-- Hoogle documentation, generated by Haddock -- See Hoogle, http://www.haskell.org/hoogle/ -- | Pseudo-random number generation -- -- This package provides basic pseudo-random number generation, including -- the ability to split random number generators. -- --

System.Random: pure pseudo-random number interface

-- -- In pure code, use System.Random.uniform and -- System.Random.uniformR from System.Random to generate -- pseudo-random numbers with a pure pseudo-random number generator like -- System.Random.StdGen. -- -- As an example, here is how you can simulate rolls of a six-sided die -- using System.Random.uniformR: -- -- 
--   >>> let roll = uniformR (1, 6)        :: RandomGen g => g -> (Word, g)
--   
--   >>> let rolls = unfoldr (Just . roll) :: RandomGen g => g -> [Word]
--   
--   >>> let pureGen = mkStdGen 42
--   
--   >>> take 10 (rolls pureGen)           :: [Word]
--   [1,1,3,2,4,5,3,4,6,2]
--
-- -- See System.Random for more details. -- --

System.Random.Stateful: monadic pseudo-random number -- interface

-- -- In monadic code, use System.Random.Stateful.uniformM and -- System.Random.Stateful.uniformRM from -- System.Random.Stateful to generate pseudo-random numbers with a -- monadic pseudo-random number generator, or using a monadic adapter. -- -- As an example, here is how you can simulate rolls of a six-sided die -- using System.Random.Stateful.uniformRM: -- -- 
--   >>> let rollM = uniformRM (1, 6)                 :: StatefulGen g m => g -> m Word
--   
--   >>> let pureGen = mkStdGen 42
--   
--   >>> runStateGen_ pureGen (replicateM 10 . rollM) :: [Word]
--   [1,1,3,2,4,5,3,4,6,2]
--
-- -- The monadic adapter System.Random.Stateful.runStateGen_ is used -- here to lift the pure pseudo-random number generator pureGen -- into the System.Random.Stateful.StatefulGen context. -- -- The monadic interface can also be used with existing monadic -- pseudo-random number generators. In this example, we use the one -- provided in the mwc-random package: -- -- 
--   >>> import System.Random.MWC as MWC
--   
--   >>> let rollM = uniformRM (1, 6)       :: StatefulGen g m => g -> m Word
--   
--   >>> monadicGen <- MWC.create
--   
--   >>> replicateM 10 (rollM monadicGen) :: IO [Word]
--   [2,3,6,6,4,4,3,1,5,4]
--
-- -- See System.Random.Stateful for more details. @package random @version 1.2.1.2 -- | This library deals with the common task of pseudo-random number -- generation. module System.Random -- | RandomGen is an interface to pure pseudo-random number -- generators. -- -- StdGen is the standard RandomGen instance provided by -- this library. class RandomGen g -- | 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. -- | Deprecated: No longer used next :: RandomGen g => g -> (Int, g) -- | Returns a Word8 that is uniformly distributed over the entire -- Word8 range. genWord8 :: RandomGen g => g -> (Word8, g) -- | Returns a Word16 that is uniformly distributed over the entire -- Word16 range. genWord16 :: RandomGen g => g -> (Word16, g) -- | Returns a Word32 that is uniformly distributed over the entire -- Word32 range. genWord32 :: RandomGen g => g -> (Word32, g) -- | Returns a Word64 that is uniformly distributed over the entire -- Word64 range. genWord64 :: RandomGen g => g -> (Word64, g) -- | genWord32R upperBound g returns a Word32 that is -- uniformly distributed over the range [0, upperBound]. genWord32R :: RandomGen g => Word32 -> g -> (Word32, g) -- | genWord64R upperBound g returns a Word64 that is -- uniformly distributed over the range [0, upperBound]. genWord64R :: RandomGen g => Word64 -> g -> (Word64, g) -- | genShortByteString n g returns a ShortByteString of -- length n filled with pseudo-random bytes. genShortByteString :: RandomGen g => Int -> g -> (ShortByteString, g) -- | Yields the range of values returned by next. -- -- It is required that: -- -- -- -- The default definition spans the full range of Int. -- | Deprecated: No longer used genRange :: RandomGen g => g -> (Int, Int) -- | 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. split :: RandomGen g => g -> (g, g) -- | Generates a value uniformly distributed over all possible values of -- that type. -- -- This is a pure version of uniformM. -- --

Examples

-- -- 
--   >>> import System.Random
--   
--   >>> let pureGen = mkStdGen 137
--   
--   >>> uniform pureGen :: (Bool, StdGen)
--   (True,StdGen {unStdGen = SMGen 11285859549637045894 7641485672361121627})
--
uniform :: (RandomGen g, Uniform a) => g -> (a, g) -- | Generates a value uniformly distributed over the provided range, which -- is interpreted as inclusive in the lower and upper bound. -- -- -- -- 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

