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sparseMatrix.R
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## Methods for virtual class "sparseMatrix" of sparse matrices
## ~~~~ COERCIONS ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
..sparse2unpacked <- function(from)
.Call(R_sparse_as_dense, from, FALSE)
..sparse2packed <- function(from) {
if(!.hasSlot(from, "uplo"))
from <-
if(isSymmetric(from))
forceSymmetric(from)
else if(!(it <- isTriangular(from)))
stop("matrix is not symmetric or triangular")
else if (attr(it, "kind") == "U")
triu(from)
else tril(from)
.Call(R_sparse_as_dense, from, TRUE)
}
..sparse2dge <- function(from)
.sparse2dense(.sparse2g(..sparse2d(from)))
..sparse2lge <- function(from)
.sparse2dense(.sparse2g(..sparse2l(from)))
..sparse2nge <- function(from)
.sparse2dense(.sparse2g(..sparse2n(from)))
..tT2gC <- ..sT2gC <- function(from) .T2C(.sparse2g(from))
..tC2gT <- ..sC2gT <- function(from) .CR2T(.sparse2g(from))
..gT2tC <- function(from) .T2C(.M2tri(from))
..gT2sC <- function(from) .T2C(.M2sym(from))
..gC2tT <- function(from) .CR2T(.M2tri(from))
..gC2sT <- function(from) .CR2T(.M2sym(from))
## To sparseMatrix .........................................
setAs("ANY", "sparseMatrix",
function(from) Matrix(from, sparse = TRUE, doDiag = FALSE))
## If people used table() instead of xtabs():
setAs("table", "sparseMatrix",
function(from) {
if(length(dim(from)) != 2L)
stop("only 2-dimensional tables can be coerced to sparseMatrix")
as(unclass(from), "CsparseMatrix")
})
## To dense ................................................
for (.cl in paste0(c("C", "R", "T"), "sparseMatrix")) {
setAs(.cl, "denseMatrix", ..sparse2unpacked)
setAs(.cl, "unpackedMatrix", ..sparse2unpacked)
setAs(.cl, "packedMatrix", ..sparse2packed)
}
rm(.cl)
## To base matrix, base vector .............................
for (.cl in paste0(c("C", "R", "T"), "sparseMatrix")) {
setAs(.cl, "matrix", .sparse2m)
setAs(.cl, "vector", .sparse2v)
setMethod("as.vector", signature(x = .cl),
function(x, mode = "any") as.vector(.sparse2v(x), mode))
}
rm(.cl)
setMethod("as.numeric", signature(x = "dsparseMatrix"),
function(x, ...) .sparse2v(x))
setMethod("as.numeric", signature(x = "lsparseMatrix"),
function(x, ...) as.double(.sparse2v(x)))
setMethod("as.numeric", signature(x = "nsparseMatrix"),
function(x, ...) as.double(.sparse2v(x)))
setMethod("as.logical", signature(x = "dsparseMatrix"),
function(x, ...) as.logical(.sparse2v(x)))
setMethod("as.logical", signature(x = "lsparseMatrix"),
function(x, ...) .sparse2v(x))
setMethod("as.logical", signature(x = "nsparseMatrix"),
function(x, ...) .sparse2v(x))
## To "kind" ...............................................
.kinds <- c("d", "l", "n")
for (.kind in .kinds) {
.otherkinds <- .kinds[.kinds != .kind]
for (.otherkind in .otherkinds) {
.def <- get(sprintf("..sparse2%s", .otherkind),
mode = "function", inherits = FALSE)
## dsparseMatrix->[^d]Matrix, etc.
setAs(paste0( .kind, "sparseMatrix"),
paste0(.otherkind, "Matrix"), .def)
## dsparseMatrix->[^d]sparseMatrix, etc.
setAs(paste0( .kind, "sparseMatrix"),
paste0(.otherkind, "sparseMatrix"), .def)
}
}
rm(.kinds, .kind, .otherkinds, .otherkind, .def)
## To "structure" ..........................................
setAs("CsparseMatrix", "generalMatrix", .sparse2g)
setAs("RsparseMatrix", "generalMatrix", .sparse2g)
setAs("TsparseMatrix", "generalMatrix", .sparse2g)
## setAs("sparseMatrix", "triangularMatrix", .) # inherited from Matrix
## setAs("sparseMatrix", "symmetricMatrix", .) # inherited from Matrix
## To "storage" ............................................
setAs("CsparseMatrix", "TsparseMatrix", .CR2T)
setAs("CsparseMatrix", "RsparseMatrix", .CR2RC)
setAs("RsparseMatrix", "CsparseMatrix", .CR2RC)
setAs("RsparseMatrix", "TsparseMatrix", .CR2T)
setAs("TsparseMatrix", "CsparseMatrix", .T2C)
setAs("TsparseMatrix", "RsparseMatrix", .T2R)
for (.kind in c("d", "l", "n"))
for (.repr in c("C", "R"))
setAs(paste0(.kind, "s", .repr, "Matrix"),
paste0(if(.repr == "C") "R" else "C", "sparseMatrix"),
.tCR2RC)
rm(.kind, .repr)
