# scipy.sparse.linalg.inv

scipy.sparse.linalg.inv(A)

  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.

scipy.sparse.linalg.aslinearoperator scipy.sparse.linalg.expm