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rbind.zoo <- function(..., deparse.level = 1)
{
args <- Filter(Negate(is.null), list(...))
indexes <- do.call("c", unname(lapply(args, index)))
my.table <- function(x) {
ix <- ORDER(x)
x <- x[ix]
table(MATCH(x,x))
}
if(max(my.table(indexes)) > 1L) stop("indexes overlap")
if(any(sapply(args, function(x) is.null(dim(x)) && length(x) == 0L && length(index(x)) > 0L)))
stop("zero-length vectors with non-zero-length index are not allowed")
ncols <- sapply(args, NCOL)
if(!all(ncols == ncols[1L])) stop("number of columns differ")
## process colnames() if any
nams <- lapply(args, colnames)
namsNULL <- sapply(nams, is.null)
if(all(namsNULL)) namsOK <- TRUE else {
if(sum(namsNULL) > 0L) namsOK <- FALSE else {
nam1 <- nams[[1L]]
namsID <- sapply(nams, function(x) identical(x, nam1))
if(all(namsID)) namsOK <- TRUE else {
namsSORT <- sapply(nams, function(x) identical(sort(x), sort(nam1)))
if(!all(namsSORT)) namsOK <- FALSE else {
namsOK <- TRUE
for(i in which(!namsID)) args[[i]] <- args[[i]][,nam1]
}
}
}
}
if(!namsOK) warning("column names differ")
## collect data
argsdata <- lapply(args, coredata)
## (special case: rbinding of vectors with one-column matrices)
nulldim <- sapply(argsdata, function(a) is.null(dim(a)))
if(ncols[1L] == 1L) {
if(nulldim[1] & any(!nulldim)) {
argsdata <- lapply(argsdata, function(a) if(is.null(dim(a))) a else a[,1, drop = TRUE])
nulldim <- rep(TRUE, length(nulldim))
}
if(!nulldim[1] & any(nulldim)) {
argsdata <- lapply(argsdata, function(a) if(is.null(dim(a))) as.matrix(a) else a)
nulldim <- rep(FALSE, length(nulldim))
}
}
if((ncols[1L] > 1L) | !all(nulldim))
rval <- zoo(do.call("rbind", argsdata), indexes)
else
rval <- zoo(do.call("c", argsdata), indexes)
freq <- if(!("zooreg" %in% unlist(sapply(args, class)))) NULL
else {
freq <- c(frequency(rval), unlist(sapply(args, frequency)))
if((length(freq) == (length(args)+1L)) &&
identical(all.equal(max(freq)/freq, round(max(freq)/freq)), TRUE))
max(freq) else NULL
}
if(!is.null(freq)) {
attr(rval, "frequency") <- freq
class(rval) <- c("zooreg", class(rval))
}
return(rval)
}
c.zoo <- function(...) {
rbind.zoo(...)
}
cbind.zoo <- function(..., all = TRUE, fill = NA, suffixes = NULL, drop = FALSE, sep = ".")
{
merge.zoo(..., all = all, fill = fill, suffixes = suffixes, retclass = "zoo", drop = drop, sep = sep)
}
merge.zoo <- function(..., all = TRUE, fill = NA, suffixes = NULL, check.names = FALSE, retclass = c("zoo", "list", "data.frame"), drop = TRUE, sep = ".")
{
if (!is.null(retclass)) retclass <- match.arg(retclass)
# cl are calls to the args and args is a list of the arguments
cl <- as.list(match.call())
cl[[1]] <- cl$all <- cl$fill <- cl$retclass <- cl$suffixes <- cl$check.names <- cl$drop <- cl$sep <- NULL
args <- list(...)
