On Wed, 13 Feb 2008, Henrik Bengtsson wrote:
> Hi,
>
> this is related to a question just raised on Bioconductor where one
> function sets the random seed internally but never resets it, which
> results in enforced down streams random samples being deterministic.
>
> What is the best way to reset the random seed when you use set.seed()
> within a function? Is it still to re-assign '.Random.seed' in the
> global environment as following example illustrates? I'm not too kind
> of having function modifying the global environment, if not really
> necessary.
It is necessary. Of course, any use of random numbers modifies this
variable in the global environment, so many, many functions already do.
There is a write-up in 'R Internals' of what is permissible in
modifying the base and global environments.
> foo <- function(n) {
> # Pop random seed
> if (!exists(".Random.seed", mode="numeric"))
> sample(NA);
> oldSeed <- .Random.seed;
>
> # Fixed seed to get reproducible samples here
> set.seed(0xbeef);
> x <- sample(5);
>
> # Proof of concept: 'x' should be the same all the time
> stopifnot(identical( x, as.integer(c(4,2,5,1,3)) ));
>
> # Push random seed to old state
> assign(".Random.seed", oldSeed, envir=globalenv())
>
> # Continue as nothing happened
> sample(n);
> }
>
>> foo(5)
> [1] 4 2 3 5 1
>> foo(5)
> [1] 4 2 3 1 5
>> foo(5)
> [1] 5 3 1 4 2
>> foo(5)
> [1] 5 3 2 4 1
>> foo(5)
>
> Is this the way to do it?
>
> Thanks
>
> Henrik
>
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--
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)
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