spbandwidth — SciPy v1.15.3 Manual (original) (raw)
scipy.sparse.linalg.
scipy.sparse.linalg.spbandwidth(A)[source]#
Return the lower and upper bandwidth of a 2D numeric array.
Computes the lower and upper limits on the bandwidth of the sparse 2D array A
. The result is summarized as a 2-tuple of positive integers (lo, hi)
. A zero denotes no sub/super diagonal entries on that side (tringular). The maximum value for lo``(``hi
) is one less than the number of rows(cols).
Only the sparse structure is used here. Values are not checked for zeros.
Parameters:
ASciPy sparse array or matrix
A sparse matrix preferrably in CSR or CSC format.
Returns:
below, above2-tuple of int
The distance to the farthest non-zero diagonal below/above the main diagonal.
Added in version 1.15.0.
Examples
import numpy as np from scipy.sparse.linalg import spbandwidth from scipy.sparse import csc_array, eye_array A = csc_array([[3, 0, 0], [1, -1, 0], [2, 0, 1]], dtype=float) spbandwidth(A) (2, 0) D = eye_array(3, format='csr') spbandwidth(D) (0, 0)