Matrix (version 1.4-0)

sparseLU-class: Sparse LU decomposition of a square sparse matrix

Description

Objects of this class contain the components of the LU decomposition of a sparse square matrix.

Objects from the Class

Objects can be created by calls of the form new("sparseLU", ...) but are more commonly created by function lu() applied to a sparse matrix, such as a matrix of class '>dgCMatrix.

Slots

L:

Object of class "'>dtCMatrix", the lower triangular factor from the left.

U:

Object of class "'>dtCMatrix", the upper triangular factor from the right.

p:

Object of class "integer", permutation applied from the left.

q:

Object of class "integer", permutation applied from the right.

Dim:

the dimension of the original matrix; inherited from class '>MatrixFactorization.

Extends

Class "'>LU", directly. Class "'>MatrixFactorization", by class "LU".

Methods

expand

signature(x = "sparseLU") Returns a list with components P, L, U, and Q, where \(P\) and \(Q\) represent fill-reducing permutations, and \(L\), and \(U\) the lower and upper triangular matrices of the decomposition. The original matrix corresponds to the product \(P'LUQ\).

See Also

lu, solve, '>dgCMatrix

Examples

# NOT RUN {
## Extending the one in   examples(lu), calling the matrix  A,
## and confirming the factorization identities :
A <- as(readMM(system.file("external/pores_1.mtx",
                            package = "Matrix")),
         "CsparseMatrix")
## with dimnames(.) - to see that they propagate to L, U :
dimnames(A) <- dnA <- list(paste0("r", seq_len(nrow(A))),
                           paste0("C", seq_len(ncol(A))))
str(luA <- lu(A)) # p is a 0-based permutation of the rows
                  # q is a 0-based permutation of the columns
xA <- expand(luA)
## which is simply doing
stopifnot(identical(xA$ L, luA@L),
          identical(xA$ U, luA@U),
          identical(xA$ P, as(luA@p +1L, "pMatrix")),
          identical(xA$ Q, as(luA@q +1L, "pMatrix")))

P.LUQ <- with(xA, t(P) %*% L %*% U %*% Q)
stopifnot(all.equal(A, P.LUQ, tolerance = 1e-12),
          identical(dimnames(P.LUQ), dnA))
## permute rows and columns of original matrix
pA <- A[luA@p + 1L, luA@q + 1L]
stopifnot(identical(pA, with(xA, P %*% A %*% t(Q))))

pLU <- drop0(luA@L %*% luA@U) # L %*% U -- dropping extra zeros
stopifnot(all.equal(pA, pLU, tolerance = 1e-12))
# }