| 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
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
- class Uniform a
- class UniformRange a
- class Finite a
- data Seed g
- class (KnownNat (SeedSize g), 1 <= SeedSize g, Typeable g) => SeedGen g where
- 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
RandomGenis an interface to pure pseudo-random number generators.StdGen, the standard pseudo-random number generator provided in this library, is an instance ofRandomGen. It uses the SplitMix implementation provided by the splitmix package. Programmers may, of course, supply their own instances ofRandomGen.
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
splitif 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 Source #
RandomGen is an interface to pure pseudo-random number generators.
StdGen is the standard RandomGen instance provided by this library.
Since: 1.0.0
Methods
genWord8 :: g -> (Word8, g) Source #
genWord16 :: g -> (Word16, g) Source #
genWord32 :: g -> (Word32, g) Source #
genWord64 :: g -> (Word64, g) Source #
genWord32R :: Word32 -> g -> (Word32, g) Source #
genWord32R upperBound g returns a Word32 that is uniformly
distributed over the range [0, upperBound].
Since: 1.2.0
genWord64R :: Word64 -> g -> (Word64, g) Source #
genWord64R upperBound g returns a Word64 that is uniformly
distributed over the range [0, upperBound].
Since: 1.2.0
unsafeUniformFillMutableByteArray Source #
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
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
Instances
class RandomGen g => SplitGen g where Source #
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) Source #
Returns two distinct pseudo-random number generators.
Implementations should take care to ensure that the resulting generators are not correlated.
Since: 1.3.0
uniform :: (Uniform a, RandomGen g) => g -> (a, g) Source #
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})
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) Source #
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
>>>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
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) Source #
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) Source #
random :: RandomGen g => g -> (a, g) Source #
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: 1.0.0
randomRs :: RandomGen g => (a, a) -> g -> [a] Source #
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] Source #
Plural variant of random, producing an infinite list of
pseudo-random values instead of returning a new generator.
Since: 1.0.0
Instances
| Random CBool Source # | |
| Random CChar Source # | |
| Random CDouble Source # | Note - |
| Random CFloat Source # | Note - |
| Random CInt Source # | |
| Random CIntMax Source # | |
| Random CIntPtr Source # | |
| Random CLLong Source # | |
| Random CLong Source # | |
| Random CPtrdiff Source # | |
| Random CSChar Source # | |
| Random CShort Source # | |
| Random CSigAtomic Source # | |
Defined in System.Random Methods randomR :: RandomGen g => (CSigAtomic, CSigAtomic) -> g -> (CSigAtomic, g) Source # random :: RandomGen g => g -> (CSigAtomic, g) Source # randomRs :: RandomGen g => (CSigAtomic, CSigAtomic) -> g -> [CSigAtomic] Source # randoms :: RandomGen g => g -> [CSigAtomic] Source # | |
| Random CSize Source # | |
| Random CUChar Source # | |
| Random CUInt Source # | |
| Random CUIntMax Source # | |
| Random CUIntPtr Source # | |
| Random CULLong Source # | |
| Random CULong Source # | |
| Random CUShort Source # | |
| Random CWchar Source # | |
| Random Int16 Source # | |
| Random Int32 Source # | |
| Random Int64 Source # | |
| Random Int8 Source # | |
| Random Word16 Source # | |
| Random Word32 Source # | |
| Random Word64 Source # | |
| Random Word8 Source # | |
| Random Integer Source # | |
| Random Bool Source # | |
| Random Char Source # | |
| Random Double Source # | Note - |
| Random Float Source # | Note - |
| Random Int Source # | |
| Random Word Source # | |
| (Random a, Random b) => Random (a, b) Source # | Note - |
| (Random a, Random b, Random c) => Random (a, b, c) Source # | Note - |
| (Random a, Random b, Random c, Random d) => Random (a, b, c, d) Source # | Note - |
Defined in System.Random | |
| (Random a, Random b, Random c, Random d, Random e) => Random (a, b, c, d, e) Source # | Note - |
| (Random a, Random b, Random c, Random d, Random e, Random f) => Random (a, b, c, d, e, f) Source # | Note - |
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) Source # random :: RandomGen g => g -> ((a, b, c, d, e, f), g) Source # randomRs :: RandomGen g => ((a, b, c, d, e, f), (a, b, c, d, e, f)) -> g -> [(a, b, c, d, e, f)] Source # randoms :: RandomGen g => g -> [(a, b, c, d, e, f)] Source # | |
| (Random a, Random b, Random c, Random d, Random e, Random f, Random g) => Random (a, b, c, d, e, f, g) Source # | Note - |
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) Source # random :: RandomGen g0 => g0 -> ((a, b, c, d, e, f, g), g0) Source # 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)] Source # randoms :: RandomGen g0 => g0 -> [(a, b, c, d, e, f, g)] Source # | |
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
class UniformRange a Source #
The class of types for which a uniformly distributed value can be drawn from a range.
