| Copyright | (c) Brent Yorgey 2016 |
|---|---|
| License | BSD3 (see LICENSE) |
| Maintainer | byorgey@gmail.com |
| Stability | experimental |
| Portability | non-portable (multi-param classes, functional dependencies, undecidable instances) |
| Safe Haskell | Safe |
| Language | Haskell2010 |
Control.Monad.Random.Lazy
Description
Random monads that are lazy in the generator state. For a strict version, see Control.Monad.Random.Strict, which has the same interface.
Synopsis
- type Rand g = RandT g Identity
- liftRand :: (g -> (a, g)) -> Rand g a
- runRand :: Rand g a -> g -> (a, g)
- evalRand :: Rand g a -> g -> a
- execRand :: Rand g a -> g -> g
- mapRand :: ((a, g) -> (b, g)) -> Rand g a -> Rand g b
- withRand :: (g -> g) -> Rand g a -> Rand g a
- evalRandIO :: Rand StdGen a -> IO a
- data RandT g m a
- liftRandT :: (g -> m (a, g)) -> RandT g m a
- runRandT :: RandT g m a -> g -> m (a, g)
- evalRandT :: Monad m => RandT g m a -> g -> m a
- execRandT :: Monad m => RandT g m a -> g -> m g
- mapRandT :: (m (a, g) -> n (b, g)) -> RandT g m a -> RandT g n b
- withRandT :: (g -> g) -> RandT g m a -> RandT g m a
- evalRandTIO :: MonadIO m => RandT StdGen m a -> m a
- class Uniform a
- class (KnownNat (SeedSize g), 1 <= SeedSize g, Typeable g) => SeedGen g where
- type family SeedSize g :: Nat
- class Finite a
- class UniformRange a
- data StdGen
- class RandomGen g => SplitGen g where
- splitGen :: g -> (g, g)
- class RandomGen g where
- next :: g -> (Int, g)
- 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)
- genShortByteString :: Int -> g -> (ShortByteString, g)
- unsafeUniformFillMutableByteArray :: MutableByteArray s -> Int -> Int -> g -> ST s g
- genRange :: g -> (Int, Int)
- split :: g -> (g, g)
- data Seed g
- class Random a where
- uniformShortByteString :: RandomGen g => Int -> g -> (ShortByteString, g)
- uniformByteArray :: RandomGen g => Bool -> Int -> g -> (ByteArray, g)
- mkStdGen :: Int -> StdGen
- mkStdGen64 :: Word64 -> StdGen
- seedSize :: SeedGen g => Int
- seedSizeProxy :: forall proxy g. SeedGen g => proxy g -> Int
- mkSeed :: (SeedGen g, MonadFail m) => ByteArray -> m (Seed g)
- 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)
- seedGenTypeName :: SeedGen g => String
- mkSeedFromByteString :: (SeedGen g, MonadFail m) => ByteString -> m (Seed g)
- unSeed :: Seed g -> ByteArray
- unSeedToByteString :: Seed g -> ByteString
- withSeedFile :: (SeedGen g, MonadIO m) => FilePath -> (Seed g -> m (a, Seed g)) -> m a
- nonEmptyToSeed :: SeedGen g => NonEmpty Word64 -> Seed g
- nonEmptyFromSeed :: SeedGen g => Seed g -> NonEmpty Word64
- 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)
- genByteString :: RandomGen g => Int -> g -> (ByteString, g)
- uniformByteString :: RandomGen g => Int -> g -> (ByteString, g)
- uniformFillMutableByteArray :: RandomGen g => MutableByteArray s -> Int -> Int -> g -> ST s g
- initStdGen :: MonadIO m => m StdGen
- setStdGen :: MonadIO m => StdGen -> m ()
- getStdGen :: MonadIO m => m StdGen
- newStdGen :: MonadIO m => m StdGen
- getStdRandom :: MonadIO m => (StdGen -> (a, StdGen)) -> m a
- randomRIO :: (Random a, MonadIO m) => (a, a) -> m a
- randomIO :: (Random a, MonadIO m) => m a
- module Control.Monad.Random.Class
- module Control.Monad
- module Control.Monad.Fix
- module Control.Monad.Trans
The Rand monad
Arguments
| :: (g -> (a, g)) | pure random transformer |
| -> Rand g a | equivalent generator-passing computation |
Construct a random monad computation from a function.
(The inverse of runRand.)
Arguments
| :: Rand g a | generator-passing computation to execute |
| -> g | initial generator |
| -> (a, g) | return value and final generator |
Unwrap a random monad computation as a function.