-- -- 
--   >>> import System.Random
--   
--   >>> let pureGen = mkStdGen 137
--   
--   >>> uniformR (1 :: Int, 4 :: Int) pureGen
--   (4,StdGen {unStdGen = SMGen 11285859549637045894 7641485672361121627})
--
uniformR :: (RandomGen g, UniformRange a) => (a, a) -> g -> (a, g) -- | Generates a ByteString of the specified size using a pure -- pseudo-random number generator. See uniformByteStringM for the -- monadic version. -- --

Examples

-- -- 
--   >>> import System.Random
--   
--   >>> import Data.ByteString
--   
--   >>> let pureGen = mkStdGen 137
--   
--   >>> unpack . fst . genByteString 10 $ pureGen
--   [51,123,251,37,49,167,90,109,1,4]
--
genByteString :: RandomGen g => Int -> g -> (ByteString, g) -- | 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. class Random a -- | 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 2021
--   
--   >>> fst $ randomR ('a', 'z') gen
--   't'
--   
--   >>> fst $ randomR ('z', 'a') gen
--   't'
--
-- -- 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 2021
--   ('t',6.240232662366563)
--
-- -- In case when a lawful range is desired uniformR should be used -- instead. randomR :: (Random a, 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 2021
--   
--   >>> fst $ randomR ('a', 'z') gen
--   't'
--   
--   >>> fst $ randomR ('z', 'a') gen
--   't'
--
-- -- 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 2021
--   ('t',6.240232662366563)
--
-- -- In case when a lawful range is desired uniformR should be used -- instead. randomR :: (Random a, RandomGen g, UniformRange a) => (a, a) -> g -> (a, g) -- | The same as randomR, but using a default range determined by -- the type: -- -- random :: (Random a, RandomGen g) => g -> (a, g) -- | The same as randomR, but using a default range determined by -- the type: -- -- random :: (Random a, RandomGen g, Uniform a) => g -> (a, g) -- | Plural variant of randomR, producing an infinite list of -- pseudo-random values instead of returning a new generator. randomRs :: (Random a, RandomGen g) => (a, a) -> g -> [a] -- | Plural variant of random, producing an infinite list of -- pseudo-random values instead of returning a new generator. randoms :: (Random a, RandomGen g) => g -> [a] -- | The class of types for which a uniformly distributed value can be -- drawn from all possible values of the type. class Uniform a -- | The class of types for which a uniformly distributed value can be -- drawn from a range. class UniformRange a -- | A type class for data with a finite number of inhabitants. This type -- class is used in default implementations of Uniform. -- -- Users are not supposed to write instances of Finite manually. -- There is a default implementation in terms of Generic instead. -- -- 
--   >>> :set -XDeriveGeneric -XDeriveAnyClass
--   
--   >>> import GHC.Generics (Generic)
--   
--   >>> data MyBool = MyTrue | MyFalse deriving (Generic, Finite)
--   
--   >>> data Action = Code MyBool | Eat (Maybe Bool) | Sleep deriving (Generic, Finite)
--
class Finite a -- | The standard pseudo-random number generator. data StdGen -- | Constructs a StdGen deterministically. mkStdGen :: Int -> StdGen -- | Initialize StdGen using system entropy (i.e. -- /dev/urandom) when it is available, while falling back on -- using system time as the seed. initStdGen :: MonadIO m => m StdGen -- | 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)
--   [5,6,6,1,1,6,4,2,4,1]
--
-- -- 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)
--   [4,6,1,1,4,4,3,2,1,2]
--
getStdRandom :: MonadIO m => (StdGen -> (a, StdGen)) -> m a -- | Gets the global pseudo-random number generator. Extracts the contents -- of globalStdGen getStdGen :: MonadIO m => m StdGen -- | Sets the global pseudo-random number generator. Overwrites the -- contents of globalStdGen setStdGen :: MonadIO m => StdGen -> m () -- | Applies split to the current global pseudo-random generator -- globalStdGen, updates it with one of the results, and returns -- the other. newStdGen :: MonadIO m => m StdGen -- | A variant of randomM that uses the global pseudo-random number -- generator globalStdGen. -- -- 
--   >>> import Data.Int
--   
--   >>> randomIO :: IO Int32
--   -1580093805
--
-- -- 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
--   -1649127057
--
randomIO :: (Random a, MonadIO m) => m a -- | A variant of randomRM that uses the global pseudo-random number -- generator globalStdGen -- -- 
--   >>> randomRIO (2020, 2100) :: IO Int
--   2040
--
-- -- 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
--   2079
--
