#### Logical Symmetric Sparse Matrices in Compressed column-oriented format ### contains = "nsparseMatrix" setAs("nsCMatrix", "matrix", function(from) as(as(from, "ngCMatrix"), "matrix")) setAs("nsCMatrix", "ngCMatrix", function(from) .Call(Csparse_symmetric_to_general, from)) ## Specific conversions, should they be necessary. Better to convert as ## as(x, "TsparseMatrix") or as(x, "denseMatrix") setAs("nsCMatrix", "nsTMatrix", function(from) .Call(Csparse_to_Tsparse, from, FALSE)) setAs("nsCMatrix", "dsCMatrix", function(from) new("dsCMatrix", i = from@i, p = from@p, x = rep(1, length(from@i)), uplo = from@uplo, Dim = from@Dim, Dimnames = from@Dimnames)) setAs("nsCMatrix", "dgTMatrix", function(from) as(as(x, "dsCMatrix"), "dgTMatrix")) ## have rather tril() and triu() methods than ## setAs("nsCMatrix", "ntCMatrix", ....) setMethod("tril", "nsCMatrix", function(x, k = 0, ...) { if(x@uplo == "L" && k == 0) ## same internal structure (speedup potential !?) new("ntCMatrix", uplo = x@uplo, i = x@i, p = x@p, Dim = x@Dim, Dimnames = x@Dimnames) else tril(as(x, "ngCMatrix"), k = k, ...) }) setMethod("triu", "nsCMatrix", function(x, k = 0, ...) { if(x@uplo == "U" && k == 0) ## same internal structure (speedup potential !?) new("ntCMatrix", uplo = x@uplo, i = x@i, p = x@p, Dim = x@Dim, Dimnames = x@Dimnames) else triu(as(x, "ngCMatrix"), k = k, ...) }) ## FIXME: generalize to "nsparseMatrix" or (class union) "symmetric sparse" setMethod("image", "nsCMatrix", function(x, ...) { x <- as(as(x, "dsCMatrix"), "dgTMatrix") callGeneric() }) setMethod("chol", signature(x = "nsCMatrix", pivot = "missing"), function(x, pivot, ...) chol(x, pivot = FALSE)) ## .Call(nsCMatrix_chol, x, FALSE)) setMethod("chol", signature(x = "nsCMatrix", pivot = "logical"), function(x, pivot, ...) stop("temporarily disabled"))## FIXME ## .Call(nsCMatrix_chol, x, pivot)) ## Use more general method from CsparseMatrix class ## setMethod("t", signature(x = "nsCMatrix"), ## function(x) ## .Call(nsCMatrix_trans, x), ## valueClass = "nsCMatrix")