module Random: Random
Basic functions
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 full_init : int array -> unit
Same as Random.init but takes more data as seed.
val self_init : unit -> unit
Initialize the generator with a more-or-less random seed chosen in a system-dependent
way.
val bits : unit -> int
Return 30 random bits in a nonnegative integer.
Before 3.12.0 used a different
algorithm (affects all the following functions)
val int : int -> int
Random.int bound returns a random integer between 0 (inclusive) and bound
(exclusive). bound must be greater than 0 and less than 230.
val int32 : Int32.t -> Int32.t
Random.int32 bound returns a random integer between 0 (inclusive) and bound
(exclusive). bound must be greater than 0.
val nativeint : Nativeint.t -> Nativeint.t
Random.nativeint bound returns a random integer between 0 (inclusive) and bound
(exclusive). bound must be greater than 0.
val int64 : Int64.t -> Int64.t
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 bool : unit -> bool
Random.bool () returns true or false with probability 0.5 each.
Advanced functions
module State: sig .. end
The functions from module State manipulate the current state
of the random generator explicitely.
val get_state : unit -> [ `Consider_using_Random_State_default ]
OCaml's Random.get_state makes a copy of the default state, which is almost
certainly not what you want. State.default, which is the actual default state, is
probably what you want.
val set_state : State.t -> unit
Set the state of the generator used by the basic functions.