randomRIO :: (Random a, MonadIO m) => (a, a) -> m a instance System.Random.Random GHC.Num.Integer.Integer instance System.Random.Random GHC.Int.Int8 instance System.Random.Random GHC.Int.Int16 instance System.Random.Random GHC.Int.Int32 instance System.Random.Random GHC.Int.Int64 instance System.Random.Random GHC.Types.Int instance System.Random.Random GHC.Types.Word instance System.Random.Random GHC.Word.Word8 instance System.Random.Random GHC.Word.Word16 instance System.Random.Random GHC.Word.Word32 instance System.Random.Random GHC.Word.Word64 instance System.Random.Random Foreign.C.Types.CBool instance System.Random.Random Foreign.C.Types.CChar instance System.Random.Random Foreign.C.Types.CSChar instance System.Random.Random Foreign.C.Types.CUChar instance System.Random.Random Foreign.C.Types.CShort instance System.Random.Random Foreign.C.Types.CUShort instance System.Random.Random Foreign.C.Types.CInt instance System.Random.Random Foreign.C.Types.CUInt instance System.Random.Random Foreign.C.Types.CLong instance System.Random.Random Foreign.C.Types.CULong instance System.Random.Random Foreign.C.Types.CPtrdiff instance System.Random.Random Foreign.C.Types.CSize instance System.Random.Random Foreign.C.Types.CWchar instance System.Random.Random Foreign.C.Types.CSigAtomic instance System.Random.Random Foreign.C.Types.CLLong instance System.Random.Random Foreign.C.Types.CULLong instance System.Random.Random Foreign.C.Types.CIntPtr instance System.Random.Random Foreign.C.Types.CUIntPtr instance System.Random.Random Foreign.C.Types.CIntMax instance System.Random.Random Foreign.C.Types.CUIntMax instance System.Random.Random Foreign.C.Types.CFloat instance System.Random.Random Foreign.C.Types.CDouble instance System.Random.Random GHC.Types.Char instance System.Random.Random GHC.Types.Bool instance System.Random.Random GHC.Types.Double instance System.Random.Random GHC.Types.Float instance (System.Random.Random a, System.Random.Random b) => System.Random.Random (a, b) instance (System.Random.Random a, System.Random.Random b, System.Random.Random c) => System.Random.Random (a, b, c) instance (System.Random.Random a, System.Random.Random b, System.Random.Random c, System.Random.Random d) => System.Random.Random (a, b, c, d) instance (System.Random.Random a, System.Random.Random b, System.Random.Random c, System.Random.Random d, System.Random.Random e) => System.Random.Random (a, b, c, d, e) instance (System.Random.Random a, System.Random.Random b, System.Random.Random c, System.Random.Random d, System.Random.Random e, System.Random.Random f) => System.Random.Random (a, b, c, d, e, f) instance (System.Random.Random a, System.Random.Random b, System.Random.Random c, System.Random.Random d, System.Random.Random e, System.Random.Random f, System.Random.Random g) => System.Random.Random (a, b, c, d, e, f, g) -- | This library deals with the common task of pseudo-random number -- generation. module System.Random.Stateful -- | StatefulGen is an interface to monadic pseudo-random number -- generators. class Monad m => StatefulGen g m -- | uniformWord32R upperBound g generates a Word32 that is -- uniformly distributed over the range [0, upperBound]. uniformWord32R :: StatefulGen g m => Word32 -> g -> m Word32 -- | uniformWord64R upperBound g generates a Word64 that is -- uniformly distributed over the range [0, upperBound]. uniformWord64R :: StatefulGen g m => Word64 -> g -> m Word64 -- | Generates a Word8 that is uniformly distributed over the entire -- Word8 range. -- -- The default implementation extracts a Word8 from -- uniformWord32. uniformWord8 :: StatefulGen g m => g -> m Word8 -- | Generates a Word16 that is uniformly distributed over the -- entire Word16 range. -- -- The default implementation extracts a Word16 from -- uniformWord32. uniformWord16 :: StatefulGen g m => g -> m Word16 -- | Generates a Word32 that is uniformly distributed over the -- entire Word32 range. -- -- The default implementation extracts a Word32 from -- uniformWord64. uniformWord32 :: StatefulGen g m => g -> m Word32 -- | Generates a Word64 that is uniformly distributed over the -- entire Word64 range. -- -- The default implementation combines two Word32 from -- uniformWord32 into one Word64. uniformWord64 :: StatefulGen g m => g -> m Word64 -- | uniformShortByteString n g generates a ShortByteString -- of length n filled with pseudo-random bytes. uniformShortByteString :: StatefulGen g m => Int -> g -> m ShortByteString -- | uniformShortByteString n g generates a ShortByteString -- of length n filled with pseudo-random bytes. uniformShortByteString :: (StatefulGen g m, MonadIO m) => Int -> g -> m ShortByteString -- | This class is designed for stateful pseudo-random number generators -- that can be saved as and restored from an immutable data type. class StatefulGen (MutableGen f m) m => FrozenGen f m where { -- | Represents the state of the pseudo-random number generator for use -- with thawGen and freezeGen. type MutableGen f m = (g :: Type) | g -> f; } -- | Saves the state of the pseudo-random number generator as a frozen -- seed. freezeGen :: FrozenGen f m => MutableGen f m -> m f -- | Restores the pseudo-random number generator from its frozen seed. thawGen :: FrozenGen f m => f -> m (MutableGen f m) -- | Interface to operations on RandomGen wrappers like -- IOGenM and StateGenM. class (RandomGen r, StatefulGen g m) => RandomGenM g r m | g -> r applyRandomGenM :: RandomGenM g r m => (r -> (a, r)) -> g -> m a -- | Runs a mutable pseudo-random number generator from its -- FrozenGen state. -- --

