random
(stdlib)Pseudo random number generation
Random number generator. The method is attributed to B.A. Wichmann and I.D.Hill, in 'An efficient and portable pseudo-random number generator', Journal of Applied Statistics. AS183. 1982. Also Byte March 1987.
The current algorithm is a modification of the version attributed to Richard A O'Keefe in the standard Prolog library.
Every time a random number is requested, a state is used to calculate
it, and a new state produced. The state can either be implicit (kept
in the process dictionary) or be an explicit argument and return value.
In this implementation, the state (the type ran()
) consists of a
tuple of three integers.
It should be noted that this random number generator is not cryptographically
strong. If a strong cryptographic random number generator is needed for
example crypto:rand_bytes/1
could be used instead.
Functions
seed() -> ran()
Seeds random number generation with default (fixed) values in the process dictionary, and returns the old state.
seed(A1, A2, A3) -> undefined | ran()
A1 = A2 = A3 = integer()
Seeds random number generation with integer values in the process dictionary, and returns the old state.
One way of obtaining a seed is to use the BIF now/0
:
... {A1,A2,A3} = now(), random:seed(A1, A2, A3), ...
seed({A1, A2, A3}) -> undefined | ran()
A1 = A2 = A3 = integer()
seed({A1, A2, A3})
is equivalent to seed(A1, A2, A3)
.
seed0() -> ran()
Returns the default state.
uniform()-> float()
Returns a random float uniformly distributed between 0.0
and 1.0
, updating the state in the process dictionary.
uniform(N) -> integer()
N = integer()
Given an integer N >= 1
, uniform/1
returns a
random integer uniformly distributed between 1
and
N
, updating the state in the process dictionary.
uniform_s(State0) -> {float(), State1}
State0 = State1 = ran()
Given a state, uniform_s/1
returns a random float uniformly
distributed between 0.0
and 1.0
, and a new state.
uniform_s(N, State0) -> {integer(), State1}
N = integer()
State0 = State1 = ran()
Given an integer N >= 1
and a state, uniform_s/2
returns a random integer uniformly distributed between 1
and
N
, and a new state.
Note
Some of the functions use the process dictionary variable
random_seed
to remember the current seed.
If a process calls uniform/0
or uniform/1
without
setting a seed first, seed/0
is called automatically.