scipy.sparse.linalg.

spbandwidth#

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)