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import geopandas
import networkx
import numpy
def get_frames(ways: geopandas.GeoDataFrame):
"""Extract nodes, edges, and relations from a GeoDataFrame of ways.
Args:
ways (geopandas.GeoDataFrame): A GeoDataFrame containing information about ways.
Returns:
nodes (geopandas.GeoDataFrame): A GeoDataFrame containing node geometries.
edges (geopandas.GeoDataFrame): A GeoDataFrame containing ways information.
rel (geopandas.GeoDataFrame): A GeoDataFrame representing relations between nodes and edges.
"""
edges = ways.explode(index_parts=False)[["id", "name", "geometry"]]
edges.index.name = "way_id"
edges = edges.reset_index()
nodes = geopandas.GeoDataFrame({"geometry": edges.boundary.explode(index_parts=False).geometry.unique()})
nodes.index.name = "node_id"
nodes.reset_index(inplace=True)
rel = edges.sjoin(nodes).to_crs("epsg:2154")
return nodes, edges, rel
def get(ways: geopandas.GeoDataFrame) -> networkx.Graph:
""" Convert a GeoDataFrame of ways into a networkx Graph.
Args:
ways (geopandas.GeoDataFrame): A GeoDataFrame containing information about ways.
Returns:
networkx.Graph: A networkx Graph representing the geographical network.
"""
nodes, edges, rel = get_frames(ways)
graph = networkx.Graph()
for node in rel['node_id'].unique():
graph.add_node(node, shape=nodes.loc[node, "geometry"])
for idx in rel['way_id'].unique():
node_id1, node_id2 = rel.loc[idx]['node_id']
way = edges.loc[idx]
graph.add_edge(
node_id1, node_id2,
weight=way.geometry.length,
shape=way.geometry,
id_=idx,
)
return graph
def weighted_adjacency_matrix(graph: networkx.Graph) -> numpy.ndarray:
"""Generate the weighted adjacency matrix from a networkx Graph.
Args:
graph (networkx.Graph): A networkx Graph representing the network.
Returns:
numpy.ndarray: A NumPy array representing the weighted adjacency matrix.
"""
weights = numpy.full((graph.number_of_nodes(),)*2, numpy.inf)
numpy.fill_diagonal(weights, 0., wrap=False)
for i in graph:
for j in graph[i]:
weights[i, j] = graph[i][j]["weight"]
return weights |