[R-pkg-devel] Read and restore .Random.seed in package

On Mon, 19 Sep 2022, Jan van der Laan wrote:

I have a function in which I need to draw some random numbers. 
However, for some use cases, it is necessary that the same random 
numbers are drawn (when the input is the same) [1]. So I would like to 
do a set.seed in my function. This could, however, mess up the seed 
set by the user. So what I would like to do is store .Random.seed, 
call set.seed, draw my random numbers and restore .Random.seed to its 
original value. For an example see the bottom of the mail.

Am I allowed on CRAN to read and restore .Random.seed in a package 
function? This seems to conflict with the "Packages should not modify 
the global environment (user?s workspace)." policy. Is there another 
way to get the same random numbers each time a function is called 
without messing up the seed set by the user? [2]]

My understanding is that restoring the .Random.seed is exempt from this 
policy. See the first lines in stats:::simulate.lm for how R itself 
deals with this situation:

simulate.lm <- function(object, nsim = 1, seed = NULL, ...)
{
 ??? if(!exists(".Random.seed", envir = .GlobalEnv, inherits = FALSE))
 ??????? runif(1)???????????????????? # initialize the RNG if necessary
 ??? if(is.null(seed))
 ??????? RNGstate <- get(".Random.seed", envir = .GlobalEnv)
 ??? else {
 ??????? R.seed <- get(".Random.seed", envir = .GlobalEnv)
 ????set.seed(seed)
 ??????? RNGstate <- structure(seed, kind = as.list(RNGkind()))
 ??????? on.exit(assign(".Random.seed", R.seed, envir = .GlobalEnv))
 ??? }

[...]

[1] Records are randomly distributed over cluster nodes. For some use 
cases it is necessary that the same records end up on the same cluster 
nodes when the function is called multiple times.

[2] A possible solution would be to document that the user should 
ensure that the same seed is used when calling this function for the 
use cases where this is needed.


set_seed <- function(seed, ...) {
?if (!exists(".Random.seed")) set.seed(NULL)
?old_seed <- .Random.seed
?if (length(seed) > 1) {
?? .Random.seed <<- seed
?} else {
?? set.seed(seed, ...)
?}
?invisible(old_seed)
}

foo <- function(n) {
?old_seed <- set_seed(1)
?on.exit(set_seed(old_seed))
?runif(n)
}

Using these:

set.seed(2)
foo(5)

[1] 0.2655087 0.3721239 0.5728534 0.9082078 0.2016819

runif(5)

[1] 0.1848823 0.7023740 0.5733263 0.1680519 0.9438393

foo(5)

[1] 0.2655087 0.3721239 0.5728534 0.9082078 0.2016819

runif(5)

[1] 0.9434750 0.1291590 0.8334488 0.4680185 0.5499837