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#### Logical Symmetric Sparse Matrices in Compressed column-oriented format
### contains = "lsparseMatrix"
setAs("lsCMatrix", "matrix",
function(from) as(as(from, "generalMatrix"), "matrix"))
setAs("lsCMatrix", "lgCMatrix",
function(from) .Call(Csparse_symmetric_to_general, from))
## needed for indexing (still ?)
setAs("lsCMatrix", "lgTMatrix",
function(from) as(as(from, "generalMatrix"), "lgTMatrix"))
aslsC.by.lgC <- function(from) as(as(from, "lgCMatrix"), "symmetricMatrix")
setAs("lgTMatrix", "lsCMatrix", aslsC.by.lgC) # <-> needed for Matrix()
setAs("matrix", "lsCMatrix", aslsC.by.lgC)
## Specific conversions, should they be necessary. Better to convert as
## as(x, "TsparseMatrix") or as(x, "denseMatrix")
setAs("lsCMatrix", "lsTMatrix",
function(from) .Call(Csparse_to_Tsparse, from, FALSE))
setAs("lsCMatrix", "dsCMatrix",
function(from) new("dsCMatrix", i = from@i, p = from@p,
x = as.double(from@x), uplo = from@uplo,
Dim = from@Dim, Dimnames = from@Dimnames))
if(FALSE) # needed ?
setAs("lsCMatrix", "dgTMatrix",
function(from) as(as(from, "dsCMatrix"), "dgTMatrix"))
## have rather tril() and triu() methods than
## setAs("lsCMatrix", "ltCMatrix", ....)
setMethod("tril", "lsCMatrix",
function(x, k = 0, ...) {
if(x@uplo == "L" && k == 0)
## same internal structure + diag
new("ltCMatrix", uplo = x@uplo, i = x@i, p = x@p,
x = x@x, Dim = x@Dim, Dimnames = x@Dimnames)
else tril(as(x, "lgCMatrix"), k = k, ...)
})
setMethod("triu", "lsCMatrix",
function(x, k = 0, ...) {
if(x@uplo == "U" && k == 0)
new("ltCMatrix", uplo = x@uplo, i = x@i, p = x@p,
x = x@x, Dim = x@Dim, Dimnames = x@Dimnames)
else triu(as(x, "lgCMatrix"), k = k, ...)
})
setMethod("chol", signature(x = "lsCMatrix"),
function(x, pivot=FALSE, ...)
chol(as(x, "dgCMatrix"), pivot=pivot, ...))
## Use more general method from CsparseMatrix class
## setMethod("t", signature(x = "lsCMatrix"),
## function(x)
## .Call(lsCMatrix_trans, x),
## valueClass = "lsCMatrix")
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