########################################
# Author: Antoine Sachet
# Date: 09/15
#
# credit to:
# - http://stackoverflow.com/questions/1358003/tricks-to-manage-the-available-memory-in-an-r-session
#
########################################
#' List objects in the global environment
#'
#' List objects in memory: name, type, dims, byte size, etc.
#' The shorthand `lsos()` is very convenient for tracking memory usage.
#'
#' @return Data.frame containing object and memory information
#'
#' @param pos
#' @param pattern
#' @param order.by
#' @param decreasing
#' @param head
#' @param n
#'
#' @describeIn ls.objects Advanced printing
#' @note http://stackoverflow.com/questions/1358003/tricks-to-manage-the-available-memory-in-an-r-session.
#'
#' @examples lsos()
#'
#' @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)
if(length(names)>0) {
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(format(utils::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)
} else {
out <- data.frame(Type=character(), Size=integer(), PrettySize=character(),
Rows=integer(), Columns=integer())
}
out
}
#' @describeIn ls.objects Print the 10 largest objects in memory, ordered by size.
#' @export
lsos <- function(..., n=10) {
ls.objects(..., order.by="Size", decreasing=TRUE, head=TRUE, n=n)
}
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