On 10/05/2019 8:55 a.m., Martin Maechler wrote:
Ulrike Grömping
on Fri, 10 May 2019 06:39:39 +0200 writes:
> Mark,
> I used
> if (getRversion()>="3.6.0") RNGkind(sample.kind="Rounding")
> And that works. Actually, using rnorm afterwards also
> yields the same random numbers.
Yes, "of course", 'sample.kind' was only introduced into 3.6.0.
We had always recommended
RNGversion("3.5.0")
possibly wrapped in suppressWarnings().
That *does* work in old and new versions of R.
Note that in R >= 3.6.0 , e.g., inside your if(.) { ** }
you could also use set.seed(<n>, sample.kind="Rounding")
That's good advice. There's a couple of other things I'd add:
- Be sure to do this only in test code with saved results. Functions
should never need to do this, and you really don't want to leave that
setting in place after an example.
- At some point in the future (maybe in a year or so), update your
package to depend on "R (>= 3.6.0)", remove the RNGversion() line and
update saved test results.
Duncan Murdoch
Martin
> My question arose from the fact that I confused myself about the noLD
output I was supposed to reproduce. Therefore, my problem should be entirely
explained by Duncan Murdoch's initial explanation: the sample() change does not
only lead to different results in discrete sampling but also to different results
from random number calls for other functions (like rnorm)
*IFF* callled after sample() [etc].
So yes, do call RNGversion("3.5.0")
before set.seed() before the first call to sample() / sample.int()
or functions using those [or 'rwilcox()', see its help in R >= 3.6.0!].
Martin
> Best, Ulrike
> Am 10.05.2019 um 04:58 schrieb R. Mark Sharp:
>> I was dealing with a similar issue but in the context of getting the same
unit test code to work on multiple versions of R in a Travis-CI build. It seems
RNGkind(sample.kind="Rounding”) does not work prior to version 3.6 so I resorted to
using version dependent construction of the argument list to set.seed() in do.call().
>>
>> I better solution will be greatly appreciated.
>>
>> #' Work around for unit tests using sample()
>> #'
>> #' @param seed argument to \code{set.seed}
>> set_seed <- function(seed = 1) {
>> version <- as.integer(R.Version()$major) +
(as.numeric(R.Version()$minor) / 10.0)
>> if (version >= 3.6) {
>> args <- list(seed, sample.kind = "Rounding")
>> } else {
>> args <- list(seed)
>> }
>> suppressWarnings(do.call(set.seed, args))
>> }
>>
>> Mark
>>
>> R. Mark Sharp, Ph.D.
>> Data Scientist and Biomedical Statistical Consultant
>> 7526 Meadow Green St.
>> San Antonio, TX 78251
>> mobile: 210-218-2868
>> rmsh...@me.com
>>
>>
>>
>>
>>
>>
>>
>>
>>
>>
>>
>>> On May 9, 2019, at 12:45 PM, Duncan Murdoch <murdoch.dun...@gmail.com>
wrote:
>>>
>>> On 09/05/2019 12:43 p.m., Ulrike Grömping wrote:
>>>> Hmmmh, but does that also apply if the sample.kind has been set to the
>>>> old version? I.e., would
>>>> if (getRversion()>="3.6.0") RNGkind(sample.kind="Rounding")
>>>> val <- 10
>>>> set.seed(val)
>>>> discard <- sample(1000, 100)
>>>> rnorm(36)
>>>> produce the same normal random numbers in 3.5.3 and 3.6.0? I would
have
>>>> expected it to, but it seems to produce the same normal random numbers
>>>> as R version 3.6.0 in the previous version of the test code without
the
>>>> RNGkind call.
>>> I'm not seeing that, but I'm not using the exact versions you tested. If I run your code
in "R version 3.5.2 (2018-12-20)" and "R Under development (unstable) (2019-05-02
r76454)" I get this output from both:
>>>
>>>> if (getRversion()>="3.6.0") RNGkind(sample.kind="Rounding")
>>>> val <- 10
>>>> set.seed(val)
>>>> discard <- sample(1000, 100)
>>>> rnorm(36)
>>> [1] -0.4006375 -0.3345566 1.3679540 2.1377671 0.5058193 0.7863424
-0.9022119 0.5328970 -0.6458943 0.2909875 -1.2375945
>>> [12] -0.4561763 -0.8303227 0.3401156 1.0663764 1.2161258 0.7356907
-0.4812086 0.5627448 -1.2463197 0.3809222 -1.4304273
>>> [23] -1.0484455 -0.2185036 -1.4899362 1.1727063 -1.4798270 -0.4303878
-1.0516386 1.5225863 0.5928281 -0.2226615 0.7128943
>>> [34] 0.7166008 0.4402419 0.1588306
>>>
>>> Okay, I just installed 3.6.0, and I get the same values there. I
don't see a Mac binary for 3.5.3, so I can't test that one.
>>>
>>> Duncan Murdoch
>>>
>>> ______________________________________________
>>> R-package-devel@r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-package-devel
> --
> ##############################################
> ## Prof. Ulrike Groemping
> ## FB II
> ## Beuth University of Applied Sciences Berlin
> ##############################################
> ## prof.beuth-hochschule.de/groemping
> ## Phone: +49(0)30 4504 5127
> ## Fax: +49(0)30 4504 66 5127
> ## Home office: +49(0)30 394 04 863
> ##############################################
> ______________________________________________
> R-package-devel@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-package-devel
______________________________________________
R-package-devel@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-package-devel
