cuthill_mckee_ordering¶

cuthill_mckee_ordering(G, heuristic=None)[source]¶

Generate an ordering (permutation) of the graph nodes to make a sparse matrix.

Uses the Cuthill-McKee heuristic (based on breadth-first search) [R338].

Parameters:	G : graph A NetworkX graph heuristic : function, optional Function to choose starting node for RCM algorithm. If None a node from a psuedo-peripheral pair is used. A user-defined function can be supplied that takes a graph object and returns a single node.
Returns:	nodes : generator Generator of nodes in Cuthill-McKee ordering.

See also

reverse_cuthill_mckee_ordering

Notes

The optimal solution the the bandwidth reduction is NP-complete [R339].

References

[R338]

(1, 2) E. Cuthill and J. McKee. Reducing the bandwidth of sparse symmetric matrices, In Proc. 24th Nat. Conf. ACM, pages 157-172, 1969. http://doi.acm.org/10.1145/800195.805928

[R339]

(1, 2) Steven S. Skiena. 1997. The Algorithm Design Manual. Springer-Verlag New York, Inc., New York, NY, USA.

Examples

>>> from networkx.utils import cuthill_mckee_ordering
>>> G = nx.path_graph(4)
>>> rcm = list(cuthill_mckee_ordering(G))
>>> A = nx.adjacency_matrix(G, nodelist=rcm) 

Smallest degree node as heuristic function:

>>> def smallest_degree(G):
...     node,deg = sorted(G.degree().items(), key = lambda x:x[1])[0]
...     return node
>>> rcm = list(cuthill_mckee_ordering(G, heuristic=smallest_degree))