Examples

-- -- 
--   >>> import Data.Int (Int8)
--   
--   >>> withMutableGen (IOGen (mkStdGen 217)) (uniformListM 5) :: IO ([Int8], IOGen StdGen)
--   ([-74,37,-50,-2,3],IOGen {unIOGen = StdGen {unStdGen = SMGen 4273268533320920145 15251669095119325999}})
--
withMutableGen :: FrozenGen f m => f -> (MutableGen f m -> m a) -> m (a, f) -- | Same as withMutableGen, but only returns the generated value. -- --

Examples

-- -- 
--   >>> import System.Random.Stateful
--   
--   >>> let pureGen = mkStdGen 137
--   
--   >>> withMutableGen_ (IOGen pureGen) (uniformRM (1 :: Int, 6 :: Int))
--   4
--
withMutableGen_ :: FrozenGen f m => f -> (MutableGen f m -> m a) -> m a -- | Generates a pseudo-random value using monadic interface and -- Random instance. -- --

Examples

-- -- 
--   >>> import System.Random.Stateful
--   
--   >>> let pureGen = mkStdGen 137
--   
--   >>> g <- newIOGenM pureGen
--   
--   >>> randomM g :: IO Double
--   0.5728354935654512
--
randomM :: (RandomGenM g r m, Random a) => g -> m a -- | Generates a pseudo-random value using monadic interface and -- Random instance. -- --

Examples

-- -- 
--   >>> import System.Random.Stateful
--   
--   >>> let pureGen = mkStdGen 137
--   
--   >>> g <- newIOGenM pureGen
--   
--   >>> randomRM (1, 100) g :: IO Int
--   52
--
randomRM :: (RandomGenM g r m, Random a) => (a, a) -> g -> m a -- | Splits a pseudo-random number generator into two. Overwrites the -- mutable wrapper with one of the resulting generators and returns the -- other. splitGenM :: RandomGenM g r m => g -> m r -- | Wrapper for pure state gen, which acts as an immutable seed for the -- corresponding stateful generator StateGenM newtype StateGen g StateGen :: g -> StateGen g [unStateGen] :: StateGen g -> g -- | Opaque data type that carries the type of a pure pseudo-random number -- generator. data StateGenM g StateGenM :: StateGenM g -- | Runs a monadic generating action in the State monad using a -- pure pseudo-random number generator. -- --

Examples

-- -- 
--   >>> import System.Random.Stateful
--   
--   >>> let pureGen = mkStdGen 137
--   
--   >>> runStateGen pureGen randomM :: (Int, StdGen)
--   (7879794327570578227,StdGen {unStdGen = SMGen 11285859549637045894 7641485672361121627})
--
runStateGen :: RandomGen g => g -> (StateGenM g -> State g a) -> (a, g) -- | Runs a monadic generating action in the State monad using a -- pure pseudo-random number generator. Returns only the resulting -- pseudo-random value. -- --

Examples

-- -- 
--   >>> import System.Random.Stateful
--   
--   >>> let pureGen = mkStdGen 137
--   
--   >>> runStateGen_ pureGen randomM :: Int
--   7879794327570578227
--
runStateGen_ :: RandomGen g => g -> (StateGenM g -> State g a) -> a -- | Runs a monadic generating action in the StateT monad using a -- pure pseudo-random number generator. -- --

