scipy.linalg.lu_factor¶
- scipy.linalg.lu_factor(a, overwrite_a=False, check_finite=True)[source]¶
Compute pivoted LU decomposition of a matrix.
The decomposition is:
A = P L U
where P is a permutation matrix, L lower triangular with unit diagonal elements, and U upper triangular.
Parameters: a : (M, M) array_like
Matrix to decompose
overwrite_a : bool, optional
Whether to overwrite data in A (may increase performance)
check_finite : bool, optional
Whether to check that the input matrix contains only finite numbers. Disabling may give a performance gain, but may result in problems (crashes, non-termination) if the inputs do contain infinities or NaNs.
Returns: lu : (N, N) ndarray
Matrix containing U in its upper triangle, and L in its lower triangle. The unit diagonal elements of L are not stored.
piv : (N,) ndarray
Pivot indices representing the permutation matrix P: row i of matrix was interchanged with row piv[i].
See also
- lu_solve
- solve an equation system using the LU factorization of a matrix
Notes
This is a wrapper to the *GETRF routines from LAPACK.