## More granular coercions .................................
## DEPRECATED IN 1.5-0; see ./zzz.R
if(FALSE) {
.kinds <- c("d", "l", "n")
.strs <- c("g", "t", "s")
.reprs <- c("C", "R", "T")
.map.str <- c(g = "e", t = "r", s = "y")
.map.repr <- list(C = list(R = .CR2RC, T = .CR2T),
R = list(C = .CR2RC, T = .CR2T),
T = list(C = .T2C, R = .T2R))
for (.kind in .kinds) {
## This kind to other kinds, preserving structure and storage
.otherkinds <- .kinds[.kinds != .kind]
for (.otherkind in .otherkinds) {
.def <- get(sprintf("..sparse2%s", .otherkind),
mode = "function", inherits = FALSE)
for (.str in .strs)
for (.repr in .reprs)
setAs(paste0( .kind, .str, .repr, "Matrix"),
paste0(.otherkind, .str, .repr, "Matrix"), .def)
}
## Non-symmetric to symmetric, preserving kind and storage
for (.str in c("g", "t"))
for (.repr in .reprs)
setAs(paste0(.kind, .str, .repr, "Matrix"),
paste0(.kind, "s", .repr, "Matrix"), ..M2sym)
## Non-triangular to triangular, preserving kind and storage
for (.str in c("g", "s"))
for (.repr in .reprs)
setAs(paste0(.kind, .str, .repr, "Matrix"),
paste0(.kind, "t", .repr, "Matrix"), ..M2tri)
## Non-general to general, preserving kind and storage
for (.str in c("t", "s"))
for (.repr in .reprs)
setAs(paste0(.kind, .str, .repr, "Matrix"),
paste0(.kind, "g", .repr, "Matrix"), .sparse2g)
## C->[^C], R->[^R], T->[^T], preserving kind and structure
for (.str in .strs) {
for (.repr in .reprs) {
.otherreprs <- .reprs[.reprs != .repr]
for (.otherrepr in .otherreprs)
setAs(paste0(.kind, .str, .repr, "Matrix"),
paste0(.kind, .str, .otherrepr, "Matrix"),
.map.repr[[c(.repr, .otherrepr)]])
}
}
## Sparse to dense, preserving kind and structure
for (.str in .strs) {
for (.repr in .reprs) {
setAs(paste0(.kind, .str, .repr, "Matrix"),
paste0(.kind, .str, .map.str[[.str]], "Matrix"),
..sparse2unpacked)
if (.str == "g") next
setAs(paste0(.kind, .str, .repr, "Matrix"),
paste0(.kind, .str, "p", "Matrix"),
..sparse2packed)
}
}
## sC<->sR, preserving kind
.def.template <- function(from)
new(.TO, Dim = from@Dim, Dimnames = from@Dimnames,
uplo = if(from@uplo == "U") "L" else "U",
p = from@p, j = from@i, x = from@x)
for (.repr in c("C", "R")) {
.otherrepr <- if(.repr == "C") "R" else "C"
.from <- paste0(.kind, "s", .repr, "Matrix")
.to <- paste0(.kind, "s", .otherrepr, "Matrix")
.def <- .def.template
.b <- body(.def)
.b[[2L]] <- .to
if(.repr != "C") { # reverse j = from@i
.m <- match("j", names(.b))
names(.b)[.m] <- "i"
.b[[.m]][[3L]] <- quote(j)
}
if(.kind == "n") { # delete x = from@x
.m <- match("x", names(.b))
.b[[.m]] <- NULL
}
body(.def) <- .b
setAs(.from, .to, .def)
setAs(.from, paste0(.otherrepr, "sparseMatrix"), .def)
}
## gC->[^g]T, [^g]C->gT, gT->[^g]C, [^g]T->gC, preserving kind
for (.str in c("t", "s")) {
for (.repr in c("C", "T")) {
.otherrepr <- if(.repr == "C") "T" else "C"
setAs(paste0(.kind, "g", .repr, "Matrix"),
paste0(.kind, .str, .otherrepr, "Matrix"),
get(paste0("..g", .repr, "2", .str, .otherrepr),
mode = "function", inherits = FALSE))
setAs(paste0(.kind, .str, .repr, "Matrix"),
paste0(.kind, "g", .otherrepr, "Matrix"),
get(paste0("..", .str, .repr, "2g", .otherrepr),
mode = "function", inherits = FALSE))
}
}
}
rm(.kinds, .kind, .otherkinds, .otherkind,
.strs, .str, .map.str,
.reprs, .repr, .otherreprs, .otherrepr, .map.repr,
.from, .to, .def, .def.template, .b, .m)
## For whatever reason, we also have these granular ones in Matrix 1.4-1:
setAs("RsparseMatrix", "dgeMatrix", ..sparse2dge)
setAs( "dtCMatrix", "dgeMatrix", ..sparse2dge)
setAs( "dsCMatrix", "dgeMatrix", ..sparse2dge)
setAs( "dtTMatrix", "dgeMatrix", ..sparse2dge)
setAs( "dsTMatrix", "dgeMatrix", ..sparse2dge)
setAs( "ngTMatrix", "lgeMatrix", ..sparse2lge)
} ## DEPRECATED IN 1.5-0; see ./zzz.R
rm(..sparse2unpacked, ..sparse2packed,
..sparse2dge, ..sparse2lge, ..sparse2nge)
## ~~~~ CONSTRUCTORS ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
spMatrix <- function(nrow, ncol, i = integer(), j = integer(), x = double())
new(paste0(.M.kind(x), "gTMatrix"), # rely on new() to check validity
Dim = c(as.integer(nrow), as.integer(ncol)),
i = as.integer(i) - 1L,
j = as.integer(j) - 1L,
x = if(is.integer(x)) as.double(x) else x)
if(FALSE) {
## This version was used in Matrix <= 1.5-1
sparseMatrix <- function(i = ep, j = ep, p, x, dims, dimnames,
symmetric = FALSE, triangular = FALSE, index1 = TRUE,
repr = "C", giveCsparse = (repr == "C"),
check = TRUE, use.last.ij = FALSE)
{
## Purpose: user-level substitute for most new(<sparseMatrix>, ..) calls
## Author: Douglas Bates, Date: 12 Jan 2009, based on Martin's version
if((m.i <- missing(i)) + (m.j <- missing(j)) + (m.p <- missing(p)) != 1)
stop("exactly one of 'i', 'j', or 'p' must be missing from call")
if(!m.p) {
p <- as.integer(p)
if((lp <- length(p)) < 1 || p[1] != 0 || any((dp <- p[-1] - p[-lp]) < 0))
stop("'p' must be a non-decreasing vector (0, ...)")
