[Bioc-devel] reproducible with mclapply?

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 or you do what I suggested.  Because of how
mclapply works (via fork) it is not clear to me that it is possible to use
a parallel version of the random number generator, but I am not sure about
this.  The snippet from the documentation quoted above suggests I am wrong.

Best,
Kasper

On Wed, Jun 3, 2015 at 11:25 PM, Vladislav Petyuk <petyuk at gmail.com>
wrote:

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 is generated (seeds <- sample.int(length(input), replace=TRUE)).
Those seeds are basically arguments to the function under mclapply/lapply
that help to control random number generation for each iteration

(set.seed

(seeds[idx])).
There are two different roles of set.seed. First left the user to control
random number generation and the second (within the function) makes sure
that it is the same for individual iterations regardless how the loop is
executed.
Does that make sense?

On Wed, Jun 3, 2015 at 7:07 PM, Yu, Guangchuang <gcyu at connect.hku.hk>
wrote:

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 example seed=FALSE to disable the

set.seed

and if user want the result reproducible, e.g. in demonstration, set
seed=TRUE explicitly and set.seed will be run inside the function.

Bests,
Guangchuang

On Wed, Jun 3, 2015 at 8:42 PM, Kasper Daniel Hansen <
kasperdanielhansen at gmail.com> wrote:

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 <

stvjc at channing.harvard.edu>

wrote:

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 <gcyu at connect.hku.hk

wrote:

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 Wed, Jun 3, 2015 at 5:17 PM, Vincent Carey <

stvjc at channing.harvard.edu>

wrote:

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 <

gcyu at connect.hku.hk>

wrote:

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) sample(1:10),

+               mc.cores=2)

digest(m, 'crc32')

[1] "e95b9134"

By default, set.seed() will be ignored since mclapply will set

the

seed

internally.

If we use mc.set.seed=FALSE to disable this feature. It works as
indicated
below:

set.seed(0)
m <- mclapply(1:10, function(x) sample(1:10),

+               mc.cores=2, mc.set.seed = FALSE)

digest(m, 'crc32')

[1] "6bbada78"

set.seed(0)
m <- mclapply(1:10, function(x) sample(1:10),

+               mc.cores=2, mc.set.seed = FALSE)

digest(m, 'crc32')

[1] "6bbada78"

The problems is that the results are also depending on the number

of

cores.

set.seed(0)
m <- mclapply(1:10, function(x) sample(1:10),

+               mc.cores=4, mc.set.seed = FALSE)

digest(m, 'crc32')

[1] "a22e0aab"


Any idea?

Best Regards,
Guangchuang
--
--~--~---------~--~----~------------~-------~--~----~
Guangchuang Yu, PhD Candidate
State Key Laboratory of Emerging Infectious Diseases
School of Public Health
The University of Hong Kong
Hong Kong SAR, China
www: http://ygc.name
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--
--~--~---------~--~----~------------~-------~--~----~
Guangchuang Yu, PhD Candidate
State Key Laboratory of Emerging Infectious Diseases
School of Public Health
The University of Hong Kong
Hong Kong SAR, China
www: http://ygc.name
-~----------~----~----~----~------~----~------~--~---

        [[alternative HTML version deleted]]

--
--~--~---------~--~----~------------~-------~--~----~
Guangchuang Yu, PhD Candidate
State Key Laboratory of Emerging Infectious Diseases
School of Public Health
The University of Hong Kong
Hong Kong SAR, China
www: http://ygc.name
-~----------~----~----~----~------~----~------~--~---

        [[alternative HTML version deleted]]

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