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Matrix <- function(data = NA, nrow = 1, ncol = 1, byrow = FALSE,
dimnames = NULL, sparse = NULL,
doDiag = TRUE, forceCheck = FALSE)
{
i.M <- i.sM <- i.dM <- i.sV <- i.m <- FALSE
mnrow <- missing(nrow)
mncol <- missing(ncol)
if(isS4(data)) {
cld <- getClassDef(class(data))
i.M <- extends(cld, "Matrix")
if(i.M) {
i.sM <- extends(cld, "sparseMatrix")
i.dM <- i.sM && extends(cld, "diagonalMatrix")
} else if(extends(cld, "sparseVector")) {
## need to transmit missingness to 'spV2M'
call. <- quote(spV2M(x = data, nrow =, ncol =, byrow = byrow))
if(!mnrow)
call.[[3L]] <- quote(nrow)
if(!mncol)
call.[[4L]] <- quote(ncol)
data <- eval(call.)
i.M <- i.sM <- i.sV <- forceCheck <- TRUE
}
} else {
i.m <- is.matrix(data)
}
if(!i.M) {
## validate non-Matrix 'data', throwing type errors _early_
if(is.object(data)) {
if(i.m)
class(data) <- NULL # retaining 'dim'
else
data <- as.vector(data)
}
mode. <- mode(data)
kind <- switch(mode., numeric = "d", logical = "l",
stop("invalid 'data'"))
}
if(i.M || i.m) {
## 'data' is a Matrix or a numeric or logical matrix
## without a 'class' attribute
if(!i.sV && !(mnrow && mncol && missing(byrow)))
warning("'nrow', 'ncol', 'byrow' disregarded for [mM]atrix 'data'")
if(!is.null(dimnames))
dimnames(data) <- dimnames
if(is.null(sparse))
sparse <- sparseDefault(data)
if(i.M) {
## return early in these cases:
if(i.dM)
## !doDiag has been documented to result in a coercion to
## symmetricMatrix; we must use diag2*() below because the
## "usual" as(<diagonalMatrix>, "(Csparse|unpacked)Matrix")
## inherits from triangularMatrix, _not_ symmetricMatrix
return(if(doDiag)
data
else if(sparse)
.diag2sparse(data, ".", "s", "C", "U")
else .diag2dense(data, ".", "s", FALSE, "U"))
if(!forceCheck)
return(if(i.sM == sparse)
data
else if(sparse)
as(data, "CsparseMatrix")
else as(data, "unpackedMatrix"))
}
} else {
## 'data' is a numeric or logical vector or non-matrix array
## without a 'class' attribute
if(length(data) == 1L && !is.na(data) && data == 0 &&
(is.null(sparse) || sparse)) {
## Matrix(0, ...): sparseMatrix unless sparse=FALSE
## MJ: we should _try_ to behave as R's do_matrix()
## in the edge cases ... integer overflow is "OK"
## since anyNA(Dim) is caught by validity methods
if(mnrow == mncol) {
nrow <- as.integer(nrow)
ncol <- as.integer(ncol)
} else if(mnrow) {
ncol <- as.integer(ncol)
if(ncol == 0L)
stop("data is too long")
nrow <- as.integer(ceiling(1 / ncol))
} else {
nrow <- as.integer(nrow)
if(nrow == 0L)
stop("data is too long")
ncol <- as.integer(ceiling(1 / nrow))
}
square <- nrow == ncol
if(is.null(dimnames))
dimnames <- list(NULL, NULL)
if(square && doDiag)
return(new(paste0(kind, "diMatrix"),
Dim = c(nrow, ncol),
Dimnames = dimnames,
x = vector(mode., nrow)))
data <- new(paste0(kind, if(square) "s" else "g", "CMatrix"),
Dim = c(nrow, ncol),
Dimnames = dimnames,
p = integer(ncol + 1))
i.M <- i.sM <- sparse <- TRUE
} else {
## usual case: vector|array->matrix
data <- .External(Mmatrix,
data, nrow, ncol, byrow, dimnames, mnrow, mncol)
if(is.null(sparse))
sparse <- sparseDefault(data)
i.m <- TRUE
}
}
## 'data' is a Matrix (but _not_ a diagonalMatrix) or a
## numeric or logical matrix without a 'class' attribute
if(doDiag && isDiagonal(data))
## as(<[mM]atrix>, "diagonalMatrix") uses check = TRUE (a waste)
return(forceDiagonal(data))
if(i.m || i.sM != sparse) {
data <- as(data, if(sparse) "CsparseMatrix" else "unpackedMatrix")
if(i.m)
