Pseudo-random number generators (PRNG).
With multiple domains, each domain has its own generator that evolves independently of the generators of other domains. When a domain is created, its generator is initialized by splitting the state of the generator associated with the parent domain.
In contrast, all threads within a domain share the same domain-local generator. Independent generators can be created with the Random.split function and used with the functions from the Random.State module.
Initialize the domain-local generator, using the argument as a seed. The same seed will always yield the same sequence of numbers.
Same as Random.init but takes more data as seed.
Initialize the domain-local generator with a random seed chosen in a system-dependent way. If /dev/urandom is available on the host machine, it is used to provide a highly random initial seed. Otherwise, a less random seed is computed from system parameters (current time, process IDs, domain-local state).
Random.int bound returns a random integer between 0 (inclusive) and bound (exclusive). bound must be greater than 0 and less than 230.
Random.full_int bound returns a random integer between 0 (inclusive) and bound (exclusive). bound may be any positive integer.
If bound is less than 230, Random.full_int bound is equal to Random.int bound. If bound is greater than 230 (on 64-bit systems or non-standard environments, such as JavaScript), Random.full_int returns a value, where Random.int raises Stdlib.Invalid_argument.
Random.int32 bound returns a random integer between 0 (inclusive) and bound (exclusive). bound must be greater than 0.
Random.int64 bound returns a random integer between 0 (inclusive) and bound (exclusive). bound must be greater than 0.
Random.float bound returns a random floating-point number between 0 and bound (inclusive). If bound is negative, the result is negative or zero. If bound is 0, the result is 0.
val bits32 : unit -> Int32.tRandom.bits32 () returns 32 random bits as an integer between Int32.min_int and Int32.max_int.
val bits64 : unit -> Int64.tRandom.bits64 () returns 64 random bits as an integer between Int64.min_int and Int64.max_int.
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.
module State : sig ... endval get_state : unit -> State.tget_state() returns a fresh copy of the current state of the domain-local generator (which is used by the basic functions).
val set_state : State.t -> unitset_state s updates the current state of the domain-local generator (which is used by the basic functions) by copying the state s into it.