### 10.31 Random Number Generator—`library(random)`

This library module provides a random number generator using algorithm AS 183 from the Journal of Applied Statistics as the basic algorithm.

The state of the random number generator corresponds to a term `random(X,Y,Z,B)` where X is an integer in the range [1,30268], Y is an integer in the range [1,30306], Z is an integer in the range [1,30322], and B is a nonzero integer.

Exported predicates:

`getrand(-RandomState)`

returns the random number generator’s current state

`setrand(+RandomState)`

sets the random number generator’s state to RandomState. RandomState can either be a random state previously obtained with `getrand/1`, or an arbitrary integer. The latter is useful when you want to initialize the random state to a fresh value. If RandomState is not an integer or a valid random state, it raises an error.

`maybe`

succeeds determinately with probability 1/2, fails with probability 1/2. We use a separate "random bit" generator for this test to avoid doing much arithmetic.

`maybe(+Probability)`

succeeds determinately with probability Probability, fails with probability 1-Probability. Arguments =< 0 always fail, >= 1 always succeed.

`maybe(+P, +N)`

succeeds determinately with probability P/N, where 0 =< P =< N and P and N are integers. If this condition is not met, it fails. It is equivalent to `random(0, N, X), X < P`, but is somewhat faster.

`random(-Uniform)`

unifies Uniform with a new random number in [0.0,1.0)

`random(+L, +U, -R)`

unifies R with a random integer in [L,U) when L and U are integers (note that U will never be generated), or to a random floating number in [L,U) otherwise.

`random_member(-Elem, +List)`

unifies Elem with a random element of List, which must be proper. Takes O(N) time (average and best case).

`random_select(?Elem, ?List, ?Rest)`

unifies Elem with a random element of List and Rest with all the other elements of List (in order). Either List or Rest should be proper, and List should/will have one more element than Rest. Takes O(N) time (average and best case).

`random_subseq(+List, -Sbsq, -Cmpl)`

unifies Sbsq with a random sub-sequence of List, and Cmpl with its complement. After this, `subseq(List, Sbsq, Cmpl)` will be true. Each of the 2**|List| solutions is equally likely. Like its name-sake `subseq/3`, if you supply Sbsq and Cmpl it will interleave them to find List. Takes O(N) time. List should be proper.

`random_permutation(?List, ?Perm)`

unifies Perm with a random permutation of List. Either List or Perm should be proper, and they should/will have the same length. Each of the N! permutations is equally likely, where `length(List, N)`. This takes O(N lg N) time and is bidirectional.

`random_perm2(A,B, X,Y)`

unifies X,Y = A,B or X,Y = B,A, making the choice at random, each choice being equally likely. It is equivalent to `random_permutation([A,B], [X,Y])`.

`random_numlist(+P, +L, +U, -List)`

where P is a probability (0..1) and L=<U are integers unifies List with a random subsequence of the integers L..U, each integer being included with probability P.

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