## as(<matrix>, "CsparseMatrix"), as(<matrix>, "unpackedMatrix")
## already check for symmetric, triangular structure
return(data)
}
if(!is(data, "generalMatrix"))
data
else if(isSymmetric(data))
forceSymmetric(data)
else if(!(it <- isTriangular(data)))
data
else if(attr(it, "kind") == "U")
triu(data)
else tril(data)
}
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 <- # keep in sync with toeplitz(<sparseVector>)
## 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 if(is.integer(x)) "d" 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(!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" = .M2C(r), "T" = r, "R" = .M2R(r),
## should never happen:
stop("invalid 'repr'; must be \"C\", \"R\", or \"T\""))
}
spMatrix <- function(nrow, ncol,
i = integer(0L), j = integer(0L), x = double(0L))
new(paste0(if(is.integer(x)) "d" else .M.kind(x), "gTMatrix"),
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)
Diagonal <- function(n, x = NULL, names = FALSE)
{
nx <- length(x)
if(missing(n))
n <- nx
else if(!is.numeric(n) || length(n) != 1L || is.na(n) || n < 0L)
stop("'n' must be a non-negative integer")
if(is.double(n) && n >= .Machine$integer.max + 1)
stop("dimensions cannot exceed 2^31-1")
n <- as.integer(n) # discarding attributes
if(is.null(x)) {
r <- new("ddiMatrix")
r@diag <- "U"
if(n > 0L) {
r@Dim <- c(n, n)
if(is.character(names) && length(names) == n)
r@Dimnames <- list(names, names)
}
return(r)
}
if(is.object(x))
stop(gettextf("'x' has unsupported class \"%s\"", class(x)[1L]),
domain = NA)
names.x <- names(x) # keeping for later
r <- new(switch(typeof(x),
## discarding attributes, incl. 'dim' and 'names'
logical = { x <- as.logical(x); "ldiMatrix" },
integer =,
double = { x <- as.double(x); "ddiMatrix" },
stop(gettextf("'x' has unsupported type \"%s\"", typeof(x)),
domain = NA)))
if(n == 0L)
return(r)
if(nx != 1L)
r@x <-
if(nx == n)
x
else if(nx > 0L)
rep_len(x, n)
else stop("attempt to recycle 'x' of length 0 to length 'n' (n > 0)")
else if(is.na(x) || x != 1)
r@x <- rep.int(x, n)
else r@diag <- "U"
r@Dim <- c(n, n)
if(is.character(names)) {
if(length(names) == n)
r@Dimnames <- list(names, names)
} else if(isTRUE(names) && !is.null(names.x)) {
names.x <- rep_len(names.x, n) # we know length(names.x) > 0L
r@Dimnames <- list(names.x, names.x)
}
r
}
.sparseDiagonal <- function(n, x = NULL, uplo = "U", shape = "t",
unitri = TRUE, kind, cols)
{
if(missing(n))
n <- length(x)
else if(!is.numeric(n) || length(n) != 1L || is.na(n) || n < 0L)
stop("'n' must be a non-negative integer")
if(is.double(n) && n >= .Machine$integer.max + 1)
stop("dimensions cannot exceed 2^31-1")
n <- nj <- as.integer(n) # stripping attributes
if(!(missing(shape) ||
(is.character(shape) && length(shape) == 1L && !is.na(shape) &&
any(shape == c("g", "t", "s")))))
stop("'shape' must be one of \"g\", \"t\", \"s\"")
if(!((m.kind <- missing(kind)) ||
(is.character(kind) && length(kind) == 1L && !is.na(kind) &&
any(kind == c("d", "l", "n")))))
stop("'kind' must be one of \"d\", \"l\", \"n\"")
if(m.kind || kind != "n") {
if(is.null(x))
x <- if(m.kind) { kind <- "d"; 1 } else switch(kind, d = 1, l = TRUE)
else if(is.object(x))
stop(gettextf("'x' has unsupported class \"%s\"",
class(x)[1L]),
domain = NA)
else {
kind. <- switch(typeof(x),
## discarding attributes, incl. 'dim' in array case
logical = { x <- as.logical(x); "l" },
integer =,
double = { x <- as.double(x); "d" },
stop(gettextf("'x' has unsupported type \"%s\"",
typeof(x)),
domain = NA))
if(m.kind)
kind <- kind.
