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 n1 nodes within reachable nodes.
\[C(u) = \frac{n  1}{\sum_{v=1}^{n1} d(v, u)},\]where \(d(v, u)\) is the shortestpath distance between \(v\) and \(u\), and \(n\) is the number of nodes that can reach \(u\).
 Parameters
 graphnetworkx.Graph
Graph representing street network. Ideally generated from GeoDataFrame using
momepy.gdf_to_nx()
 namestr, optional
calculated attribute name
 weightstr (default ‘mm_len’)
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 node n during ego_graph generation. verbosebool (default True)
if True, shows progress bars in loops and indication of steps
 **kwargs
kwargs for
networkx.closeness_centrality
 Returns
 Graph
networkx.Graph
Examples
>>> network_graph = mm.closeness_centrality(network_graph)