System.Random

random-1.3.0: Pseudo-random number generation

Copyright | (c) The University of Glasgow 2001
License | BSD-style (see the file LICENSE in the 'random' repository)
Maintainer | libraries@haskell.org
Stability | stable
Safe Haskell | Trustworthy
Language | Haskell2010

System.Random

Contents

- Introduction
- Usage
- Pure number generator interface
  - Seed
- Generators for sequences of pseudo-random bytes
  - Lists
  - Bytes
    - Deprecated
  - Standard pseudo-random number generator
  - Global standard pseudo-random number generator
- Compatibility and reproducibility
  - Backwards compatibility and deprecations
  - Reproducibility
- Notes for pseudo-random number generator implementors
  - How to implement `RandomGen`
- References

Description

This library deals with the common task of pseudo-random number generation.

Synopsis

- class RandomGen g where
  - genWord8 :: g -> (Word8, g)
  - genWord16 :: g -> (Word16, g)
  - genWord32 :: g -> (Word32, g)
  - genWord64 :: g -> (Word64, g)
  - genWord32R :: Word32 -> g -> (Word32, g)
  - genWord64R :: Word64 -> g -> (Word64, g)
  - unsafeUniformFillMutableByteArray :: MutableByteArray s -> Int -> Int -> g -> ST s g
  - split :: g -> (g, g)
- class RandomGen g => SplitGen g where
  - splitGen :: g -> (g, g)
- uniform :: (Uniform a, RandomGen g) => g -> (a, g)
- uniformR :: (UniformRange a, RandomGen g) => (a, a) -> g -> (a, g)
- class Random a where
  - randomR :: RandomGen g => (a, a) -> g -> (a, g)
  - random :: RandomGen g => g -> (a, g)
  - randomRs :: RandomGen g => (a, a) -> g -> [a]
  - randoms :: RandomGen g => g -> [a]
- class Uniform a
- class UniformRange a
- class Finite a
- data Seed g
- class (KnownNat (SeedSize g), 1 <= SeedSize g, Typeable g) => SeedGen g where
  - type SeedSize g :: Nat
  - fromSeed :: Seed g -> g
  - toSeed :: g -> Seed g
  - fromSeed64 :: NonEmpty Word64 -> g
  - toSeed64 :: g -> NonEmpty Word64
- seedSize :: SeedGen g => Int
- seedSizeProxy :: forall proxy g. SeedGen g => proxy g -> Int
- mkSeed :: (SeedGen g, MonadFail m) => ByteArray -> m (Seed g)
- unSeed :: Seed g -> ByteArray
- mkSeedFromByteString :: (SeedGen g, MonadFail m) => ByteString -> m (Seed g)
- unSeedToByteString :: Seed g -> ByteString
- withSeed :: SeedGen g => Seed g -> (g -> (a, g)) -> (a, Seed g)
- withSeedM :: (SeedGen g, Functor f) => Seed g -> (g -> f (a, g)) -> f (a, Seed g)
- withSeedFile :: (SeedGen g, MonadIO m) => FilePath -> (Seed g -> m (a, Seed g)) -> m a
- seedGenTypeName :: SeedGen g => String
- nonEmptyToSeed :: SeedGen g => NonEmpty Word64 -> Seed g
- nonEmptyFromSeed :: SeedGen g => Seed g -> NonEmpty Word64
- type family SeedSize g :: Nat
- uniforms :: (Uniform a, RandomGen g) => g -> [a]
- uniformRs :: (UniformRange a, RandomGen g) => (a, a) -> g -> [a]
- uniformList :: (Uniform a, RandomGen g) => Int -> g -> ([a], g)
- uniformListR :: (UniformRange a, RandomGen g) => Int -> (a, a) -> g -> ([a], g)
- uniformShuffleList :: RandomGen g => [a] -> g -> ([a], g)
- uniformByteArray :: RandomGen g => Bool -> Int -> g -> (ByteArray, g)
- uniformByteString :: RandomGen g => Int -> g -> (ByteString, g)
- uniformShortByteString :: RandomGen g => Int -> g -> (ShortByteString, g)
- uniformFillMutableByteArray :: RandomGen g => MutableByteArray s -> Int -> Int -> g -> ST s g
- genByteString :: RandomGen g => Int -> g -> (ByteString, g)
- genShortByteString :: RandomGen g => Int -> g -> (ShortByteString, g)
- data StdGen
- mkStdGen :: Int -> StdGen
- mkStdGen64 :: Word64 -> StdGen
- initStdGen :: MonadIO m => m StdGen
- getStdRandom :: MonadIO m => (StdGen -> (a, StdGen)) -> m a
- getStdGen :: MonadIO m => m StdGen
- setStdGen :: MonadIO m => StdGen -> m ()
- newStdGen :: MonadIO m => m StdGen
- randomIO :: (Random a, MonadIO m) => m a
- randomRIO :: (Random a, MonadIO m) => (a, a) -> m a
- genRange :: RandomGen g => g -> (Int, Int)
- next :: RandomGen g => g -> (Int, g)

# Introduction

This module provides type classes and instances for the following concepts:

Pure pseudo-random number generators
  `RandomGen` is an interface to pure pseudo-random number generators.

  `StdGen`, the standard pseudo-random number generator provided in this library, is an instance of `RandomGen`. It uses the SplitMix implementation provided by the splitmix package. Programmers may, of course, supply their own instances of `RandomGen`.

# Usage

In pure code, use `uniform` and `uniformR` to generate pseudo-random values with a pure pseudo-random number generator like `StdGen`.

    >>> :{
    let rolls :: RandomGen g => Int -> g -> [Word]
        rolls n = fst . uniformListR n (1, 6)
        pureGen = mkStdGen 137
    in
        rolls 10 pureGen :: [Word]
    :}
    [4,2,6,1,6,6,5,1,1,5]

To run use a monadic pseudo-random computation in pure code with a pure pseudo-random number generator, use `runStateGen` and its variants.

    >>> :{
    let rollsM :: StatefulGen g m => Int -> g -> m [Word]
        rollsM n = uniformListRM n (1, 6)
        pureGen = mkStdGen 137
    in
        runStateGen_ pureGen (rollsM 10) :: [Word]
    :}
    [4,2,6,1,6,6,5,1,1,5]

# Pure number generator interface

Pseudo-random number generators come in two flavours: pure and monadic.

`RandomGen`: pure pseudo-random number generators
  These generators produce a new pseudo-random value together with a new instance of the pseudo-random number generator.

  Pure pseudo-random number generators should implement `split` if they are splittable, that is, if there is an efficient method to turn one generator into two. The pseudo-random numbers produced by the two resulting generators should not be correlated. See [1] for some background on splittable pseudo-random generators.

`StatefulGen`: monadic pseudo-random number generators
  See System.Random.Stateful module

class RandomGen g where #

`RandomGen` is an interface to pure pseudo-random number generators.

`StdGen` is the standard `RandomGen` instance provided by this library.

Since: 1.0.0

Minimal complete definition

(genWord32 | genWord64 | next, genRange)

Methods

genWord8 :: g -> (Word8, g) #

Returns a `Word8` that is uniformly distributed over the entire `Word8` range.

Since: 1.2.0

genWord16 :: g -> (Word16, g) #

Returns a `Word16` that is uniformly distributed over the entire `Word16` range.

Since: 1.2.0

genWord32 :: g -> (Word32, g) #

Returns a `Word32` that is uniformly distributed over the entire `Word32` range.

Since: 1.2.0

genWord64 :: g -> (Word64, g) #

Returns a `Word64` that is uniformly distributed over the entire `Word64` range.

Since: 1.2.0

genWord32R :: Word32 -> g -> (Word32, g) #

`genWord32R upperBound g` returns a `Word32` that is uniformly distributed over the range `[0, upperBound]`.

Since: 1.2.0

genWord64R :: Word64 -> g -> (Word64, g) #

`genWord64R upperBound g` returns a `Word64` that is uniformly distributed over the range `[0, upperBound]`.

Since: 1.2.0

unsafeUniformFillMutableByteArray #

Arguments

:: MutableByteArray s | Mutable array to fill with random bytes
-> Int | Offset into a mutable array from the beginning in number of bytes. Offset must be non-negative, but this will not be checked
-> Int | Number of randomly generated bytes to write into the array. Number of bytes must be non-negative and less then the total size of the array, minus the offset. This also will be checked.
-> g |
-> ST s g |

Fill in the supplied `MutableByteArray` with uniformly generated random bytes. This function is unsafe because it is not required to do any bounds checking. For a safe variant use `uniformFillMutableByteArrayM` instead.

Default type class implementation uses `defaultUnsafeUniformFillMutableByteArray`.

Since: 1.3.0

split :: g -> (g, g) #

Deprecated: In favor of `splitGen`

Returns two distinct pseudo-random number generators.

Implementations should take care to ensure that the resulting generators are not correlated. Some pseudo-random number generators are not splittable. In that case, the `split` implementation should fail with a descriptive `error` message.