else if(kind != kind.) {
warning(gettextf("mismatch between typeof(x)=\"%s\" and kind=\"%s\"; using kind=\"%s\"",
typeof(x), kind, kind.),
domain = NA)
kind <- kind.
}
}
}
if(!(m.cols <- missing(cols))) {
if(!is.numeric(cols))
stop("'cols' must be numeric")
else if((nj <- length(cols)) > 0L &&
(n == 0L || anyNA(rj <- range(cols)) ||
rj[1L] < 0L || rj[2L] >= n))
stop("'cols' has elements not in seq(0, length.out = n)")
else {
cols <- as.integer(cols)
shape <- "g"
}
}
r <- new(paste0(kind, shape, "CMatrix"))
r@Dim <- c(n, nj)
if(shape != "g") {
if(!missing(uplo)) {
if(is.character(uplo) && length(uplo) == 1L && !is.na(uplo) &&
any(uplo == c("U", "L")))
r@uplo <- uplo
else stop("'uplo' must be \"U\" or \"L\"")
}
if(shape == "t" && unitri &&
(kind == "n" || (!anyNA(x) && all(if(kind == "l") x else x == 1)))) {
r@diag <- "U"
r@p <- integer(nj + 1)
return(r)
}
}
if(nj > 0L) {
r@p <- 0:nj
r@i <- if(m.cols) 0:(nj - 1L) else cols
if(kind != "n") {
x <-
if((nx <- length(x)) == n)
x
else if(nx > 0L)
rep_len(x, n)
else stop("attempt to recycle 'x' of length 0 to length 'n' (n > 0)")
r@x <- if(m.cols) x else x[1L + cols]
}
}
r
}
.trDiagonal <- function(n, x = NULL, uplo = "U", unitri = TRUE, kind)
.sparseDiagonal(n, x, uplo, shape = "t", unitri = unitri, kind = kind)
.symDiagonal <- function(n, x = NULL, uplo = "U", kind)
.sparseDiagonal(n, x, uplo, shape = "s", kind = kind)
.bdiag <- function(lst)
{
if(!is.list(lst))
stop("'lst' must be a list")
if((n <- length(lst)) == 0L)
return(new("dgTMatrix"))
if(n == 1L)
return(.M2T(asCspN(lst[[1L]])))
### FIXME? this is _slow_ when 'lst' is list of 75000 3-by-3 dense matrices
lst <- unname(lapply(lst, function(x) .M2T(asCspN(x))))
cl <- vapply(lst, class, "")
kind <- substr(cl, 1L, 1L) # "n", "l", or "d"
shape <- substr(cl, 2L, 2L) # "g", "s", or "t"
if(!(any(kind == (kind. <- "d")) || any(kind == (kind. <- "l"))))
kind. <- "n"
else if(any(z <- kind == "n"))
lst[z] <- lapply(lst[z], .sparse2kind, kind.)
shape. <-
if(all(symmetric <- shape == "s"))
"s"
else if(all(shape == "t"))
"t"
else "g"
if(shape. != "g") {
uplo <- vapply(lst, slot, "", "uplo") # "U" or "L"
if(shape. == "s")
uplo. <-
if(all(z <- uplo == "U"))
"U"
else if(!any(z))
"L"
else {
uplo.. <- if(2 * sum(z) >= n) { z <- !z; "U" } else "L"
lst[z] <- lapply(lst[z], .tCRT)
uplo..
