Module Base__.Random

This is a slightly modified version of the OCaml standard library's random.mli. We want Base's Random module to be different from OCaml's standard one:

The fact that we construct our own default random state means that code using Core.Random and code using OCaml's Random will not share the default state.

Pseudo-random number generators (PRNG).

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 : ?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 non deterministic failures for everyone. Passing ~allow_in_tests:true removes this restriction in case you legitimately want non-deterministic 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 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 explicitly. This allows using one or several deterministic PRNGs, even in a multi-threaded program, without interference from other parts of the program.

val set_state : State.t ‑> unit

Set the state of the generator used by the basic functions.