Since: 1.0.0

default split :: SplitGen g => g -> (g, g) #

#### Instances

Instances details

RandomGen StdGen # |
Instance details Defined in System.Random.Internal Methods next :: StdGen -> (Int, StdGen) # genWord8 :: StdGen -> (Word8, StdGen) # genWord16 :: StdGen -> (Word16, StdGen) # genWord32 :: StdGen -> (Word32, StdGen) # genWord64 :: StdGen -> (Word64, StdGen) # genWord32R :: Word32 -> StdGen -> (Word32, StdGen) # genWord64R :: Word64 -> StdGen -> (Word64, StdGen) # genShortByteString :: Int -> StdGen -> (ShortByteString, StdGen) # unsafeUniformFillMutableByteArray :: MutableByteArray s -> Int -> Int -> StdGen -> ST s StdGen # genRange :: StdGen -> (Int, Int) # split :: StdGen -> (StdGen, StdGen) #
RandomGen SMGen # |
Instance details Defined in System.Random.Internal Methods next :: SMGen -> (Int, SMGen) # genWord8 :: SMGen -> (Word8, SMGen) # genWord16 :: SMGen -> (Word16, SMGen) # genWord32 :: SMGen -> (Word32, SMGen) # genWord64 :: SMGen -> (Word64, SMGen) # genWord32R :: Word32 -> SMGen -> (Word32, SMGen) # genWord64R :: Word64 -> SMGen -> (Word64, SMGen) # genShortByteString :: Int -> SMGen -> (ShortByteString, SMGen) # unsafeUniformFillMutableByteArray :: MutableByteArray s -> Int -> Int -> SMGen -> ST s SMGen # genRange :: SMGen -> (Int, Int) # split :: SMGen -> (SMGen, SMGen) #
RandomGen SMGen # |
Instance details Defined in System.Random.Internal Methods next :: SMGen -> (Int, SMGen) # genWord8 :: SMGen -> (Word8, SMGen) # genWord16 :: SMGen -> (Word16, SMGen) # genWord32 :: SMGen -> (Word32, SMGen) # genWord64 :: SMGen -> (Word64, SMGen) # genWord32R :: Word32 -> SMGen -> (Word32, SMGen) # genWord64R :: Word64 -> SMGen -> (Word64, SMGen) # genShortByteString :: Int -> SMGen -> (ShortByteString, SMGen) # unsafeUniformFillMutableByteArray :: MutableByteArray s -> Int -> Int -> SMGen -> ST s SMGen # genRange :: SMGen -> (Int, Int) # split :: SMGen -> (SMGen, SMGen) #
RandomGen g => RandomGen (StateGen g) # |
Instance details Defined in System.Random.Internal Methods next :: StateGen g -> (Int, StateGen g) # genWord8 :: StateGen g -> (Word8, StateGen g) # genWord16 :: StateGen g -> (Word16, StateGen g) # genWord32 :: StateGen g -> (Word32, StateGen g) # genWord64 :: StateGen g -> (Word64, StateGen g) # genWord32R :: Word32 -> StateGen g -> (Word32, StateGen g) # genWord64R :: Word64 -> StateGen g -> (Word64, StateGen g) # genShortByteString :: Int -> StateGen g -> (ShortByteString, StateGen g) # unsafeUniformFillMutableByteArray :: MutableByteArray s -> Int -> Int -> StateGen g -> ST s (StateGen g) # genRange :: StateGen g -> (Int, Int) # split :: StateGen g -> (StateGen g, StateGen g) #
RandomGen g => RandomGen (AtomicGen g) # |
Instance details Defined in System.Random.Stateful Methods next :: AtomicGen g -> (Int, AtomicGen g) # genWord8 :: AtomicGen g -> (Word8, AtomicGen g) # genWord16 :: AtomicGen g -> (Word16, AtomicGen g) # genWord32 :: AtomicGen g -> (Word32, AtomicGen g) # genWord64 :: AtomicGen g -> (Word64, AtomicGen g) # genWord32R :: Word32 -> AtomicGen g -> (Word32, AtomicGen g) # genWord64R :: Word64 -> AtomicGen g -> (Word64, AtomicGen g) # genShortByteString :: Int -> AtomicGen g -> (ShortByteString, AtomicGen g) # unsafeUniformFillMutableByteArray :: MutableByteArray s -> Int -> Int -> AtomicGen g -> ST s (AtomicGen g) # genRange :: AtomicGen g -> (Int, Int) # split :: AtomicGen g -> (AtomicGen g, AtomicGen g) #
RandomGen g => RandomGen (IOGen g) # |
Instance details Defined in System.Random.Stateful Methods next :: IOGen g -> (Int, IOGen g) # genWord8 :: IOGen g -> (Word8, IOGen g) # genWord16 :: IOGen g -> (Word16, IOGen g) # genWord32 :: IOGen g -> (Word32, IOGen g) # genWord64 :: IOGen g -> (Word64, IOGen g) # genWord32R :: Word32 -> IOGen g -> (Word32, IOGen g) # genWord64R :: Word64 -> IOGen g -> (Word64, IOGen g) # genShortByteString :: Int -> IOGen g -> (ShortByteString, IOGen g) # unsafeUniformFillMutableByteArray :: MutableByteArray s -> Int -> Int -> IOGen g -> ST s (IOGen g) # genRange :: IOGen g -> (Int, Int) # split :: IOGen g -> (IOGen g, IOGen g) #
RandomGen g => RandomGen (STGen g) # |
Instance details Defined in System.Random.Stateful Methods next :: STGen g -> (Int, STGen g) # genWord8 :: STGen g -> (Word8, STGen g) # genWord16 :: STGen g -> (Word16, STGen g) # genWord32 :: STGen g -> (Word32, STGen g) # genWord64 :: STGen g -> (Word64, STGen g) # genWord32R :: Word32 -> STGen g -> (Word32, STGen g) # genWord64R :: Word64 -> STGen g -> (Word64, STGen g) # genShortByteString :: Int -> STGen g -> (ShortByteString, STGen g) # unsafeUniformFillMutableByteArray :: MutableByteArray s -> Int -> Int -> STGen g -> ST s (STGen g) # genRange :: STGen g -> (Int, Int) # split :: STGen g -> (STGen g, STGen g) #
RandomGen g => RandomGen (TGen g) # |
Instance details Defined in System.Random.Stateful Methods next :: TGen g -> (Int, TGen g) # genWord8 :: TGen g -> (Word8, TGen g) # genWord16 :: TGen g -> (Word16, TGen g) # genWord32 :: TGen g -> (Word32, TGen g) # genWord64 :: TGen g -> (Word64, TGen g) # genWord32R :: Word32 -> TGen g -> (Word32, TGen g) # genWord64R :: Word64 -> TGen g -> (Word64, TGen g) # genShortByteString :: Int -> TGen g -> (ShortByteString, TGen g) # unsafeUniformFillMutableByteArray :: MutableByteArray s -> Int -> Int -> TGen g -> ST s (TGen g) # genRange :: TGen g -> (Int, Int) # split :: TGen g -> (TGen g, TGen g) #

class RandomGen g => SplitGen g where #

Pseudo-random generators that can be split into two separate and independent psuedo-random generators should provide an instance for this type class.

Historically this functionality was included in the `RandomGen` type class in the `split` function, however, few pseudo-random generators possess this property of splittability. This lead the old `split` function being usually implemented in terms of `error`.

Since: 1.3.0

Methods

splitGen :: g -> (g, g) #

Returns two distinct pseudo-random number generators.

Implementations should take care to ensure that the resulting generators are not correlated.

Since: 1.3.0

#### Instances

Instances details

SplitGen StdGen # |
Instance details Defined in System.Random.Internal Methods splitGen :: StdGen -> (StdGen, StdGen) #
SplitGen SMGen # |
Instance details Defined in System.Random.Internal Methods splitGen :: SMGen -> (SMGen, SMGen) #
SplitGen SMGen # |
Instance details Defined in System.Random.Internal Methods splitGen :: SMGen -> (SMGen, SMGen) #
SplitGen g => SplitGen (AtomicGen g) # |
Instance details Defined in System.Random.Stateful Methods splitGen :: AtomicGen g -> (AtomicGen g, AtomicGen g) #
SplitGen g => SplitGen (IOGen g) # |
Instance details Defined in System.Random.Stateful Methods splitGen :: IOGen g -> (IOGen g, IOGen g) #
SplitGen g => SplitGen (STGen g) # |
Instance details Defined in System.Random.Stateful Methods splitGen :: STGen g -> (STGen g, STGen g) #
SplitGen g => SplitGen (TGen g) # |
Instance details Defined in System.Random.Stateful Methods splitGen :: TGen g -> (TGen g, TGen g) #

uniform :: (Uniform a, RandomGen g) => g -> (a, g) #

Generates a value uniformly distributed over all possible values of that type.

This is a pure version of `uniformM`.

#### Examples

Expand

    >>> import System.Random
    >>> let pureGen = mkStdGen 137
    >>> uniform pureGen :: (Bool, StdGen)
    (True,StdGen {unStdGen = SMGen 11285859549637045894 7641485672361121627})

You can use type applications to disambiguate the type of the generated numbers:

    >>> :seti -XTypeApplications
    >>> uniform @Bool pureGen
    (True,StdGen {unStdGen = SMGen 11285859549637045894 7641485672361121627})

Since: 1.2.0

uniformR :: (UniformRange a, RandomGen g) => (a, a) -> g -> (a, g) #

Generates a value uniformly distributed over the provided range, which is interpreted as inclusive in the lower and upper bound.

- `uniformR (1 :: Int, 4 :: Int)` generates values uniformly from the set \(\{1,2,3,4\}\)
- `uniformR (1 :: Float, 4 :: Float)` generates values uniformly from the set \(\{x\;|\;1 \le x \le 4\}\)

The following law should hold to make the function always defined:

    uniformR (a, b) = uniformR (b, a)

This is a pure version of `uniformRM`.

#### Examples

Expand

    >>> import System.Random
    >>> let pureGen = mkStdGen 137
    >>> uniformR (1 :: Int, 4 :: Int) pureGen
    (4,StdGen {unStdGen = SMGen 11285859549637045894 7641485672361121627})

You can use type applications to disambiguate the type of the generated numbers:

    >>> :seti -XTypeApplications
    >>> uniformR @Int (1, 4) pureGen
    (4,StdGen {unStdGen = SMGen 11285859549637045894 7641485672361121627})

Since: 1.2.0

class Random a where #

The class of types for which random values can be generated. Most instances of `Random` will produce values that are uniformly distributed on the full range, but for those types without a well-defined "full range" some sensible default subrange will be selected.

`Random` exists primarily for backwards compatibility with version 1.1 of this library. In new code, use the better specified `Uniform` and `UniformRange` instead.

Since: 1.0.0

Minimal complete definition

Nothing

Methods

randomR :: RandomGen g => (a, a) -> g -> (a, g) #

Takes a range (lo,hi) and a pseudo-random number generator g, and returns a pseudo-random value uniformly distributed over the closed interval [lo,hi], together with a new generator. It is unspecified what happens if lo>hi, but usually the values will simply get swapped.

    >>> let gen = mkStdGen 26
    >>> fst $ randomR ('a', 'z') gen
    'z'
    >>> fst $ randomR ('a', 'z') gen
    'z'

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.