ep <- rep.int(seq_along(dp), dp)
}
stopifnot(length(repr) == 1L, repr %in% c("C", "T", "R"))
## NB: up to 2020-05, only had giveCsparse=TRUE --> "C" or "T" -- remain back-compatible:
if(missing(repr) && !giveCsparse) {
warning("'giveCsparse' has been deprecated; setting 'repr = \"T\"' for you")
repr <- "T"
} else if(!missing(repr) && !missing(giveCsparse))
warning("'giveCsparse' has been deprecated; will use 'repr' instead")
## i and j are now both defined (via default = ep). Make them 1-based indices.
i1 <- as.logical(index1)[1]
i <- as.integer(i + !(m.i || i1))
j <- as.integer(j + !(m.j || i1))
## "minimal dimensions" from (i,j,p); no warnings from empty i or j :
dims.min <- suppressWarnings(c(max(i), max(j)))
if(anyNA(dims.min)) stop("NA's in (i,j) are not allowed")
if(missing(dims)) {
dims <- if(symmetric || triangular) rep(max(dims.min), 2) else dims.min
} else { ## check dims
stopifnot(all(dims >= dims.min))
dims <- as.integer(dims)
}
if(symmetric && triangular)
stop("Both 'symmetric' and 'triangular', i.e. asking for diagonal matrix. Use 'Diagonal()' instead")
sx <-
if(symmetric) {
if(dims[1] != dims[2]) stop("symmetric matrix must be square")
"s"
} else if(triangular) {
if(dims[1] != dims[2]) stop("triangular matrix must be square")
"t"
} else "g"
isPat <- missing(x) ## <-> patter"n" Matrix
kx <- if(isPat) "n" else .M.kind(x)
r <- new(paste0(kx, sx, "TMatrix"))
r@Dim <- dims
if(symmetric && all(i >= j)) r@uplo <- "L" # else "U", the default
else if(triangular) {
r@uplo <-
if(all(i >= j))
"L"
else if(all(i <= j))
"U"
else stop("triangular matrix must have all i >= j or i <= j")
}
if(!isPat) {
if(kx == "d" && !is.double(x)) x <- as.double(x)
if(length(x) != (n <- length(i))) { ## recycle
if(length(x) != 1 && n %% length(x) != 0)
warning("length(i) is not a multiple of length(x)")
x <- rep_len(x, n)
}
if(use.last.ij && (id <- anyDuplicated(cbind(i,j), fromLast=TRUE))) {
i <- i[-id]
j <- j[-id]
x <- x[-id]
if(any(idup <- duplicated(cbind(i,j), fromLast=TRUE))) {
ndup <- -which(idup)
i <- i[ndup]
j <- j[ndup]
x <- x[ndup]
}
}
r@x <- x
}
r@i <- i - 1L
r@j <- j - 1L
if(haveDN <- !missing(dimnames) && !is.null(dimnames))
r@Dimnames <- dimnames
if(check)
validObject(r)
if(haveDN && (check || !(is.character(validDim(dims)) ||
is.character(validDN(dimnames, dims)))))