}
else if(any(uplo != (uplo. <- uplo[1L])))
shape. <- "g"
}
i_off <- c(0L, cumsum(vapply(lst, function(x) x@Dim[1L], 0L)))
j_off <- c(0L, cumsum(vapply(lst, function(x) x@Dim[2L], 0L)))
r <- new(paste0(kind., shape., "TMatrix"))
r@Dim <- r@Dim <- c(i_off[n + 1L], j_off[n + 1L])
if(shape. == "g")
lst[symmetric] <- lapply(lst[symmetric], .sparse2g)
else r@uplo <- uplo.
r@i <- unlist(lapply(seq_len(n), function(k) i_off[k] + lst[[k]]@i),
FALSE, FALSE)
r@j <- unlist(lapply(seq_len(n), function(k) j_off[k] + lst[[k]]@j),
FALSE, FALSE)
if(kind. != "n")
r@x <- unlist(lapply(lst, slot, "x"), FALSE, FALSE)
r
}
bdiag <- function(...)
{
if((n <- ...length()) == 0L)
new("dgCMatrix")
else if(n > 1L)
.M2C(.bdiag(list(...)))
else if(!is.list(x <- ..1))
as(x, "CsparseMatrix")
else if(length(x) == 1L)
as(x[[1L]], "CsparseMatrix")
else .M2C(.bdiag(x))
}
bandSparse <- function(n, m = n, k, diagonals,
symmetric = FALSE,
repr = "C", giveCsparse = (repr == "C"))
{
## Purpose: Compute a band-matrix by speciyfying its (sub-)diagonal(s)
## ----------------------------------------------------------------------
## Arguments: (n,m) : Matrix dimension
## k : integer vector of "diagonal numbers", with identical
## meaning as in band(*, k)
## diagonals: (optional!) list of (sub/super)diagonals
## symmetric: if TRUE, specify only upper or lower triangle;
## ----------------------------------------------------------------------
## Author: Martin Maechler, Date: 20 Feb 2009, 22:42
if(use.x <- !missing(diagonals)) # when specified, must be matrix or list
diag.isMat <- is.matrix(diagonals)
len.k <- length(k)
stopifnot(!use.x || is.list(diagonals) || diag.isMat,
k == as.integer(k), n == as.integer(n), m == as.integer(m))
k <- as.integer(k)
n <- as.integer(n)
m <- as.integer(m)
stopifnot(n >= 0, m >= 0, -n+1 <= (mik <- min(k)), (mak <- max(k)) <= m - 1)
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")
if(use.x) {
if(diag.isMat) {
if(ncol(diagonals) != len.k)
stop(gettextf("'diagonals' matrix must have %d columns (= length(k) )",
len.k), domain=NA)
getD <- function(j) diagonals[,j]
} else { ## is.list(diagonals):
if(length(diagonals) != len.k)
stop(gettextf("'diagonals' must have the same length (%d) as 'k'",
len.k), domain=NA)
getD <- function(j) diagonals[[j]]
}
}
sqr <- n == m
if(symmetric) {
if(!sqr) stop("matrix can only be symmetric if square, but n != m")
if(mik < 0 && mak > 0)
stop("for symmetric band matrix, only specify upper or lower triangle\n hence, all k must have the same sign")
} else
tri <- sqr && sign(mik)*sign(mak) >= 0 # triangular result
dims <- c(n,m)
k.lengths <- ## This is a bit "ugly"; I got the cases "by inspection"
if(n >= m) {
ifelse(k >= m-n, m - pmax(0,k), n+k)
} else { ## n < m (?? k >= -n+1 always !!)
