dist (float) – distance to buffer around the place geometry, in meters
- Returns
gdf – a GeoDataFrame with one row for each query
- Return type
geopandas.GeoDataFrame
osmnx.geometries module¶
Download geospatial entities’ geometries and attributes from OpenStreetMap.
Retrieve points of interest, building footprints, or any other objects from OSM, including their geometries and attribute data, and construct a GeoDataFrame of them.
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osmnx.geometries.
geometries_from_address
(address, tags, dist=1000)¶ Create GeoDataFrame of OSM entities within some distance N, S, E, W of address.
- Parameters
address (string) – the address to geocode and use as the central point around which to get the geometries
tags (dict) – Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
dist (numeric) – distance in meters
- Returns
gdf
- Return type
geopandas.GeoDataFrame
Notes
You can configure the Overpass server timeout, memory allocation, and other custom settings via ox.config().
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osmnx.geometries.
geometries_from_bbox
(north, south, east, west, tags)¶ Create a GeoDataFrame of OSM entities within a N, S, E, W bounding box.
- Parameters
north (float) – northern latitude of bounding box
south (float) – southern latitude of bounding box
east (float) – eastern longitude of bounding box
west (float) – western longitude of bounding box
tags (dict) – Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
- Returns
gdf
- Return type
geopandas.GeoDataFrame
Notes
You can configure the Overpass server timeout, memory allocation, and other custom settings via ox.config().
-
osmnx.geometries.
geometries_from_place
(query, tags, which_result=None, buffer_dist=None)¶ Create a GeoDataFrame of OSM entities within the boundaries of a place.
- Parameters
query (string or dict or list) – the query or queries to geocode to get place boundary polygon(s)
tags (dict) – Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
which_result (int) – which geocoding result to use. if None, auto-select the first multi/polygon or raise an error if OSM doesn’t return one.
buffer_dist (float) – distance to buffer around the place geometry, in meters
- Returns
gdf
- Return type
geopandas.GeoDataFrame
Notes
You can configure the Overpass server timeout, memory allocation, and other custom settings via ox.config().
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osmnx.geometries.
geometries_from_point
(center_point, tags, dist=1000)¶ Create GeoDataFrame of OSM entities within some distance N, S, E, W of a point.
- Parameters
center_point (tuple) – the (lat, lng) center point around which to get the geometries
tags (dict) – Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
dist (numeric) – distance in meters
- Returns
gdf
- Return type
geopandas.GeoDataFrame
Notes
You can configure the Overpass server timeout, memory allocation, and other custom settings via ox.config().
-
osmnx.geometries.
geometries_from_polygon
(polygon, tags)¶ Create GeoDataFrame of OSM entities within boundaries of a (multi)polygon.
- Parameters
polygon (shapely.geometry.Polygon or shapely.geometry.MultiPolygon) – geographic boundaries to fetch geometries within
tags (dict) – Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
- Returns
gdf
- Return type
geopandas.GeoDataFrame
Notes
You can configure the Overpass server timeout, memory allocation, and other custom settings via ox.config().
-
osmnx.geometries.
geometries_from_xml
(filepath, polygon=None, tags=None)¶ Create a GeoDataFrame of OSM entities in an OSM-formatted XML file.
Because this function creates a GeoDataFrame of geometries from an OSM-formatted XML file that has already been downloaded (i.e. no query is made to the Overpass API) the polygon and tags arguments are not required. If they are not supplied to the function, geometries_from_xml() will return geometries for all of the tagged elements in the file. If they are supplied they will be used to filter the final GeoDataFrame.
- Parameters
filepath (string) – path to file containing OSM XML data
polygon (shapely.geometry.Polygon) – optional geographic boundary to filter objects
tags (dict) – optional dict of tags for filtering objects from the XML. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
- Returns
gdf
- Return type
geopandas.GeoDataFrame
osmnx.graph module¶
Graph creation functions.
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osmnx.graph.
graph_from_address
(address, dist=1000, dist_type='bbox', network_type='all_private', simplify=True, retain_all=False, truncate_by_edge=False, return_coords=False, clean_periphery=True, custom_filter=None)¶ Create a graph from OSM within some distance of some address.
- Parameters
address (string) – the address to geocode and use as the central point around which to construct the graph
dist (int) – retain only those nodes within this many meters of the center of the graph
dist_type (string) – {‘network’, ‘bbox’} if ‘bbox’, retain only those nodes within a bounding box of the distance parameter. if ‘network’, retain only those nodes within some network distance from the center-most node.
network_type (string) – what type of street network to get if custom_filter is None. One of ‘walk’, ‘bike’, ‘drive’, ‘drive_service’, ‘all’, or ‘all_private’.
simplify (bool) – if True, simplify graph topology with the simplify_graph function
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.
truncate_by_edge (bool) – if True, retain nodes outside bounding box if at least one of node’s neighbors is within the bounding box
return_coords (bool) – optionally also return the geocoded coordinates of the address
clean_periphery (bool,) – if True, buffer 500m to get a graph larger than requested, then simplify, then truncate it to requested spatial boundaries
custom_filter (string) – a custom network filter to be used instead of the network_type presets, e.g., ‘[“power”~”line”]’ or ‘[“highway”~”motorway|trunk”]’. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional.
- Returns
- Return type
networkx.MultiDiGraph or optionally (networkx.MultiDiGraph, (lat, lng))
Notes
You can configure the Overpass server timeout, memory allocation, and other custom settings via ox.config().
-
osmnx.graph.
graph_from_bbox
(north, south, east, west, network_type='all_private', simplify=True, retain_all=False, truncate_by_edge=False, clean_periphery=True, custom_filter=None)¶ Create a graph from OSM within some bounding box.
- Parameters
north (float) – northern latitude of bounding box
south (float) – southern latitude of bounding box
east (float) – eastern longitude of bounding box
west (float) – western longitude of bounding box
network_type (string) – what type of street network to get if custom_filter is None. One of ‘walk’, ‘bike’, ‘drive’, ‘drive_service’, ‘all’, or ‘all_private’.
simplify (bool) – if True, simplify graph topology with the simplify_graph function
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.
truncate_by_edge (bool) – if True, retain nodes outside bounding box if at least one of node’s neighbors is within the bounding box
clean_periphery (bool) – if True, buffer 500m to get a graph larger than requested, then simplify, then truncate it to requested spatial boundaries
custom_filter (string) – a custom network filter to be used instead of the network_type presets, e.g., ‘[“power”~”line”]’ or ‘[“highway”~”motorway|trunk”]’. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional.
- Returns
G
- Return type
networkx.MultiDiGraph
Notes
You can configure the Overpass server timeout, memory allocation, and other custom settings via ox.config().
