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
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 edgeweightto 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)