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scipy.linalg.lu_factor

# scipy.linalg.lu

`scipy.linalg.``lu`(a, permute_l=False, overwrite_a=False, check_finite=True)

  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, N) array_like Array to decompose permute_l : bool, optional Perform the multiplication P*L (Default: do not permute) overwrite_a : bool, optional Whether to overwrite data in a (may improve 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: | (If permute_l == False) p : (M, M) ndarray Permutation matrix l : (M, K) ndarray Lower triangular or trapezoidal matrix with unit diagonal. K = min(M, N) u : (K, N) ndarray Upper triangular or trapezoidal matrix (If permute_l == True) pl : (M, K) ndarray Permuted L matrix. K = min(M, N) u : (K, N) ndarray Upper triangular or trapezoidal matrix

  Notes

  This is a LU factorization routine written for Scipy.