Pseudo-random number generation.
This is a wrapper of the standard library's Random
library, though it does not share
state with that library.
Note that all of these "basic" functions mutate a global random state.
val init : int ‑> unit
Initialize the generator, using the argument as a seed. The same seed will always yield the same sequence of numbers.
val self_init : ?allow_in_tests:bool ‑> unit ‑> unit
Initialize the generator with a more-or-less random seed chosen in a system-dependent
way. By default, self_init
is disallowed in inline tests, as it's often used for no
good reason and it just creates nondeterministic failures for everyone. Passing
~allow_in_tests:true
removes this restriction in case you legitimately want
nondeterministic values, like in Filename.temp_dir
.
val bits : unit ‑> int
Return 30 random bits in a nonnegative integer.
val int : int ‑> int
Random.int bound
returns a random integer between 0 (inclusive) and bound
(exclusive). bound
must be greater than 0.
val int32 : int32 ‑> int32
Random.int32 bound
returns a random integer between 0 (inclusive) and bound
(exclusive). bound
must be greater than 0.
val nativeint : nativeint ‑> nativeint
Random.nativeint bound
returns a random integer between 0 (inclusive) and bound
(exclusive). bound
must be greater than 0.
val int64 : int64 ‑> int64
Random.int64 bound
returns a random integer between 0 (inclusive) and bound
(exclusive). bound
must be greater than 0.
val float : float ‑> float
Random.float bound
returns a random floating-point number between 0 (inclusive) and
bound
(exclusive). If bound
is negative, the result is negative or zero. If
bound
is 0, the result is 0.
val int_incl : int ‑> int ‑> int
Produces a random value between the given inclusive bounds. Raises if bounds are given in decreasing order.
val float_range : float ‑> float ‑> float
Produces a value between the given bounds (inclusive and exclusive, respectively). Raises if bounds are given in decreasing order.
module State : sig ... end
The functions from module State
manipulate the current state of the random generator
explicitly. This allows using one or several deterministic PRNGs, even in a
multi-threaded program, without interference from other parts of the program.