Permute 2 2.2.8

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Compute pivoted LU decomposition of a matrix.

The decomposition is:

$Permute 2 2.2.8$

Permute 2 2.2.8 Full

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

Parameters:	a:(M, N) array_like Array to decompose permute_l:bool, optional Perform the multiplication PL (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

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

Permute 2 2.2.8 Torrent

This is a LU factorization routine written for Scipy.

Permute 2 2.2.8 Test

Examples