## fixup* needs a valid argument!
r@Dimnames <- fixupDN(r@Dimnames)
switch(repr,
"C" = as(r, "CsparseMatrix"),
"T" = r,# TsparseMatrix
"R" = as(r, "RsparseMatrix"),
stop("invalid 'repr'; must be \"C\", \"T\", or \"R\""))
}
} else {
## This version modifies the above (backwards compatibly) as follows:
## * avoids default value 'ep' for 'i' and 'j', which is likely to confuse
## users not familiar with lazy evaluation and which was never explained
## in ../man/sparseMatrix.Rd
## * uses a default value of 'repr' showing all allowed values,
## in conjunction with match.arg()
## * omits the default value of 'giveCsparse' to further discourage use
## * performs a few more (cheap) checks on the arguments to avoid bad errors
## * supports length-0 'i', 'j'
## * gives more appropriate errors in the missing(i) case
## * allocates less in many places
sparseMatrix <- function(i, j, p, x, dims, dimnames,
symmetric = FALSE, triangular = FALSE, index1 = TRUE,
repr = c("C", "R", "T"), giveCsparse,
check = TRUE, use.last.ij = FALSE)
{
if((m.i <- missing(i)) + (m.j <- missing(j)) + (m.p <- missing(p)) != 1L)
stop("exactly one of 'i', 'j', and 'p' must be missing from call")
if(symmetric && triangular)
stop("use Diagonal() to construct diagonal (symmetric && triangular) sparse matrices")
index1 <- as.logical(index1) # allowing {0,1}
repr <-
## NB: prior to 2020-05, we had 'giveCsparse' {T->"C" [default], F->"T"}
## but no 'repr' ... the following is to remain backwards compatible
if(missing(giveCsparse))
match.arg(repr)
else if(!missing(repr)) {
warning("'giveCsparse' is deprecated; using 'repr' instead")
match.arg(repr)
## } else {
## repr <- if(giveCsparse) "C" else "T"
## warning(gettextf("'giveCsparse' is deprecated; setting repr=\"%s\" for you", repr),
## domain = NA)
## }
} else if(giveCsparse) {
## NOT YET:
## warning("'giveCsparse' is deprecated; setting repr=\"C\" for you")
"C"
} else {
warning("'giveCsparse' is deprecated; setting repr=\"T\" for you")
"T"
}
if(!m.p) {
p <- as.integer(p)
if((n.p <- length(p)) == 0L || anyNA(p) || p[1L] != 0L ||
any((dp <- p[-1L] - p[-n.p]) < 0L))
stop("'p' must be a nondecreasing vector c(0, ...)")
if((n.dp <- length(dp)) > .Machine$integer.max)
stop("dimensions cannot exceed 2^31-1")
i. <- rep.int(seq.int(from = 0L, length.out = n.dp), dp)
if(m.i) i <- i. else j <- i.
}
if(!m.i)
i <- if(index1) as.integer(i) - 1L else as.integer(i) # need 0-index
if(!m.j)
j <- if(index1) as.integer(j) - 1L else as.integer(j) # need 0-index
rij <- cbind(if(n.i <- length(i)) range(i) else 0:-1,
if(n.j <- length(j)) range(j) else 0:-1,
deparse.level = 0L)
if(anyNA(rij))
stop("'i' and 'j' must not contain NA") # and not overflow
if(any(rij[1L, ] < 0L))
stop("'i' and 'j' must be ", if(index1) "positive" else "non-negative")
dims <-
if(!missing(dims)) {
if(length(dims) != 2L ||
any(is.na(dims) | dims < 0L | dims >= .Machine$integer.max + 1))
stop("invalid 'dims'")
if(any(dims - 1L < rij[2L, ]))
stop("'dims' must contain all (i,j) pairs")
as.integer(dims)
} else if(symmetric || triangular)
rep.int(max(rij), 2L) + 1L
else rij[2L, ] + 1L
kind <- if(m.x <- missing(x)) "n" else .M.kind(x)
shape <-
if(symmetric) {
if(dims[1L] != dims[2L])
stop("symmetric matrix must be square")
"s"
} else if(triangular) {
if(dims[1L] != dims[2L])
stop("triangular matrix must be square")
"t"
} else "g"
r <- new(paste0(kind, shape, "TMatrix"))
r@Dim <- dims
if(haveDN <- !missing(dimnames) && !is.null(dimnames))
r@Dimnames <-
if(is.character(validDN(dimnames, dims)))
dimnames
else fixupDN(dimnames) # needs a valid argument
if((symmetric || triangular) && all(i >= j))
r@uplo <- "L" # else "U", the prototype
if(!m.x) {
if(is.integer(x))
x <- as.double(x)
if((n.x <- length(x)) > 0L && n.x != n.i) {
if(n.x < n.i) {
if(n.i %% n.x != 0L)
warning(if(m.i) "p[length(p)] " else "length(i) ",
"is not an integer multiple of length(x)")
x <- rep_len(x, n.i) # recycle
} else if(n.x == 1L)
x <- x[0L] # tolerate length(i) = 0, length(x) = 1
else stop("length(x) must not exceed ",
if(m.i) "p[length(p)]" else "length(i)")
}
if(use.last.ij && n.i == n.j &&
anyDuplicated.matrix(ij <- cbind(i, j, deparse.level = 0L),
fromLast = TRUE)) {
which.not.dup <- which(!duplicated(ij, fromLast = TRUE))
i <- i[which.not.dup]
j <- j[which.not.dup]
x <- x[which.not.dup]
}
r@x <- x
}
r@i <- i
r@j <- j
if(check)
validObject(r)
switch(repr, "C" = .T2C(r), "T" = r, "R" = .T2R(r),
## should never happen:
stop("invalid 'repr'; must be \"C\", \"R\", or \"T\""))
