recursive_simple_cycles(G)

A :None:None:`simple cycle`, or :None:None:`elementary circuit`, is a closed path where no node appears twice. Two elementary circuits are distinct if they are not cyclic permutations of each other.

This version uses a recursive algorithm to build a list of cycles. You should probably use the iterator version called simple_cycles(). Warning: This recursive version uses lots of RAM! It appears in NetworkX for pedagogical value.

Notes

The implementation follows pp. 79-80 in .

The time complexity is $O((n+e)(c+1))$ for $n$ nodes, $e$ edges and $c$ elementary circuits.

Parameters

G : NetworkX DiGraph

A directed graph

Returns

A list of cycles, where each cycle is represented by a list of nodes

along the cycle.

Example:

>>> edges = [(0, 0), (0, 1), (0, 2), (1, 2), (2, 0), (2, 1), (2, 2)]

>>> G = nx.DiGraph(edges)

>>> nx.recursive_simple_cycles(G)

[[0], [2], [0, 1, 2], [0, 2], [1, 2]]

Find simple cycles (elementary circuits) of a directed graph.

See Also

cycle_basis

simple_cycles

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

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GitHub : /networkx/algorithms/cycles.py#227
type: <class 'function'>
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