Examples

-- -- 
--   >>> import System.Random.Stateful
--   
--   >>> let pureGen = mkStdGen 137
--   
--   >>> runStateGenT pureGen randomM :: IO (Int, StdGen)
--   (7879794327570578227,StdGen {unStdGen = SMGen 11285859549637045894 7641485672361121627})
--
runStateGenT :: RandomGen g => g -> (StateGenM g -> StateT g m a) -> m (a, g) -- | Runs a monadic generating action in the StateT monad using a -- pure pseudo-random number generator. Returns only the resulting -- pseudo-random value. -- --

Examples

-- -- 
--   >>> import System.Random.Stateful
--   
--   >>> let pureGen = mkStdGen 137
--   
--   >>> runStateGenT_ pureGen randomM :: IO Int
--   7879794327570578227
--
runStateGenT_ :: (RandomGen g, Functor f) => g -> (StateGenM g -> StateT g f a) -> f a -- | Runs a monadic generating action in the ST monad using a pure -- pseudo-random number generator. runStateGenST :: RandomGen g => g -> (forall s. StateGenM g -> StateT g (ST s) a) -> (a, g) -- | Runs a monadic generating action in the ST monad using a pure -- pseudo-random number generator. Same as runStateGenST, but -- discards the resulting generator. runStateGenST_ :: RandomGen g => g -> (forall s. StateGenM g -> StateT g (ST s) a) -> a -- | Frozen version of mutable AtomicGenM generator newtype AtomicGen g AtomicGen :: g -> AtomicGen g [unAtomicGen] :: AtomicGen g -> g -- | Wraps an IORef that holds a pure pseudo-random number -- generator. All operations are performed atomically. -- -- newtype AtomicGenM g AtomicGenM :: IORef g -> AtomicGenM g [unAtomicGenM] :: AtomicGenM g -> IORef g -- | Creates a new AtomicGenM. newAtomicGenM :: MonadIO m => g -> m (AtomicGenM g) -- | Atomically applies a pure operation to the wrapped pseudo-random -- number generator. -- --

Examples

-- -- 
--   >>> import System.Random.Stateful
--   
--   >>> let pureGen = mkStdGen 137
--   
--   >>> g <- newAtomicGenM pureGen
--   
--   >>> applyAtomicGen random g :: IO Int
--   7879794327570578227
--
applyAtomicGen :: MonadIO m => (g -> (a, g)) -> AtomicGenM g -> m a -- | Global mutable standard pseudo-random number generator. This is the -- same generator that was historically used by randomIO and -- randomRIO functions. -- -- 
--   >>> replicateM 10 (uniformRM ('a', 'z') globalStdGen)
--   "tdzxhyfvgr"
--
globalStdGen :: AtomicGenM StdGen -- | Frozen version of mutable IOGenM generator newtype IOGen g IOGen :: g -> IOGen g [unIOGen] :: IOGen g -> g -- | Wraps an IORef that holds a pure pseudo-random number -- generator. -- -- -- -- An example use case is writing pseudo-random bytes into a file: -- -- 
--   >>> import UnliftIO.Temporary (withSystemTempFile)
--   
--   >>> import Data.ByteString (hPutStr)
--   
--   >>> let ioGen g = withSystemTempFile "foo.bin" $ \_ h -> uniformRM (0, 100) g >>= flip uniformByteStringM g >>= hPutStr h
--
-- -- and then run it: -- -- 
--   >>> newIOGenM (mkStdGen 1729) >>= ioGen
--
newtype IOGenM g IOGenM :: IORef g -> IOGenM g [unIOGenM] :: IOGenM g -> IORef g -- | Creates a new IOGenM. newIOGenM :: MonadIO m => g -> m (IOGenM g) -- | Applies a pure operation to the wrapped pseudo-random number -- generator. -- --

Examples

-- -- 
--   >>> import System.Random.Stateful
--   
--   >>> let pureGen = mkStdGen 137
--   
--   >>> g <- newIOGenM pureGen
--   
--   >>> applyIOGen random g :: IO Int
--   7879794327570578227
--
applyIOGen :: MonadIO m => (g -> (a, g)) -> IOGenM g -> m a -- | Frozen version of mutable STGenM generator newtype STGen g STGen :: g -> STGen g [unSTGen] :: STGen g -> g -- | Wraps an STRef that holds a pure pseudo-random number -- generator. -- -- newtype STGenM g s STGenM :: STRef s g -> STGenM g s [unSTGenM] :: STGenM g s -> STRef s g -- | Creates a new STGenM. newSTGenM :: g -> ST s (STGenM g s) -- | Applies a pure operation to the wrapped pseudo-random number -- generator. -- --