(The inverse of liftRand.)
Arguments
| :: Rand g a | generator-passing computation to execute |
| -> g | initial generator |
| -> a | return value of the random computation |
Arguments
| :: Rand g a | generator-passing computation to execute |
| -> g | initial generator |
| -> g | final generator |
evalRandIO :: Rand StdGen a -> IO a Source #
Evaluate a random computation in the IO monad, splitting the global
standard generator to get a new one for the computation.
The RandT monad transformer
A random transformer monad parameterized by:
g- The generator.m- The inner monad.
The return function leaves the generator unchanged, while >>= uses the
final generator of the first computation as the initial generator of the
second.
Instances
Arguments
| :: (g -> m (a, g)) | impure random transformer |
| -> RandT g m a | equivalent generator-passing computation |
Construct a random monad computation from an impure function.
(The inverse of runRandT.)
Arguments
| :: RandT g m a | generator-passing computation to execute |
| -> g | initial generator |
| -> m (a, g) | return value and final generator |
Unwrap a random monad computation as an impure function.
(The inverse of liftRandT.)
evalRandTIO :: MonadIO m => RandT StdGen m a -> m a Source #
Evaluate a random computation that is embedded in the IO monad,
splitting the global standard generator to get a new one for the
computation.
Some convenience re-exports
The class of types for which a uniformly distributed value can be drawn from all possible values of the type.
Since: random-1.2.0
Instances
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 0x01020304FiveByteGen 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: random-1.3.0
Minimal complete definition
Associated Types
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
Convert from a binary representation to a pseudo-random number generator
Since: random-1.3.0
Convert to a binary representation of a pseudo-random number generator
Since: random-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: random-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: random-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
| type SeedSize StdGen | |
Defined in System.Random.Seed | |
| type SeedSize SMGen | |
Defined in System.Random.Seed | |
| type SeedSize SMGen | |
Defined in System.Random.Seed | |
| type SeedSize (StateGen g) | |
Defined in System.Random.Seed | |
| type SeedSize (AtomicGen g) | |
Defined in System.Random.Stateful | |
| type SeedSize (IOGen g) | |
Defined in System.Random.Stateful | |
| type SeedSize (STGen g) | |
Defined in System.Random.Stateful | |
| type SeedSize (TGen g) | |
Defined in System.Random.Stateful | |
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
class UniformRange a #
The class of types for which a uniformly distributed value can be drawn from a range.
Since: random-1.2.0
Instances
The standard pseudo-random number generator.
Instances
| Show StdGen | |
| NFData StdGen | |
Defined in System.Random.Internal | |
| Eq StdGen | |
| RandomGen StdGen | |
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 # | |
| SplitGen StdGen | |
| SeedGen StdGen | |
| MonadSplit StdGen IO Source # | |
| type SeedSize StdGen | |
Defined in System.Random.Seed | |
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: random-1.3.0
Methods
Returns two distinct pseudo-random number generators.
Implementations should take care to ensure that the resulting generators are not correlated.
Since: random-1.3.0
RandomGen is an interface to pure pseudo-random number generators.
StdGen is the standard RandomGen instance provided by this library.
Since: random-1.0.0
Methods
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: random-1.0.0
genWord16 :: g -> (Word16, g) #
genWord32 :: g -> (Word32, g) #
genWord64 :: g -> (Word64, g) #
genWord32R :: Word32 -> g -> (Word32, g) #
genWord32R upperBound g returns a Word32 that is uniformly
distributed over the range [0, upperBound].
Since: random-1.2.0
genWord64R :: Word64 -> g -> (Word64, g) #
genWord64R upperBound g returns a Word64 that is uniformly
distributed over the range [0, upperBound].
Since: random-1.2.0
genShortByteString :: Int -> g -> (ShortByteString, g) #
Same as uniformByteArray FalseShortByteString.
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: random-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: random-1.3.0
Yields the range of values returned by next.
It is required that:
- If
(a, b) =, thengenRangega < b. genRangemust not examine its argument so the value it returns is determined only by the instance ofRandomGen.
The default definition spans the full range of Int.
Since: random-1.0.0
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: random-1.0.0
Instances
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: random-1.3.0
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: random-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: random-1.0.0
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 asChar), 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 ofInt.
