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 edge weight 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.

**kwargsdict

Keyword arguments for networkx.closeness_centrality.

Returns
netxGraph

A networkx.Graph object.

Examples

>>> network_graph = mm.closeness_centrality(network_graph)