-
osmnx.graph.
graph_from_place
(query, network_type='all_private', simplify=True, retain_all=False, truncate_by_edge=False, which_result=None, buffer_dist=None, clean_periphery=True, custom_filter=None)¶ Create graph from OSM within the boundaries of some geocodable place(s).
The query must be geocodable and OSM must have polygon boundaries for the geocode result. If OSM does not have a polygon for this place, you can instead get its street network using the graph_from_address function, which geocodes the place name to a point and gets the network within some distance of that point. Alternatively, you might try to vary the which_result parameter to use a different geocode result. For example, the first geocode result (ie, the default) might resolve to a point geometry, but the second geocode result for this query might resolve to a polygon, in which case you can use graph_from_place with which_result=2. which_result=None will auto-select the first multi/polygon among the geocoding results.
- Parameters
query (string or dict or list) – the query or queries to geocode to get place boundary polygon(s)
network_type (string) – what type of street network to get if custom_filter is None. One of ‘walk’, ‘bike’, ‘drive’, ‘drive_service’, ‘all’, or ‘all_private’.
simplify (bool) – if True, simplify graph topology with the simplify_graph function
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.
truncate_by_edge (bool) – if True, retain nodes outside boundary polygon if at least one of node’s neighbors is within the polygon
which_result (int) – which geocoding result to use. if None, auto-select the first multi/polygon or raise an error if OSM doesn’t return one.
buffer_dist (float) – distance to buffer around the place geometry, in meters
clean_periphery (bool) – if True, buffer 500m to get a graph larger than requested, then simplify, then truncate it to requested spatial boundaries
custom_filter (string) – a custom network filter to be used instead of the network_type presets, e.g., ‘[“power”~”line”]’ or ‘[“highway”~”motorway|trunk”]’. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional.
- Returns
G
- Return type
networkx.MultiDiGraph
Notes
You can configure the Overpass server timeout, memory allocation, and other custom settings via ox.config().
-
osmnx.graph.
graph_from_point
(center_point, dist=1000, dist_type='bbox', network_type='all_private', simplify=True, retain_all=False, truncate_by_edge=False, clean_periphery=True, custom_filter=None)¶ Create a graph from OSM within some distance of some (lat, lng) point.
- Parameters
center_point (tuple) – the (lat, lng) center point around which to construct the graph
dist (int) – retain only those nodes within this many meters of the center of the graph, with distance determined according to dist_type argument
dist_type (string) – {‘network’, ‘bbox’} if ‘bbox’, retain only those nodes within a bounding box of the distance parameter. if ‘network’, retain only those nodes within some network distance from the center-most node.
network_type (string) – what type of street network to get if custom_filter is None. One of ‘walk’, ‘bike’, ‘drive’, ‘drive_service’, ‘all’, or ‘all_private’.
simplify (bool) – if True, simplify graph topology with the simplify_graph function
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.
truncate_by_edge (bool) – if True, retain nodes outside bounding box if at least one of node’s neighbors is within the bounding box
clean_periphery (bool,) – if True, buffer 500m to get a graph larger than requested, then simplify, then truncate it to requested spatial boundaries
custom_filter (string) – a custom network filter to be used instead of the network_type presets, e.g., ‘[“power”~”line”]’ or ‘[“highway”~”motorway|trunk”]’. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional.
- Returns
G
- Return type
networkx.MultiDiGraph
Notes
You can configure the Overpass server timeout, memory allocation, and other custom settings via ox.config().
-
osmnx.graph.
graph_from_polygon
(polygon, network_type='all_private', simplify=True, retain_all=False, truncate_by_edge=False, clean_periphery=True, custom_filter=None)¶ Create a graph from OSM within the boundaries of some shapely polygon.
- Parameters
polygon (shapely.geometry.Polygon or shapely.geometry.MultiPolygon) – the shape to get network data within. coordinates should be in units of latitude-longitude degrees.
network_type (string) – what type of street network to get if custom_filter is None. One of ‘walk’, ‘bike’, ‘drive’, ‘drive_service’, ‘all’, or ‘all_private’.
simplify (bool) – if True, simplify graph topology with the simplify_graph function
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.
truncate_by_edge (bool) – if True, retain nodes outside boundary polygon if at least one of node’s neighbors is within the polygon
clean_periphery (bool) – if True, buffer 500m to get a graph larger than requested, then simplify, then truncate it to requested spatial boundaries
custom_filter (string) – a custom network filter to be used instead of the network_type presets, e.g., ‘[“power”~”line”]’ or ‘[“highway”~”motorway|trunk”]’. Also pass in a network_type that is in settings.bidirectional_network_types if you want graph to be fully bi-directional.
- Returns
G
- Return type
networkx.MultiDiGraph
Notes
You can configure the Overpass server timeout, memory allocation, and other custom settings via ox.config().
-
osmnx.graph.
graph_from_xml
(filepath, bidirectional=False, simplify=True, retain_all=False)¶ Create a graph from data in an OSM-formatted XML file.
- Parameters
filepath (string) – path to file containing OSM XML data
bidirectional (bool) – if True, create bi-directional edges for one-way streets
simplify (bool) – if True, simplify graph topology with the simplify_graph function
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.
- Returns
G
- Return type
networkx.MultiDiGraph
osmnx.io module¶
Serialize graphs to/from files on disk.
-
osmnx.io.
load_graphml
(filepath, node_type=None, node_dtypes=None, edge_dtypes=None)¶ Load an OSMnx-saved GraphML file from disk.
Converts the node/edge attributes to appropriate data types, which can be customized if needed by passing in node_dtypes or edge_dtypes arguments.
- Parameters
filepath (string) – path to the GraphML file
node_type (None) – deprecated, do not use; use node_dtypes instead
node_dtypes (dict) – dict of node attribute names:types to convert values’ data types
edge_dtypes (dict) – dict of edge attribute names:types to convert values’ data types
- Returns
G
- Return type
networkx.MultiDiGraph
-
osmnx.io.
save_graph_geopackage
(G, filepath=None, encoding='utf-8')¶ Save graph nodes and edges to disk as layers in a GeoPackage file.
- Parameters
G (networkx.MultiDiGraph) – input graph
filepath (string) – path to the GeoPackage file including extension. if None, use default data folder + graph.gpkg
encoding (string) – the character encoding for the saved file
- Returns
- Return type
None
-
osmnx.io.
save_graph_shapefile
(G, filepath=None, encoding='utf-8')¶ Save graph nodes and edges to disk as ESRI shapefiles.
The shapefile format is proprietary and outdated. Whenever possible, you should use the superior GeoPackage file format instead, for instance, via the save_graph_geopackage function.