Examples

-- -- 
--   >>> import System.Random.Stateful
--   
--   >>> let pureGen = mkStdGen 137
--   
--   >>> (runSTGen pureGen (\g -> applySTGen random g)) :: (Int, StdGen)
--   (7879794327570578227,StdGen {unStdGen = SMGen 11285859549637045894 7641485672361121627})
--
applySTGen :: (g -> (a, g)) -> STGenM g s -> ST s a -- | Runs a monadic generating action in the ST monad using a pure -- pseudo-random number generator. -- --

Examples

-- -- 
--   >>> import System.Random.Stateful
--   
--   >>> let pureGen = mkStdGen 137
--   
--   >>> (runSTGen pureGen (\g -> applySTGen random g)) :: (Int, StdGen)
--   (7879794327570578227,StdGen {unStdGen = SMGen 11285859549637045894 7641485672361121627})
--
runSTGen :: RandomGen g => g -> (forall s. STGenM g s -> ST s a) -> (a, g) -- | Runs a monadic generating action in the ST monad using a pure -- pseudo-random number generator. Returns only the resulting -- pseudo-random value. -- --

Examples

-- -- 
--   >>> import System.Random.Stateful
--   
--   >>> let pureGen = mkStdGen 137
--   
--   >>> (runSTGen_ pureGen (\g -> applySTGen random g)) :: Int
--   7879794327570578227
--
runSTGen_ :: RandomGen g => g -> (forall s. STGenM g s -> ST s a) -> a -- | Frozen version of mutable TGenM generator newtype TGen g TGen :: g -> TGen g [unTGen] :: TGen g -> g -- | Wraps a TVar that holds a pure pseudo-random number generator. newtype TGenM g TGenM :: TVar g -> TGenM g [unTGenM] :: TGenM g -> TVar g -- | Creates a new TGenM in STM. newTGenM :: g -> STM (TGenM g) -- | Creates a new TGenM in IO. newTGenMIO :: MonadIO m => g -> m (TGenM g) -- | Applies a pure operation to the wrapped pseudo-random number -- generator. -- --

Examples

-- -- 
--   >>> import Control.Concurrent.STM
--   
--   >>> import System.Random.Stateful
--   
--   >>> import Data.Int (Int32)
--   
--   >>> let pureGen = mkStdGen 137
--   
--   >>> stmGen <- newTGenMIO pureGen
--   
--   >>> atomically $ applyTGen uniform stmGen :: IO Int32
--   637238067
--
applyTGen :: (g -> (a, g)) -> TGenM g -> STM a -- | The class of types for which a uniformly distributed value can be -- drawn from all possible values of the type. class Uniform a -- | Generates a value uniformly distributed over all possible values of -- that type. -- -- There is a default implementation via Generic: -- -- 
--   >>> :set -XDeriveGeneric -XDeriveAnyClass
--   
--   >>> import GHC.Generics (Generic)
--   
--   >>> import System.Random.Stateful
--   
--   >>> data MyBool = MyTrue | MyFalse deriving (Show, Generic, Finite, Uniform)
--   
--   >>> data Action = Code MyBool | Eat (Maybe Bool) | Sleep deriving (Show, Generic, Finite, Uniform)
--   
--   >>> gen <- newIOGenM (mkStdGen 42)
--   
--   >>> uniformListM 10 gen :: IO [Action]
--   [Code MyTrue,Code MyTrue,Eat Nothing,Code MyFalse,Eat (Just False),Eat (Just True),Eat Nothing,Eat (Just False),Sleep,Code MyFalse]
--
uniformM :: (Uniform a, StatefulGen g m) => g -> m a -- | Generates a value uniformly distributed over all possible values of -- that type. -- -- There is a default implementation via Generic: -- -- 
--   >>> :set -XDeriveGeneric -XDeriveAnyClass
--   
--   >>> import GHC.Generics (Generic)
--   
--   >>> import System.Random.Stateful
--   
--   >>> data MyBool = MyTrue | MyFalse deriving (Show, Generic, Finite, Uniform)
--   
--   >>> data Action = Code MyBool | Eat (Maybe Bool) | Sleep deriving (Show, Generic, Finite, Uniform)
--   
--   >>> gen <- newIOGenM (mkStdGen 42)
--   
--   >>> uniformListM 10 gen :: IO [Action]
--   [Code MyTrue,Code MyTrue,Eat Nothing,Code MyFalse,Eat (Just False),Eat (Just True),Eat Nothing,Eat (Just False),Sleep,Code MyFalse]
--
uniformM :: (Uniform a, StatefulGen g m, Generic a, GUniform (Rep a)) => g -> m a -- | Generates a list of pseudo-random values. -- --