There is no requirement to follow the `Ord` instance and the concept of range can be defined on per type basis. For example product types will treat their values independently:

    >>> fst $ randomR (('a', 5.0), ('z', 10.0)) $ mkStdGen 26
    ('z',5.22694980853051)

In case when a lawful range is desired `uniformR` should be used instead.

Since: 1.0.0

default randomR :: (RandomGen g, UniformRange a) => (a, a) -> g -> (a, g) #

random :: RandomGen g => g -> (a, g) #

The same as `randomR`, 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 floating point types, the range is normally the closed interval `[0,1]`.
- For `Integer`, the range is (arbitrarily) the range of `Int`.

Since: 1.0.0

default random :: (RandomGen g, Uniform a) => g -> (a, g) #

randomRs :: RandomGen g => (a, a) -> g -> [a] #

Plural variant of `randomR`, producing an infinite list of pseudo-random values instead of returning a new generator.

Since: 1.0.0

randoms :: RandomGen g => g -> [a] #

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

Since: 1.0.0

#### Instances

Instances details

Random CBool # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CBool, CBool) -> g -> (CBool, g) # random :: RandomGen g => g -> (CBool, g) # randomRs :: RandomGen g => (CBool, CBool) -> g -> [CBool] # randoms :: RandomGen g => g -> [CBool] #
Random CChar # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CChar, CChar) -> g -> (CChar, g) # random :: RandomGen g => g -> (CChar, g) # randomRs :: RandomGen g => (CChar, CChar) -> g -> [CChar] # randoms :: RandomGen g => g -> [CChar] #
Random CDouble # | Note - `random` produces values in the closed range `[0,1]`.
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CDouble, CDouble) -> g -> (CDouble, g) # random :: RandomGen g => g -> (CDouble, g) # randomRs :: RandomGen g => (CDouble, CDouble) -> g -> [CDouble] # randoms :: RandomGen g => g -> [CDouble] #
Random CFloat # | Note - `random` produces values in the closed range `[0,1]`.
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CFloat, CFloat) -> g -> (CFloat, g) # random :: RandomGen g => g -> (CFloat, g) # randomRs :: RandomGen g => (CFloat, CFloat) -> g -> [CFloat] # randoms :: RandomGen g => g -> [CFloat] #
Random CInt # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CInt, CInt) -> g -> (CInt, g) # random :: RandomGen g => g -> (CInt, g) # randomRs :: RandomGen g => (CInt, CInt) -> g -> [CInt] # randoms :: RandomGen g => g -> [CInt] #
Random CIntMax # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CIntMax, CIntMax) -> g -> (CIntMax, g) # random :: RandomGen g => g -> (CIntMax, g) # randomRs :: RandomGen g => (CIntMax, CIntMax) -> g -> [CIntMax] # randoms :: RandomGen g => g -> [CIntMax] #
Random CIntPtr # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CIntPtr, CIntPtr) -> g -> (CIntPtr, g) # random :: RandomGen g => g -> (CIntPtr, g) # randomRs :: RandomGen g => (CIntPtr, CIntPtr) -> g -> [CIntPtr] # randoms :: RandomGen g => g -> [CIntPtr] #
Random CLLong # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CLLong, CLLong) -> g -> (CLLong, g) # random :: RandomGen g => g -> (CLLong, g) # randomRs :: RandomGen g => (CLLong, CLLong) -> g -> [CLLong] # randoms :: RandomGen g => g -> [CLLong] #
Random CLong # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CLong, CLong) -> g -> (CLong, g) # random :: RandomGen g => g -> (CLong, g) # randomRs :: RandomGen g => (CLong, CLong) -> g -> [CLong] # randoms :: RandomGen g => g -> [CLong] #
Random CPtrdiff # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CPtrdiff, CPtrdiff) -> g -> (CPtrdiff, g) # random :: RandomGen g => g -> (CPtrdiff, g) # randomRs :: RandomGen g => (CPtrdiff, CPtrdiff) -> g -> [CPtrdiff] # randoms :: RandomGen g => g -> [CPtrdiff] #
Random CSChar # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CSChar, CSChar) -> g -> (CSChar, g) # random :: RandomGen g => g -> (CSChar, g) # randomRs :: RandomGen g => (CSChar, CSChar) -> g -> [CSChar] # randoms :: RandomGen g => g -> [CSChar] #
Random CShort # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CShort, CShort) -> g -> (CShort, g) # random :: RandomGen g => g -> (CShort, g) # randomRs :: RandomGen g => (CShort, CShort) -> g -> [CShort] # randoms :: RandomGen g => g -> [CShort] #
Random CSigAtomic # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CSigAtomic, CSigAtomic) -> g -> (CSigAtomic, g) # random :: RandomGen g => g -> (CSigAtomic, g) # randomRs :: RandomGen g => (CSigAtomic, CSigAtomic) -> g -> [CSigAtomic] # randoms :: RandomGen g => g -> [CSigAtomic] #
Random CSize # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CSize, CSize) -> g -> (CSize, g) # random :: RandomGen g => g -> (CSize, g) # randomRs :: RandomGen g => (CSize, CSize) -> g -> [CSize] # randoms :: RandomGen g => g -> [CSize] #
Random CUChar # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CUChar, CUChar) -> g -> (CUChar, g) # random :: RandomGen g => g -> (CUChar, g) # randomRs :: RandomGen g => (CUChar, CUChar) -> g -> [CUChar] # randoms :: RandomGen g => g -> [CUChar] #
Random CUInt # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CUInt, CUInt) -> g -> (CUInt, g) # random :: RandomGen g => g -> (CUInt, g) # randomRs :: RandomGen g => (CUInt, CUInt) -> g -> [CUInt] # randoms :: RandomGen g => g -> [CUInt] #
Random CUIntMax # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CUIntMax, CUIntMax) -> g -> (CUIntMax, g) # random :: RandomGen g => g -> (CUIntMax, g) # randomRs :: RandomGen g => (CUIntMax, CUIntMax) -> g -> [CUIntMax] # randoms :: RandomGen g => g -> [CUIntMax] #
Random CUIntPtr # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CUIntPtr, CUIntPtr) -> g -> (CUIntPtr, g) # random :: RandomGen g => g -> (CUIntPtr, g) # randomRs :: RandomGen g => (CUIntPtr, CUIntPtr) -> g -> [CUIntPtr] # randoms :: RandomGen g => g -> [CUIntPtr] #
Random CULLong # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CULLong, CULLong) -> g -> (CULLong, g) # random :: RandomGen g => g -> (CULLong, g) # randomRs :: RandomGen g => (CULLong, CULLong) -> g -> [CULLong] # randoms :: RandomGen g => g -> [CULLong] #
Random CULong # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CULong, CULong) -> g -> (CULong, g) # random :: RandomGen g => g -> (CULong, g) # randomRs :: RandomGen g => (CULong, CULong) -> g -> [CULong] # randoms :: RandomGen g => g -> [CULong] #
Random CUShort # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CUShort, CUShort) -> g -> (CUShort, g) # random :: RandomGen g => g -> (CUShort, g) # randomRs :: RandomGen g => (CUShort, CUShort) -> g -> [CUShort] # randoms :: RandomGen g => g -> [CUShort] #
Random CWchar # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (CWchar, CWchar) -> g -> (CWchar, g) # random :: RandomGen g => g -> (CWchar, g) # randomRs :: RandomGen g => (CWchar, CWchar) -> g -> [CWchar] # randoms :: RandomGen g => g -> [CWchar] #
Random Int16 # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (Int16, Int16) -> g -> (Int16, g) # random :: RandomGen g => g -> (Int16, g) # randomRs :: RandomGen g => (Int16, Int16) -> g -> [Int16] # randoms :: RandomGen g => g -> [Int16] #
Random Int32 # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (Int32, Int32) -> g -> (Int32, g) # random :: RandomGen g => g -> (Int32, g) # randomRs :: RandomGen g => (Int32, Int32) -> g -> [Int32] # randoms :: RandomGen g => g -> [Int32] #
Random Int64 # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (Int64, Int64) -> g -> (Int64, g) # random :: RandomGen g => g -> (Int64, g) # randomRs :: RandomGen g => (Int64, Int64) -> g -> [Int64] # randoms :: RandomGen g => g -> [Int64] #
Random Int8 # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (Int8, Int8) -> g -> (Int8, g) # random :: RandomGen g => g -> (Int8, g) # randomRs :: RandomGen g => (Int8, Int8) -> g -> [Int8] # randoms :: RandomGen g => g -> [Int8] #
Random Word16 # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (Word16, Word16) -> g -> (Word16, g) # random :: RandomGen g => g -> (Word16, g) # randomRs :: RandomGen g => (Word16, Word16) -> g -> [Word16] # randoms :: RandomGen g => g -> [Word16] #
Random Word32 # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (Word32, Word32) -> g -> (Word32, g) # random :: RandomGen g => g -> (Word32, g) # randomRs :: RandomGen g => (Word32, Word32) -> g -> [Word32] # randoms :: RandomGen g => g -> [Word32] #
Random Word64 # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (Word64, Word64) -> g -> (Word64, g) # random :: RandomGen g => g -> (Word64, g) # randomRs :: RandomGen g => (Word64, Word64) -> g -> [Word64] # randoms :: RandomGen g => g -> [Word64] #
Random Word8 # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (Word8, Word8) -> g -> (Word8, g) # random :: RandomGen g => g -> (Word8, g) # randomRs :: RandomGen g => (Word8, Word8) -> g -> [Word8] # randoms :: RandomGen g => g -> [Word8] #
Random Integer # | Note - `random` generates values in the `Int` range
Instance details Defined in System.Random Methods randomR :: RandomGen g => (Integer, Integer) -> g -> (Integer, g) # random :: RandomGen g => g -> (Integer, g) # randomRs :: RandomGen g => (Integer, Integer) -> g -> [Integer] # randoms :: RandomGen g => g -> [Integer] #
Random Bool # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (Bool, Bool) -> g -> (Bool, g) # random :: RandomGen g => g -> (Bool, g) # randomRs :: RandomGen g => (Bool, Bool) -> g -> [Bool] # randoms :: RandomGen g => g -> [Bool] #
Random Char # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (Char, Char) -> g -> (Char, g) # random :: RandomGen g => g -> (Char, g) # randomRs :: RandomGen g => (Char, Char) -> g -> [Char] # randoms :: RandomGen g => g -> [Char] #
Random Double # | Note - `random` produces values in the closed range `[0,1]`.
Instance details Defined in System.Random Methods randomR :: RandomGen g => (Double, Double) -> g -> (Double, g) # random :: RandomGen g => g -> (Double, g) # randomRs :: RandomGen g => (Double, Double) -> g -> [Double] # randoms :: RandomGen g => g -> [Double] #
Random Float # | Note - `random` produces values in the closed range `[0,1]`.
Instance details Defined in System.Random Methods randomR :: RandomGen g => (Float, Float) -> g -> (Float, g) # random :: RandomGen g => g -> (Float, g) # randomRs :: RandomGen g => (Float, Float) -> g -> [Float] # randoms :: RandomGen g => g -> [Float] #
Random Int # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (Int, Int) -> g -> (Int, g) # random :: RandomGen g => g -> (Int, g) # randomRs :: RandomGen g => (Int, Int) -> g -> [Int] # randoms :: RandomGen g => g -> [Int] #
Random Word # |
Instance details Defined in System.Random Methods randomR :: RandomGen g => (Word, Word) -> g -> (Word, g) # random :: RandomGen g => g -> (Word, g) # randomRs :: RandomGen g => (Word, Word) -> g -> [Word] # randoms :: RandomGen g => g -> [Word] #
(Random a, Random b) => Random (a, b) # | Note - `randomR` treats `a` and `b` types independently
Instance details Defined in System.Random Methods randomR :: RandomGen g => ((a, b), (a, b)) -> g -> ((a, b), g) # random :: RandomGen g => g -> ((a, b), g) # randomRs :: RandomGen g => ((a, b), (a, b)) -> g -> [(a, b)] # randoms :: RandomGen g => g -> [(a, b)] #
(Random a, Random b, Random c) => Random (a, b, c) # | Note - `randomR` treats `a`, `b` and `c` types independently
Instance details Defined in System.Random Methods randomR :: RandomGen g => ((a, b, c), (a, b, c)) -> g -> ((a, b, c), g) # random :: RandomGen g => g -> ((a, b, c), g) # randomRs :: RandomGen g => ((a, b, c), (a, b, c)) -> g -> [(a, b, c)] # randoms :: RandomGen g => g -> [(a, b, c)] #
(Random a, Random b, Random c, Random d) => Random (a, b, c, d) # | Note - `randomR` treats `a`, `b`, `c` and `d` types independently
Instance details Defined in System.Random Methods randomR :: RandomGen g => ((a, b, c, d), (a, b, c, d)) -> g -> ((a, b, c, d), g) # random :: RandomGen g => g -> ((a, b, c, d), g) # randomRs :: RandomGen g => ((a, b, c, d), (a, b, c, d)) -> g -> [(a, b, c, d)] # randoms :: RandomGen g => g -> [(a, b, c, d)] #
(Random a, Random b, Random c, Random d, Random e) => Random (a, b, c, d, e) # | Note - `randomR` treats `a`, `b`, `c`, `d` and `e` types independently
Instance details Defined in System.Random Methods randomR :: RandomGen g => ((a, b, c, d, e), (a, b, c, d, e)) -> g -> ((a, b, c, d, e), g) # random :: RandomGen g => g -> ((a, b, c, d, e), g) # randomRs :: RandomGen g => ((a, b, c, d, e), (a, b, c, d, e)) -> g -> [(a, b, c, d, e)] # randoms :: RandomGen g => g -> [(a, b, c, d, e)] #
(Random a, Random b, Random c, Random d, Random e, Random f) => Random (a, b, c, d, e, f) # | Note - `randomR` treats `a`, `b`, `c`, `d`, `e` and `f` types independently
Instance details Defined in System.Random Methods randomR :: RandomGen g => ((a, b, c, d, e, f), (a, b, c, d, e, f)) -> g -> ((a, b, c, d, e, f), g) # random :: RandomGen g => g -> ((a, b, c, d, e, f), g) # randomRs :: RandomGen g => ((a, b, c, d, e, f), (a, b, c, d, e, f)) -> g -> [(a, b, c, d, e, f)] # randoms :: RandomGen g => g -> [(a, b, c, d, e, f)] #
(Random a, Random b, Random c, Random d, Random e, Random f, Random g) => Random (a, b, c, d, e, f, g) # | Note - `randomR` treats `a`, `b`, `c`, `d`, `e`, `f` and `g` types independently
Instance details Defined in System.Random Methods randomR :: RandomGen g0 => ((a, b, c, d, e, f, g), (a, b, c, d, e, f, g)) -> g0 -> ((a, b, c, d, e, f, g), g0) # random :: RandomGen g0 => g0 -> ((a, b, c, d, e, f, g), g0) # randomRs :: RandomGen g0 => ((a, b, c, d, e, f, g), (a, b, c, d, e, f, g)) -> g0 -> [(a, b, c, d, e, f, g)] # randoms :: RandomGen g0 => g0 -> [(a, b, c, d, e, f, g)] #