- Parameters
G (networkx.MultiDiGraph) – input graph
filepath (string) – path to the shapefiles folder (no file extension). if None, use default data folder + graph_shapefile
encoding (string) – the character encoding for the saved files
- Returns
- Return type
None
-
osmnx.io.
save_graph_xml
(data, filepath=None, node_tags=['highway'], node_attrs=['id', 'timestamp', 'uid', 'user', 'version', 'changeset', 'lat', 'lon'], edge_tags=['highway', 'lanes', 'maxspeed', 'name', 'oneway'], edge_attrs=['id', 'timestamp', 'uid', 'user', 'version', 'changeset'], oneway=False, merge_edges=True, edge_tag_aggs=None)¶ Save graph to disk as an OSM-formatted XML .osm file.
This function exists only to allow serialization to the .osm file format for applications that require it, and has constraints to conform to that. To save/load full-featured OSMnx graphs to/from disk for later use, use the save_graphml and load_graphml functions instead.
Note: for large networks this function can take a long time to run. Before using this function, make sure you configured OSMnx as described in the example below when you created the graph.
Example
>>> import osmnx as ox >>> utn = ox.settings.useful_tags_node >>> oxna = ox.settings.osm_xml_node_attrs >>> oxnt = ox.settings.osm_xml_node_tags >>> utw = ox.settings.useful_tags_way >>> oxwa = ox.settings.osm_xml_way_attrs >>> oxwt = ox.settings.osm_xml_way_tags >>> utn = list(set(utn + oxna + oxnt)) >>> utw = list(set(utw + oxwa + oxwt)) >>> ox.config(all_oneway=True, useful_tags_node=utn, useful_tags_way=utw) >>> G = ox.graph_from_place('Piedmont, CA, USA', network_type='drive') >>> ox.save_graph_xml(G, filepath='./data/graph1.osm')
- Parameters
data (networkx multi(di)graph OR a length 2 iterable of nodes/edges) – geopandas GeoDataFrames
filepath (string) – path to the .osm file including extension. if None, use default data folder + graph.osm
node_tags (list) – osm node tags to include in output OSM XML
node_attrs (list) – osm node attributes to include in output OSM XML
edge_tags (list) – osm way tags to include in output OSM XML
edge_attrs (list) – osm way attributes to include in output OSM XML
oneway (bool) – the default oneway value used to fill this tag where missing
merge_edges (bool) – if True merges graph edges such that each OSM way has one entry and one entry only in the OSM XML. Otherwise, every OSM way will have a separate entry for each node pair it contains.
edge_tag_aggs (list of length-2 string tuples) – useful only if merge_edges is True, this argument allows the user to specify edge attributes to aggregate such that the merged OSM way entry tags accurately represent the sum total of their component edge attributes. For example, if the user wants the OSM way to have a “length” attribute, the user must specify edge_tag_aggs=[(‘length’, ‘sum’)] in order to tell this method to aggregate the lengths of the individual component edges. Otherwise, the length attribute will simply reflect the length of the first edge associated with the way.
- Returns
- Return type
None
-
osmnx.io.
save_graphml
(G, filepath=None, gephi=False, encoding='utf-8')¶ Save graph to disk as GraphML file.
- Parameters
G (networkx.MultiDiGraph) – input graph
filepath (string) – path to the GraphML file including extension. if None, use default data folder + graph.graphml
gephi (bool) – if True, give each edge a unique key/id to work around Gephi’s interpretation of the GraphML specification
encoding (string) – the character encoding for the saved file
- Returns
- Return type
None
osmnx.plot module¶
Plot spatial geometries, street networks, and routes.
-
osmnx.plot.
get_colors
(n, cmap='viridis', start=0.0, stop=1.0, alpha=1.0, return_hex=False)¶ Get n evenly-spaced colors from a matplotlib colormap.
- Parameters
n (int) – number of colors
cmap (string) – name of a matplotlib colormap
start (float) – where to start in the colorspace
stop (float) – where to end in the colorspace
alpha (float) – opacity, the alpha channel for the RGBa colors
return_hex (bool) – if True, convert RGBa colors to HTML-like hexadecimal RGB strings. if False, return colors as (R, G, B, alpha) tuples.
- Returns
color_list
- Return type
list
-
osmnx.plot.
get_edge_colors_by_attr
(G, attr, num_bins=None, cmap='viridis', start=0, stop=1, na_color='none', equal_size=False)¶ Get colors based on edge attribute values.
- Parameters
G (networkx.MultiDiGraph) – input graph
attr (string) – name of a numerical edge attribute
num_bins (int) – if None, linearly map a color to each value. otherwise, assign values to this many bins then assign a color to each bin.
cmap (string) – name of a matplotlib colormap
start (float) – where to start in the colorspace
stop (float) – where to end in the colorspace
na_color (string) – what color to assign edges with missing attr values
equal_size (bool) – ignored if num_bins is None. if True, bin into equal-sized quantiles (requires unique bin edges). if False, bin into equal-spaced bins.
- Returns
edge_colors – series labels are edge IDs (u, v, k) and values are colors
- Return type
pandas.Series
-
osmnx.plot.
get_node_colors_by_attr
(G, attr, num_bins=None, cmap='viridis', start=0, stop=1, na_color='none', equal_size=False)¶ Get colors based on node attribute values.
- Parameters
G (networkx.MultiDiGraph) – input graph
attr (string) – name of a numerical node attribute
num_bins (int) – if None, linearly map a color to each value. otherwise, assign values to this many bins then assign a color to each bin.
cmap (string) – name of a matplotlib colormap
start (float) – where to start in the colorspace
stop (float) – where to end in the colorspace
na_color (string) – what color to assign nodes with missing attr values
equal_size (bool) – ignored if num_bins is None. if True, bin into equal-sized quantiles (requires unique bin edges). if False, bin into equal-spaced bins.
- Returns
node_colors – series labels are node IDs and values are colors
- Return type
pandas.Series
-
osmnx.plot.
plot_figure_ground
(G=None, address=None, point=None, dist=805, network_type='drive_service', street_widths=None, default_width=4, figsize=(8, 8), edge_color='w', smooth_joints=True, **pg_kwargs)¶ Plot a figure-ground diagram of a street network.
- Parameters
G (networkx.MultiDiGraph) – input graph, must be unprojected
address (string) – address to geocode as the center point if G is not passed in
point (tuple) – center point if address and G are not passed in
dist (numeric) – how many meters to extend north, south, east, west from center point
network_type (string) – what type of network to get
street_widths (dict) – dict keys are street types and values are widths to plot in pixels
default_width (numeric) – fallback width in pixels for any street type not in street_widths
figsize (numeric) – (width, height) of figure, should be equal
edge_color (string) – color of the edges’ lines
smooth_joints (bool) – if True, plot nodes same width as streets to smooth line joints and prevent cracks between them from showing
pg_kwargs – keyword arguments to pass to plot_graph
- Returns
fig, ax – matplotlib figure, axis
- Return type
tuple
-
osmnx.plot.
plot_footprints
(gdf, ax=None, figsize=(8, 8), color='orange', bgcolor='#111111', bbox=None, save=False, show=True, close=False, filepath=None, dpi=600)¶ Plot a GeoDataFrame of geospatial entities’ footprints.