}
}
## ~~~~ METHODS ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
### Subsetting -- basic things (drop = "missing") are done in ./Matrix.R
### FIXME : we defer to the "*gT" -- conveniently, but not efficient for gC !
## [dl]sparse -> [dl]gT -- treat both in one via superclass
## -- more useful when have "z" (complex) and even more
setMethod("[", signature(x = "sparseMatrix", i = "index", j = "missing",
drop = "logical"),
function (x, i,j, ..., drop) {
Matrix.msg("sp[i,m,l] : nargs()=",nargs(), .M.level = 2)
cld <- getClassDef(class(x))
na <- nargs()
x <- if(na == 4) as(x, "TsparseMatrix")[i, , drop=drop]
else if(na == 3) as(x, "TsparseMatrix")[i, drop=drop]
else ## should not happen
stop("Matrix-internal error in <sparseM>[i,,d]; please report")
##
## try_as(x, c(cl, sub("T","C", viaCl)))
if(is(x, "Matrix") && extends(cld, "CsparseMatrix"))
as(x, "CsparseMatrix") else x
})
setMethod("[", signature(x = "sparseMatrix", i = "missing", j = "index",
drop = "logical"),
function (x,i,j, ..., drop) {
Matrix.msg("sp[m,i,l] : nargs()=",nargs(), .M.level = 2)
cld <- getClassDef(class(x))
##> why should this be needed; can still happen in <Tsparse>[..]:
##> if(!extends(cld, "generalMatrix")) x <- as(x, "generalMatrix")
## viaCl <- paste0(.M.kind(x, cld), "gTMatrix")
x <- as(x, "TsparseMatrix")[, j, drop=drop]
##simpler than x <- callGeneric(x = as(x, "TsparseMatrix"), j=j, drop=drop)
if(is(x, "Matrix") && extends(cld, "CsparseMatrix"))
as(x, "CsparseMatrix") else x
})
setMethod("[", signature(x = "sparseMatrix",
i = "index", j = "index", drop = "logical"),
function (x, i, j, ..., drop) {
Matrix.msg("sp[i,i,l] : nargs()=",nargs(), .M.level = 2)
cld <- getClassDef(class(x))
## be smart to keep symmetric indexing of <symm.Mat.> symmetric:
##> doSym <- (extends(cld, "symmetricMatrix") &&
##> length(i) == length(j) && all(i == j))
##> why should this be needed; can still happen in <Tsparse>[..]:
##> if(!doSym && !extends(cld, "generalMatrix"))
##> x <- as(x, "generalMatrix")
## viaCl <- paste0(.M.kind(x, cld),
## if(doSym) "sTMatrix" else "gTMatrix")
x <- as(x, "TsparseMatrix")[i, j, drop=drop]
if(is(x, "Matrix") && extends(cld, "CsparseMatrix"))
as(x, "CsparseMatrix") else x
})
### "[<-" : -----------------
## setReplaceMethod("[", .........)
## -> ./Tsparse.R
## & ./Csparse.R & ./Rsparse.R {those go via Tsparse}
## x[] <- value :
setReplaceMethod("[", signature(x = "sparseMatrix", i = "missing", j = "missing",
value = "ANY"),## double/logical/...
function (x, i,j,..., value) {
if(all0(value)) { # be faster
cld <- getClassDef(class(x))
x <- diagU2N(x, cl = cld)
for(nm in intersect(nsl <- names(cld@slots),
c("x", "i","j", "factors")))
length(slot(x, nm)) <- 0L
if("p" %in% nsl)
x@p <- rep.int(0L, ncol(x)+1L)
} else { ## typically non-sense: assigning to full sparseMatrix
x[TRUE] <- value
}
x
})
## Do not use as.vector() (see ./Matrix.R ) for sparse matrices :
setReplaceMethod("[", signature(x = "sparseMatrix", i = "missing", j = "ANY",
value = "sparseMatrix"),
function (x, i, j, ..., value)
callGeneric(x=x, , j=j, value = as(value, "sparseVector")))
setReplaceMethod("[", signature(x = "sparseMatrix", i = "ANY", j = "missing",
value = "sparseMatrix"),
function (x, i, j, ..., value)
if(nargs() == 3)
callGeneric(x=x, i=i, value = as(value, "sparseVector"))
else
callGeneric(x=x, i=i, , value = as(value, "sparseVector")))
setReplaceMethod("[", signature(x = "sparseMatrix", i = "ANY", j = "ANY",
value = "sparseMatrix"),
function (x, i, j, ..., value)
callGeneric(x=x, i=i, j=j, value = as(value, "sparseVector")))
### --- print() and show() methods ---
.formatSparseSimple <- function(m, asLogical=FALSE, digits=NULL,
col.names, note.dropping.colnames = TRUE,
dn=dimnames(m))
{
stopifnot(is.logical(asLogical))
if(asLogical)
cx <- array("N", dim(m), dimnames=dn)
else { ## numeric (or --not yet implemented-- complex):
cx <- apply(m, 2, format, digits=digits)
if(is.null(dim(cx))) {# e.g. in 1 x 1 case
dim(cx) <- dim(m)
dimnames(cx) <- dn
}
}
if (missing(col.names))
col.names <- {
if(!is.null(cc <- getOption("sparse.colnames")))
cc
else if(is.null(dn[[2]]))
FALSE
else { # has column names == dn[[2]]
ncol(m) < 10
}
}
if(identical(col.names, FALSE))
cx <- emptyColnames(cx, msg.if.not.empty = note.dropping.colnames)
else if(is.character(col.names)) {
stopifnot(length(col.names) == 1)
cn <- col.names
switch(substr(cn, 1,3),
"abb" = {
iarg <- as.integer(sub("^[^0-9]*", '', cn))
colnames(cx) <- abbreviate(colnames(cx), minlength = iarg)
},
"sub" = {
iarg <- as.integer(sub("^[^0-9]*", '', cn))
