annotate env/share/doc/networkx-2.5/examples/algorithms/plot_rcm.py @ 0:4f3585e2f14b draft default tip

"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"

"""
===
Rcm
===

Cuthill-McKee ordering of matrices

The reverse Cuthill-McKee algorithm gives a sparse matrix ordering that
reduces the matrix bandwidth.
"""

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(f"lower bandwidth: {(y - x).max()}")
# print(f"upper bandwidth: {(x - y).max()}")
print(f"bandwidth: {(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(f"lower bandwidth: {(y - x).max()}")
# print(f"upper bandwidth: {(x - y).max()}")
print(f"bandwidth: {(y - x).max() + (x - y).max() + 1}")
print(B)