iterors (version 1.0)

iRNGStream: Iterators returning distant random-number seeds.

Description

The iRNGStream creates a sequence of random number seeds that are very "far apart" (2^127 steps) in the overall random number sequence, so that each can be used to make a parallel, psudo-independent random iterator. This uses parallel::nextRNGStream and the "L'Ecuyer-CMRG" generator.

Usage

iRNGStream(seed)

Value

An iteror which produces seed values. vector to be passed to nextRNGStream or nextRNGSubStream.

An iteror which yields successive seed values.

Arguments

seed

Either a single number to be passed to set.seed or a

Details

iRNGSubStream creates seeds that are somewhat less far apart (2^76 steps), which might be used as "substream" seeds.

Originally from the itertools package.

References

For more details on the L'Ecuyer-CMRG generator, see vignette("parallel", package="parallel").

See Also

set.seed, nextRNGStream, nextRNGSubStream

Examples

global.seed <- .Random.seed

rng.seeds <- iRNGStream(313)
print(nextOr(rng.seeds))
print(nextOr(rng.seeds))

# create three pseudo-independent and
# reproducible random number streams
it1 <- isample(c(0, 1), 1, seed=nextOr(rng.seeds))
it2 <- isample(c(0, 1), 1, seed=nextOr(rng.seeds))
it3 <- isample(c(0, 1), 1, seed=nextOr(rng.seeds))

all(.Random.seed == global.seed)
take(it1, 5, "numeric") # 0 0 0 1 1
take(it2, 5, "numeric") # 0 1 1 1 1
take(it3, 5, "numeric") # 1 1 1 0 0

# none of this affects the global seed
all(global.seed == .Random.seed)

# \donttest{
# Compute random numbers in three parallel processes with three
# well-separated seeds. Requires package "foreach"
library(foreach)
foreach(1:3, rseed=iRNGSubStream(1970), .combine='c') %dopar% {
  RNGkind("L'Ecuyer-CMRG") # would be better to initialize workers only once
  assign('.Random.seed', rseed, pos=.GlobalEnv)
  runif(1)
}
# }