colnames(cx) <- substr(colnames(cx), 1, iarg)
},
stop(gettextf("invalid 'col.names' string: %s", cn), domain=NA))
}
## else: nothing to do for col.names == TRUE
cx
}## .formatSparseSimple
### NB: Want this to work also for logical or numeric traditional matrix 'x':
formatSparseM <- function(x, zero.print = ".", align = c("fancy", "right"),
m = as(x,"matrix"), asLogical=NULL, uniDiag=NULL,
digits=NULL, cx, iN0, dn = dimnames(m))
{
cld <- getClassDef(class(x))
if(is.null(asLogical)) {
asLogical <- extends1of(cld,
c("nsparseMatrix", "indMatrix", # -> simple T / F{ binary
"lsparseMatrix")) ||
(extends(cld, "matrix") && is.logical(x))
# has NA and (non-)structural FALSE
}
if(missing(cx))
cx <- .formatSparseSimple(m, asLogical=asLogical, digits=digits, dn=dn)
if(is.null(d <- dim(cx))) {# e.g. in 1 x 1 case
d <- dim(cx) <- dim(m)
dimnames(cx) <- dn
}
if(missing(iN0))
iN0 <- 1L + .Call(m_encodeInd, non0ind(x, cld), di = d, FALSE, FALSE)
## ne <- length(iN0)
if(asLogical) {
cx[m] <- "|"
if(!extends(cld, "sparseMatrix"))
x <- as(x,"sparseMatrix")
if(anyFalse(x@x)) { ## any (x@x == FALSE)
## Careful for *non-sorted* Tsparse, e.g. from U-diag
if(extends(cld, "TsparseMatrix")) {
## have no "fast uniqTsparse():
x <- as(x, "CsparseMatrix")
cld <- getClassDef(class(x))
}
F. <- is0(x@x) # the 'FALSE' ones
### FIXME: have iN0 already above -- *really* need the following ??? --FIXME--
ij <- non0.i(x, cld, uniqT=FALSE)
if(extends(cld, "symmetricMatrix")) {
## also get "other" triangle
notdiag <- ij[,1] != ij[,2] # but not the diagonals again
ij <- rbind(ij, ij[notdiag, 2:1], deparse.level=0)
F. <- c(F., F.[notdiag])
}
iN0 <- 1L + .Call(m_encodeInd, ij, di = d, FALSE, FALSE)
cx[iN0[F.]] <- ":" # non-structural FALSE (or "o", "," , "-" or "f")?
}
}
else if(match.arg(align) == "fancy" && !is.integer(m)) {
fi <- apply(m, 2, format.info) ## fi[3,] == 0 <==> not expo.
## now 'format' the zero.print by padding it with ' ' on the right:
## case 1: non-exponent: fi[2,] + as.logical(fi[2,] > 0)
## the column numbers of all 'zero' entries -- (*large*)
cols <- 1L + (0:(prod(d)-1L))[-iN0] %/% d[1]
pad <-
ifelse(fi[3,] == 0,
fi[2,] + as.logical(fi[2,] > 0),
## exponential:
fi[2,] + fi[3,] + 4)
## now be efficient ; sprintf() is relatively slow
## and pad is much smaller than 'cols'; instead of "simply"
## zero.print <- sprintf("%-*s", pad[cols] + 1, zero.print)
if(any(doP <- pad > 0)) { #
## only pad those that need padding - *before* expanding
z.p.pad <- rep.int(zero.print, length(pad))
z.p.pad[doP] <- sprintf("%-*s", pad[doP] + 1, zero.print)
zero.print <- z.p.pad[cols]
}
else
zero.print <- rep.int(zero.print, length(cols))
} ## else "right" : nothing to do
if(!asLogical && isTRUE(uniDiag)) { ## use "I" in diagonal -- pad correctly
if(any(diag(x) != 1))
stop("uniDiag=TRUE, but not all diagonal entries are 1")
D <- diag(cx) # use
if(any((ir <- regexpr("1", D)) < 0)) {
warning("uniDiag=TRUE, not all entries in diagonal coded as 1")
} else {
ir <- as.vector(ir)
nD <- nchar(D, "bytes")
## replace "1..." by "I " (I plus blanks)
substr(D, ir, nD) <- sprintf("I%*s", nD - ir, "")
diag(cx) <- D
}
}
cx[-iN0] <- zero.print
cx
}## formatSparseM()
##' The `format()` method for sparse Matrices; also used inside sparseMatrix print()ing,
##' exported as it might be useful directly.
formatSpMatrix <- function(x, digits = NULL, # getOption("digits"),
maxp = 1e9, # ~ 1/2 * .Machine$integer.max, ## getOption("max.print"),
cld = getClassDef(class(x)), zero.print = ".",
col.names, note.dropping.colnames = TRUE, uniDiag = TRUE,
align = c("fancy", "right"))
{
stopifnot(extends(cld, "sparseMatrix"))
validObject(x) # have seen seg.faults for invalid objects
d <- dim(x)
unitD <- extends(cld, "triangularMatrix") && x@diag == "U"
## Will note it is *unit*-diagonal by using "I" instead of "1"
if(unitD)
x <- .Call(R_sparse_diag_U2N, x)
if(maxp < 100) maxp <- 100L # "stop gap"
if(prod(d) > maxp) { # "Large" => will be "cut"
## only coerce to dense that part which won't be cut :
nr <- maxp %/% d[2]
m <- as(x[1:max(1, nr), ,drop=FALSE], "matrix")
} else {
m <- as(x, "matrix")
}
dn <- dimnames(m) ## will be === dimnames(cx)
binary <- extends(cld,"nsparseMatrix") || extends(cld, "indMatrix") # -> simple T / F
logi <- binary || extends(cld,"lsparseMatrix") # has NA and (non-)structural FALSE
cx <- .formatSparseSimple(m, asLogical = logi, digits=digits,
col.names=col.names,
note.dropping.colnames=note.dropping.colnames, dn=dn)
if(is.logical(zero.print))
zero.print <- if(zero.print) "0" else " "
if(binary) {
cx[!m] <- zero.print
cx[m] <- "|"
