On Thu, 04-06-2015, at 15:50, Kasper Daniel Hansen
wrote:
> Note you're not guaranteed that two random streams starting with different
> seeds will be (approximately) independent, so the suggestion on SO makes
> the numbers reproducible but technically wrong.
>
But whether or not that is a pr
You're ignoring the fact that some random number generators should never be
used inside of mclapply(), period. You should add that to your post and
you should show how to set the random number generator appropriately.
You seem to be only focusing on reproducibility of the code and not
correctness
The only bad thing I see so far in using set.seed inside the function is
that it interferes with previously set seed by the user. So follow-up
stochastic computation will be out user's control. Perhaps there are other
undesirable effect that I do not see at this point.
I tweaked the solution a bi
I'll add a section to the BiocParallel docs.
Valerie
On 06/04/2015 07:55 AM, Kasper Daniel Hansen wrote:
Yes, based on the documentation that particular random stream generator
would work with mclapply.
This is absolutely a subject which ought to be covered in the BiocParallel
documentation.
Yes, based on the documentation that particular random stream generator
would work with mclapply.
This is absolutely a subject which ought to be covered in the BiocParallel
documentation.
And commenting on another set of recommendations: please NEVER used
set.seed inside a function. Unfortunatel
It does appear to me that the doRNG vignette sec 1.1 describes a solution
to the problem posed. It is less clear to me that this method is readily
adopted with BiocParallel unless registerDoPar is in use Should we
address this topic explicitly in the vignette?
On Thu, Jun 4, 2015 at 9:50 AM,
Note you're not guaranteed that two random streams starting with different
seeds will be (approximately) independent, so the suggestion on SO makes
the numbers reproducible but technically wrong.
If you want true independence you either need to use a parallel version of
the random number generator
There are different ways set.seed can be used. The way it is suggested on
the aforementioned stackoverflow post is basically a two stage process.
First seed is provided by a user (set.seed(1)). That is user can change
the outcome from run to run. Based on that seed, a vector of randomized
seeds
There is one possible solution posted in
http://stackoverflow.com/questions/30610375/how-to-run-permutations-using-mclapply-in-a-reproducible-way-regardless-of-numbe/30627984#30627984
.
As Kasper suggested, it's not a proper way to use set.seed inside a package.
I suggest using a parameter for ex
For this situation, generate the permutation indexes outside of the
mclapply, and the do mclapply over a list with the indices.
And btw., please don't use set.seed inside a package; that control should
completely be left to the user.
Best,
Kasper
On Wed, Jun 3, 2015 at 7:08 AM, Vincent Carey
wr
This document indicates how to achieve reproducibility independent of the
underlying physical environment.
http://cran.r-project.org/web/packages/doRNG/vignettes/doRNG.pdf
Let me know if that satisfies the question.
On Wed, Jun 3, 2015 at 5:32 AM, Yu, Guangchuang wrote:
> Der Vincent,
>
> RNGk
Der Vincent,
RNGkind("L'Ecuyer-CMRG") works as using mc.set.seed=FALSE.
When mc.cores changes, the output is not reproducible.
I think this issue is also of concern within the Bioconductor
community as parallel version of permutation test is commonly used
now.
Best Regards,
Guangchuang
On W
Hi, this question belongs on R-help, but perhaps
https://stat.ethz.ch/R-manual/R-devel/library/parallel/html/RngStream.html
will be useful.
Best regards
On Wed, Jun 3, 2015 at 3:11 AM, Yu, Guangchuang wrote:
> Dear all,
>
> I have an issue of setting seed value when using parallel package.
>
Dear all,
I have an issue of setting seed value when using parallel package.
> library("parallel")
> library("digest")
>
> set.seed(0)
> m <- mclapply(1:10, function(x) sample(1:10),
+ mc.cores=2)
> digest(m, 'crc32')
[1] "4827c80c"
>
> set.seed(0)
> m <- mclapply(1:10, function(x)
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