## Module

Module Random## Documentation

Module
**Random**

:
**sig end**

Pseudo-random number generators (PRNG).

**=== **
**Basic functions**
**===**

*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 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).

*val bits *
:
**unit -> int**

Return 30 random bits in a nonnegative integer.

**Before3.12.0**
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 2^{30.

*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 and
**bound**
(inclusive). 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**
**===**

**=== **
**Advanced functions**
**===**

**=== 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 end**

*val get_state *
:
**unit -> State.t**

Return the current state of the generator used by the basic functions.

*val set_state *
:
**State.t -> unit**

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