} else { # non-binary ==> has 'x' slot
## show only "structural" zeros as 'zero.print', not all of them..
## -> cannot use 'm' alone
d <- dim(cx)
ne <- length(iN0 <- 1L + .Call(m_encodeInd, non0ind(x, cld),
di = d, FALSE, FALSE))
if(0 < ne && (logi || ne < prod(d))) {
cx <- formatSparseM(x, zero.print, align, m=m,
asLogical = logi, uniDiag = unitD & uniDiag,
digits=digits, cx=cx, iN0=iN0, dn=dn)
} else if (ne == 0)# all zeroes
cx[] <- zero.print
}
cx
}## formatSpMatrix()
## FIXME(?) -- ``merge this'' (at least ``synchronize'') with
## - - - prMatrix() from ./Auxiliaries.R
## FIXME: prTriang() in ./Auxiliaries.R should also get align = "fancy"
##
printSpMatrix <- function(x, digits = NULL, # getOption("digits"),
maxp = max(100L, getOption("max.print")),
cld = getClassDef(class(x)), zero.print = ".",
col.names, note.dropping.colnames = TRUE, uniDiag = TRUE,
col.trailer = '', align = c("fancy", "right"))
{
stopifnot(extends(cld, "sparseMatrix"))
cx <- formatSpMatrix(x, digits=digits, maxp=maxp, cld=cld,
zero.print=zero.print, col.names=col.names,
note.dropping.colnames=note.dropping.colnames,
uniDiag=uniDiag, align=align)
if(col.trailer != '')
cx <- cbind(cx, col.trailer, deparse.level = 0)
## right = TRUE : cheap attempt to get better "." alignment
print(cx, quote = FALSE, right = TRUE, max = maxp)
invisible(x)
} ## printSpMatrix()
##' The "real" show() / print() method, calling the above printSpMatrix():
printSpMatrix2 <- function(x, digits = NULL, # getOption("digits"),
maxp = max(100L, getOption("max.print")), zero.print = ".",
col.names, note.dropping.colnames = TRUE, uniDiag = TRUE,
suppRows = NULL, suppCols = NULL,
col.trailer = if(suppCols) "......" else "",
align = c("fancy", "right"),
width = getOption("width"), fitWidth = TRUE)
{
d <- dim(x)
cl <- class(x)
cld <- getClassDef(cl)
xtra <- if(extends(cld, "triangularMatrix") && x@diag == "U")
" (unitriangular)" else ""
cat(sprintf('%d x %d sparse Matrix of class "%s"%s\n',
d[1], d[2], cl, xtra))
setW <- !missing(width) && width > getOption("width")
if(setW) {
op <- options(width = width) ; on.exit( options(op) ) }
if((isFALSE(suppRows) && isFALSE(suppCols)) ||
(!isTRUE(suppRows) && !isTRUE(suppCols) && prod(d) <= maxp))
{ ## "small matrix" and supp* not TRUE : no rows or columns are suppressed
if(missing(col.trailer) && is.null(suppCols))
suppCols <- FALSE # for default 'col.trailer'
printSpMatrix(x, cld=cld, digits=digits, maxp=maxp,
zero.print=zero.print, col.names=col.names,
note.dropping.colnames=note.dropping.colnames, uniDiag=uniDiag,
col.trailer=col.trailer, align=align)
}
else { ## d[1] > maxp / d[2] >= nr : -- this needs [,] working:
validObject(x)
sTxt <- c(" ", gettext(
"in show(); maybe adjust 'options(max.print= *, width = *)'"),
"\n ..............................\n")
useW <- width - (format.info(d[1], digits=digits)[1] + 3+1)
## == width - space for the largest row label : "[<last>,] "
## Suppress rows and/or columns in printing ...
## ---------------------------------------- but which exactly depends on format
## Determining number of columns - first assuming all zeros : ". . "..: 2 chars/column
## i.e., we get the *maximal* numbers of columns to keep, nc :
if(is.null(suppCols)) # i.e., "it depends" ..
suppCols <- (d[2] * 2 > useW) # used in 'col.trailer' default
nCc <- 1 + nchar(col.trailer, "width")
if(suppCols) {
nc <- (useW - nCc) %/% 2
x <- x[ , 1:nc, drop = FALSE]
} else
nc <- d[2]
nr <- maxp %/% nc # if nc becomes smaller, nr will become larger (!)
