Control.Monad.Random.Class

Takes a range (lo,hi) and a random number generator g, and returns a computation that returns a random value uniformly distributed in the closed interval [lo,hi], together with a new generator. It is unspecified what happens if lo>hi. For continuous types there is no requirement that the values lo and hi are ever produced, but they may be, depending on the implementation and the interval.

See randomR for details.

The same as getRandomR, but using a default range determined by the type:

• For bounded types (instances of Bounded, such as Char), the range is normally the whole type.

• For fractional types, the range is normally the semi-closed interval [0,1).

• For Integer, the range is (arbitrarily) the range of Int.

See random for details.

Plural variant of getRandomR, producing an infinite list of random values instead of returning a new generator.

See randomRs for details.

Plural variant of getRandom, producing an infinite list of random values instead of returning a new generator.

See randoms for details.

The getSplit operation allows one to obtain two distinct random number generators.

See split for details.

If x :: m a is a computation in some random monad, then interleave x works by splitting the generator, running x using one half, and using the other half as the final generator state of interleave x (replacing whatever the final generator state otherwise would have been). This means that computation needing random values which comes after interleave x does not necessarily depend on the computation of x. For example:

>>> evalRandIO $ snd <$> ((,) <$> undefined <*> getRandom)
*** Exception: Prelude.undefined
>>> evalRandIO $ snd <$> ((,) <$> interleave undefined <*> getRandom)
6192322188769041625

This can be used, for example, to allow random computations to run in parallel, or to create lazy infinite structures of random values. In the example below, the infinite tree randTree cannot be evaluated lazily: even though it is cut off at two levels deep by hew 2, the random value in the right subtree still depends on generation of all the random values in the (infinite) left subtree, even though they are ultimately unneeded. Inserting a call to interleave, as in randTreeI, solves the problem: the generator splits at each Node, so random values in the left and right subtrees are generated independently.

data Tree = Leaf | Node Int Tree Tree deriving Show

hew :: Int -> Tree -> Tree
hew 0 _    = Leaf
hew _ Leaf = Leaf
hew n (Node x l r) = Node x (hew (n-1) l) (hew (n-1) r)

randTree :: Rand StdGen Tree
randTree = Node <$> getRandom <*> randTree <*> randTree

randTreeI :: Rand StdGen Tree
randTreeI = interleave $ Node <$> getRandom <*> randTreeI <*> randTreeI

>>> hew 2 <$> evalRandIO randTree
Node 2168685089479838995 (Node (-1040559818952481847) Leaf Leaf) (Node ^CInterrupted.
>>> hew 2 <$> evalRandIO randTreeI
Node 8243316398511136358 (Node 4139784028141790719 Leaf Leaf) (Node 4473998613878251948 Leaf Leaf)