ifelse(k >= -n+1, n + pmin(0,k), m-k)
}
i <- j <- integer(sum(k.lengths))
if(use.x)
x <- if(len.k > 0) # carefully getting correct type/mode
rep.int(getD(1)[1], length(i))
off.i <- 0L
for(s in seq_len(len.k)) {
kk <- k[s] ## *is* integer
l.kk <- k.lengths[s] ## == length of (sub-)diagonal kk
ii1 <- seq_len(l.kk)
ind <- ii1 + off.i
if(kk >= 0) {
i[ind] <- ii1
j[ind] <- ii1 + kk
} else { ## k < 0
i[ind] <- ii1 - kk
j[ind] <- ii1
}
if(use.x) {
xx <- getD(s)
if(length(xx) < l.kk)
warning(gettextf("the %d-th (sub)-diagonal (k = %d) is too short; filling with NA's",
s, kk), domain=NA)
x[ind] <- xx[ii1]
}
off.i <- off.i + l.kk
}
if(symmetric) { ## we should have smarter sparseMatrix()
UpLo <- if(min(k) >= 0) "U" else "L"
T <-
if(use.x) {
if(is.integer(x))
x <- as.double(x)
cc <- paste0(.M.kind(x), "sTMatrix")
new(cc, i= i-1L, j= j-1L, x = x, Dim= dims, uplo=UpLo)
} else new("nsTMatrix", i= i-1L, j= j-1L, Dim= dims, uplo=UpLo)
switch(repr, "C" = .M2C(T), "T" = T, "R" = .M2R(T),
stop("invalid 'repr'; must be \"C\", \"T\", or \"R\""))
}
else { ## not symmetric, possibly triangular
if(use.x)
sparseMatrix(i=i, j=j, x=x, dims=dims, triangular=tri, repr=repr)
else
sparseMatrix(i=i, j=j, dims=dims, triangular=tri, repr=repr)
}
}
rsparsematrix <- function(nrow, ncol, density,
nnz = round(density * maxE),
symmetric = FALSE,
rand.x = function(n) signif(rnorm(n), 2L), ...)
{
maxE <- if(symmetric) nrow*(nrow+1)/2 else nrow*ncol
stopifnot((nnz <- as.integer(nnz)) >= 0,
nrow >= 0, ncol >= 0, nnz <= maxE)
## sampling with*out* replacement (replace=FALSE !):
ijI <- -1L +
if(symmetric) sample(indTri(nrow, diag=TRUE), nnz)
else sample.int(maxE, nnz)
## i,j below correspond to ij <- decodeInd(code, nr) :
if(is.null(rand.x))
sparseMatrix(i = ijI %% nrow,
j = ijI %/% nrow,
index1 = FALSE,
symmetric = symmetric,
dims = c(nrow, ncol), ...)
else
sparseMatrix(i = ijI %% nrow,
j = ijI %/% nrow,
x = rand.x(nnz),
index1 = FALSE,
symmetric = symmetric,
dims = c(nrow, ncol), ...)
}
Hilbert <- function(n)
{
n <- as.integer(n)
i <- seq_len(n)
new("dpoMatrix", Dim = c(n, n), x = c(1/outer(i - 1L, i, `+`)))
}
spV2M <- function(x, nrow, ncol, byrow = FALSE,
check = TRUE, symmetric = FALSE)
{
if(check && !is(x, "sparseVector"))
stop("'x' must inherit from \"sparseVector\"")
if(!missing(ncol)) { ncol <- as.integer(ncol)
if(ncol < 0) stop("'ncol' must be >= 0") }
if(!missing(nrow)) { nrow <- as.integer(nrow)
if(nrow < 0) stop("'nrow' must be >= 0") }
n <- length(x)
if(symmetric) {
if(missing(nrow)) stop("Must specify 'nrow' when 'symmetric' is true")
if(!missing(ncol) && nrow != ncol)
stop("'nrow' and 'ncol' must be the same when 'symmetric' is true")
## otherwise ncol will not used at all when (symmetric)
if(check && as.double(nrow)^2 != n)
stop("'x' must have length nrow^2 when 'symmetric' is true")
## x <- x[indTri(nrow, upper=TRUE, diag=TRUE)]
} else if(missing(nrow)) {
nrow <- as.integer(
if(missing(ncol)) { ## both missing: --> (n x 1)
ncol <- 1L
n
} else {
if(n %% ncol != 0) warning("'ncol' is not a factor of length(x)")
as.integer(ceiling(n / ncol))
})
} else if(missing(ncol)) {
ncol <- if(symmetric) nrow else {
if(n %% nrow != 0) warning("'nrow' is not a factor of length(x)")
as.integer(ceiling(n / nrow)) }
} else { ## both nrow and ncol specified
n.n <- as.double(ncol) * nrow # no integer overflow
if(n.n < n) stop("nrow * ncol < length(x)", domain = NA)
if(n.n != n) warning("nrow * ncol != length(x)", domain = NA)
}
## now nrow * ncol >= n (or 'symmetric')
## ~~~~~~~~~~~~~~~~
kind <- .M.kind(x) # "d", "n", "l", "i", "z", ...
