R/dot_ls.objects.R

In thiyangt/fformpp: Feature-based FORecast Model Performance Prediction

##' List the object size

##' Modified from Dirk Eddelbuettel's version
##' http://stackoverflow.com/questions/1358003/tricks-to-manage-the-available-memory-in-an-r-session

##' improved list of objects
##' TODO: Better default sorting
##' @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)
  out <- data.frame(obj.type, obj.prettysize, obj.dim)

  names(out) <- c("Type", "Size", "Rows", "Columns")
  if (!missing(order.by))
    out <- out[order(out[[order.by]], decreasing=decreasing), ]
  if (head)
    out <- head(out, n)
  out
}