Since: random-1.0.0
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: random-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: random-1.0.0
Instances
| Random CBool | |
| Random CChar | |
| Random CDouble | Note - |
| Random CFloat | Note - |
| Random CInt | |
| Random CIntMax | |
| Random CIntPtr | |
| Random CLLong | |
| Random CLong | |
| Random CPtrdiff | |
| Random CSChar | |
| Random CShort | |
| Random CSigAtomic | |
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 | |
| Random CUChar | |
| Random CUInt | |
| Random CUIntMax | |
| Random CUIntPtr | |
| Random CULLong | |
| Random CULong | |
| Random CUShort | |
| Random CWchar | |
| Random Int16 | |
| Random Int32 | |
| Random Int64 | |
| Random Int8 | |
| Random Word16 | |
| Random Word32 | |
| Random Word64 | |
| Random Word8 | |
| Random Integer | |
| Random Bool | |
| Random Char | |
| Random Double | Note - |
| Random Float | Note - |
| Random Int | |
| Random Word | |
| (Random a, Random b) => Random (a, b) | Note - |
| (Random a, Random b, Random c) => Random (a, b, c) | Note - |
| (Random a, Random b, Random c, Random d) => Random (a, b, c, d) | Note - |
| (Random a, Random b, Random c, Random d, Random e) => Random (a, b, c, d, e) | Note - |
Defined in System.Random | |
| (Random a, Random b, Random c, Random d, Random e, Random f) => Random (a, b, c, d, e, f) | Note - |
| (Random a, Random b, Random c, Random d, Random e, Random f, Random g) => Random (a, b, c, d, e, f, g) | Note - |
Defined in System.Random | |
uniformShortByteString :: RandomGen g => Int -> g -> (ShortByteString, g) #
Same as uniformByteArray FalseShortByteString.
Returns a ShortByteString of length n filled with pseudo-random bytes.
Examples
>>>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: random-1.3.0
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: random-1.3.0
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: random-1.3.0
seedSizeProxy :: forall proxy g. SeedGen g => proxy g -> Int #
Just like seedSize, except it accepts a proxy as an argument.
Since: random-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
>>>: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: random-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: random-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: random-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: random-1.3.0
unSeedToByteString :: Seed g -> ByteString #
Just like unSeed, but produced a ByteString. Results in a memcopy of the seed.
Since: random-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: random-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: random-1.3.0
nonEmptyFromSeed :: SeedGen g => Seed g -> NonEmpty Word64 #
Convert a Seed to a list of 64bit words.
Since: random-1.3.0
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
>>>let gen = mkStdGen 2023>>>import Data.Word (Word16)>>>take 5 $ uniforms gen :: [Word16][56342,15850,25292,14347,13919]
Since: random-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
>>>let gen = mkStdGen 2023>>>take 5 $ uniformRs (10, 100) gen :: [Int][32,86,21,57,39]
Since: random-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
>>>let gen = mkStdGen 2023>>>import Data.Word (Word16)>>>uniformList 5 gen :: ([Word16], StdGen)([56342,15850,25292,14347,13919],StdGen {unStdGen = SMGen 6446154349414395371 1920468677557965761})
Since: random-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
>>>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: random-1.3.0
uniformShuffleList :: RandomGen g => [a] -> g -> ([a], g) #
Shuffle elements of a list in a uniformly random order.
Examples
>>>uniformShuffleList "ELVIS" $ mkStdGen 252("LIVES",StdGen {unStdGen = SMGen 17676540583805057877 5302934877338729551})
Since: random-1.3.0
genByteString :: 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
>>>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: random-1.2.0
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
>>>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: random-1.3.0
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: random-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: random-1.2.1
setStdGen :: MonadIO m => StdGen -> m () #
Sets the global pseudo-random number generator. Overwrites the contents of
globalStdGen
Since: random-1.0.0
getStdGen :: MonadIO m => m StdGen #
Gets the global pseudo-random number generator. Extracts the contents of
globalStdGen
Since: random-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: random-1.0.0
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: random-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 Int2028
Similar to randomIO, this function is equivalent to getStdRandom
randomRuniformRM instead, possibly with the
globalStdGen if relying on the global state is
acceptable.
>>>import System.Random.Stateful>>>uniformRM (2020, 2100) globalStdGen :: IO Int2044
Since: random-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 Int32114794456
This function is equivalent to getStdRandom randomuniformM instead, possibly with
the globalStdGen if relying on the global state is
acceptable.
>>>import System.Random.Stateful>>>uniformM globalStdGen :: IO Int32-1768545016
Since: random-1.0.0
module Control.Monad.Random.Class
module Control.Monad
module Control.Monad.Fix
module Control.Monad.Trans