if(is.null(suppRows)) suppRows <- (nr < d[1])
if(suppRows) {
n2 <- ceiling(nr / 2)
nr1 <- min(d[1], max(1L, n2)) #{rows} in 1st part
nr2 <- max(1L, nr-n2) #{rows} in 2nd part
nr <- nr1+nr2 # total #{rows} to be printed
if(fitWidth) {
## one iteration of improving the width, by "fake printing" :
cM <- formatSpMatrix(x[seq_len(nr1), , drop = FALSE],
digits=digits, maxp=maxp, zero.print=zero.print,
col.names=col.names, align=align,
note.dropping.colnames=note.dropping.colnames, uniDiag=FALSE)
## width needed (without the 'col.trailer's 'nCc'):
matW <- nchar(capture.output(print(cM, quote=FALSE, right=FALSE))[[1]])
needW <- matW + (if(suppCols) nCc else 0)
if(needW > useW) { ## need more width
op <- options(width = width+(needW-useW))
if(!setW) on.exit( options(op) )
}
}
printSpMatrix(x[seq_len(nr1), , drop=FALSE],
digits=digits, maxp=maxp,
zero.print=zero.print, col.names=col.names,
note.dropping.colnames=note.dropping.colnames, uniDiag=uniDiag,
col.trailer = col.trailer, align=align)
suppTxt <- if(suppCols)
gettextf("suppressing %d columns and %d rows", d[2]-nc , d[1]-nr)
else gettextf("suppressing %d rows", d[1]-nr)
cat("\n ..............................",
"\n ........", suppTxt, sTxt, sep='')
## tail() automagically uses "[..,]" rownames:
printSpMatrix(tail(x, nr2),
digits=digits, maxp=maxp,
zero.print=zero.print, col.names=col.names,
note.dropping.colnames=note.dropping.colnames, uniDiag=FALSE,
col.trailer = col.trailer, align=align)
}
else if(suppCols) {
printSpMatrix(x[ , 1:nc , drop = FALSE],
digits=digits, maxp=maxp,
zero.print=zero.print, col.names=col.names,
note.dropping.colnames=note.dropping.colnames, uniDiag=uniDiag,
col.trailer = col.trailer, align=align)
cat("\n .....", gettextf("suppressing %d columns", d[2]-nc), sTxt, sep='')
}
else stop("logic programming error in printSpMatrix2(), please report")
invisible(x)
}
} ## printSpMatrix2 ()
setMethod("format", signature(x = "sparseMatrix"), formatSpMatrix)
setMethod("print", signature(x = "sparseMatrix"), printSpMatrix2)
setMethod("show", signature(object = "sparseMatrix"),
function(object) printSpMatrix2(object))
## For very large and very sparse matrices, the above show()
## is not really helpful; Use summary() showing "triplet" as an alternative:
mat2triplet <- function(x, uniqT = FALSE) {
T <- as(x, "TsparseMatrix")
if(uniqT && anyDuplicatedT(T)) T <- .uniqTsparse(T)
if(is(T, "nsparseMatrix"))
list(i = T@i + 1L, j = T@j + 1L)
else list(i = T@i + 1L, j = T@j + 1L, x = T@x)
}
setMethod("summary", signature(object = "sparseMatrix"),
function(object, uniqT = FALSE, ...) {
d <- dim(object)
## return a data frame (int, int, {double|logical|...}) :
r <- as.data.frame(mat2triplet(object, uniqT=uniqT))
attr(r, "header") <-
sprintf('%d x %d sparse Matrix of class "%s", with %d entries',
d[1], d[2], class(object), nrow(r))
## use ole' S3 technology for such a simple case
class(r) <- c("sparseSummary", class(r))
r
})
print.sparseSummary <- function (x, ...) {
cat(attr(x, "header"),"\n")
print.data.frame(x, ...)
invisible(x)
}
## MJ: no longer needed ... replacement below
if(FALSE) {
## Fallback, used for RsparseMatrix and others, but not [CT]sparseMatrix,
## which have their own methods
setMethod("isDiagonal", signature(object = "sparseMatrix"),
function(object) {
d <- object@Dim
d[1L] == d[2L] && callGeneric(as(object, "TsparseMatrix"))
})
## Fallback, used for RsparseMatrix and others, but not [CT]sparseMatrix,
## triangularMatrix, or symmetricMatrix which have their own methods
setMethod("isTriangular", signature(object = "sparseMatrix"),
function(object, upper = NA, ...) {
d <- object@Dim
if(d[1L] == d[2L])
callGeneric(as(object, "TsparseMatrix"), upper = upper, ...)
else FALSE
})
setMethod("diag", signature(x = "sparseMatrix"),
function(x, nrow, ncol, names)
diag(as(x, "CsparseMatrix"), names = names))
} ## MJ
setMethod("dim<-", signature(x = "sparseMatrix"),
function(x, value) {
if(!is.numeric(value) || length(value) != 2L)
stop("dimensions must be numeric of length 2")
if(anyNA(value))
stop("dimensions cannot contain NA")
if(any(value < 0))
stop("dimensions cannot contain negative values")
if(!is.integer(value)) {
if(any(value > .Machine$integer.max))
stop("dimensions cannot exceed 2^31-1")
value <- as.integer(value)
}
if(all(value == (d <- x@Dim)))
return(x)
if((pv <- prod(value)) != (pd <- prod(d)))
stop(gettextf("assigned dimensions [product %.0f] do not match object length [%.0f]",
pv, pd, domain = NA))
r <- spV2M(as(x, "sparseVector"),
nrow = value[1L], ncol = value[2L])
## 'r' is a TsparseMatrix
if(extends(cd <- getClassDef(class(x)) , "CsparseMatrix"))
as(r, "CsparseMatrix")
else if(extends(cd, "RsparseMatrix"))
as(r, "RsparseMatrix")
else r
})
setMethod("rep", "sparseMatrix",
function(x, ...) rep(as(x, "sparseVector"), ...))
setMethod("cov2cor", signature(V = "sparseMatrix"),
function(V) {