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#### Sparse Matrices in Compressed column-oriented format
### contains = "dsparseMatrix", "CsparseMatrix"
## Specific conversions, should they be necessary. Better to convert as
## as(x, "TsparseMatrix") or as(x, "denseMatrix")
## Moved to ./Csparse.R :
## setAs("dgCMatrix", "dgTMatrix", ....
## setAs("dgCMatrix", "dgeMatrix", ....
## setAs("dgeMatrix", "dgCMatrix", ....
## rather use Csparse* to lsparse* in ./lsparseMatrix.R ,
## but this is for "back-compatibility" (have had tests for it..):
setAs("dgCMatrix", "ngCMatrix",
function(from) .Call(Csparse_to_nz_pattern, from, FALSE))
setAs("dgCMatrix", "lgCMatrix",
function(from) { ## FIXME use .Call() too!
r <- new("lgCMatrix")
r@x <- as.logical(from@x)
## and copy the other slots
for(nm in c("i", "p", "Dim", "Dimnames"))
slot(r, nm) <- slot(from, nm)
r
})
setMethod("image", "dgCMatrix",
function(x, ...) {
x <- as(x, "dgTMatrix")
callGeneric()
})
## Group Methods, see ?Arith (e.g.)
## -----
setMethod("Arith", ## "+", "-", "*", "^", "%%", "%/%", "/"
signature(e1 = "dgCMatrix", e2 = "dgCMatrix"),
function(e1, e2) {
d <- dimCheck(e1, e2)
dn <- dimNamesCheck(e1, e2)
ij1 <- non0ind(e1)
ij2 <- non0ind(e2)
switch(.Generic,
"+" = , "-" =
## special "T" convention: repeated entries are *summed*
as(new("dgTMatrix", Dim = d, Dimnames = dn,
i = c(ij1[,1], ij2[,1]),
j = c(ij1[,2], ij2[,2]),
x = c(callGeneric(e1@x, 0), callGeneric(0,e2@x))),
"dgCMatrix"),
"*" =
{ ## X * 0 == 0 * X == 0 --> keep common non-0
ii <- WhichintersectInd(ij1, ij2, nrow=d[1])
ij <- ij1[ii[[1]], , drop = FALSE]
as(new("dgTMatrix", Dim = d, Dimnames = dn,
i = ij[,1],
j = ij[,2],
x = e1@x[ii[[1]]] * e2@x[ii[[2]]]),
"dgCMatrix")
},
"^" =
{
ii <- WhichintersectInd(ij1, ij2, nrow=d[1])
