scipy.sparse.linalg.inv¶
- scipy.sparse.linalg.inv(A)[source]¶
Compute the inverse of a sparse matrix
- Parameters
- A(M,M) ndarray or sparse matrix
square matrix to be inverted
- Returns
- Ainv(M,M) ndarray or 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).todense() matrix([[ 1., 0.], [ 0., 1.]])
New in version 0.12.0.