Examples

-- -- 
--   >>> import System.Random.Stateful
--   
--   >>> let pureGen = mkStdGen 137
--   
--   >>> g <- newIOGenM pureGen
--   
--   >>> uniformListM 10 g :: IO [Bool]
--   [True,True,True,True,False,True,True,False,False,False]
--
uniformListM :: (StatefulGen g m, Uniform a) => Int -> g -> m [a] -- | A definition of Uniform for Finite types. If your data -- has several fields of sub-Word cardinality, this instance may -- be more efficient than one, derived via Generic and -- GUniform. -- -- 
--   >>> :set -XDeriveGeneric -XDeriveAnyClass
--   
--   >>> import GHC.Generics (Generic)
--   
--   >>> import System.Random.Stateful
--   
--   >>> data Triple = Triple Word8 Word8 Word8 deriving (Show, Generic, Finite)
--   
--   >>> instance Uniform Triple where uniformM = uniformViaFiniteM
--   
--   >>> gen <- newIOGenM (mkStdGen 42)
--   
--   >>> uniformListM 5 gen :: IO [Triple]
--   [Triple 60 226 48,Triple 234 194 151,Triple 112 96 95,Triple 51 251 15,Triple 6 0 208]
--
uniformViaFiniteM :: (StatefulGen g m, Generic a, GFinite (Rep a)) => g -> m a -- | The class of types for which a uniformly distributed value can be -- drawn from a range. class UniformRange a -- | Generates a value uniformly distributed over the provided range, which -- is interpreted as inclusive in the lower and upper bound. -- -- -- -- The following law should hold to make the function always defined: -- -- 
--   uniformRM (a, b) = uniformRM (b, a)
--
uniformRM :: (UniformRange a, StatefulGen g m) => (a, a) -> g -> m a -- | Efficiently generates a sequence of pseudo-random bytes in a platform -- independent manner. genShortByteStringIO :: MonadIO m => Int -> m Word64 -> m ShortByteString -- | Same as genShortByteStringIO, but runs in ST. genShortByteStringST :: Int -> ST s Word64 -> ST s ShortByteString -- | Generates a pseudo-random ByteString of the specified size. uniformByteStringM :: StatefulGen g m => Int -> g -> m ByteString -- | Generates uniformly distributed Double in the range -- <math>. Numbers are generated by generating uniform -- Word64 and dividing it by <math>. It's used to implement -- UniformRange instance for Double. uniformDouble01M :: forall g m. StatefulGen g m => g -> m Double -- | Generates uniformly distributed Double in the range -- <math>. Number is generated as <math>. Constant is 1/2 of -- smallest nonzero value which could be generated by -- uniformDouble01M. uniformDoublePositive01M :: forall g m. StatefulGen g m => g -> m Double -- | Generates uniformly distributed Float in the range -- <math>. Numbers are generated by generating uniform -- Word32 and dividing it by <math>. It's used to implement -- UniformRange instance for Float. uniformFloat01M :: forall g m. StatefulGen g m => g -> m Float -- | Generates uniformly distributed Float in the range -- <math>. Number is generated as <math>. Constant is 1/2 of -- smallest nonzero value which could be generated by -- uniformFloat01M. uniformFloatPositive01M :: forall g m. StatefulGen g m => g -> m Float -- | Generates uniformly distributed Enum. One can use it to define -- a Uniform instance: -- -- 
--   data Colors = Red | Green | Blue deriving (Enum, Bounded)
--   instance Uniform Colors where uniformM = uniformEnumM
--
uniformEnumM :: forall a g m. (Enum a, Bounded a, StatefulGen g m) => g -> m a -- | Generates uniformly distributed Enum in the given range. One -- can use it to define a UniformRange instance: -- -- 
--   data Colors = Red | Green | Blue deriving (Enum)
--   instance UniformRange Colors where
--     uniformRM = uniformEnumRM
--     inInRange (lo, hi) x = isInRange (fromEnum lo, fromEnum hi) (fromEnum x)
--
