jax.scipy.linalg.lu_factor(a, overwrite_a=False, check_finite=True)[source]ΒΆ

Compute pivoted LU decomposition of a matrix.

LAX-backend implementation of lu_factor().

Original docstring below.

The decomposition is:

A = P L U

where P is a permutation matrix, L lower triangular with unit diagonal elements, and U upper triangular.

  • 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.


  • 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].