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# Cuthill-McKee ordering of matrices # The reverse Cuthill-McKee algorithm gives a sparse matrix ordering that # reduces the matrix bandwidth. # Requires NumPy # Copyright (C) 2011-2016 by # Author: Aric Hagberg <aric.hagberg@gmail.com> # BSD License import networkx as nx from networkx.utils import reverse_cuthill_mckee_ordering import numpy as np # build low-bandwidth numpy matrix G=nx.grid_2d_graph(3,3) rcm = list(reverse_cuthill_mckee_ordering(G)) print("ordering",rcm) print("unordered Laplacian matrix") A = nx.laplacian_matrix(G) x,y = np.nonzero(A) #print("lower bandwidth:",(y-x).max()) #print("upper bandwidth:",(x-y).max()) print("bandwidth: %d"%((y-x).max()+(x-y).max()+1)) print(A) B = nx.laplacian_matrix(G,nodelist=rcm) print("low-bandwidth Laplacian matrix") x,y = np.nonzero(B) #print("lower bandwidth:",(y-x).max()) #print("upper bandwidth:",(x-y).max()) print("bandwidth: %d"%((y-x).max()+(x-y).max()+1)) print(B)