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Please note that the recommended version of Scilab is 6.0.2. This page might be outdated.

See the recommended documentation of this function

# 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.

### Used Functions

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

## Comments

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