scipy.sparse.linalg.inv#

scipy.sparse.linalg.inv(A)[source]#

Compute the inverse of a sparse matrix

Parameters:

A(M, M) sparse matrix: square matrix to be inverted

Returns:

Ainv(M, M) sparse matrix: inverse of A

Notes

This computes the sparse inverse of A. If the inverse of A is expected to be non-sparse, it will likely be faster to convert A to dense and use scipy.linalg.inv.

Examples

>>> from scipy.sparse import csc_matrix
>>> from scipy.sparse.linalg import inv
>>> A = csc_matrix([[1., 0.], [1., 2.]])
>>> Ainv = inv(A)
>>> Ainv
<2x2 sparse matrix of type '<class 'numpy.float64'>'
    with 3 stored elements in Compressed Sparse Column format>
>>> A.dot(Ainv)
<2x2 sparse matrix of type '<class 'numpy.float64'>'
    with 2 stored elements in Compressed Sparse Column format>
>>> A.dot(Ainv).toarray()
array([[ 1.,  0.],
       [ 0.,  1.]])

New in version 0.12.0.