has.x <- kind != "n"
clStem <- if(symmetric) "sTMatrix" else "gTMatrix"
## "careful_new()" :
cNam <- paste0(kind, clStem)
chngCl <- is.null(newCl <- getClassDef(cNam))
if(chngCl) { ## e.g. "igTMatrix" is not yet implemented
if(kind == "z")
stop(gettextf("Class %s is not yet implemented", dQuote(cNam)),
domain = NA)
## coerce to "double":
newCl <- getClassDef(paste0("d", clStem))
}
r <- new(newCl, Dim = c(nrow, ncol))
## now "compute" the (i,j,x) slots given x@(i,x)
i0 <- x@i - 1L
if(byrow) { ## need as.integer(.) since <sparseVector> @ i can be double
j <- as.integer(i0 %% ncol)
i <- as.integer(i0 %/% ncol)
} else { ## default{byrow = FALSE}
i <- as.integer(i0 %% nrow)
j <- as.integer(i0 %/% nrow)
}
if(has.x)
x <- if(chngCl) as.numeric(x@x) else x@x
if(symmetric) { ## using uplo = "U"
i0 <- i <= j ## i.e., indTri(nrow, upper=TRUE, diag=TRUE)
i <- i[i0]
j <- j[i0]
if(has.x) x <- x[i0]
}
r@j <- j
r@i <- i
if(has.x) r@x <- x
r
}
.sparseV2Mat <- function(from)
spV2M(from, nrow = from@length, ncol = 1L, check = FALSE)
sp2vec <- function(x, mode = .type.kind[.M.kind(x)])
{
## sparseVector -> vector
has.x <- .hasSlot(x, "x")## has "x" slot
m.any <- (mode == "any")
if(m.any)
mode <- if(has.x) mode(x@x) else "logical"
else if(has.x) # is.<mode>() is much faster than inherits() | is():
xxOk <- switch(mode,
"double" = is.double(x@x),
"logical" = is.logical(x@x),
"integer" = is.integer(x@x),
"complex" = is.complex(x@x),
## otherwise (does not happen with default 'mode'):
inherits(x@x, mode))
r <- vector(mode, x@length)
r[x@i] <-
if(has.x) {
if(m.any || xxOk) x@x else as(x@x, mode)
} else TRUE
r
}
newSpV <- function(class, x, i, length, drop0 = TRUE, checkSort = TRUE)
{
if(has.x <- !missing(x)) {
if(length(x) == 1 && (li <- length(i)) != 1) ## recycle x :
x <- rep.int(x, li)
if(drop0 && isTRUE(any(x0 <- x == 0))) {
keep <- is.na(x) | !x0
x <- x[keep]
i <- i[keep]
}
}
if(checkSort && is.unsorted(i)) {
ii <- sort.list(i)
if(has.x) x <- x[ii]
i <- i[ii]
}
if(has.x)
new(class, x = x, i = i, length = length)
else
new(class, i = i, length = length)
}
newSpVec <- function(class, x, prev)
newSpV(class = class, x = x, i = prev@i, length = prev@length)
sparseVector <- function(x, i, length)
newSpV(class = paste0(if(missing(x)) "n" else .M.kind(x), "sparseVector"),
x = x, i = i, length = length)
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