Since: 1.2.0
Instances
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
Seed
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 mkSeed and
unSeed to get access to the raw bytes in a safe manner.
Since: 1.3.0
class (KnownNat (SeedSize g), 1 <= SeedSize g, Typeable g) => SeedGen g where Source #
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: 1.3.0
Minimal complete definition
Associated Types
type SeedSize g :: Nat Source #
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 Source #
Convert from a binary representation to a pseudo-random number generator
Since: 1.3.0
toSeed :: g -> Seed g Source #
Convert to a binary representation of a pseudo-random number generator
Since: 1.3.0
fromSeed64 :: NonEmpty Word64 -> g Source #
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 Source #
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
| SeedGen StdGen Source # | |||||
Defined in System.Random.Seed Associated Types
| |||||
| SeedGen SMGen Source # | |||||
| SeedGen SMGen Source # | |||||
| SeedGen g => SeedGen (AtomicGen g) Source # | |||||
Defined in System.Random.Seed Associated Types
| |||||
| SeedGen g => SeedGen (StateGen g) Source # | |||||
Defined in System.Random.Seed Associated Types
| |||||
| SeedGen g => SeedGen (IOGen g) Source # | |||||
Defined in System.Random.Stateful Associated Types
| |||||
| SeedGen g => SeedGen (STGen g) Source # | |||||
Defined in System.Random.Stateful Associated Types
| |||||
| SeedGen g => SeedGen (TGen g) Source # | |||||
Defined in System.Random.Stateful Associated Types
| |||||
seedSizeProxy :: forall proxy g. SeedGen g => proxy g -> Int Source #
Just like seedSize, except it accepts a proxy as an argument.
Since: 1.3.0
mkSeedFromByteString :: (SeedGen g, MonadFail m) => ByteString -> m (Seed g) Source #
Just like mkSeed, but uses ByteString as argument. Results in a memcopy of the seed.
Since: 1.3.0
unSeedToByteString :: Seed g -> ByteString Source #
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) Source #
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: 1.3.0
withSeedM :: (SeedGen g, Functor f) => Seed g -> (g -> f (a, g)) -> f (a, Seed g) Source #
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 Source #
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 Source #
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 Source #
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 Source #
Convert a Seed to a list of 64bit words.
Since: 1.3.0
type family SeedSize g :: Nat Source #
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 Source # | |
Defined in System.Random.Seed | |
| type SeedSize SMGen Source # | |
Defined in System.Random.Seed | |
| type SeedSize SMGen Source # | |
Defined in System.Random.Seed | |
| type SeedSize (AtomicGen g) Source # | |
Defined in System.Random.Seed | |
| type SeedSize (StateGen g) Source # | |
Defined in System.Random.Seed | |
| type SeedSize (IOGen g) Source # | |
Defined in System.Random.Stateful | |
| type SeedSize (STGen g) Source # | |
Defined in System.Random.Stateful | |
| type SeedSize (TGen g) Source # | |
Defined in System.Random.Stateful | |
Generators for sequences of pseudo-random bytes
Lists
uniforms :: (Uniform a, RandomGen g) => g -> [a] Source #
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: 1.3.0
uniformRs :: (UniformRange a, RandomGen g) => (a, a) -> g -> [a] Source #
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: 1.3.0
uniformList :: (Uniform a, RandomGen g) => Int -> g -> ([a], g) Source #
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: 1.3.0
uniformListR :: (UniformRange a, RandomGen g) => Int -> (a, a) -> g -> ([a], g) Source #
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: 1.3.0
uniformShuffleList :: RandomGen g => [a] -> g -> ([a], g) Source #
Shuffle elements of a list in a uniformly random order.