uniformEnumRM :: forall a g m. (Enum a, StatefulGen g m) => (a, a) -> g -> m a instance Control.DeepSeq.NFData g => Control.DeepSeq.NFData (System.Random.Stateful.AtomicGen g) instance Foreign.Storable.Storable g => Foreign.Storable.Storable (System.Random.Stateful.AtomicGen g) instance System.Random.Internal.RandomGen g => System.Random.Internal.RandomGen (System.Random.Stateful.AtomicGen g) instance GHC.Show.Show g => GHC.Show.Show (System.Random.Stateful.AtomicGen g) instance GHC.Classes.Ord g => GHC.Classes.Ord (System.Random.Stateful.AtomicGen g) instance GHC.Classes.Eq g => GHC.Classes.Eq (System.Random.Stateful.AtomicGen g) instance Control.DeepSeq.NFData g => Control.DeepSeq.NFData (System.Random.Stateful.IOGen g) instance Foreign.Storable.Storable g => Foreign.Storable.Storable (System.Random.Stateful.IOGen g) instance System.Random.Internal.RandomGen g => System.Random.Internal.RandomGen (System.Random.Stateful.IOGen g) instance GHC.Show.Show g => GHC.Show.Show (System.Random.Stateful.IOGen g) instance GHC.Classes.Ord g => GHC.Classes.Ord (System.Random.Stateful.IOGen g) instance GHC.Classes.Eq g => GHC.Classes.Eq (System.Random.Stateful.IOGen g) instance Control.DeepSeq.NFData g => Control.DeepSeq.NFData (System.Random.Stateful.STGen g) instance Foreign.Storable.Storable g => Foreign.Storable.Storable (System.Random.Stateful.STGen g) instance System.Random.Internal.RandomGen g => System.Random.Internal.RandomGen (System.Random.Stateful.STGen g) instance GHC.Show.Show g => GHC.Show.Show (System.Random.Stateful.STGen g) instance GHC.Classes.Ord g => GHC.Classes.Ord (System.Random.Stateful.STGen g) instance GHC.Classes.Eq g => GHC.Classes.Eq (System.Random.Stateful.STGen g) instance Control.DeepSeq.NFData g => Control.DeepSeq.NFData (System.Random.Stateful.TGen g) instance Foreign.Storable.Storable g => Foreign.Storable.Storable (System.Random.Stateful.TGen g) instance System.Random.Internal.RandomGen g => System.Random.Internal.RandomGen (System.Random.Stateful.TGen g) instance GHC.Show.Show g => GHC.Show.Show (System.Random.Stateful.TGen g) instance GHC.Classes.Ord g => GHC.Classes.Ord (System.Random.Stateful.TGen g) instance GHC.Classes.Eq g => GHC.Classes.Eq (System.Random.Stateful.TGen g) instance System.Random.Internal.RandomGen g => System.Random.Internal.FrozenGen (System.Random.Stateful.TGen g) GHC.Conc.Sync.STM instance System.Random.Internal.RandomGen r => System.Random.Stateful.RandomGenM (System.Random.Stateful.TGenM r) r GHC.Conc.Sync.STM instance System.Random.Internal.RandomGen g => System.Random.Internal.StatefulGen (System.Random.Stateful.TGenM g) GHC.Conc.Sync.STM instance System.Random.Internal.RandomGen g => System.Random.Internal.FrozenGen (System.Random.Stateful.STGen g) (GHC.ST.ST s) instance System.Random.Internal.RandomGen r => System.Random.Stateful.RandomGenM (System.Random.Stateful.STGenM r s) r (GHC.ST.ST s) instance System.Random.Internal.RandomGen g => System.Random.Internal.StatefulGen (System.Random.Stateful.STGenM g s) (GHC.ST.ST s) instance (System.Random.Internal.RandomGen g, Control.Monad.IO.Class.MonadIO m) => System.Random.Internal.FrozenGen (System.Random.Stateful.IOGen g) m instance (System.Random.Internal.RandomGen r, Control.Monad.IO.Class.MonadIO m) => System.Random.Stateful.RandomGenM (System.Random.Stateful.IOGenM r) r m instance (System.Random.Internal.RandomGen g, Control.Monad.IO.Class.MonadIO m) => System.Random.Internal.StatefulGen (System.Random.Stateful.IOGenM g) m instance (System.Random.Internal.RandomGen g, Control.Monad.IO.Class.MonadIO m) => System.Random.Internal.FrozenGen (System.Random.Stateful.AtomicGen g) m instance (System.Random.Internal.RandomGen r, Control.Monad.IO.Class.MonadIO m) => System.Random.Stateful.RandomGenM (System.Random.Stateful.AtomicGenM r) r m instance (System.Random.Internal.RandomGen g, Control.Monad.IO.Class.MonadIO m) => System.Random.Internal.StatefulGen (System.Random.Stateful.AtomicGenM g) m instance (System.Random.Internal.RandomGen r, Control.Monad.State.Class.MonadState r m) => System.Random.Stateful.RandomGenM (System.Random.Internal.StateGenM r) r m