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nsparseMatrix class is a virtual class of sparse
“pattern” matrices, i.e., binary matrices conceptually
with TRUE/FALSE entries. Only the positions of the
elements that are TRUE are stored. These can be stored in the “triplet” form
(TsparseMatrix, subclasses ngTMatrix,
nsTMatrix, and ntTMatrix which really contain pairs, not
triplets) or in compressed column-oriented form (class
CsparseMatrix, subclasses ngCMatrix,
nsCMatrix, and ntCMatrix) or--rarely--in
compressed row-oriented form (class RsparseMatrix,
subclasses ngRMatrix, nsRMatrix, and ntRMatrix).
The second letter in the name of these non-virtual classes indicates
general, symmetric, or triangular.
new("ngCMatrix",
...) and so on. More frequently objects are created by coercion of
a numeric sparse matrix to the pattern form for use in
the symbolic analysis phase
of an algorithm involving sparse matrices. Such algorithms often
involve two phases: a symbolic phase wherein the positions of the
non-zeros in the result are determined and a numeric phase wherein the
actual results are calculated. During the symbolic phase only the
positions of the non-zero elements in any operands are of interest,
hence numeric sparse matrices can be treated as sparse pattern
matrices.dgCMatrix
(m <- Matrix(c(0,0,2:0), 3,5, dimnames=list(LETTERS[1:3],NULL)))
## ``extract the nonzero-pattern of (m) into an nMatrix'':
nm <- as(m, "nsparseMatrix") ## -> will be a "ngCMatrix"
str(nm) # no 'x' slot
nnm <- !nm # no longer sparse
(nnm <- as(nnm, "sparseMatrix"))# "lgCMatrix"
## consistency check:
stopifnot(xor(as( nm, "matrix"),
as(nnm, "matrix")))
## low-level way of adding "non-structural zeros" :
nnm@x[2:4] <- c(FALSE,NA,NA)
nnm
as(nnm, "nMatrix") # NAs *and* non-structural 0 |---> 'TRUE'
data(KNex)
nmm <- as(KNex $ mm, "ngCMatrix")
str(xlx <- crossprod(nmm))# "nsCMatrix"
stopifnot(isSymmetric(xlx))
image(xlx, main=paste("crossprod(nmm) : Sparse", class(xlx)))
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