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 : boolean

Whether to overwrite data in A (may increase performance)

check_finite : boolean, optional

Whether to check the input matrixes contain only finite numbers. Disabling may give a performance gain, but may result to 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

solve an equation system using the LU factorization of a matrix


This is a wrapper to the *GETRF routines from LAPACK.

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