On Wed, 28 May 2008, John Fox wrote:
Dear Brian and Bill,
Here's an interesting contrasting example (taken from this month's Help Desk
column in R News, which Bill has already seen), first verifying the relative
timings for Brian's example:
system.time({
+ a <- vector("list", 10001)
+ for(i in 0:10000) a[[i+1]] <- i
+ })
user system elapsed
0.03 0.00 0.03
system.time({
+ a <- list()
+ for(i in 0:10000) a[[i+1]] <- i
+ })
user system elapsed
0.47 0.02 0.49
system.time({
+ matrices <- vector(mode="list", length=1000)
+ for (i in 1:1000)
+ matrices[[i]] <- matrix(rnorm(10000), 100, 100)
+ })
user system elapsed
2.59 0.00 2.61
system.time({
+ matrices <- list()
+ for (i in 1:1000)
+ matrices[[i]] <- matrix(rnorm(10000), 100, 100)
+ })
user system elapsed
2.61 0.00 2.60
Brian will, I'm sure, have the proper explanation, but I suppose that the
NULL elements in the initialized list in the first example provide
sufficient space for the integers that eventually get stored there, while
that's not the case for the matrices in the second example. I believe that
the second example is more typical of what one would actually put in a list.
Your explanation is incorrect as a list is just a header plus a set of
SEXP pointers, and is never used to store data directly.
The main point is that with only 1000 elements, the difference in
re-allocating the list on your system is only going to be about (0.49 -
0.04)/10 ~ 0.04, too small to time accurately (especially under Windows).
So finding 0.02 is not really contrasting.
The point that pre-allocation may only help when list allocation is
taking an appreciable part of the time is a sound one.
Note that because of GC tuning such things are very variable. Running
repeatedly either version on my Linux box gets timings from about 3.8 down
to 2.5 seconds -- and after settling down to 2.5-2.7s, the 13th run took
3.2s.
Regards,
John
------------------------------
John Fox, Professor
Department of Sociology
McMaster University
Hamilton, Ontario, Canada
web: socserv.mcmaster.ca/jfox
-----Original Message-----
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
On
Behalf Of Prof Brian Ripley
Sent: May-28-08 2:04 AM
To: [EMAIL PROTECTED]
Cc: r-help@r-project.org
Subject: Re: [R] how to bind lists recursively
But pre-allocation still helps
a <- vector("list", 10001)
for(i in 0:10000) a[[i+1]] <- i
gives
user system elapsed
0.042 0.001 0.057
on my system, against
user system elapsed
0.743 0.000 1.907
for Bill's 'best' solution.
On Wed, 28 May 2008, [EMAIL PROTECTED] wrote:
This is somewhat subtle.
Rolf's solution (here corrected to...)
a <- list()
for(i in 0:10000) a[[i+1]] <- i
is the best of the loop solutions (or at least the best I know of). The
apparently similar
a <- list(0)
for(i in 1:10000) a <- c(a, list(i))
will take a lot longer, although the result is the same. For example:
system.time({
a <- list()
for(i in 0:10000) a[[i+1]] <- i
})
user system elapsed
0.59 0.00 0.59
system.time({
a <- list(0)
for(i in 1:10000) a <- c(a, list(i))
})
user system elapsed
6.87 0.00 6.89
That's a factor of about 11 times as long. The best of the lot is
a <- as.list(0:10000)
of course, but this has problems with generalisation, (which everyone
suspects is going to be needed here...).
Bill Venables.
-----Original Message-----
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
On Behalf Of Rolf Turner
Sent: Wednesday, 28 May 2008 1:02 PM
To: Daniel Yang
Cc: r-help@r-project.org
Subject: Re: [R] how to bind lists recursively
On 28/05/2008, at 2:43 PM, Daniel Yang wrote:
Dear all,
I want to create a list that contains 0,1,2,3, ..., 10000 as its
elements. I used the following code, which apparently doesn't work
very well.
a <- 0
for(i in 1:10000) {
a <- list(a, i)
}
The result is not what I wanted. So how to create the bind lists
recursively so that the last element would be the newly added one
while the previous elements all remain the same?
a <- list()
for(i in 1:10000) a[[i]] <- i
(The word ``bind'' is inappropriate.)
cheers,
Rolf Turner
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