parent <- parent.frame()
is.plain <- function(x)
all(class(x) %in% c("array", "integer", "numeric", "factor", "matrix", "logical", "character"))
is.scalar <- function(x) is.plain(x) && length(x) == 1
# ensure all ... plain args are of length 1 or have same NROW as arg 1
stopifnot(all(sapply(args, function(x) is.zoo(x) || !is.plain(x) ||
(is.plain(x) && (NROW(x) == NROW(args[[1]]) || is.scalar(x))))))
scalars <- sapply(args, is.scalar)
if(!is.zoo(args[[1]])) args[[1]] <- as.zoo(args[[1]])
for(i in seq_along(args))
if (is.plain(args[[i]]))
args[[i]] <- zoo(args[[i]], index(args[[1]]), attr(args[[1]], "frequency"))
else if (!is.zoo(args[[i]]))
args[[i]] <- as.zoo(args[[i]])
## retain frequency if all series have integer multiples of the same frequency
## and at least one of the original objects is a "zooreg" object
freq <- if(!("zooreg" %in% unlist(sapply(args, class)))) NULL
else {
freq <- unlist(sapply(args, frequency))
if((length(freq) == length(args)) &&
identical(all.equal(max(freq)/freq, round(max(freq)/freq)), TRUE))
max(freq) else NULL
}
# use argument names if suffixes not specified
if (is.null(suffixes)) {
makeNames <- function(l) {
nm <- names(l)
fixup <- if (is.null(nm))
seq_along(l)
else nm == ""
dep <- sapply(l[fixup], function(x) deparse(x)[1])
if (is.null(nm))
return(dep)
if (any(fixup))
nm[fixup] <- dep
nm
}
suffixes <- makeNames(as.list(substitute(list(...)))[-1])
}
if (length(suffixes) != length(cl)) {
warning("length of suffixes and does not match number of merged objects")
suffixes <- rep(suffixes, length.out = length(cl))
}
# extend all to a length equal to the number of args
all <- rep(as.logical(all), length.out = length(cl))
## check indexes:
indexlist <- lapply(args, index)
## 1. for non-unique entries
index_duplicates <- function(x) length(unique(MATCH(x, x))) < length(x)
if(any(sapply(indexlist, index_duplicates)))
stop("series cannot be merged with non-unique index entries in a series")
## 2. for differing classes
indexclasses <- sapply(indexlist, function(x) class(x)[1])
if (!all(indexclasses == indexclasses[1L])) {
warning(paste("Index vectors are of different classes:",
paste(indexclasses, collapse = " ")))
if(all(indexclasses %in% c("numeric", "integer"))) {
indexlist <- lapply(indexlist, as.numeric)
} else if(all(vapply(indexlist, function(e) inherits(e, "Date") || is.numeric(e), NA))) {
indexlist <- lapply(indexlist, as.Date)
}
}
# fn to get the unique elements in x, in sorted order, using only
# [, match, length and order
sort.unique <- function(x) {
ix <- MATCH(x, x) == seq_len(length(x))
x <- x[ix]
ix <- ORDER(x)
x[ix]
}
# fn to get intersection of each element in list of lists
intersect.list <- function(list) {
my.table <- function(x) {
ix <- ORDER(x)
x <- x[ix]
table(MATCH(x, x))
}
union <- do.call("c", unname(list))
sort.unique(union)[which(my.table(union) == length(list))]
}
indexintersect <- intersect.list(indexlist)
# get the indexes of the final answer which is the union of
# all indexes of args corresponding to all=TRUE with the intersection
# of all indexes
indexunion <- do.call("c", unname(indexlist[all]))
indexes <- if(is.null(indexunion)) indexintersect
else sort.unique(c(indexunion, indexintersect))
# previously, we used to do:
# if (is.null(indexunion)) indexunion <- do.call("c", indexlist)[0]
# indexes <- sort.unique(c(indexunion, indexintersect))
## check whether resulting objects still got the same frequency
if(!is.null(freq)) {
freq <- c(frequency(zoo(,indexes)), freq)
freq <- if((length(freq) == 2) && identical(all.equal(max(freq)/freq, round(max(freq)/freq)), TRUE))
max(freq) else NULL
}
# the f function does the real work
# it takes a zoo object, a, and fills in a matrix corresponding to
# indexes with the values in a. ret.zoo is TRUE if it is to return
# a zoo object. If ret.zoo is FALSE it simply returns with the matrix
# just calculated.
# match0 is convenience wrapper for MATCH with nomatch=0 default
match0 <- function(a, b, nomatch = 0, ...) MATCH(a, b, nomatch = nomatch, ...)
f <- if (any(all)) {
function(a, ret.zoo = TRUE) {
if (length(a) == 0 && length(dim(a)) == 0)
return(if(ret.zoo) {
rval <- zoo(, indexes)
attr(rval, "frequency") <- freq
if(!is.null(freq)) class(rval) <- c("zooreg", class(rval))
rval
} else numeric())
z <- matrix(fill, length(indexes), NCOL(a))
if (length(dim(a)) > 0)
z[match0(index(a), indexes), ] <- a[match0(indexes, index(a)), , drop = FALSE]
else {
z[match0(index(a), indexes), ] <- a[match0(indexes, index(a))]
z <- z[, 1, drop=TRUE]
}
if (ret.zoo) {
z <- zoo(z, indexes)
attr(z, "oclass") <- attr(a, "oclass")
attr(z, "levels") <- attr(a, "levels")
attr(z, "frequency") <- freq
if(!is.null(freq)) class(z) <- c("zooreg", class(z))
}
return(z)
