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_setup_residual_graph(G, weight)

The node set of the residual graph corresponds to the set V' from the Baswana-Sen paper and the edge set corresponds to the set E' from the paper.

This function associates distinct weights to the edges of the residual graph (even for unweighted input graphs), as required by the algorithm.

Parameters

G : NetworkX graph

An undirected simple graph.

weight : object

The edge attribute to use as distance.

Returns

NetworkX graph

The residual graph used for the Baswana-Sen algorithm.

Setup residual graph as a copy of G with unique edges weights.

Examples

See :

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/sparsifiers.py#187
type: <class 'function'>
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