Random seed

Source: R/seed.R

with_seed() runs code with a specific random seed and resets it afterwards.

with_preserve_seed() runs code with the current random seed and resets it afterwards.

with_seed(
  seed,
  code,
  .rng_kind = NULL,
  .rng_normal_kind = NULL,
  .rng_sample_kind = NULL
)

local_seed(
  seed,
  .local_envir = parent.frame(),
  .rng_kind = NULL,
  .rng_normal_kind = NULL,
  .rng_sample_kind = NULL
)

with_preserve_seed(code)

local_preserve_seed(.local_envir = parent.frame())

Arguments

seed

[integer(1)]
The random seed to use to evaluate the code.

code

[any]
Code to execute in the temporary environment

.rng_kind, .rng_normal_kind, .rng_sample_kind

[character(1)]
Kind of RNG to use. Passed as the kind, normal.kind, and sample.kind arguments of RNGkind().

.local_envir

[environment]
The environment to use for scoping.

Value

[any]
The results of the evaluation of the code argument.

See also

withr for examples

Examples

# Same random values:
with_preserve_seed(runif(5))
#> [1] 0.10169262 0.76999328 0.08906143 0.53659237 0.26213892
with_preserve_seed(runif(5))
#> [1] 0.10169262 0.76999328 0.08906143 0.53659237 0.26213892

# Use a pseudorandom value as seed to advance the RNG and pick a different
# value for the next call:
with_seed(seed <- sample.int(.Machine$integer.max, 1L), runif(5))
#> [1] 0.5885083 0.3289879 0.4357050 0.2184870 0.3697503
with_seed(seed, runif(5))
#> [1] 0.5885083 0.3289879 0.4357050 0.2184870 0.3697503
with_seed(seed <- sample.int(.Machine$integer.max, 1L), runif(5))
#> [1] 0.6099326 0.6076366 0.4936592 0.6276273 0.5535448