G_proj = G.copy()
start_time = time.time()
// create a GeoDataFrame of the nodes, name it, convert osmid to str
nodes, data = zip(*G_proj.nodes(data=True))
gdf_nodes = gpd.GeoDataFrame(list(data), index=nodes)
gdf_nodes.crs = G_proj.graph["crs"]
gdf_nodes.gdf_name = "{}_nodes".format(G_proj.name)
// create new lat/lon columns just to save that data for later reference
// if they do not already exist (i.e., don"t overwrite in subsequent re-projections)
if "lon" not in gdf_nodes.columns or "lat" not in gdf_nodes.columns:
gdf_nodes["lon"] = gdf_nodes["x"]
gdf_nodes["lat"] = gdf_nodes["y"]
// create a geometry column from x/y columns
gdf_nodes["geometry"] = gdf_nodes.apply(lambda row: Point(row["x"], row["y"]), axis=1)
gdf_nodes.set_geometry("geometry", inplace=True)
utils.log("Created a GeoDataFrame from graph in {:,.2f} seconds".format(time.time()-start_time))
// project the nodes GeoDataFrame to UTM
gdf_nodes_utm = project_gdf(gdf_nodes, to_crs=to_crs)
// extract data for all edges that have geometry attribute
edges_with_geom = []
for u, v, key, data in G_proj.edges(keys=True, data=True):
if "geometry" in data:
edges_with_geom.append({"u":u, "v":v, "key":key, "geometry":data["geometry"]})
// create an edges GeoDataFrame and project to UTM, if there were any edges
// with a geometry attribute. geom attr only exists if graph has been
// simplified, otherwise you don"t have to project anything for the edges
// because the nodes still contain all spatial data
if len(edges_with_geom) > 0:
gdf_edges = gpd.GeoDataFrame(edges_with_geom)
gdf_edges.crs = G_proj.graph["crs"]
gdf_edges.gdf_name = "{}_edges".format(G_proj.name)
gdf_edges_utm = project_gdf(gdf_edges, to_crs=to_crs)
// extract projected x and y values from the nodes" geometry column
start_time = time.time()
gdf_nodes_utm["x"] = gdf_nodes_utm["geometry"].map(lambda point: point.x)
gdf_nodes_utm["y"] = gdf_nodes_utm["geometry"].map(lambda point: point.y)
gdf_nodes_utm = gdf_nodes_utm.drop("geometry", axis=1)
utils.log("Extracted projected node geometries from GeoDataFrame in {:,.2f} seconds".format(time.time()-start_time))
// clear the graph to make it a blank slate for the projected data
start_time = time.time()
edges = list(G_proj.edges(keys=True, data=True))
After Change
// create a geometry column from x/y columns
gdf_nodes["geometry"] = gdf_nodes.apply(lambda row: Point(row["x"], row["y"]), axis=1)
gdf_nodes.set_geometry("geometry", inplace=True)
utils.log("Created a GeoDataFrame from graph")
// project the nodes GeoDataFrame to UTM
gdf_nodes_utm = project_gdf(gdf_nodes, to_crs=to_crs)
// extract data for all edges that have geometry attribute
edges_with_geom = []
for u, v, key, data in G_proj.edges(keys=True, data=True):
if "geometry" in data:
edges_with_geom.append({"u":u, "v":v, "key":key, "geometry":data["geometry"]})
// create an edges GeoDataFrame and project to UTM, if there were any edges
// with a geometry attribute. geom attr only exists if graph has been
// simplified, otherwise you don"t have to project anything for the edges
// because the nodes still contain all spatial data
if len(edges_with_geom) > 0:
gdf_edges = gpd.GeoDataFrame(edges_with_geom)
gdf_edges.crs = G_proj.graph["crs"]
gdf_edges.gdf_name = "{}_edges".format(G_proj.name)
gdf_edges_utm = project_gdf(gdf_edges, to_crs=to_crs)
// extract projected x and y values from the nodes" geometry column
gdf_nodes_utm["x"] = gdf_nodes_utm["geometry"].map(lambda point: point.x)
gdf_nodes_utm["y"] = gdf_nodes_utm["geometry"].map(lambda point: point.y)
gdf_nodes_utm = gdf_nodes_utm.drop("geometry", axis=1)
utils.log("Extracted projected node geometries from GeoDataFrame")
// clear the graph to make it a blank slate for the projected data
edges = list(G_proj.edges(keys=True, data=True))
graph_name = G_proj.graph["name"]
G_proj.clear()
// add the projected nodes and all their attributes to the graph
G_proj.add_nodes_from(gdf_nodes_utm.index)
attributes = gdf_nodes_utm.to_dict()
for label in gdf_nodes_utm.columns:
nx.set_node_attributes(G_proj, name=label, values=attributes[label])
// add the edges and all their attributes (including reconstructed geometry,
// when it exists) to the graph
for u, v, key, attributes in edges:
if "geometry" in attributes:
row = gdf_edges_utm[(gdf_edges_utm["u"]==u) & (gdf_edges_utm["v"]==v) & (gdf_edges_utm["key"]==key)]
attributes["geometry"] = row["geometry"].iloc[0]
// attributes dict contains key, so we don"t need to explicitly pass it here
G_proj.add_edge(u, v, **attributes)
// set the graph"s CRS attribute to the new, projected CRS and return the
// projected graph
G_proj.graph["crs"] = gdf_nodes_utm.crs
G_proj.graph["name"] = "{}_UTM".format(graph_name)
if "streets_per_node" in G.graph:
G_proj.graph["streets_per_node"] = G.graph["streets_per_node"]
utils.log("Rebuilt projected graph")
return G_proj