- Parameters
gdf (geopandas.GeoDataFrame) – GeoDataFrame of footprints (shapely Polygons and MultiPolygons)
ax (axis) – if not None, plot on this preexisting axis
figsize (tuple) – if ax is None, create new figure with size (width, height)
color (string) – color of the footprints
bgcolor (string) – background color of the plot
bbox (tuple) – bounding box as (north, south, east, west). if None, will calculate from the spatial extents of the geometries in gdf
save (bool) – if True, save the figure to disk at filepath
show (bool) – if True, call pyplot.show() to show the figure
close (bool) – if True, call pyplot.close() to close the figure
filepath (string) – if save is True, the path to the file. file format determined from extension. if None, use settings.imgs_folder/image.png
dpi (int) – if save is True, the resolution of saved file
- Returns
fig, ax – matplotlib figure, axis
- Return type
tuple
-
osmnx.plot.
plot_graph
(G, ax=None, figsize=(8, 8), bgcolor='#111111', node_color='w', node_size=15, node_alpha=None, node_edgecolor='none', node_zorder=1, edge_color='#999999', edge_linewidth=1, edge_alpha=None, show=True, close=False, save=False, filepath=None, dpi=300, bbox=None)¶ Plot a graph.
- Parameters
G (networkx.MultiDiGraph) – input graph
ax (matplotlib axis) – if not None, plot on this preexisting axis
figsize (tuple) – if ax is None, create new figure with size (width, height)
bgcolor (string) – background color of plot
node_color (string or list) – color(s) of the nodes
node_size (int) – size of the nodes: if 0, then skip plotting the nodes
node_alpha (float) – opacity of the nodes, note: if you passed RGBA values to node_color, set node_alpha=None to use the alpha channel in node_color
node_edgecolor (string) – color of the nodes’ markers’ borders
node_zorder (int) – zorder to plot nodes: edges are always 1, so set node_zorder=0 to plot nodes below edges
edge_color (string or list) – color(s) of the edges’ lines
edge_linewidth (float) – width of the edges’ lines: if 0, then skip plotting the edges
edge_alpha (float) – opacity of the edges, note: if you passed RGBA values to edge_color, set edge_alpha=None to use the alpha channel in edge_color
show (bool) – if True, call pyplot.show() to show the figure
close (bool) – if True, call pyplot.close() to close the figure
save (bool) – if True, save the figure to disk at filepath
filepath (string) – if save is True, the path to the file. file format determined from extension. if None, use settings.imgs_folder/image.png
dpi (int) – if save is True, the resolution of saved file
bbox (tuple) – bounding box as (north, south, east, west). if None, will calculate from spatial extents of plotted geometries.
- Returns
fig, ax – matplotlib figure, axis
- Return type
tuple
-
osmnx.plot.
plot_graph_route
(G, route, route_color='r', route_linewidth=4, route_alpha=0.5, orig_dest_size=100, ax=None, **pg_kwargs)¶ Plot a route along a graph.
- Parameters
G (networkx.MultiDiGraph) – input graph
route (list) – route as a list of node IDs
route_color (string) – color of the route
route_linewidth (int) – width of the route line
route_alpha (float) – opacity of the route line
orig_dest_size (int) – size of the origin and destination nodes
ax (matplotlib axis) – if not None, plot route on this preexisting axis instead of creating a new fig, ax and drawing the underlying graph
pg_kwargs – keyword arguments to pass to plot_graph
- Returns
fig, ax – matplotlib figure, axis
- Return type
tuple
-
osmnx.plot.
plot_graph_routes
(G, routes, route_colors='r', **pgr_kwargs)¶ Plot several routes along a graph.
- Parameters
G (networkx.MultiDiGraph) – input graph
routes (list) – routes as a list of lists of node IDs
route_colors (string or list) – if string, 1 color for all routes. if list, the colors for each route.
pgr_kwargs – keyword arguments to pass to plot_graph_route
- Returns
fig, ax – matplotlib figure, axis
- Return type
tuple
osmnx.pois module¶
Download points of interests (POIs) from OpenStreetMap.
Deprecated: use the new geometries module instead.
-
osmnx.pois.
pois_from_address
(address, tags, dist=1000)¶ Get point of interests (POIs) within some distance N, S, E, W of address.
Deprecated: use geometries module instead.
- Parameters
address (string) – the address to geocode to a lat-lng point
tags (dict) – Dict of tags used for finding POIs from the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one tag given. The dict keys should be OSM tags, (e.g., amenity, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
dist (numeric) – distance in meters
- Returns
gdf
- Return type
geopandas.GeoDataFrame
Notes
You can configure the Overpass server timeout, memory allocation, and other custom settings via ox.config().
-
osmnx.pois.
pois_from_place
(place, tags, which_result=None)¶ Get points of interest (POIs) within the boundaries of some place.
Deprecated: use geometries module instead.
- Parameters
place (string) – the query to geocode to get place boundary polygon
tags (dict) – Dict of tags used for finding POIs from the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one tag given. The dict keys should be OSM tags, (e.g., amenity, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
which_result (int) – which geocoding result to use. if None, auto-select the first multi/polygon or raise an error if OSM doesn’t return one.
- Returns
gdf
- Return type
geopandas.GeoDataFrame
Notes
You can configure the Overpass server timeout, memory allocation, and other custom settings via ox.config().
-
osmnx.pois.
pois_from_point
(point, tags, dist=1000)¶ Get point of interests (POIs) within some distance N, S, E, W of a point.
Deprecated: use geometries module instead.
- Parameters
point (tuple) – a (lat, lng) point
tags (dict) – Dict of tags used for finding POIs from the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one tag given. The dict keys should be OSM tags, (e.g., amenity, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
dist (numeric) – distance in meters
- Returns
gdf
- Return type
geopandas.GeoDataFrame
Notes
You can configure the Overpass server timeout, memory allocation, and other custom settings via ox.config().
-
osmnx.pois.
pois_from_polygon
(polygon, tags)¶ Get point of interests (POIs) within some polygon.
Deprecated: use geometries module instead.
- Parameters
polygon (shapely.geometry.Polygon) – geographic boundaries to fetch POIs within
tags (dict) – Dict of tags used for finding POIs from the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one tag given. The dict keys should be OSM tags, (e.g., amenity, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
- Returns
gdf
- Return type
geopandas.GeoDataFrame
Notes
You can configure the Overpass server timeout, memory allocation, and other custom settings via ox.config().
osmnx.projection module¶
Project spatial geometries and street networks.
