I am interested in measuring the time it takes to run an expression.
system.time(expr) does this but I would like to have it report just 'more
than xxx seconds', where xxx is a argument to the timing function, when it
takes a long time. This is useful automating the process of seeing how
processing time grows with the size of a dataset.
My latest attempt is the following function, which adds a 'censored=TRUE'
attribute when the cpu or elapsed time exceeds some limit:
system.time2 <- function (expr, gcFirst = TRUE, cpu = Inf, elapsed = Inf)
{
setTimeLimit(cpu = cpu, elapsed = elapsed, transient = TRUE)
censored <- NULL
time <- system.time(gcFirst = gcFirst, tryCatch(expr, error =
function(e) if (grepl("reached (CPU|elapsed) time limit",
conditionMessage(e)))
censored <<- conditionMessage(e)
else stop(e)))
attr(time, "censored") <- censored
time
}
It would be used as
system.time(times <- lapply(10^(1:7), function(n)system.time2(for(i in
1:n)lgamma(1:i), elapsed=10) ))
user system elapsed
33.55 0.25 33.82
vapply(times, function(t)t[["elapsed"]], 0)
[1] 0.02 0.00 0.03 3.08 10.02 10.14 10.18
# following gives which times are valid
vapply(times, function(t)is.null(attr(t,"censored")), NA)
[1] TRUE TRUE TRUE TRUE FALSE FALSE FALSE
I have two questions.
* Is this a reasonable way to compute such a censored time?
* Is there a getTimeLimit()-like function?