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edge_load_centrality(G, cutoff=False)

WARNING: This concept of edge load has not been analysed or discussed outside of NetworkX that we know of. It is based loosely on load_centrality in the sense that it counts the number of shortest paths which cross each edge. This function is for demonstration and testing purposes.

Parameters

G : graph

A networkx graph

cutoff : bool, optional (default=False)

If specified, only consider paths of length <= cutoff.

Returns

A dict keyed by edge 2-tuple to the number of shortest paths
which use that edge. Where more than one path is shortest
the count is divided equally among paths.

Compute edge load.

Examples

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

networkx.algorithms.centrality.closeness.incremental_closeness_centrality networkx.algorithms.centrality.harmonic.harmonic_centrality networkx.algorithms.centrality.betweenness.betweenness_centrality networkx.algorithms.centrality.betweenness.edge_betweenness_centrality networkx.algorithms.centrality.closeness.closeness_centrality networkx.algorithms.centrality.betweenness_subset.betweenness_centrality_subset networkx.algorithms.centrality.betweenness_subset.edge_betweenness_centrality_subset networkx.algorithms.centrality.degree_alg.degree_centrality

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


GitHub : /networkx/algorithms/centrality/load.py#139
type: <class 'function'>
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