R/lsos.R

#' list objects and sizes
#'
#' Easy way to manage memory, commonly suggested to put this in .Rprofile.
#' Here it is in a package.
#'
#' @param ... environment (usually the global one)
#' @param n  number of items to report
#' @export
#' @references
#' \url{http://stackoverflow.com/questions/1358003/tricks-to-manage-the-available-memory-in-an-r-session}
#' Also available in package \code{dmisc}
lsos <- function (..., n = 10)
{
  .ls.objects(..., order.by = "Size", decreasing = TRUE, head = TRUE,
              n = n)
}

.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)
  out
}
patr1ckm/patr1ckm documentation built on May 24, 2019, 8:21 p.m.