Warning
This documents an unmaintained version of NetworkX. Please upgrade to a maintained version and see the current NetworkX documentation.
reverse_cuthill_mckee_ordering¶
- reverse_cuthill_mckee_ordering(G, heuristic=None)[source]¶
Generate an ordering (permutation) of the graph nodes to make a sparse matrix.
Uses the reverse Cuthill-McKee heuristic (based on breadth-first search) [R334].
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 reverse Cuthill-McKee ordering.
See also
Notes
The optimal solution the the bandwidth reduction is NP-complete [R335].
References
[R334] (1, 2) E. Cuthill and J. McKee. Reducing the bandwidth of sparse symmetric matrices, In Proc. 24th Nat. Conf. ACM, pages 157-72, 1969. http://doi.acm.org/10.1145/800195.805928 [R335] (1, 2) Steven S. Skiena. 1997. The Algorithm Design Manual. Springer-Verlag New York, Inc., New York, NY, USA. Examples
>>> from networkx.utils import reverse_cuthill_mckee_ordering >>> G = nx.path_graph(4) >>> rcm = list(reverse_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(reverse_cuthill_mckee_ordering(G, heuristic=smallest_degree))