Hi Bert,
Thanks for your response. What you suggest is more or less the fix I suggested
in my email (my second version of .rcolors). I writing more because I was
wondering if there was a better way to work with RNG that would avoid doing
that. It doesn’t feel very friendly for my package to be making changes to the
user’s global environment, even though I am setting them back (and if it
weren’t for the fact that setting the new R 3.6 argument
`sample.kind=“Rounding”` creates a warning, I wouldn’t have even realized I was
affecting the user’s settings, so it seems potentially hazardous that packages
could be changing users settings without them being aware of it). So I was
wondering if there was a way to more fully isolate the command.
Thanks,
Elizabeth
> On Apr 16, 2019, at 9:36 AM, Bert Gunter <bgunter.4...@gmail.com> wrote:
>
> I think I'm missing something. Why does something like this not do what you
> want:
>
> > RNGkind()
> [1] "Mersenne-Twister" "Inversion"
> > f <- function(){
> + cur <- RNGkind(NULL)[1]
> + RNGkind("Super-Duper")
> + print(RNGkind())
> + RNGkind(cur)
> + }
> > f()
> [1] "Super-Duper" "Inversion"
> > RNGkind()
> [1] "Mersenne-Twister" "Inversion"
>
> Cheers,
> Bert
>
> Bert Gunter
>
> "The trouble with having an open mind is that people keep coming along and
> sticking things into it."
> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
>
>
> On Tue, Apr 16, 2019 at 9:13 AM Elizabeth Purdom <epur...@stat.berkeley.edu
> <mailto:epur...@stat.berkeley.edu>> wrote:
> Hello,
>
> I have a package, and inside of it I have a small function that selects a
> random palette of colors for graphing purposes. It’s a large number of
> colors, which is why I don’t manually select them, but I did want them to
> stay constant so I set the seed before doing so. So I had a little function
> in my package that does this:
>
> .rcolors<-function(){
> set.seed(23589)
> x<-sample(colors()[-c(152:361)])
> return(x)
> }
> massivePalette<-unique(c(bigPalette,.rcolors()))
>
> Now that the sample function has been changed in R 3.6, I would need to use
> `sample.kind=“Rounding”` to get the same set of colors as I had previously.
> However, I don’t want to do that in my package, because that appears to
> change the global environment sampling:
>
> > RNGkind()
> [1] "Mersenne-Twister" "Inversion" "Rejection"
> > RNGkind(sample.kind="Rejection")
> > x<-clusterExperiment:::.rcolors() #now I have changed the function so that
> > sample.kind=“Rounding” — I’ve suppressed the warnings
> > RNGkind()
> [1] "Mersenne-Twister" "Inversion" "Rounding”
>
> So I could do something like this:
>
> .rcolors<-function(){
> currentRNG<-RNGkind()
> suppressWarnings(RNGkind(sample.kind="Rounding"))
> set.seed(23589)
> x<-sample(colors()[-c(152:361)])
> #set it back to default
> suppressWarnings(RNGkind(sample.kind=currentRNG[3]))
> return(x)
> }
>
> But is there a way to change the random sampling in the function environment
> and not change it in the global environment? (For this function, I can just
> break down and accept that I will have different colors from this point on,
> but I’d like to know more generally; especially since it means that my
> `fixed` colors are not really fixed since they depend on the user’s setting
> of random sampling techniques, which I hadn’t considered before).
>
> All of the best,
> Elizabeth Purdom
>
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