}
} else {
# if all contains only FALSE elements then the following f is used
# instead of the prior f for performance purposes. If all contains
# only FALSE then the resulting index is the intersection of the
# index of each argument so we can just return a[index] or a[index,].
# Also if we are not to return a zoo object then unclass it prior to return.
function(a, ret.zoo = TRUE) {
if (!ret.zoo) class(a) <- NULL
if (length(dim(a)) == 0) {
if (length(a) == 0) {
rval <- if(ret.zoo) zoo(, indexes) else numeric()
} else
rval <- as.zoo(a[match0(indexes, attr(a, "index"))])
} else
rval <- as.zoo(a[match0(indexes, attr(a, "index")), , drop=FALSE])
if(is.zoo(rval) && !is.null(freq)) {
attr(rval, "frequency") <- freq
class(rval) <- unique(c("zooreg", class(rval)))
}
return(rval)
}
}
# if retclass is NULL do not provide a return value but instead
# update each argument that is a variable, i.e. not an expression,
# in place.
if (is.null(retclass)) {
for(vn in cl) {
if (is.name(vn))
tryCatch(
eval(substitute(v <- f(v), list(f = f, v = vn)), parent),
condition = function(x) {}
)
}
invisible(return(NULL))
}
# apply f to each arg, put result of doing this on all args in list rval
# and then cbind that list together to produce the required matrix
rval <- lapply(args, f, ret.zoo = retclass %in% c("list", "data.frame"))
## have commented this next line out. Is it needed?
# for(i in which(scalars)) rval[[i]] <- rval[[i]][] <- zoo(coredata(rval[[i]])[1], index(rval[[1]]), freq)
names(rval) <- suffixes
if (retclass == "list") {
return(rval)
}
if (retclass == "data.frame") {
## transform list to data.frame
## this is simple if all list elements are vectors, but with
## matrices a bit more effort seems to be needed:
charindex <- index2char(index(rval[[1]]), frequency = freq)
nam1 <- names(rval)
rval <- lapply(rval, as.list)
todf <- function(x) {
class(x) <- "data.frame"
attr(x, "row.names") <- charindex
return(x)
}
rval <- lapply(rval, todf)
## name processing
nam2 <- sapply(rval, function(z) 1:NCOL(z))
for(i in 1:length(nam2)) nam2[[i]] <- paste(names(nam2)[i], nam2[[i]], sep = sep)
nam1 <- unlist(ifelse(sapply(rval, NCOL) > 1, nam2, nam1))
rval <- do.call("cbind", rval)
names(rval) <- nam1
## turn zoo factors into plain factors
is.zoofactor <- function(x) !is.null(attr(x, "oclass")) && attr(x, "oclass") == "factor"
for(i in 1:NCOL(rval)) if(is.zoofactor(rval[,i])) rval[,i] <- coredata(rval[,i])
return(rval)
}
# remove zero length arguments
rval <- rval[sapply(rval, function(x) length(x) > 0)]
# if there is more than one non-zero length argument then cbind them
# Note that cbind will create matrices, even when given a single vector,
# so - if drop=TRUE - we do not to use it in the single vector case.
rval <- if (length(rval) > 1L | (length(rval) == 1L & !drop))
do.call("cbind", rval)
else if (length(rval) > 0L)
rval[[1]]
# return if vector since remaining processing is only for column names
if (length(dim(rval)) == 0L) {
# fixed bug: coredata was missing
rval <- zoo(coredata(rval), indexes)
attr(rval, "frequency") <- freq
if(!is.null(freq)) class(rval) <- c("zooreg", class(rval))
return(rval)
}
# processing from here on is to compute nice column names
if (length(unlist(sapply(args, colnames))) > 0) {
fixcolnames <- function(a) {
# if (length(a) == 0)
# return(NULL)
if (length(dim(a)) ==0) {
if (length(a) == 0) return(NULL) else return("")
} else {
if (ncol(a) == 0) return(NULL)
rval <- colnames(a)
if (is.null(rval)) {
rval <- paste(1:NCOL(a), suffixes[i], sep = sep)
}
else {
rval[rval == ""] <- as.character(which(rval == ""))
}
return(rval)
}
}
zoocolnames <- lapply(args, fixcolnames)
zcn <- unlist(zoocolnames)
fixme <- lapply(zoocolnames, function(x) x %in% zcn[duplicated(zcn)])
f <- function(i) {
rval <- zoocolnames[[i]]
rval[rval == ""] <- suffixes[i]
rval
}
zoocolnames <- lapply(seq_along(args), f)
f <- function(i) ifelse(fixme[[i]], paste(zoocolnames[[i]],
suffixes[i], sep = sep), zoocolnames[[i]])
if (any(duplicated(unlist(zoocolnames))))
zoocolnames <- lapply(seq_along(args), f)
} else {
fixcolnames <- function(a) {
if (length(a) == 0)
return(NULL)
if (NCOL(a) < 2)
return("")
else return(paste(sep, 1:NCOL(a), sep = ""))
}
zoocolnames <- lapply(args, fixcolnames)
zoocolnames <- lapply(seq_along(args), function(i)
if (!is.null(zoocolnames[[i]])) # NULL returned if false
paste(suffixes[i], zoocolnames[[i]], sep = ""))
}
zoocolnames <- unlist(zoocolnames)
colnames(rval) <- if (check.names) make.names(make.unique(zoocolnames))
else if (ncol(rval) == length(zoocolnames)) zoocolnames else
colnames(rval)
# rval <- zoo(rval, indexes)
rval <- zoo(coredata(rval), indexes)
attr(rval, "frequency") <- freq
if(!is.null(freq)) class(rval) <- c("zooreg", class(rval))
return(rval)
}
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