Examples
>>>uniformShuffleList "ELVIS" $ mkStdGen 252("LIVES",StdGen {unStdGen = SMGen 17676540583805057877 5302934877338729551})
Since: 1.3.0
Bytes
Arguments
| :: RandomGen g | |
| => Bool | Should byte array be allocated 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) Source #
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: 1.3.0
uniformShortByteString :: RandomGen g => Int -> g -> (ShortByteString, g) Source #
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: 1.3.0
uniformFillMutableByteArray Source #
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) Source #
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
>>>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) Source #
Deprecated: In favor of uniformShortByteString
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: 1.2.0
Standard pseudo-random number generator
The standard pseudo-random number generator.
Instances
| Show StdGen Source # | |||||
| NFData StdGen Source # | |||||
Defined in System.Random.Internal | |||||
| Eq StdGen Source # | |||||
| RandomGen StdGen Source # | |||||
Defined in System.Random.Internal Methods next :: StdGen -> (Int, StdGen) Source # genWord8 :: StdGen -> (Word8, StdGen) Source # genWord16 :: StdGen -> (Word16, StdGen) Source # genWord32 :: StdGen -> (Word32, StdGen) Source # genWord64 :: StdGen -> (Word64, StdGen) Source # genWord32R :: Word32 -> StdGen -> (Word32, StdGen) Source # genWord64R :: Word64 -> StdGen -> (Word64, StdGen) Source # genShortByteString :: Int -> StdGen -> (ShortByteString, StdGen) Source # unsafeUniformFillMutableByteArray :: MutableByteArray s -> Int -> Int -> StdGen -> ST s StdGen Source # | |||||
| SplitGen StdGen Source # | |||||
| SeedGen StdGen Source # | |||||
Defined in System.Random.Seed Associated Types
| |||||
| type SeedSize StdGen Source # | |||||
Defined in System.Random.Seed | |||||
mkStdGen :: Int -> StdGen Source #
Constructs a StdGen deterministically from an Int seed. See mkStdGen64 for a Word64
variant that is architecture agnostic.
mkStdGen64 :: Word64 -> StdGen Source #
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 Source #
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 Source #
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 Source #
Gets the global pseudo-random number generator. Extracts the contents of
globalStdGen
Since: 1.0.0
setStdGen :: MonadIO m => StdGen -> m () Source #
Sets the global pseudo-random number generator. Overwrites the contents of
globalStdGen
Since: 1.0.0
newStdGen :: MonadIO m => m StdGen Source #
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 Source #
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: 1.0.0
randomRIO :: (Random a, MonadIO m) => (a, a) -> m a Source #
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: 1.0.0
Compatibility and reproducibility
Backwards compatibility and deprecations
Version 1.2 mostly maintains backwards compatibility with version 1.1. This has a few consequences users should be aware of:
- The type class
Randomis only provided for backwards compatibility. New code should useUniformandUniformRangeinstead. - The methods
nextandgenRangeinRandomGenare deprecated and only provided for backwards compatibility. New instances ofRandomGenshould implement word-based methods instead. See below for more information about how to write aRandomGeninstance. This library provides instances for
Randomfor 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 therandomimplementation for unbounded types actually generates a value based on some fixed range.For
Integer,randomgenerates a value in theIntrange. ForFloatandDouble,randomgenerates a floating point value in the range[0, 1).This library does not provide
Uniforminstances 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^nbits of randomness for somen, implementgenWord8,genWord16,genWord32andgenWord64. See below for more details. - If the pseudo-random number generator does not have a power-of-2
modulus, implement
nextandgenRange. See below for more details. - If the pseudo-random number generator is splittable, implement
split. If there is no suitable implementation,splitshould 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
- 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