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]]
Thanks.
Jan
[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
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