On 04/13/2011 02:55 PM, Barth B. Riley wrote:
Dear list
I am running some simulations in R involving reading in several
hundred datasets, performing some statistics and outputting those
statistics to file. I have noticed that it seems that the time it
takes to process of a dataset (or, say, a set of 100 datasets) seems
to take longer as the simulation progresses. Has anyone else noticed
this? I am curious to know if this has to do with how R processes
code in loops or if it might be due to memory usage issues (e.g.,
repeatedly reading data into the same matrix).
Hi Barth
The 'it gets slower' symptom is often due to repeatedly 'growing by 1' a
list or other data structure, e.g.,
m = matrix(100000, 100)
n = 20000
result = list()
system.time(for (i in seq_len(n)) result[[i]] = m)
versus 'pre-allocate and fill'
result = vector("list", n)
system.time(for (i in seq_len(n)) result[[i]] = m)
The former causes 'result' to be copied on each new assignment, and the
size of the copy gets larger each time.
Thanks in advance
Barth
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