class Uniform a #

The class of types for which a uniformly distributed value can be drawn from all possible values of the type.

Since: 1.2.0

#### Instances

Instances details

Uniform CBool # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CBool #
Uniform CChar # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CChar #
Uniform CInt # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CInt #
Uniform CIntMax # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CIntMax #
Uniform CIntPtr # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CIntPtr #
Uniform CLLong # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CLLong #
Uniform CLong # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CLong #
Uniform CPtrdiff # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CPtrdiff #
Uniform CSChar # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CSChar #
Uniform CShort # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CShort #
Uniform CSigAtomic # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CSigAtomic #
Uniform CSize # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CSize #
Uniform CUChar # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CUChar #
Uniform CUInt # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CUInt #
Uniform CUIntMax # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CUIntMax #
Uniform CUIntPtr # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CUIntPtr #
Uniform CULLong # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CULLong #
Uniform CULong # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CULong #
Uniform CUShort # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CUShort #
Uniform CWchar # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m CWchar #
Uniform Int16 # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m Int16 #
Uniform Int32 # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m Int32 #
Uniform Int64 # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m Int64 #
Uniform Int8 # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m Int8 #
Uniform Word16 # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m Word16 #
Uniform Word32 # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m Word32 #
Uniform Word64 # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m Word64 #
Uniform Word8 # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m Word8 #
Uniform () # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m () #
Uniform Bool # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m Bool #
Uniform Char # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m Char #
Uniform Int # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m Int #
Uniform Word # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m Word #
SeedGen g => Uniform (Seed g) # |
Instance details Defined in System.Random.Seed Methods uniformM :: StatefulGen g0 m => g0 -> m (Seed g) #
(Finite a, Uniform a) => Uniform (Maybe a) # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m (Maybe a) #
(Finite a, Uniform a, Finite b, Uniform b) => Uniform (Either a b) # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m (Either a b) #
(Uniform a, Uniform b) => Uniform (a, b) # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m (a, b) #
(Uniform a, Uniform b, Uniform c) => Uniform (a, b, c) # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m (a, b, c) #
(Uniform a, Uniform b, Uniform c, Uniform d) => Uniform (a, b, c, d) # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m (a, b, c, d) #
(Uniform a, Uniform b, Uniform c, Uniform d, Uniform e) => Uniform (a, b, c, d, e) # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m (a, b, c, d, e) #
(Uniform a, Uniform b, Uniform c, Uniform d, Uniform e, Uniform f) => Uniform (a, b, c, d, e, f) # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g m => g -> m (a, b, c, d, e, f) #
(Uniform a, Uniform b, Uniform c, Uniform d, Uniform e, Uniform f, Uniform g) => Uniform (a, b, c, d, e, f, g) # |
Instance details Defined in System.Random.Internal Methods uniformM :: StatefulGen g0 m => g0 -> m (a, b, c, d, e, f, g) #

class UniformRange a #

The class of types for which a uniformly distributed value can be drawn from a range.

