scipy.sparse.linalg.

inv#

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

Compute the inverse of a sparse arrays

Parameters:
A(M, M) sparse arrays

square matrix to be inverted

Returns:
Ainv(M, M) sparse arrays

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_array
>>> from scipy.sparse.linalg import inv
>>> A = csc_array([[1., 0.], [1., 2.]])
>>> Ainv = inv(A)
>>> Ainv
<Compressed Sparse Column sparse array of dtype 'float64'
    with 3 stored elements and shape (2, 2)>
>>> A.dot(Ainv)
<Compressed Sparse Column sparse array of dtype 'float64'
    with 2 stored elements and shape (2, 2)>
>>> A.dot(Ainv).toarray()
array([[ 1.,  0.],
       [ 0.,  1.]])

Added in version 0.12.0.