A splittable pseudo-random number generator (SPRNG) functions like a PRNG in that it can be used as a stream of random values; it can also be "split" to produce a second, independent stream of random values.
This module implements a splittable pseudo-random number generator that sacrifices cryptographic-quality randomness in favor of performance.
The primary difference between Splittable_random and Random is the State.split
operation for generating new pseudo-random states. While it is easy to simulate
State.split using Random, the result has undesirable statistical properties; the
new state does not behave independently of the original. It is better to switch to
Splittable_random if you need an operation like State.split, as this module has
been implemented with the statistical properties of splitting in mind. For most other
purposes, Random is likely a better choice, as its implementation passes all Diehard
tests, while Splittable_random fails some Diehard tests.
module State : sig ... endProduce a random number uniformly distributed in the given inclusive range. (In the
case of float, hi may or may not be attainable, depending on rounding.)
val int32 : State.t ‑> lo:Base.int32 ‑> hi:Base.int32 ‑> Base.int32val int63 : State.t ‑> lo:Base.Int63.t ‑> hi:Base.Int63.t ‑> Base.Int63.tval int64 : State.t ‑> lo:Base.int64 ‑> hi:Base.int64 ‑> Base.int64val nativeint : State.t ‑> lo:Base.nativeint ‑> hi:Base.nativeint ‑> Base.nativeintval float : State.t ‑> lo:Base.float ‑> hi:Base.float ‑> Base.floatval unit_float : State.t ‑> Base.floatunit_float state = float state ~lo:0. ~hi:1., but slightly more efficient (and
right endpoint is exclusive).