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System.Random

Portability | portable
Stability | stable
Maintainer | libraries@haskell.org

Contents

The `RandomGen` class, and the `StdGen` generator
The `Random` class
The global random number generator
References

Description
Random numbers.
Synopsis

class RandomGen g where

next :: g -> (Int, g)
split :: g -> (g, g)
genRange :: g -> (Int, Int)

data StdGen
mkStdGen :: Int -> StdGen
class Random a where

random :: RandomGen g => g -> (a, g)
randomR :: RandomGen g => (a, a) -> g -> (a, g)
randoms :: RandomGen g => g -> [a]
randomRs :: RandomGen g => (a, a) -> g -> [a]
randomIO :: IO a
randomRIO :: (a, a) -> IO a

getStdRandom :: (StdGen -> (a, StdGen)) -> IO a
getStdGen :: IO StdGen
setStdGen :: StdGen -> IO ()
newStdGen :: IO StdGen

Documentation

This library deals with the common task of pseudo-random number generation. The library makes it possible to generate repeatable results, by starting with a specified initial random number generator; or to get different results on each run by using the system-initialised generator, or by supplying a seed from some other source.

The library is split into two layers:

- A core random number generator provides a supply of bits. The class `RandomGen` provides a common interface to such generators.
- The class `Random` provides a way to extract particular values from a random number generator. For example, the `Float` instance of `Random` allows one to generate random values of type `Float`.

Comment found in this file when merging with Library Report:

The June 1988 (v31 #6) issue of the Communications of the ACM has an article by Pierre L'Ecuyer called, Efficient and Portable Combined Random Number Generators. Here is the Portable Combined Generator of L'Ecuyer for 32-bit computers. It has a period of roughly 2.30584e18.

Transliterator: Lennart Augustsson

The `RandomGen` class, and the `StdGen` generator
class RandomGen g where

RandomGen The class `RandomGen` provides a common interface to random number generators.
Methods

next :: g -> (Int, g)
The `next` operation allows one to extract at least 30 bits (one `Int`'s worth) from the generator, returning a new generator as well. The integer returned may be positive or negative.
split :: g -> (g, g)
The `split` operation allows one to obtain two distinct random number generators. This is very useful in functional programs (for example, when passing a random number generator down to recursive calls), but very little work has been done on statistically robust implementations of `split ([1,4]` are the only examples we know of).
genRange :: g -> (Int, Int)

Instances

RandomGen StdGen

data StdGen

The System.Random library provides one instance of `RandomGen`, the abstract data type `StdGen`.

The result of repeatedly using next should be at least as statistically robust as the Minimal Standard Random Number Generator described by [System.Random#Park, System.Random#Carta]. Until more is known about implementations of `split`, all we require is that `split` deliver generators that are (a) not identical and (b) independently robust in the sense just given.

The `show`/`Read` instances of `StdGen` provide a primitive way to save the state of a random number generator. It is required that `read (show g) == g`.

In addition, `read` may be used to map an arbitrary string (not necessarily one produced by `show`) onto a value of type `StdGen`. In general, the `read` instance of `StdGen` has the following properties:

- It guarantees to succeed on any string.
- It guarantees to consume only a finite portion of the string.
- Different argument strings are likely to result in different results.

The function `mkStdGen` provides an alternative way of producing an initial generator, by mapping an `Int` into a generator. Again, distinct arguments should be likely to produce distinct generators.

Programmers may, of course, supply their own instances of `RandomGen`.

Instances

RandomGen StdGen
Show StdGen
Read StdGen

mkStdGen :: Int -> StdGen
The `Random` class
class Random a where

The `Random` class With a source of random number supply in hand, the `Random` class allows the programmer to extract random values of a variety of types.

- `randomR` takes a range (lo,hi) and a random number generator g, and 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.
- `random` does the same as `randomR`, but does not take a range.

1. For bounded types (instances of `Bounded`, such as `Char`), the range is normally the whole type.
2. For fractional types, the range is normally the semi-closed interval `[0,1)`.
3. For `Integer`, the range is (arbitrarily) the range of `Int`.

- The plural versions, `randomRs` and `randoms`, produce an infinite list of random values, and do not return a new generator.
- The `IO` versions, `randomRIO` and `randomIO`, use the global random number generator (see Section 17.3 http://www.haskell.org/onlinelibrary/random.html#global-rng).

Methods

random :: RandomGen g => g -> (a, g)
Minimal complete definition: `random` and `randomR`
randomR :: RandomGen g => (a, a) -> g -> (a, g)
randoms :: RandomGen g => g -> [a]
Default methods
randomRs :: RandomGen g => (a, a) -> g -> [a]
randomIO :: IO a
randomRIO :: (a, a) -> IO a

Instances

Random Int
Random Char
Random Bool
Random Integer
Random Double
Random Float

The global random number generator
There is a single, implicit, global random number generator of type `StdGen`, held in some global variable maintained by the `IO` monad. It is initialised automatically in some system-dependent fashion, for example, by using the time of day, or Linux's kernel random number generator. To get deterministic behaviour, use `setStdGen`.
getStdRandom :: (StdGen -> (a, StdGen)) -> IO a

`getStdRandom` uses the supplied function to get a value from the current global random generator, and updates the global generator with the new generator returned by the function. For example, `rollDice` gets a random integer between 1 and 6:

      rollDice :: IO Int
      rollDice = getStdRandom (randomR (1,6))

getStdGen :: IO StdGen
`getStdGen` gets the global random number generator.
setStdGen :: StdGen -> IO ()
`setStdGen` sets the global random number generator.
newStdGen :: IO StdGen
References

- [1] FW Burton and RL Page, Distributed random number generation, Journal of Functional Programming, 2(2):203-212, April 1992.
- [2] SK Park, and KW Miller, Random number generators - good ones are hard to find, Comm ACM 31(10), Oct 1988, pp1192-1201.
- [3] DG Carta, Two fast implementations of the minimal standard random number generator, Comm ACM, 33(1), Jan 1990, pp87-88.
- [4] P Hellekalek, Don't trust parallel Monte Carlo, Department of Mathematics, University of Salzburg, http://random.mat.sbg.ac.at/~peter/pads98.ps, 1998.

The Web site http://random.mat.sbg.ac.at/ is a great source of information.

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