[R-pkg-devel] Save and restoring random number seed in a package function

Great to see you're handling the corner case when .Random.seed is not
set.  Note that your current implementation of boot.array() still
risks leaving .Random.seed modified in case an error or an interrupt
occurs while evaluating boot.array().  If that happens, one certainly
can argue that it modifies the .GlobalEnv environment.  A more robust
solution is:

boot.array <- function(boot.out) {
  genv <- globalenv()

  # Make sure to leave '.Random.seed' as-is on exit
  old_seed <- genv$.Random.seed
  on.exit(suspendInterrupts({
    if (is.null(old_seed)) {
      rm(".Random.seed", envir = genv, inherits = FALSE)
    } else {
      assign(".Random.seed", value = old_seed, envir = genv, inherits =
FALSE)
    }
  }))

  # Assign saved seed from boot.out
  assign(".Random.seed", value = boot.out$seed, envir = genv)

  # Generate same random numbers from boot() call
}

This implementation leaves .GlobalEnv unmodified when the function
exits, regardless of how.

If CRAN would not allow temporarily modifying the .Random.seed this
way, there would not be possible to distribute a lot of statistical
algorithm on CRAN. I can't speak for CRAN, but I would assume they
accept this type of approach, since it should have no side effects.
FWIW, this strategy is used by several CRAN packages for generating
random numbers in "stealth mode" while R's RNG, e.g. 'future.apply'
(mine) and 'withr'. If you have a GitHub account, you find hundres of
other CRAN examples by searching "org:cran assign .Random.seed".  So,
you're not alone in this need.  As a fallback, you could use
`withr::with_seed()` which uses the above approach. That would put the
burden on the 'withr' maintainer to argue for this approach.

Hope this helps,

Henrik


On Wed, Sep 14, 2022 at 8:11 AM Noah Greifer <noah.greifer at gmail.com>
wrote:

Yes, set.seed() cannot accept .Random.Seed as an input; it can only take

a

single integer. As said in this answer
<https://stackoverflow.com/a/13997608/6348551>, there is a one-way
relationship between set.seed() and .Random.Seed. My understanding is

that

the recommended way to restore the seed is to assign the saved seed to
.Random.Seed in the global environment, though this is the method that is
not allowed by the CRAN policy. Unfortunately saving it in the

environment

of the inner function is not sufficient.

One potential inconsistency with CRAN's policy is that generating a

random

number itself changes the global environment by changing the value of
.Random.Seed. The boot.array() code just does it manually using assign().
Indeed, the boot.array() code does less damage to the global environment

in

that it resets the seed to what it would have been had boot.array() not
been run.

Noah

On Wed, Sep 14, 2022 at 10:39 AM James Pustejovsky <jepusto at gmail.com>
wrote:

I'm interested in this question too. Noah, is there a reason you are

using

assign(".Random.seed",...) rather than set.seed()?

On Wed, Sep 14, 2022 at 9:31 AM Noah Greifer <noah.greifer at gmail.com>
wrote:

Hello fellow developers,

I am attempting to solve the problem of saving the state of the random
generator so that the state can be recovered in a future call.
Essentially,
my function generates random numbers, performs an operation on them
(saving
the result), and throws them out (saving them would require too much
memory). A second function is meant to take the output of the first
function, generate the same random numbers, and perform a different
operation on them.

This is exactly what happens in the *boot* package: the boot()

function

saves the random seed (extracted from .Random.Seed), and the

boot.array()

function extracts the saved seed from the boot() output, sets the

seed to

that value, re-generates the same set of random numbers, and then
re-sets the seed to what it was before boot.array() was called. This

has

the following benefits: 1) it allows the same random numbers to be

drawn;

2) the random numbers don't need to be saved, which is good because

they

would take up a lot of memory and boot.array() is an optional

function (it

is used in boot.ci() with type = "bca" for those curious); and 3) the
seed
carries on from where it left off before boot.array() was called

instead

of
being set to what it was after boot() was called.

This is implemented in boot in the following way (code abbreviated):

boot <- function(...) {
  seed <- .Random.Seed
  #Random numbers generated
  out <- list(seed = seed
                  #Other stuff is in this list
              )
  out
}

boot.array <- function(boot.out) {
  #Save current random seed in `temp`
  if (exists(".Random.seed", envir = .GlobalEnv, inherits = FALSE))
    temp <- get(".Random.seed", envir = .GlobalEnv, inherits = FALSE)
  else temp <- NULL

  #Assign saved seed from boot.out
  assign(".Random.seed", boot.out$seed, envir = .GlobalEnv)

  #Generate same random numbers from boot() call

  #Restore random seed to what it was before boot.array() call
  if (!is.null(temp))
    assign(".Random.seed", temp, envir = .GlobalEnv)
  else rm(.Random.seed, pos = 1)
}

This seems to work as intended. However, this violates the CRAN

policy of

changing the global environment. When I used this exact code in a

package

I
submitted, the package was rejected for it. The message I received was

Please do not modify the .GlobalEnv (e.g.: by changing the

.Random.seed

which is part of the global environment). This is not allowed by the

CRAN

policies.

I'm curious what you think the best course of action might be, and

what

the
current policy means for the *boot* package. Thanks for your help.

Noah

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