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)