## 3 cases:
## 1) X^0 := 1 (even for X=0) ==> dense
## 2) 0^Y := 0 for Y != 0 =====
## 3) x^y :
## FIXME: dgeM[cbind(i,j)] <- V is not yet possible
## nor dgeM[ i_vect ] <- V
## r <- as(e2, "dgeMatrix")
## ...
r <- as(e2, "matrix")
Yis0 <- is0(r)
r[complementInd(ij1, dim=d)] <- 0 ## 2)
r[1:1 + ij2[ii[[2]], , drop=FALSE]] <-
e1@x[ii[[1]]] ^ e2@x[ii[[2]]] ## 3)
r[Yis0] <- 1 ## 1)
as(r, "dgeMatrix")
},
"%%" = , "%/%" = , "/" = ## 0 op 0 |-> NaN => dense
callGeneric(as(e1, "dgeMatrix"), e2)
)
})
setMethod("Arith",
signature(e1 = "dgCMatrix", e2 = "numeric"),
function(e1, e2) {
if(length(e2) == 1) { ## e.g., Mat ^ a
f0 <- callGeneric(0, e2)
if(is0(f0)) { # remain sparse
e1@x <- callGeneric(e1@x, e2)
e1
} else { ## non-sparse, since '0 o e2' is not 0
## FIXME: dgeMatrix [cbind(i,j)] <- .. is not yet possible
## r <- as(e1, "dgeMatrix")
## r[] <- f0
## r[non0ind(e1)] <- callGeneric(e1@x, e2)
r <- as(e1, "matrix")
r[] <- f0
r[non0ind(e1) + 1:1] <- callGeneric(e1@x, e2)
as(r, "dgeMatrix")
}
} else {
## FIXME: maybe far from optimal:
warning("coercing sparse to dense matrix for arithmetic")
callGeneric(as(e1, "dgeMatrix"), e2)
}
})
setMethod("Arith",
signature(e1 = "numeric", e2 = "dgCMatrix"),
function(e1, e2) {
if(length(e1) == 1) {
f0 <- callGeneric(e1, 0)
if(is0(f0)) { # stay sparse, even "dgC"
e2@x <- callGeneric(e1, e2@x)
e2
} else {
## FIXME: dgeMatrix [cbind(i,j)] <- .. is not yet possible
r <- as(e2, "matrix")
r[] <- f0
r[non0ind(e2) + 1:1] <- callGeneric(e1, e2@x)
as(r, "dgeMatrix")
}
} else {
## FIXME: maybe far from optimal:
warning("coercing sparse to dense matrix for arithmetic")
callGeneric(e1, as(e2, "dgeMatrix"))
}
})
## "Math" is up in ./Csparse.R
## "Math2" is up in ./dMatrix.R
###---- end {Group Methods} -----------------
## "[<-" methods { setReplaceMethod()s } are now in ./Csparse.R
setMethod("writeHB", signature(obj = "dgCMatrix"),
function(obj, file, ...) {
.Deprecated("writeMM")
.Call(Matrix_writeHarwellBoeing, obj,
as.character(file), "DGC")
})
setMethod("writeMM", signature(obj = "dgCMatrix"),
function(obj, file, ...)
.Call(Matrix_writeMatrixMarket, obj, as.character(file), "DGC"))
## TODO (in C):
## setMethod("colSums", signature(x = "dgCMatrix"),
## function(x, na.rm = FALSE, dims = 1)
## .Call(dgCMatrix_colsums, x, na.rm, TRUE, FALSE),
## valueClass = "numeric")
## setMethod("colMeans", signature(x = "dgCMatrix"),
## function(x, na.rm = FALSE, dims = 1)
## .Call(dgCMatrix_colsums, x, na.rm, TRUE, TRUE),
## valueClass = "numeric")
setMethod("colSums", signature(x = "dgCMatrix"), .as.dgT.Fun)
setMethod("colMeans", signature(x = "dgCMatrix"), .as.dgT.Fun)
setMethod("rowSums", signature(x = "dgCMatrix"),
function(x, na.rm = FALSE, dims = 1)
tapply1(x@x, factor(x@i, 0:(x@Dim[1]-1)), sum, na.rm = na.rm),
valueClass = "numeric")
setMethod("rowMeans", signature(x = "dgCMatrix"),
function(x, na.rm = FALSE, dims = 1)
tapply1(x@x, factor(x@i, 0:(x@Dim[1]-1)), mean, na.rm = na.rm),
valueClass = "numeric")
setMethod("qr", signature(x = "dgCMatrix"),
function(x, tol = 1e-07, LAPACK = FALSE)
.Call(dgCMatrix_QR, x, TRUE))
setMethod("lu", signature(x = "dgCMatrix"),
function(x, ...) .Call(dgCMatrix_LU, x, TRUE, 1))
setMethod("solve", signature(a = "dgCMatrix", b = "matrix"),
function(a, b, ...) .Call(dgCMatrix_matrix_solve, a, b),
valueClass = "dgeMatrix")
setMethod("solve", signature(a = "dgCMatrix", b = "ddenseMatrix"),
function(a, b, ...) .Call(dgCMatrix_matrix_solve, a, b),
valueClass = "dgeMatrix")
setMethod("solve", signature(a = "dgCMatrix", b = "dsparseMatrix"),
function(a, b, ...)
.Call(dgCMatrix_matrix_solve, a, as(b, "denseMatrix")),
valueClass = "dgeMatrix")
setMethod("solve", signature(a = "dgCMatrix", b = "missing"),
function(a, b, ...) .Call(dgCMatrix_matrix_solve, a, b=NULL),
valueClass = "dgeMatrix")
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