Since: 1.2.0

#### Instances

Instances details

UniformRange CBool # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CBool, CBool) -> g -> m CBool # isInRange :: (CBool, CBool) -> CBool -> Bool #
UniformRange CChar # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CChar, CChar) -> g -> m CChar # isInRange :: (CChar, CChar) -> CChar -> Bool #
UniformRange CDouble # | See Floating point number caveats.
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CDouble, CDouble) -> g -> m CDouble # isInRange :: (CDouble, CDouble) -> CDouble -> Bool #
UniformRange CFloat # | See Floating point number caveats.
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CFloat, CFloat) -> g -> m CFloat # isInRange :: (CFloat, CFloat) -> CFloat -> Bool #
UniformRange CInt # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CInt, CInt) -> g -> m CInt # isInRange :: (CInt, CInt) -> CInt -> Bool #
UniformRange CIntMax # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CIntMax, CIntMax) -> g -> m CIntMax # isInRange :: (CIntMax, CIntMax) -> CIntMax -> Bool #
UniformRange CIntPtr # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CIntPtr, CIntPtr) -> g -> m CIntPtr # isInRange :: (CIntPtr, CIntPtr) -> CIntPtr -> Bool #
UniformRange CLLong # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CLLong, CLLong) -> g -> m CLLong # isInRange :: (CLLong, CLLong) -> CLLong -> Bool #
UniformRange CLong # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CLong, CLong) -> g -> m CLong # isInRange :: (CLong, CLong) -> CLong -> Bool #
UniformRange CPtrdiff # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CPtrdiff, CPtrdiff) -> g -> m CPtrdiff # isInRange :: (CPtrdiff, CPtrdiff) -> CPtrdiff -> Bool #
UniformRange CSChar # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CSChar, CSChar) -> g -> m CSChar # isInRange :: (CSChar, CSChar) -> CSChar -> Bool #
UniformRange CShort # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CShort, CShort) -> g -> m CShort # isInRange :: (CShort, CShort) -> CShort -> Bool #
UniformRange CSigAtomic # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CSigAtomic, CSigAtomic) -> g -> m CSigAtomic # isInRange :: (CSigAtomic, CSigAtomic) -> CSigAtomic -> Bool #
UniformRange CSize # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CSize, CSize) -> g -> m CSize # isInRange :: (CSize, CSize) -> CSize -> Bool #
UniformRange CUChar # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CUChar, CUChar) -> g -> m CUChar # isInRange :: (CUChar, CUChar) -> CUChar -> Bool #
UniformRange CUInt # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CUInt, CUInt) -> g -> m CUInt # isInRange :: (CUInt, CUInt) -> CUInt -> Bool #
UniformRange CUIntMax # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CUIntMax, CUIntMax) -> g -> m CUIntMax # isInRange :: (CUIntMax, CUIntMax) -> CUIntMax -> Bool #
UniformRange CUIntPtr # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CUIntPtr, CUIntPtr) -> g -> m CUIntPtr # isInRange :: (CUIntPtr, CUIntPtr) -> CUIntPtr -> Bool #
UniformRange CULLong # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CULLong, CULLong) -> g -> m CULLong # isInRange :: (CULLong, CULLong) -> CULLong -> Bool #
UniformRange CULong # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CULong, CULong) -> g -> m CULong # isInRange :: (CULong, CULong) -> CULong -> Bool #
UniformRange CUShort # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CUShort, CUShort) -> g -> m CUShort # isInRange :: (CUShort, CUShort) -> CUShort -> Bool #
UniformRange CWchar # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (CWchar, CWchar) -> g -> m CWchar # isInRange :: (CWchar, CWchar) -> CWchar -> Bool #
UniformRange Int16 # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (Int16, Int16) -> g -> m Int16 # isInRange :: (Int16, Int16) -> Int16 -> Bool #
UniformRange Int32 # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (Int32, Int32) -> g -> m Int32 # isInRange :: (Int32, Int32) -> Int32 -> Bool #
UniformRange Int64 # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (Int64, Int64) -> g -> m Int64 # isInRange :: (Int64, Int64) -> Int64 -> Bool #
UniformRange Int8 # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (Int8, Int8) -> g -> m Int8 # isInRange :: (Int8, Int8) -> Int8 -> Bool #
UniformRange Word16 # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (Word16, Word16) -> g -> m Word16 # isInRange :: (Word16, Word16) -> Word16 -> Bool #
UniformRange Word32 # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (Word32, Word32) -> g -> m Word32 # isInRange :: (Word32, Word32) -> Word32 -> Bool #
UniformRange Word64 # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (Word64, Word64) -> g -> m Word64 # isInRange :: (Word64, Word64) -> Word64 -> Bool #
UniformRange Word8 # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (Word8, Word8) -> g -> m Word8 # isInRange :: (Word8, Word8) -> Word8 -> Bool #
UniformRange Integer # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (Integer, Integer) -> g -> m Integer # isInRange :: (Integer, Integer) -> Integer -> Bool #
UniformRange Natural # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (Natural, Natural) -> g -> m Natural # isInRange :: (Natural, Natural) -> Natural -> Bool #
UniformRange () # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => ((), ()) -> g -> m () # isInRange :: ((), ()) -> () -> Bool #
UniformRange Bool # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (Bool, Bool) -> g -> m Bool # isInRange :: (Bool, Bool) -> Bool -> Bool #
UniformRange Char # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (Char, Char) -> g -> m Char # isInRange :: (Char, Char) -> Char -> Bool #
UniformRange Double # | See Floating point number caveats.
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (Double, Double) -> g -> m Double # isInRange :: (Double, Double) -> Double -> Bool #
UniformRange Float # | See Floating point number caveats.
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (Float, Float) -> g -> m Float # isInRange :: (Float, Float) -> Float -> Bool #
UniformRange Int # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (Int, Int) -> g -> m Int # isInRange :: (Int, Int) -> Int -> Bool #
UniformRange Word # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => (Word, Word) -> g -> m Word # isInRange :: (Word, Word) -> Word -> Bool #
(UniformRange a, UniformRange b) => UniformRange (a, b) # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => ((a, b), (a, b)) -> g -> m (a, b) # isInRange :: ((a, b), (a, b)) -> (a, b) -> Bool #
(UniformRange a, UniformRange b, UniformRange c) => UniformRange (a, b, c) # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => ((a, b, c), (a, b, c)) -> g -> m (a, b, c) # isInRange :: ((a, b, c), (a, b, c)) -> (a, b, c) -> Bool #
(UniformRange a, UniformRange b, UniformRange c, UniformRange d) => UniformRange (a, b, c, d) # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => ((a, b, c, d), (a, b, c, d)) -> g -> m (a, b, c, d) # isInRange :: ((a, b, c, d), (a, b, c, d)) -> (a, b, c, d) -> Bool #
(UniformRange a, UniformRange b, UniformRange c, UniformRange d, UniformRange e) => UniformRange (a, b, c, d, e) # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => ((a, b, c, d, e), (a, b, c, d, e)) -> g -> m (a, b, c, d, e) # isInRange :: ((a, b, c, d, e), (a, b, c, d, e)) -> (a, b, c, d, e) -> Bool #
(UniformRange a, UniformRange b, UniformRange c, UniformRange d, UniformRange e, UniformRange f) => UniformRange (a, b, c, d, e, f) # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g m => ((a, b, c, d, e, f), (a, b, c, d, e, f)) -> g -> m (a, b, c, d, e, f) # isInRange :: ((a, b, c, d, e, f), (a, b, c, d, e, f)) -> (a, b, c, d, e, f) -> Bool #
(UniformRange a, UniformRange b, UniformRange c, UniformRange d, UniformRange e, UniformRange f, UniformRange g) => UniformRange (a, b, c, d, e, f, g) # |
Instance details Defined in System.Random.Internal Methods uniformRM :: StatefulGen g0 m => ((a, b, c, d, e, f, g), (a, b, c, d, e, f, g)) -> g0 -> m (a, b, c, d, e, f, g) # isInRange :: ((a, b, c, d, e, f, g), (a, b, c, d, e, f, g)) -> (a, b, c, d, e, f, g) -> Bool #

class Finite a #

A type class for data with a finite number of inhabitants. This type class is used in the default implementation of `Uniform`.

Users are not supposed to write instances of `Finite` manually. There is a default implementation in terms of `Generic` instead.

    >>> :seti -XDeriveGeneric -XDeriveAnyClass
    >>> import GHC.Generics (Generic)
    >>> data MyBool = MyTrue | MyFalse deriving (Generic, Finite)
    >>> data Action = Code MyBool | Eat (Maybe Bool) | Sleep deriving (Generic, Finite)

#### Instances

Instances details

Finite Void # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# Void -> Cardinality toFinite :: Integer -> Void fromFinite :: Void -> Integer
Finite Int16 # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# Int16 -> Cardinality toFinite :: Integer -> Int16 fromFinite :: Int16 -> Integer
Finite Int32 # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# Int32 -> Cardinality toFinite :: Integer -> Int32 fromFinite :: Int32 -> Integer
Finite Int64 # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# Int64 -> Cardinality toFinite :: Integer -> Int64 fromFinite :: Int64 -> Integer
Finite Int8 # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# Int8 -> Cardinality toFinite :: Integer -> Int8 fromFinite :: Int8 -> Integer
Finite Word16 # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# Word16 -> Cardinality toFinite :: Integer -> Word16 fromFinite :: Word16 -> Integer
Finite Word32 # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# Word32 -> Cardinality toFinite :: Integer -> Word32 fromFinite :: Word32 -> Integer
Finite Word64 # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# Word64 -> Cardinality toFinite :: Integer -> Word64 fromFinite :: Word64 -> Integer
Finite Word8 # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# Word8 -> Cardinality toFinite :: Integer -> Word8 fromFinite :: Word8 -> Integer
Finite Ordering # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# Ordering -> Cardinality toFinite :: Integer -> Ordering fromFinite :: Ordering -> Integer
Finite () # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# () -> Cardinality toFinite :: Integer -> () fromFinite :: () -> Integer
Finite Bool # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# Bool -> Cardinality toFinite :: Integer -> Bool fromFinite :: Bool -> Integer
Finite Char # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# Char -> Cardinality toFinite :: Integer -> Char fromFinite :: Char -> Integer
Finite Int # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# Int -> Cardinality toFinite :: Integer -> Int fromFinite :: Int -> Integer
Finite Word # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# Word -> Cardinality toFinite :: Integer -> Word fromFinite :: Word -> Integer
Finite a => Finite (Maybe a) # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# (Maybe a) -> Cardinality toFinite :: Integer -> Maybe a fromFinite :: Maybe a -> Integer
(Finite a, Finite b) => Finite (Either a b) # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# (Either a b) -> Cardinality toFinite :: Integer -> Either a b fromFinite :: Either a b -> Integer
(Finite a, Finite b) => Finite (a, b) # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# (a, b) -> Cardinality toFinite :: Integer -> (a, b) fromFinite :: (a, b) -> Integer
(Finite a, Finite b, Finite c) => Finite (a, b, c) # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# (a, b, c) -> Cardinality toFinite :: Integer -> (a, b, c) fromFinite :: (a, b, c) -> Integer
(Finite a, Finite b, Finite c, Finite d) => Finite (a, b, c, d) # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# (a, b, c, d) -> Cardinality toFinite :: Integer -> (a, b, c, d) fromFinite :: (a, b, c, d) -> Integer
(Finite a, Finite b, Finite c, Finite d, Finite e) => Finite (a, b, c, d, e) # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# (a, b, c, d, e) -> Cardinality toFinite :: Integer -> (a, b, c, d, e) fromFinite :: (a, b, c, d, e) -> Integer
(Finite a, Finite b, Finite c, Finite d, Finite e, Finite f) => Finite (a, b, c, d, e, f) # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# (a, b, c, d, e, f) -> Cardinality toFinite :: Integer -> (a, b, c, d, e, f) fromFinite :: (a, b, c, d, e, f) -> Integer
(Finite a, Finite b, Finite c, Finite d, Finite e, Finite f, Finite g) => Finite (a, b, c, d, e, f, g) # |
Instance details Defined in System.Random.GFinite Methods cardinality :: Proxy# (a, b, c, d, e, f, g) -> Cardinality toFinite :: Integer -> (a, b, c, d, e, f, g) fromFinite :: (a, b, c, d, e, f, g) -> Integer

## Seed

data Seed g #

This is a binary form of pseudo-random number generator's state. It is designed to be safe and easy to use for input/output operations like restoring from file, transmitting over the network, etc.

