# lu

LU factorization with pivoting

## Calling Sequence

    [L,U]= lu(A)
                [L,U,E]= lu(A)

## Arguments

A

  real or complex matrix (m x n).

L

  real or complex matrices (m x min(m,n)).

U

  real or complex matrices (min(m,n) x n ).

E

  a (n x n) permutation matrix.

## Description

`[L,U]= lu(A)` produces two matrices `L` and `U` such that `A = L*U` with `U` upper triangular and `L` a general matrix without any particular structure. In fact, the matrix `A` is factored as `E*A=B*U` where the matrix `B` is lower triangular and the matrix `L` is computed from `L=E'*B`.

If `A` has rank `k`, rows `k+1` to `n` of `U` are zero.

`[L,U,E]= lu(A)` produces three matrices `L`, `U` and `E` such that `E*A = L*U` with `U` upper triangular and `E*L` lower triangular for a permutation matrix `E`.

If `A` is a real matrix, using the function `lufact` and `luget` it is possible to obtain the permutation matrices and also when `A` is not full rank the column compression of the matrix `L`.

## Example #1

In the following example, we create the Hilbert matrix of size 4 and factor it with A=LU. Notice that the matrix L is not lower triangular. To get a lower triangular L matrix, we should have given the output argument E to Scilab.

    a = testmatrix("hilb",4);
    [l,u]=lu(a)
    norm(l*u-a)

## Example #2

In the following example, we create the Hilbert matrix of size 4 and factor it with EA=LU. Notice that the matrix L is lower triangular.

    a = testmatrix("hilb",4);
    [l,u,e]=lu(a)
    norm(l*u-e*a)

## Example #3

The following example shows how to use the lufact and luget functions.

    a=rand(4,4);
    [l,u]=lu(a)
    norm(l*u-a)

    [h,rk]=lufact(sparse(a))
    [P,L,U,Q]=luget(h);
    ludel(h)
    P=full(P);
    L=full(L);
    U=full(U);
    Q=full(Q);
    norm(P*L*U*Q-a)

## See Also

- lufact
- luget
- lusolve
- qr
- svd

## Used Functions

lu decompositions are based on the Lapack routines DGETRF for real matrices and ZGETRF for the complex case.