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flow_hierarchy(G, weight=None)

Flow hierarchy is defined as the fraction of edges not participating in cycles in a directed graph .

Notes

The algorithm described in computes the flow hierarchy through exponentiation of the adjacency matrix. This function implements an alternative approach that finds strongly connected components. An edge is in a cycle if and only if it is in a strongly connected component, which can be found in $O(m)$ time using Tarjan's algorithm.

Parameters

G : DiGraph or MultiDiGraph

A directed graph

weight : key,optional (default=None)

Attribute to use for node weights. If None the weight defaults to 1.

Returns

h : float

Flow hierarchy value

Returns the flow hierarchy of a directed network.

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/hierarchy.py#9
type: <class 'function'>
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