Constructor is not exported, becasue it is important for implementation to enforce the invariant of the underlying byte array being of the exact same length as the generator has specified in `SeedSize`. Use `mkSize` and `unSize` to get access to the raw bytes in a safe manner.

Since: 1.3.0

#### Instances

Instances details

Show (Seed g) # |
Instance details Defined in System.Random.Internal Methods showsPrec :: Int -> Seed g -> ShowS # show :: Seed g -> String # showList :: [Seed g] -> ShowS #
Eq (Seed g) # |
Instance details Defined in System.Random.Internal Methods (==) :: Seed g -> Seed g -> Bool # (/=) :: Seed g -> Seed g -> Bool #
Ord (Seed g) # |
Instance details Defined in System.Random.Internal Methods compare :: Seed g -> Seed g -> Ordering # (<) :: Seed g -> Seed g -> Bool # (<=) :: Seed g -> Seed g -> Bool # (>) :: Seed g -> Seed g -> Bool # (>=) :: Seed g -> Seed g -> Bool # max :: Seed g -> Seed g -> Seed g # min :: Seed g -> Seed g -> Seed g #
SeedGen g => Uniform (Seed g) # |
Instance details Defined in System.Random.Seed Methods uniformM :: StatefulGen g0 m => g0 -> m (Seed g) #

class (KnownNat (SeedSize g), 1 <= SeedSize g, Typeable g) => SeedGen g where #

Interface for converting a pure pseudo-random number generator to and from non-empty sequence of bytes. Seeds are stored in Little-Endian order regardless of the platform it is being used on, which provides cross-platform compatibility, while providing optimal performance for the most common platform type.

Conversion to and from a `Seed` serves as a building block for implementing serialization for any pure or frozen pseudo-random number generator.

It is not trivial to implement platform independence. For this reason this type class has two alternative ways of creating an instance for this class. The easiest way for constructing a platform indepent seed is by converting the inner state of a generator to and from a list of 64 bit words using `toSeed64` and `fromSeed64` respectively. In that case cross-platform support will be handled automaticaly.

    >>> :set -XDataKinds -XTypeFamilies
    >>> import Data.Word (Word8, Word32)
    >>> import Data.Bits ((.|.), shiftR, shiftL)
    >>> import Data.List.NonEmpty (NonEmpty ((:|)))
    >>> data FiveByteGen = FiveByteGen Word8 Word32 deriving Show
    >>> :{
    instance SeedGen FiveByteGen where
      type SeedSize FiveByteGen = 5
      fromSeed64 (w64 :| _) =
        FiveByteGen (fromIntegral (w64 `shiftR` 32)) (fromIntegral w64)
      toSeed64 (FiveByteGen x1 x4) =
        let w64 = (fromIntegral x1 `shiftL` 32) .|. fromIntegral x4
         in (w64 :| [])
    :}

    >>> FiveByteGen 0x80 0x01020304
    FiveByteGen 128 16909060
    >>> fromSeed (toSeed (FiveByteGen 0x80 0x01020304))
    FiveByteGen 128 16909060
    >>> toSeed (FiveByteGen 0x80 0x01020304)
    Seed [0x04, 0x03, 0x02, 0x01, 0x80]
    >>> toSeed64 (FiveByteGen 0x80 0x01020304)
    549772722948 :| []

However, when performance is of utmost importance or default handling of cross platform independence is not sufficient, then an adventurous developer can try implementing conversion into bytes directly with `toSeed` and `fromSeed`.

Properties that must hold:

    > fromSeed (toSeed gen) == gen

    > fromSeed64 (toSeed64 gen) == gen

Note, that there is no requirement for every `Seed` to roundtrip, eg. this proprty does not even hold for `StdGen`:

    >>> let seed = nonEmptyToSeed (0xab :| [0xff00]) :: Seed StdGen
    >>> seed == toSeed (fromSeed seed)
    False

Since: 1.3.0

Minimal complete definition

fromSeed, toSeed | fromSeed64, toSeed64

Associated Types

type SeedSize g :: Nat #

Number of bytes that is required for storing the full state of a pseudo-random number generator. It should be big enough to satisfy the roundtrip property:

    > fromSeed (toSeed gen) == gen

Methods

fromSeed :: Seed g -> g #

Convert from a binary representation to a pseudo-random number generator

Since: 1.3.0

toSeed :: g -> Seed g #

Convert to a binary representation of a pseudo-random number generator

Since: 1.3.0

fromSeed64 :: NonEmpty Word64 -> g #

Construct pseudo-random number generator from a list of words. Whenever list does not have enough bytes to satisfy the `SeedSize` requirement, it will be padded with zeros. On the other hand when it has more than necessary, extra bytes will be dropped.

For example if `SeedSize` is set to 2, then only the lower 16 bits of the first element in the list will be used.

Since: 1.3.0

toSeed64 :: g -> NonEmpty Word64 #

Convert pseudo-random number generator to a list of words

In case when `SeedSize` is not a multiple of 8, then the upper bits of the last word in the list will be set to zero.

Since: 1.3.0

#### Instances

Instances details

SeedGen StdGen # |
Instance details Defined in System.Random.Seed Associated Types
type SeedSize StdGen |
Instance details Defined in System.Random.Seed type SeedSize StdGen = SeedSize SMGen
Methods fromSeed :: Seed StdGen -> StdGen # toSeed :: StdGen -> Seed StdGen # fromSeed64 :: NonEmpty Word64 -> StdGen # toSeed64 :: StdGen -> NonEmpty Word64 #
SeedGen SMGen # |
Instance details Defined in System.Random.Seed Associated Types
type SeedSize SMGen |
Instance details Defined in System.Random.Seed type SeedSize SMGen = 16
Methods fromSeed :: Seed SMGen -> SMGen # toSeed :: SMGen -> Seed SMGen # fromSeed64 :: NonEmpty Word64 -> SMGen # toSeed64 :: SMGen -> NonEmpty Word64 #
SeedGen SMGen # |
Instance details Defined in System.Random.Seed Associated Types
type SeedSize SMGen |
Instance details Defined in System.Random.Seed type SeedSize SMGen = 8
Methods fromSeed :: Seed SMGen -> SMGen # toSeed :: SMGen -> Seed SMGen # fromSeed64 :: NonEmpty Word64 -> SMGen # toSeed64 :: SMGen -> NonEmpty Word64 #
SeedGen g => SeedGen (StateGen g) # |
Instance details Defined in System.Random.Seed Associated Types
type SeedSize (StateGen g) |
Instance details Defined in System.Random.Seed type SeedSize (StateGen g) = SeedSize g
Methods fromSeed :: Seed (StateGen g) -> StateGen g # toSeed :: StateGen g -> Seed (StateGen g) # fromSeed64 :: NonEmpty Word64 -> StateGen g # toSeed64 :: StateGen g -> NonEmpty Word64 #
SeedGen g => SeedGen (AtomicGen g) # |
Instance details Defined in System.Random.Stateful Associated Types
type SeedSize (AtomicGen g) |
Instance details Defined in System.Random.Stateful type SeedSize (AtomicGen g) = SeedSize g
Methods fromSeed :: Seed (AtomicGen g) -> AtomicGen g # toSeed :: AtomicGen g -> Seed (AtomicGen g) # fromSeed64 :: NonEmpty Word64 -> AtomicGen g # toSeed64 :: AtomicGen g -> NonEmpty Word64 #
SeedGen g => SeedGen (IOGen g) # |
Instance details Defined in System.Random.Stateful Associated Types
type SeedSize (IOGen g) |
Instance details Defined in System.Random.Stateful type SeedSize (IOGen g) = SeedSize g
Methods fromSeed :: Seed (IOGen g) -> IOGen g # toSeed :: IOGen g -> Seed (IOGen g) # fromSeed64 :: NonEmpty Word64 -> IOGen g # toSeed64 :: IOGen g -> NonEmpty Word64 #
SeedGen g => SeedGen (STGen g) # |
Instance details Defined in System.Random.Stateful Associated Types
type SeedSize (STGen g) |
Instance details Defined in System.Random.Stateful type SeedSize (STGen g) = SeedSize g
Methods fromSeed :: Seed (STGen g) -> STGen g # toSeed :: STGen g -> Seed (STGen g) # fromSeed64 :: NonEmpty Word64 -> STGen g # toSeed64 :: STGen g -> NonEmpty Word64 #
SeedGen g => SeedGen (TGen g) # |
Instance details Defined in System.Random.Stateful Associated Types
type SeedSize (TGen g) |
Instance details Defined in System.Random.Stateful type SeedSize (TGen g) = SeedSize g
Methods fromSeed :: Seed (TGen g) -> TGen g # toSeed :: TGen g -> Seed (TGen g) # fromSeed64 :: NonEmpty Word64 -> TGen g # toSeed64 :: TGen g -> NonEmpty Word64 #

seedSize :: SeedGen g => Int #

Get the expected size of the `Seed` in number bytes

Since: 1.3.0

seedSizeProxy :: forall proxy g. SeedGen g => proxy g -> Int #

Just like `seedSize`, except it accepts a proxy as an argument.

Since: 1.3.0

mkSeed :: (SeedGen g, MonadFail m) => ByteArray -> m (Seed g) #

Construct a `Seed` from a `ByteArray` of expected length. Whenever `ByteArray` does not match the `SeedSize` specified by the pseudo-random generator, this function will `fail`.

Since: 1.3.0

unSeed :: Seed g -> ByteArray #

Unwrap the `Seed` and get the underlying `ByteArray`

Since: 1.3.0

mkSeedFromByteString :: (SeedGen g, MonadFail m) => ByteString -> m (Seed g) #

Just like `mkSeed`, but uses `ByteString` as argument. Results in a memcopy of the seed.