-
osmnx.projection.
project_gdf
(gdf, to_crs=None, to_latlong=False)¶ Project a GeoDataFrame from its current CRS to another.
If to_crs is None, project to the UTM CRS for the UTM zone in which the GeoDataFrame’s centroid lies. Otherwise project to the CRS defined by to_crs. The simple UTM zone calculation in this function works well for most latitudes, but may not work for some extreme northern locations like Svalbard or far northern Norway.
- Parameters
gdf (geopandas.GeoDataFrame) – the GeoDataFrame to be projected
to_crs (dict or string or pyproj.CRS) – if None, project to UTM zone in which gdf’s centroid lies, otherwise project to this CRS
to_latlong (bool) – if True, project to settings.default_crs and ignore to_crs
- Returns
gdf_proj – the projected GeoDataFrame
- Return type
geopandas.GeoDataFrame
-
osmnx.projection.
project_geometry
(geometry, crs=None, to_crs=None, to_latlong=False)¶ Project a shapely geometry from its current CRS to another.
If to_crs is None, project to the UTM CRS for the UTM zone in which the geometry’s centroid lies. Otherwise project to the CRS defined by to_crs.
- Parameters
geometry (shapely.geometry.Polygon or shapely.geometry.MultiPolygon) – the geometry to project
crs (dict or string or pyproj.CRS) – the starting CRS of the passed-in geometry. if None, it will be set to settings.default_crs
to_crs (dict or string or pyproj.CRS) – if None, project to UTM zone in which geometry’s centroid lies, otherwise project to this CRS
to_latlong (bool) – if True, project to settings.default_crs and ignore to_crs
- Returns
geometry_proj, crs – the projected geometry and its new CRS
- Return type
tuple
-
osmnx.projection.
project_graph
(G, to_crs=None)¶ Project graph from its current CRS to another.
If to_crs is None, project the graph to the UTM CRS for the UTM zone in which the graph’s centroid lies. Otherwise, project the graph to the CRS defined by to_crs.
- Parameters
G (networkx.MultiDiGraph) – the graph to be projected
to_crs (dict or string or pyproj.CRS) – if None, project graph to UTM zone in which graph centroid lies, otherwise project graph to this CRS
- Returns
G_proj – the projected graph
- Return type
networkx.MultiDiGraph
osmnx.settings module¶
Global settings, can be configured by user with utils.config().
osmnx.simplification module¶
Simplify, correct, and consolidate network topology.
-
osmnx.simplification.
consolidate_intersections
(G, tolerance=10, rebuild_graph=True, dead_ends=False, reconnect_edges=True)¶ Consolidate intersections comprising clusters of nearby nodes.
Merges nearby nodes and returns either their centroids or a rebuilt graph with consolidated intersections and reconnected edge geometries. The tolerance argument should be adjusted to approximately match street design standards in the specific street network, and you should always use a projected graph to work in meaningful and consistent units like meters.
When rebuild_graph=False, it uses a purely geometrical (and relatively fast) algorithm to identify “geometrically close” nodes, merge them, and return just the merged intersections’ centroids. When rebuild_graph=True, it uses a topological (and slower but more accurate) algorithm to identify “topologically close” nodes, merge them, then rebuild/return the graph. Returned graph’s node IDs represent clusters rather than osmids. Refer to nodes’ osmid attributes for original osmids. If multiple nodes were merged together, the osmid attribute is a list of merged nodes’ osmids.
Divided roads are often represented by separate centerline edges. The intersection of two divided roads thus creates 4 nodes, representing where each edge intersects a perpendicular edge. These 4 nodes represent a single intersection in the real world. A similar situation occurs with roundabouts and traffic circles. This function consolidates nearby nodes by buffering them to an arbitrary distance, merging overlapping buffers, and taking their centroid.
- Parameters
G (networkx.MultiDiGraph) – a projected graph
tolerance (float) – nodes are buffered to this distance (in graph’s geometry’s units) and subsequent overlaps are dissolved into a single node
rebuild_graph (bool) – if True, consolidate the nodes topologically, rebuild the graph, and return as networkx.MultiDiGraph. if False, consolidate the nodes geometrically and return the consolidated node points as geopandas.GeoSeries
dead_ends (bool) – if False, discard dead-end nodes to return only street-intersection points
reconnect_edges (bool) – ignored if rebuild_graph is not True. if True, reconnect edges and their geometries in rebuilt graph to the consolidated nodes and update edge length attributes; if False, returned graph has no edges (which is faster if you just need topologically consolidated intersection counts).
- Returns
if rebuild_graph=True, returns MultiDiGraph with consolidated intersections and reconnected edge geometries. if rebuild_graph=False, returns GeoSeries of shapely Points representing the centroids of street intersections
- Return type
networkx.MultiDiGraph or geopandas.GeoSeries
-
osmnx.simplification.
simplify_graph
(G, strict=True, remove_rings=True)¶ Simplify a graph’s topology by removing interstitial nodes.
Simplify graph topology by removing all nodes that are not intersections or dead-ends. Create an edge directly between the end points that encapsulate them, but retain the geometry of the original edges, saved as a new geometry attribute on the new edge. Note that only simplified edges receive a geometry attribute. Some of the resulting consolidated edges may comprise multiple OSM ways, and if so, their multiple attribute values are stored as a list.
- Parameters
G (networkx.MultiDiGraph) – input graph
strict (bool) – if False, allow nodes to be end points even if they fail all other rules but have incident edges with different OSM IDs. Lets you keep nodes at elbow two-way intersections, but sometimes individual blocks have multiple OSM IDs within them too.
remove_rings (bool) – if True, remove isolated self-contained rings that have no endpoints
- Returns
G – topologically simplified graph, with a new geometry attribute on each simplified edge
- Return type
networkx.MultiDiGraph
osmnx.speed module¶
Calculate graph edge speeds and travel times.
-
osmnx.speed.
add_edge_speeds
(G, hwy_speeds=None, fallback=None, precision=1)¶ Add edge speeds (km per hour) to graph as new speed_kph edge attributes.
Imputes free-flow travel speeds for all edges based on mean maxspeed value of edges, per highway type. For highway types in graph that have no maxspeed value on any edge, function assigns the mean of all maxspeed values in graph.
This mean-imputation can obviously be imprecise, and the caller can override it by passing in hwy_speeds and/or fallback arguments that correspond to local speed limit standards.
