R/lsos.R

#' @export
.ls.objects <- function (pos = 1, pattern, order.by,
                        decreasing=FALSE, head=FALSE, n=5) {
    napply <- function(names, fn) sapply(names, function(x)
                                         fn(get(x, pos = pos)))
    names <- ls(pos = pos, pattern = pattern)
    obj.class <- napply(names, function(x) as.character(class(x))[1])
    obj.mode <- napply(names, mode)
    obj.type <- ifelse(is.na(obj.class), obj.mode, obj.class)
    obj.prettysize <- napply(names, function(x) {
                           capture.output(print(object.size(x), units = "auto")) })
    obj.size <- napply(names, object.size)
    obj.dim <- t(napply(names, function(x)
                        as.numeric(dim(x))[1:2]))
    vec <- is.na(obj.dim)[, 1] & (obj.type != "function")
    obj.dim[vec, 1] <- napply(names, length)[vec]
    out <- data.frame(obj.type, obj.size, obj.prettysize, obj.dim)
    names(out) <- c("Type", "Size", "PrettySize", "Rows", "Columns")
    if (!missing(order.by))
        out <- out[order(out[[order.by]], decreasing=decreasing), ]
    if (head)
        out <- head(out, n)
    print(paste("Total:",round(sum(out$Size)/1073741824,digits=2),"Gb"))
    out
}

#' @title list objects & sizes in R session
#'
#' @param ... generally unused (see source to \code{.ls.objects})
#' @param n max number of objects to list (default 10)
#' @export
#' @return data frame of object information
#' @examples \dontrun{
#' listObjects()
#'}
listObjects <- function(..., n=10) {
    .ls.objects(..., order.by="Size", decreasing=TRUE, head=TRUE, n=n)
}

## slightly modified version of Dirk's answer here:
# http://stackoverflow.com/questions/1358003/tricks-to-manage-the-available-memory-in-an-r-session
alyssafrazee/usefulstuff documentation built on May 12, 2019, 2:33 a.m.