Since: 1.3.0

unSeedToByteString :: Seed g -> ByteString #

Just like `unSeed`, but produced a `ByteString`. Results in a memcopy of the seed.

Since: 1.3.0

withSeed :: SeedGen g => Seed g -> (g -> (a, g)) -> (a, Seed g) #

Helper function that allows for operating directly on the `Seed`, while supplying a function that uses the pseudo-random number generator that is constructed from that `Seed`.

#### Example

Expand

    >>> :set -XTypeApplications
    >>> import System.Random
    >>> withSeed (nonEmptyToSeed (pure 2024) :: Seed StdGen) (uniform @Int)
    (1039666877624726199,Seed [0xe9, 0x07, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00])

Since: 1.3.0

withSeedM :: (SeedGen g, Functor f) => Seed g -> (g -> f (a, g)) -> f (a, Seed g) #

Same as `withSeed`, except it is useful with monadic computation and frozen generators.

See `withSeedMutableGen` for a helper that also handles seeds for mutable pseduo-random number generators.

Since: 1.3.0

withSeedFile :: (SeedGen g, MonadIO m) => FilePath -> (Seed g -> m (a, Seed g)) -> m a #

Read the seed from a file and use it for constructing a pseudo-random number generator. After supplied action has been applied to the constructed generator, the resulting generator will be converted back to a seed and written to the same file.

Since: 1.3.0

seedGenTypeName :: SeedGen g => String #

This is a function that shows the name of the generator type, which is useful for error reporting.

Since: 1.3.0

nonEmptyToSeed :: SeedGen g => NonEmpty Word64 -> Seed g #

Construct a seed from a list of 64-bit words. At most `SeedSize` many bytes will be used.

Since: 1.3.0

nonEmptyFromSeed :: SeedGen g => Seed g -> NonEmpty Word64 #

Convert a `Seed` to a list of 64bit words.

Since: 1.3.0

type family SeedSize g :: Nat #

Number of bytes that is required for storing the full state of a pseudo-random number generator. It should be big enough to satisfy the roundtrip property:

    > fromSeed (toSeed gen) == gen

#### Instances

Instances details

type SeedSize StdGen # |
Instance details Defined in System.Random.Seed type SeedSize StdGen = SeedSize SMGen
type SeedSize SMGen # |
Instance details Defined in System.Random.Seed type SeedSize SMGen = 16
type SeedSize SMGen # |
Instance details Defined in System.Random.Seed type SeedSize SMGen = 8
type SeedSize (StateGen g) # |
Instance details Defined in System.Random.Seed type SeedSize (StateGen g) = SeedSize g
type SeedSize (AtomicGen g) # |
Instance details Defined in System.Random.Stateful type SeedSize (AtomicGen g) = SeedSize g
type SeedSize (IOGen g) # |
Instance details Defined in System.Random.Stateful type SeedSize (IOGen g) = SeedSize g
type SeedSize (STGen g) # |
Instance details Defined in System.Random.Stateful type SeedSize (STGen g) = SeedSize g
type SeedSize (TGen g) # |
Instance details Defined in System.Random.Stateful type SeedSize (TGen g) = SeedSize g

# Generators for sequences of pseudo-random bytes

## Lists

uniforms :: (Uniform a, RandomGen g) => g -> [a] #

Produce an infinite list of pseudo-random values. Integrates nicely with list fusion. Naturally, there is no way to recover the final generator, therefore either use `split` before calling `uniforms` or use `uniformList` instead.

Similar to `randoms`, except it relies on `Uniform` type class instead of `Random`

#### Examples

Expand

    >>> let gen = mkStdGen 2023
    >>> import Data.Word (Word16)
    >>> take 5 $ uniforms gen :: [Word16]
    [56342,15850,25292,14347,13919]

Since: 1.3.0

uniformRs :: (UniformRange a, RandomGen g) => (a, a) -> g -> [a] #

Produce an infinite list of pseudo-random values in a specified range. Same as `uniforms`, integrates nicely with list fusion. There is no way to recover the final generator, therefore either use `split` before calling `uniformRs` or use `uniformListR` instead.

Similar to `randomRs`, except it relies on `UniformRange` type class instead of `Random`.

#### Examples

Expand

    >>> let gen = mkStdGen 2023
    >>> take 5 $ uniformRs (10, 100) gen :: [Int]
    [32,86,21,57,39]

Since: 1.3.0

uniformList :: (Uniform a, RandomGen g) => Int -> g -> ([a], g) #

Produce a list of the supplied length with elements generated uniformly.

See `uniformListM` for a stateful counterpart.

#### Examples

Expand

    >>> let gen = mkStdGen 2023
    >>> import Data.Word (Word16)
    >>> uniformList 5 gen :: ([Word16], StdGen)
    ([56342,15850,25292,14347,13919],StdGen {unStdGen = SMGen 6446154349414395371 1920468677557965761})

Since: 1.3.0

uniformListR :: (UniformRange a, RandomGen g) => Int -> (a, a) -> g -> ([a], g) #

Produce a list of the supplied length with elements generated uniformly.

See `uniformListM` for a stateful counterpart.

#### Examples

Expand

    >>> let gen = mkStdGen 2023
    >>> uniformListR 10 (20, 30) gen :: ([Int], StdGen)
    ([26,30,27,24,30,25,27,21,27,27],StdGen {unStdGen = SMGen 12965503083958398648 1920468677557965761})

Since: 1.3.0

uniformShuffleList :: RandomGen g => [a] -> g -> ([a], g) #

Shuffle elements of a list in a uniformly random order.

#### Examples

Expand

    >>> uniformShuffleList "ELVIS" $ mkStdGen 252
    ("LIVES",StdGen {unStdGen = SMGen 17676540583805057877 5302934877338729551})

Since: 1.3.0

## Bytes

uniformByteArray #

Arguments

:: RandomGen g |
=> Bool | Should byte array be allocted in pinned or unpinned memory.
-> Int | Number of bytes to generate
-> g | Pure pseudo-random numer generator
-> (ByteArray, g) |

Efficiently generates a sequence of pseudo-random bytes in a platform independent manner.

Since: 1.3.0

uniformByteString :: RandomGen g => Int -> g -> (ByteString, g) #

Generates a `ByteString` of the specified size using a pure pseudo-random number generator. See `uniformByteStringM` for the monadic version.

#### Examples

Expand

    >>> import System.Random
    >>> import Data.ByteString (unpack)
    >>> let pureGen = mkStdGen 137
    >>> unpack . fst $ uniformByteString 10 pureGen
    [51,123,251,37,49,167,90,109,1,4]

Since: 1.3.0

uniformShortByteString :: RandomGen g => Int -> g -> (ShortByteString, g) #

Same as ``uniformByteArray` `False``, but for `ShortByteString`.

Returns a `ShortByteString` of length `n` filled with pseudo-random bytes.

#### Examples

Expand

    >>> import System.Random
    >>> import Data.ByteString.Short (unpack)
    >>> let pureGen = mkStdGen 137
    >>> unpack . fst $ uniformShortByteString 10 pureGen
    [51,123,251,37,49,167,90,109,1,4]

Since: 1.3.0

uniformFillMutableByteArray #

Arguments

:: RandomGen g |
=> MutableByteArray s | Mutable array to fill with random bytes
-> Int | Offset into a mutable array from the beginning in number of bytes. Offset will be clamped into the range between 0 and the total size of the mutable array
-> Int | Number of randomly generated bytes to write into the array. This number will be clamped between 0 and the total size of the array without the offset.
-> g |
-> ST s g |

Fill in a slice of a mutable byte array with randomly generated bytes. This function does not fail, instead it clamps the offset and number of bytes to generate into a valid range.

Since: 1.3.0

### Deprecated

genByteString :: RandomGen g => Int -> g -> (ByteString, g) #

Deprecated: In favor of `uniformByteString`

Generates a `ByteString` of the specified size using a pure pseudo-random number generator. See `uniformByteStringM` for the monadic version.

#### Examples

Expand

    >>> import System.Random
    >>> import Data.ByteString
    >>> let pureGen = mkStdGen 137
    >>> :seti -Wno-deprecations
    >>> unpack . fst . genByteString 10 $ pureGen
    [51,123,251,37,49,167,90,109,1,4]

Since: 1.2.0

genShortByteString :: RandomGen g => Int -> g -> (ShortByteString, g) #

Deprecated: In favor of `uniformShortByteString`

Same as ``uniformByteArray` `False``, but for `ShortByteString`.

`genShortByteString n g` returns a `ShortByteString` of length `n` filled with pseudo-random bytes.

Note - This function will be removed from the type class in the next major release as it is no longer needed because of `unsafeUniformFillMutableByteArray`.

Since: 1.2.0

## Standard pseudo-random number generator

data StdGen #

The standard pseudo-random number generator.

#### Instances

Instances details

NFData StdGen # |
Instance details Defined in System.Random.Internal Methods rnf :: StdGen -> () #
Show StdGen # |
Instance details Defined in System.Random.Internal Methods showsPrec :: Int -> StdGen -> ShowS # show :: StdGen -> String # showList :: [StdGen] -> ShowS #
Eq StdGen # |
Instance details Defined in System.Random.Internal Methods (==) :: StdGen -> StdGen -> Bool # (/=) :: StdGen -> StdGen -> Bool #
RandomGen StdGen # |
Instance details Defined in System.Random.Internal Methods next :: StdGen -> (Int, StdGen) # genWord8 :: StdGen -> (Word8, StdGen) # genWord16 :: StdGen -> (Word16, StdGen) # genWord32 :: StdGen -> (Word32, StdGen) # genWord64 :: StdGen -> (Word64, StdGen) # genWord32R :: Word32 -> StdGen -> (Word32, StdGen) # genWord64R :: Word64 -> StdGen -> (Word64, StdGen) # genShortByteString :: Int -> StdGen -> (ShortByteString, StdGen) # unsafeUniformFillMutableByteArray :: MutableByteArray s -> Int -> Int -> StdGen -> ST s StdGen # genRange :: StdGen -> (Int, Int) # split :: StdGen -> (StdGen, StdGen) #
SplitGen StdGen # |
Instance details Defined in System.Random.Internal Methods splitGen :: StdGen -> (StdGen, StdGen) #
SeedGen StdGen # |
Instance details Defined in System.Random.Seed Associated Types
type SeedSize StdGen |
Instance details Defined in System.Random.Seed type SeedSize StdGen = SeedSize SMGen
Methods fromSeed :: Seed StdGen -> StdGen # toSeed :: StdGen -> Seed StdGen # fromSeed64 :: NonEmpty Word64 -> StdGen # toSeed64 :: StdGen -> NonEmpty Word64 #
type SeedSize StdGen # |
Instance details Defined in System.Random.Seed type SeedSize StdGen = SeedSize SMGen

mkStdGen :: Int -> StdGen #

Constructs a `StdGen` deterministically from an `Int` seed. See `mkStdGen64` for a `Word64` variant that is architecture agnostic.

mkStdGen64 :: Word64 -> StdGen #

Constructs a `StdGen` deterministically from a `Word64` seed.