If edge maxspeed attribute has “mph” in it, value will automatically be converted from miles per hour to km per hour. Any other speed units should be manually converted to km per hour prior to running this function, otherwise there could be unexpected results. If “mph” does not appear in the edge’s maxspeed attribute string, then function assumes kph, per OSM guidelines: https://wiki.openstreetmap.org/wiki/Map_Features/Units
- Parameters
G (networkx.MultiDiGraph) – input graph
hwy_speeds (dict) – dict keys = OSM highway types and values = typical speeds (km per hour) to assign to edges of that highway type for any edges missing speed data. Any edges with highway type not in hwy_speeds will be assigned the mean preexisting speed value of all edges of that highway type.
fallback (numeric) – default speed value (km per hour) to assign to edges whose highway type did not appear in hwy_speeds and had no preexisting speed values on any edge
precision (int) – decimal precision to round speed_kph
- Returns
G – graph with speed_kph attributes on all edges
- Return type
networkx.MultiDiGraph
-
osmnx.speed.
add_edge_travel_times
(G, precision=1)¶ Add edge travel time (seconds) to graph as new travel_time edge attributes.
Calculates free-flow travel time along each edge, based on length and speed_kph attributes. Note: run add_edge_speeds first to generate the speed_kph attribute. All edges must have length and speed_kph attributes and all their values must be non-null.
- Parameters
G (networkx.MultiDiGraph) – input graph
precision (int) – decimal precision to round travel_time
- Returns
G – graph with travel_time attributes on all edges
- Return type
networkx.MultiDiGraph
osmnx.stats module¶
Calculate graph-theoretic network measures.
-
osmnx.stats.
basic_stats
(G, area=None, clean_intersects=False, tolerance=15, circuity_dist='gc')¶ Calculate basic descriptive metric and topological stats for a graph.
For an unprojected lat-lng graph, tolerance and graph units should be in degrees, and circuity_dist should be ‘gc’. For a projected graph, tolerance and graph units should be in meters (or similar) and circuity_dist should be ‘euclidean’.
- Parameters
G (networkx.MultiDiGraph) – input graph
area (numeric) – the land area of this study site, in square meters. must be greater than 0. if None, will skip all density-based metrics.
clean_intersects (bool) – if True, calculate consolidated intersections count (and density, if area is provided) via consolidate_intersections function
tolerance (numeric) – tolerance value passed along if clean_intersects=True, see consolidate_intersections function documentation for details and usage
circuity_dist (string) – ‘gc’ or ‘euclidean’, how to calculate straight-line distances for circuity measurement; use former for lat-lng networks and latter for projected networks
- Returns
stats – dictionary of network measures containing the following elements (some keys may not be present, based on the arguments passed into the function):
n = number of nodes in the graph
m = number of edges in the graph
k_avg = average node degree of the graph
- intersection_count = number of intersections in graph, that is,
nodes with >1 street emanating from them
- streets_per_node_avg = how many streets (edges in the undirected
representation of the graph) emanate from each node (ie, intersection or dead-end) on average (mean)
- streets_per_node_counts = dict, with keys of number of streets
emanating from the node, and values of number of nodes with this count
- streets_per_node_proportion = dict, same as previous, but as a
proportion of the total, rather than counts
edge_length_total = sum of all edge lengths in the graph, in meters
edge_length_avg = mean edge length in the graph, in meters
- street_length_total = sum of all edges in the undirected
representation of the graph
- street_length_avg = mean edge length in the undirected
representation of the graph, in meters
- street_segments_count = number of edges in the undirected
representation of the graph
node_density_km = n divided by area in square kilometers
- intersection_density_km = intersection_count divided by area in
square kilometers
- edge_density_km = edge_length_total divided by area in square
kilometers
- street_density_km = street_length_total divided by area in square
kilometers
- circuity_avg = edge_length_total divided by the sum of the great
circle distances between the nodes of each edge
- self_loop_proportion = proportion of edges that have a single node
as its two endpoints (ie, the edge links nodes u and v, and u==v)
- clean_intersection_count = number of intersections in street
network, merging complex ones into single points
- clean_intersection_density_km = clean_intersection_count divided by
area in square kilometers
- Return type
dict
-
osmnx.stats.
extended_stats
(G, connectivity=False, anc=False, ecc=False, bc=False, cc=False)¶ Calculate extended topological stats and metrics for a graph.
Many of these algorithms have an inherently high time complexity. Global topological analysis of large complex networks is extremely time consuming and may exhaust computer memory. Consider using function arguments to not run metrics that require computation of a full matrix of paths if they will not be needed.
- Parameters
G (networkx.MultiDiGraph) – input graph
connectivity (bool) – if True, calculate node and edge connectivity
anc (bool) – if True, calculate average node connectivity
ecc (bool) – if True, calculate shortest paths, eccentricity, and topological metrics that use eccentricity
bc (bool) – if True, calculate node betweenness centrality
cc (bool) – if True, calculate node closeness centrality
- Returns
stats – dictionary of network measures containing the following elements (some only calculated/returned optionally, based on passed parameters):
avg_neighbor_degree
avg_neighbor_degree_avg
avg_weighted_neighbor_degree
avg_weighted_neighbor_degree_avg
degree_centrality
degree_centrality_avg
clustering_coefficient
clustering_coefficient_avg
clustering_coefficient_weighted
clustering_coefficient_weighted_avg
pagerank
pagerank_max_node
pagerank_max
pagerank_min_node
pagerank_min
node_connectivity
node_connectivity_avg
edge_connectivity
eccentricity
diameter
radius
center
periphery
closeness_centrality
closeness_centrality_avg
betweenness_centrality
betweenness_centrality_avg
- Return type
dict
osmnx.truncate module¶
Truncate graph by distance, bounding box, or polygon.
-
osmnx.truncate.
truncate_graph_bbox
(G, north, south, east, west, truncate_by_edge=False, retain_all=False, quadrat_width=0.05, min_num=3)¶ Remove every node in graph that falls outside a bounding box.
- Parameters
G (networkx.MultiDiGraph) – input graph
north (float) – northern latitude of bounding box
south (float) – southern latitude of bounding box
east (float) – eastern longitude of bounding box
west (float) – western longitude of bounding box
truncate_by_edge (bool) – if True, retain nodes outside bounding box if at least one of node’s neighbors is within the bounding box
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.
quadrat_width (numeric) – passed on to intersect_index_quadrats: the linear length (in degrees) of the quadrats with which to cut up the geometry (default = 0.05, approx 4km at NYC’s latitude)
min_num (int) – passed on to intersect_index_quadrats: the minimum number of linear quadrat lines (e.g., min_num=3 would produce a quadrat grid of 4 squares)
- Returns
G – the truncated graph
- Return type
networkx.MultiDiGraph
-
osmnx.truncate.
truncate_graph_dist
(G, source_node, max_dist=1000, weight='length', retain_all=False)¶ Remove every node farther than some network distance from source_node.
This function can be slow for large graphs, as it must calculate shortest path distances between source_node and every other graph node.
- Parameters
G (networkx.MultiDiGraph) – input graph
source_node (int) – the node in the graph from which to measure network distances to other nodes
max_dist (int) – remove every node in the graph greater than this distance from the source_node (along the network)
weight (string) – how to weight the graph when measuring distance (default ‘length’ is how many meters long the edge is)
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.
