module Random:`sig`

..`end`

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.

**Before 5.0**Random value generation used a different algorithm. This affects all the functions in this module which return random values.

`val init : ``int -> unit`

Initialize the domain-local 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 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).

`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 and less
than 2^{30}.

**Raises**`Invalid_argument`

if`bound`

<= 0 or`bound`

>= 2^{30}.

`val full_int : ``int -> int`

`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 2^{31},
then `Random.full_int bound`

yields identical output
across systems with varying `int`

sizes.

If `bound`

is less than 2^{30},
then `Random.full_int bound`

is equal to `Random.int`

` bound`

.

If `bound`

is at least 2^{30}
(on 64-bit systems, or non-standard environments such as JavaScript),
then `Random.full_int`

returns a value
whereas `Random.int`

raises `Invalid_argument`

.

**Since**4.13**Raises**`Invalid_argument`

if`bound`

<= 0.

`val int_in_range : ``min:int -> max:int -> int`

`Random.int_in_range ~min ~max`

returns a random integer
between `min`

(inclusive) and `max`

(inclusive).
Both `min`

and `max`

are allowed to be negative;
`min`

must be less than or equal to `max`

.

If both bounds fit in 32-bit signed integers
(that is, if -2^{31} <= `min`

and `max`

< 2^{31}),
then `int_in_range`

yields identical output
across systems with varying `int`

sizes.

**Since**5.2**Raises**`Invalid_argument`

if`min > max`

.

`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.

**Raises**`Invalid_argument`

if`bound`

<= 0.

`val int32_in_range : ``min:int32 -> max:int32 -> int32`

`Random.int32_in_range ~min ~max`

returns a random integer
between `min`

(inclusive) and `max`

(inclusive).
Both `min`

and `max`

are allowed to be negative;
`min`

must be less than or equal to `max`

.

**Since**5.2**Raises**`Invalid_argument`

if`min > max`

.

`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.

**Raises**`Invalid_argument`

if`bound`

<= 0.

`val nativeint_in_range : ``min:nativeint -> max:nativeint -> nativeint`

`Random.nativeint_in_range ~min ~max`

returns a random integer
between `min`

(inclusive) and `max`

(inclusive).
Both `min`

and `max`

are allowed to be negative;
`min`

must be less than or equal to `max`

.

**Since**5.2**Raises**`Invalid_argument`

if`min > max`

.

`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.

**Raises**`Invalid_argument`

if`bound`

<= 0.

`val int64_in_range : ``min:int64 -> max:int64 -> int64`

`Random.int64_in_range ~min ~max`

returns a random integer
between `min`

(inclusive) and `max`

(inclusive).
Both `min`

and `max`

are allowed to be negative;
`min`

must be less than or equal to `max`

.

**Since**5.2**Raises**`Invalid_argument`

if`min > max`

.

`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.

`val bits32 : ``unit -> Int32.t`

`Random.bits32 ()`

returns 32 random bits as an integer between
`Int32.min_int`

and `Int32.max_int`

.

**Since**4.14

`val bits64 : ``unit -> Int64.t`

`Random.bits64 ()`

returns 64 random bits as an integer between
`Int64.min_int`

and `Int64.max_int`

.

**Since**4.14

`val nativebits : ``unit -> Nativeint.t`

`Random.nativebits ()`

returns 32 or 64 random bits (depending on
the bit width of the platform) as an integer between
`Nativeint.min_int`

and `Nativeint.max_int`

.

**Since**4.14

The functions from module `Random.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`

`get_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 -> unit`

`set_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.

`val split : ``unit -> State.t`

Draw a fresh PRNG state from the current state of the domain-local
generator used by the default functions.
(The state of the domain-local generator is modified.)
See `Random.State.split`

.

**Since**5.0