The difference between `mkStdGen` is that `mkStdGen64` will work the same on 64-bit and 32-bit architectures, while the former can only use 32-bit of information for initializing the psuedo-random number generator on 32-bit operating systems

Since: 1.3.0

initStdGen :: MonadIO m => m StdGen #

Initialize `StdGen` using system entropy (i.e. `/dev/urandom`) when it is available, while falling back on using system time as the seed.

Since: 1.2.1

## Global standard pseudo-random number generator

There is a single, implicit, global pseudo-random number generator of type `StdGen`, held in a global mutable variable that can be manipulated from within the `IO` monad. It is also available as `globalStdGen`, therefore it is recommended to use the new System.Random.Stateful interface to explicitly operate on the global pseudo-random number generator.

It is initialised with `initStdGen`, although it is possible to override its value with `setStdGen`. All operations on the global pseudo-random number generator are thread safe, however in presence of concurrency they are naturally become non-deterministic. Moreover, relying on the global mutable state makes it hard to know which of the dependent libraries are using it as well, making it unpredictable in the local context. Precisely of this reason, the global pseudo-random number generator is only suitable for uses in applications, test suites, etc. and is advised against in development of reusable libraries.

It is also important to note that either using `StdGen` with pure functions from other sections of this module or by relying on `runStateGen` from stateful interface does not only give us deterministic behaviour without requiring `IO`, but it is also more efficient.

getStdRandom :: MonadIO m => (StdGen -> (a, StdGen)) -> m a #

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` produces a pseudo-random integer between 1 and 6:

    >>> rollDice = getStdRandom (randomR (1, 6))
    >>> replicateM 10 (rollDice :: IO Int)
    [1,1,1,4,5,6,1,2,2,5]

This is an outdated function and it is recommended to switch to its equivalent `applyAtomicGen` instead, possibly with the `globalStdGen` if relying on the global state is acceptable.

    >>> import System.Random.Stateful
    >>> rollDice = applyAtomicGen (uniformR (1, 6)) globalStdGen
    >>> replicateM 10 (rollDice :: IO Int)
    [2,1,1,5,4,3,6,6,3,2]

Since: 1.0.0

getStdGen :: MonadIO m => m StdGen #

Gets the global pseudo-random number generator. Extracts the contents of `globalStdGen`

Since: 1.0.0

setStdGen :: MonadIO m => StdGen -> m () #

Sets the global pseudo-random number generator. Overwrites the contents of `globalStdGen`

Since: 1.0.0

newStdGen :: MonadIO m => m StdGen #

Applies `split` to the current global pseudo-random generator `globalStdGen`, updates it with one of the results, and returns the other.

Since: 1.0.0

randomIO :: (Random a, MonadIO m) => m a #

A variant of `randomM` that uses the global pseudo-random number generator `globalStdGen`.

    >>> import Data.Int
    >>> randomIO :: IO Int32
    114794456

This function is equivalent to ``getStdRandom` `random`` and is included in this interface for historical reasons and backwards compatibility. It is recommended to use `uniformM` instead, possibly with the `globalStdGen` if relying on the global state is acceptable.

    >>> import System.Random.Stateful
    >>> uniformM globalStdGen :: IO Int32
    -1768545016

Since: 1.0.0

randomRIO :: (Random a, MonadIO m) => (a, a) -> m a #

A variant of `randomRM` that uses the global pseudo-random number generator `globalStdGen`

    >>> randomRIO (2020, 2100) :: IO Int
    2028

Similar to `randomIO`, this function is equivalent to ``getStdRandom` `randomR`` and is included in this interface for historical reasons and backwards compatibility. It is recommended to use `uniformRM` instead, possibly with the `globalStdGen` if relying on the global state is acceptable.

    >>> import System.Random.Stateful
    >>> uniformRM (2020, 2100) globalStdGen :: IO Int
    2044

Since: 1.0.0

# Compatibility and reproducibility

## Backwards compatibility and deprecations

genRange :: RandomGen g => g -> (Int, Int) #

Deprecated: No longer used

Yields the range of values returned by `next`.

It is required that:

- If `(a, b) = `genRange` g`, then `a < b`.
- `genRange` must not examine its argument so the value it returns is determined only by the instance of `RandomGen`.

The default definition spans the full range of `Int`.

Since: 1.0.0

next :: RandomGen g => g -> (Int, g) #

Deprecated: No longer used

Returns an `Int` that is uniformly distributed over the range returned by `genRange` (including both end points), and a new generator. Using `next` is inefficient as all operations go via `Integer`. See here for more details. It is thus deprecated.

Since: 1.0.0

Version 1.2 mostly maintains backwards compatibility with version 1.1. This has a few consequences users should be aware of:

- The type class `Random` is only provided for backwards compatibility. New code should use `Uniform` and `UniformRange` instead.
- The methods `next` and `genRange` in `RandomGen` are deprecated and only provided for backwards compatibility. New instances of `RandomGen` should implement word-based methods instead. See below for more information about how to write a `RandomGen` instance.

- This library provides instances for `Random` for some unbounded types for backwards compatibility. For an unbounded type, there is no way to generate a value with uniform probability out of its entire domain, so the `random` implementation for unbounded types actually generates a value based on some fixed range.

  For `Integer`, `random` generates a value in the `Int` range. For `Float` and `Double`, `random` generates a floating point value in the range `[0, 1)`.

  This library does not provide `Uniform` instances for any unbounded types.

## Reproducibility

If you have two builds of a particular piece of code against this library, any deterministic function call should give the same result in the two builds if the builds are

- compiled against the same major version of this library
- on the same architecture (32-bit or 64-bit)

# Notes for pseudo-random number generator implementors

## How to implement `RandomGen`

Consider these points when writing a `RandomGen` instance for a given pure pseudo-random number generator:

- If the pseudo-random number generator has a power-of-2 modulus, that is, it natively outputs `2^n` bits of randomness for some `n`, implement `genWord8`, `genWord16`, `genWord32` and `genWord64`. See below for more details.
- If the pseudo-random number generator does not have a power-of-2 modulus, implement `next` and `genRange`. See below for more details.
- If the pseudo-random number generator is splittable, implement `split`. If there is no suitable implementation, `split` should fail with a helpful error message.

### How to implement `RandomGen` for a pseudo-random number generator with power-of-2 modulus

Suppose you want to implement a permuted congruential generator.

    >>> data PCGen = PCGen !Word64 !Word64

It produces a full `Word32` of randomness per iteration.

    >>> import Data.Bits
    >>> :{
    let stepGen :: PCGen -> (Word32, PCGen)
        stepGen (PCGen state inc) = let
          newState = state * 6364136223846793005 + (inc .|. 1)
          xorShifted = fromIntegral (((state `shiftR` 18) `xor` state) `shiftR` 27) :: Word32
          rot = fromIntegral (state `shiftR` 59) :: Word32
          out = (xorShifted `shiftR` (fromIntegral rot)) .|. (xorShifted `shiftL` fromIntegral ((-rot) .&. 31))
          in (out, PCGen newState inc)
    :}

    >>> fst $ stepGen $ snd $ stepGen (PCGen 17 29)
    3288430965

You can make it an instance of `RandomGen` as follows:

    >>> :{
    instance RandomGen PCGen where
      genWord32 = stepGen
      split _ = error "PCG is not splittable"
    :}

### How to implement `RandomGen` for a pseudo-random number generator without a power-of-2 modulus

We do not recommend you implement any new pseudo-random number generators without a power-of-2 modulus.

Pseudo-random number generators without a power-of-2 modulus perform significantly worse than pseudo-random number generators with a power-of-2 modulus with this library. This is because most functionality in this library is based on generating and transforming uniformly pseudo-random machine words, and generating uniformly pseudo-random machine words using a pseudo-random number generator without a power-of-2 modulus is expensive.

The pseudo-random number generator from L’Ecuyer (1988) natively generates an integer value in the range `[1, 2147483562]`. This is the generator used by this library before it was replaced by SplitMix in version 1.2.

    >>> data LegacyGen = LegacyGen !Int32 !Int32
    >>> :{
    let legacyNext :: LegacyGen -> (Int, LegacyGen)
        legacyNext (LegacyGen s1 s2) = (fromIntegral z', LegacyGen s1'' s2'') where
          z' = if z < 1 then z + 2147483562 else z
          z = s1'' - s2''
          k = s1 `quot` 53668
          s1'  = 40014 * (s1 - k * 53668) - k * 12211
          s1'' = if s1' < 0 then s1' + 2147483563 else s1'
          k' = s2 `quot` 52774
          s2' = 40692 * (s2 - k' * 52774) - k' * 3791
          s2'' = if s2' < 0 then s2' + 2147483399 else s2'
    :}

You can make it an instance of `RandomGen` as follows:

    >>> :{
    instance RandomGen LegacyGen where
      next = legacyNext
      genRange _ = (1, 2147483562)
      split _ = error "Not implemented"
    :}

# References

1. Guy L. Steele, Jr., Doug Lea, and Christine H. Flood. 2014. Fast splittable pseudorandom number generators. In Proceedings of the 2014 ACM International Conference on Object Oriented Programming Systems Languages & Applications (OOPSLA '14). ACM, New York, NY, USA, 453-472. DOI: https://doi.org/10.1145/2660193.2660195