- Returns
G – the truncated graph
- Return type
networkx.MultiDiGraph
-
osmnx.truncate.
truncate_graph_polygon
(G, polygon, retain_all=False, truncate_by_edge=False, quadrat_width=0.05, min_num=3)¶ Remove every node in graph that falls outside a (Multi)Polygon.
- Parameters
G (networkx.MultiDiGraph) – input graph
polygon (shapely.geometry.Polygon or shapely.geometry.MultiPolygon) – only retain nodes in graph that lie within this geometry
retain_all (bool) – if True, return the entire graph even if it is not connected. otherwise, retain only the largest weakly connected component.
truncate_by_edge (bool) – if True, retain nodes outside boundary polygon if at least one of node’s neighbors is within the polygon
quadrat_width (numeric) – passed on to intersect_index_quadrats: the linear length (in degrees) of the quadrats with which to cut up the geometry (default = 0.05, approx 4km at NYC’s latitude)
min_num (int) – passed on to intersect_index_quadrats: the minimum number of linear quadrat lines (e.g., min_num=3 would produce a quadrat grid of 4 squares)
- Returns
G – the truncated graph
- Return type
networkx.MultiDiGraph
osmnx.utils module¶
General utility functions.
-
osmnx.utils.
citation
()¶ Print the OSMnx package’s citation information.
Boeing, G. 2017. OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks. Computers, Environment and Urban Systems, 65(126-139). https://doi.org/10.1016/j.compenvurbsys.2017.05.004
- Returns
- Return type
None
-
osmnx.utils.
config
(use_cache=False, cache_folder='cache', data_folder='data', imgs_folder='images', logs_folder='logs', log_file=False, log_console=False, log_level=20, log_name='osmnx', log_filename='osmnx', useful_tags_node=['ref', 'highway'], useful_tags_way=['bridge', 'tunnel', 'oneway', 'lanes', 'ref', 'name', 'highway', 'maxspeed', 'service', 'access', 'area', 'landuse', 'width', 'est_width', 'junction'], bidirectional_network_types=['walk'], osm_xml_node_attrs=['id', 'timestamp', 'uid', 'user', 'version', 'changeset', 'lat', 'lon'], osm_xml_node_tags=['highway'], osm_xml_way_attrs=['id', 'timestamp', 'uid', 'user', 'version', 'changeset'], osm_xml_way_tags=['highway', 'lanes', 'maxspeed', 'name', 'oneway'], all_oneway=False, overpass_settings='[out:json][timeout:{timeout}]{maxsize}', timeout=180, memory=None, max_query_area_size=2500000000, default_access='["access"!~"private"]', default_crs='epsg:4326', default_user_agent='OSMnx Python package (https://github.com/gboeing/osmnx)', default_referer='OSMnx Python package (https://github.com/gboeing/osmnx)', default_accept_language='en', nominatim_endpoint='https://nominatim.openstreetmap.org/', nominatim_key=None, overpass_endpoint='http://overpass-api.de/api', elevation_provider='google')¶ Configure OSMnx by setting the default global settings’ values.
Any parameters not passed by the caller are set to their original default values.
- Parameters
use_cache (bool) – if True, cache HTTP responses locally instead of calling API repeatedly for the same request
cache_folder (string) – path to folder in which to save/load HTTP response cache
data_folder (string) – path to folder in which to save/load graph files by default
imgs_folder (string) – path to folder in which to save plot images by default
logs_folder (string) – path to folder in which to save log files
log_file (bool) – if True, save log output to a file in logs_folder
log_console (bool) – if True, print log output to the console (terminal window)
log_level (int) – one of Python’s logger.level constants
log_name (string) – name of the logger
log_filename (string) – name of the log file, without file extension
useful_tags_node (list) – OSM “node” tags to add as graph node attributes, when present
useful_tags_way (list) – OSM “way” tags to add as graph edge attributes, when present
bidirectional_network_types (list) – network types for which a fully bidirectional graph will be created
osm_xml_node_attrs (list) – node attributes for saving .osm XML files with save_graph_xml function
osm_xml_node_tags (list) – node tags for saving .osm XML files with save_graph_xml function
osm_xml_way_attrs (list) – edge attributes for saving .osm XML files with save_graph_xml function
osm_xml_way_tags (list) – edge tags for for saving .osm XML files with save_graph_xml function
all_oneway (bool) – if True, forces all ways to be loaded as oneway ways, preserving the original order of nodes stored in the OSM way XML. Only use if specifically saving to .osm XML file with save_graph_xml function.
overpass_settings (string) – Settings string for overpass queries. For example, to query historical OSM data as of a certain date: ‘[out:json][timeout:90][date:”2019-10-28T19:20:00Z”]’. Use with caution.
timeout (int) – the timeout interval for the HTTP request and for API to use while running the query
memory (int) – Overpass server memory allocation size for the query, in bytes. If None, server will use its default allocation size. Use with caution.
max_query_area_size (int) – maximum area for any part of the geometry in meters: any polygon bigger than this will get divided up for multiple queries to API (default 50km x 50km)
default_access (string) – default filter for OSM “access” key
default_crs (string) – default coordinate reference system to set when creating graphs
default_user_agent (string) – HTTP header user-agent
default_referer (string) – HTTP header referer
default_accept_language (string) – HTTP header accept-language
nominatim_endpoint (string) – the API endpoint to use for nominatim queries
nominatim_key (string) – your API key, if you are using an endpoint that requires one
overpass_endpoint (string) – the API endpoint to use for overpass queries
elevation_provider (string) – the API provider to use for adding node elevations, can be either “google” or “airmap”
- Returns
- Return type
None
-
osmnx.utils.
log
(message, level=None, name=None, filename=None)¶ Write a message to the logger.
This logs to file and/or prints to the console (terminal), depending on the current configuration of settings.log_file and settings.log_console.
- Parameters
message (string) – the message to log
level (int) – one of Python’s logger.level constants
name (string) – name of the logger
filename (string) – name of the log file, without file extension
- Returns
- Return type
None
-
osmnx.utils.
ts
(style='datetime', template=None)¶ Get current timestamp as string.
- Parameters
style (string) – format the timestamp with this built-in template. must be one of {‘datetime’, ‘date’, ‘time’}
template (string) – if not None, format the timestamp with this template instead of one of the built-in styles
- Returns
ts – the string timestamp
- Return type
string
osmnx.utils_geo module¶
Geospatial utility functions.
-
osmnx.utils_geo.
bbox_from_point
(point, dist=1000, project_utm=False, return_crs=False)¶ Create a bounding box from a (lat, lng) center point.
