momepy.closeness_centrality#
- momepy.closeness_centrality(graph, name='closeness', weight='mm_len', radius=None, distance=None, verbose=True, **kwargs)[source]#
Calculates the closeness centrality for nodes. Wrapper around
networkx.closeness_centrality
. Closeness centrality of a node u is the reciprocal of the average shortest path distance to u over all n-1 nodes within reachable nodes.\[C(u) = \frac{n - 1}{\sum_{v=1}^{n-1} d(v, u)},\]where \(d(v, u)\) is the shortest-path distance between \(v\) and \(u\), and \(n\) is the number of nodes that can reach \(u\).
- Parameters:
- graphnetworkx.Graph
A Graph representing a street network. Ideally generated from GeoDataFrame using
momepy.gdf_to_nx()
.- namestr, optional
The calculated attribute name.
- weightstr (default ‘mm_len’)
The attribute holding the weight of edge (e.g. length, angle).
- radius: int
Include all neighbors of distance <= radius from
n
.- distancestr, optional
Use specified edge data key as distance. For example, setting
distance=’weight’
will use the edgeweight
to measure the distance from the noden
duringego_graph
generation.- verbosebool (default True)
If
True
, shows progress bars in loops and indication of steps.- **kwargsdict
Keyword arguments for
networkx.closeness_centrality
.
- Returns:
- netxGraph
A networkx.Graph object.
Examples
>>> network_graph = mm.closeness_centrality(network_graph)