Create a bounding box some distance in each direction (north, south, east, and west) from the center point and optionally project it.
- Parameters
point (tuple) – the (lat, lng) center point to create the bounding box around
dist (int) – bounding box distance in meters from the center point
project_utm (bool) – if True, return bounding box as UTM-projected coordinates
return_crs (bool) – if True, and project_utm=True, return the projected CRS too
- Returns
(north, south, east, west) or (north, south, east, west, crs_proj)
- Return type
tuple
-
osmnx.utils_geo.
bbox_to_poly
(north, south, east, west)¶ Convert bounding box coordinates to shapely Polygon.
- Parameters
north (float) – northern coordinate
south (float) – southern coordinate
east (float) – eastern coordinate
west (float) – western coordinate
- Returns
- Return type
shapely.geometry.Polygon
-
osmnx.utils_geo.
redistribute_vertices
(geom, dist)¶ Redistribute the vertices on a projected LineString or MultiLineString.
The distance argument is only approximate since the total distance of the linestring may not be a multiple of the preferred distance. This function works on only (Multi)LineString geometry types.
- Parameters
geom (shapely.geometry.LineString or shapely.geometry.MultiLineString) – a Shapely geometry (should be projected)
dist (float) – spacing length along edges. Units are same as the geom: degrees for unprojected geometries and meters for projected geometries. The smaller the dist value, the more points are created.
- Returns
the redistributed vertices as a list if geom is a LineString or MultiLineString if geom is a MultiLineString
- Return type
list or shapely.geometry.MultiLineString
-
osmnx.utils_geo.
round_geometry_coords
(shape, precision)¶ Round the coordinates of a shapely geometry to some decimal precision.
- Parameters
shape (shapely.geometry.geometry) – the geometry to round the coordinates of; must be one of {Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon}
precision (int) – decimal precision to round coordinates to
- Returns
- Return type
shapely.geometry.geometry
osmnx.utils_graph module¶
Graph utility functions.
-
osmnx.utils_graph.
add_edge_lengths
(G, precision=3)¶ Add length (meters) attribute to each edge.
Calculated via great-circle distance between each edge’s incident nodes, so ensure graph is in unprojected coordinates.
- Parameters
G (networkx.MultiDiGraph) – input graph
precision (int) – decimal precision to round lengths
- Returns
G – graph with edge length attributes
- Return type
networkx.MultiDiGraph
-
osmnx.utils_graph.
count_streets_per_node
(G, nodes=None)¶ Count how many street segments emanate from each node in this graph.
If nodes is passed, then only count the nodes in the graph with those IDs.
- Parameters
G (networkx.MultiDiGraph) – input graph
nodes (iterable) – the set of node IDs to get counts for
- Returns
streets_per_node – counts of how many streets emanate from each node with keys=node id and values=count
- Return type
dict
-
osmnx.utils_graph.
get_digraph
(G, weight='length')¶ Convert MultiDiGraph to DiGraph.
Chooses between parallel edges by minimizing weight attribute value. Note: see also get_undirected to convert MultiDiGraph to MultiGraph.
- Parameters
G (networkx.MultiDiGraph) – input graph
weight (string) – attribute value to minimize when choosing between parallel edges
- Returns
- Return type
networkx.DiGraph
-
osmnx.utils_graph.
get_largest_component
(G, strongly=False)¶ Get subgraph of MultiDiGraph’s largest weakly/strongly connected component.
- Parameters
G (networkx.MultiDiGraph) – input graph
strongly (bool) – if True, return the largest strongly instead of weakly connected component
- Returns
G – the largest connected component subgraph of the original graph
- Return type
networkx.MultiDiGraph
-
osmnx.utils_graph.
get_route_edge_attributes
(G, route, attribute=None, minimize_key='length', retrieve_default=None)¶ Get a list of attribute values for each edge in a path.
- Parameters
G (networkx.MultiDiGraph) – input graph
route (list) – list of nodes IDs constituting the path
attribute (string) – the name of the attribute to get the value of for each edge. If None, the complete data dict is returned for each edge.
minimize_key (string) – if there are parallel edges between two nodes, select the one with the lowest value of minimize_key
retrieve_default (Callable[Tuple[Any, Any], Any]) – function called with the edge nodes as parameters to retrieve a default value, if the edge does not contain the given attribute (otherwise a KeyError is raised)
- Returns
attribute_values – list of edge attribute values
- Return type
list
-
osmnx.utils_graph.
get_undirected
(G)¶ Convert MultiDiGraph to MultiGraph.
Maintains parallel edges only if their geometries differ. Note: see also get_digraph to convert MultiDiGraph to DiGraph.
- Parameters
G (networkx.MultiDiGraph) – input graph
- Returns
- Return type
networkx.MultiGraph
-
osmnx.utils_graph.
graph_from_gdfs
(gdf_nodes, gdf_edges, graph_attrs=None)¶ Convert node and edge GeoDataFrames to a MultiDiGraph.
This function is the inverse of graph_to_gdfs.
- Parameters
gdf_nodes (geopandas.GeoDataFrame) – GeoDataFrame of graph nodes
gdf_edges (geopandas.GeoDataFrame) – GeoDataFrame of graph edges, must have crs attribute set
graph_attrs (dict) – the new G.graph attribute dict; if None, add crs as the only graph-level attribute
- Returns
G
- Return type
networkx.MultiDiGraph
-
osmnx.utils_graph.
graph_to_gdfs
(G, nodes=True, edges=True, node_geometry=True, fill_edge_geometry=True)¶ Convert a graph to node and/or edge GeoDataFrames.
This function is the inverse of graph_from_gdfs.
- Parameters
G (networkx.MultiDiGraph) – input graph
nodes (bool) – if True, convert graph nodes to a GeoDataFrame and return it
edges (bool) – if True, convert graph edges to a GeoDataFrame and return it
node_geometry (bool) – if True, create a geometry column from node x and y data
fill_edge_geometry (bool) – if True, fill in missing edge geometry fields using nodes u and v
- Returns
gdf_nodes or gdf_edges or tuple of (gdf_nodes, gdf_edges)
- Return type
geopandas.GeoDataFrame or tuple
-
osmnx.utils_graph.
induce_subgraph
(G, node_subset)¶ Induce a subgraph of G: deprecated, do not use.
- Parameters
G (networkx.MultiDiGraph) – input graph
node_subset (list-like) – the subset of nodes to induce a subgraph of G
- Returns
the subgraph of G induced by node_subset
- Return type
networkx.MultiDiGraph
-
osmnx.utils_graph.
remove_isolated_nodes
(G)¶ Remove from a graph all nodes that have no incident edges.
- Parameters
G (networkx.MultiDiGraph) – graph from which to remove isolated nodes
- Returns
G – graph with all isolated nodes removed
- Return type
networkx.MultiDiGraph