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1. uniformM :: (Uniform a, StatefulGen g m) => g -> m a

   mwc-random	System.Random.MWC

   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]
   

2. uniformR :: (Variate a, PrimMonad m) => (a, a) -> Gen (PrimState m) -> m a

   mwc-random	System.Random.MWC

   Generate single uniformly distributed random variable in a given range.

   • For integral types inclusive range is used.
   • For floating point numbers range (a,b] is used if one ignores rounding errors.

3. uniformRM :: (UniformRange a, StatefulGen g m) => (a, a) -> g -> m a

   mwc-random	System.Random.MWC

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

   • uniformRM (1 :: Int, 4 :: Int) generates values uniformly from the set <math>
   • uniformRM (1 :: Float, 4 :: Float) generates values uniformly from the set <math>
   The following law should hold to make the function always defined:

   uniformRM (a, b) = uniformRM (b, a)
   

4. uniformVector :: (PrimMonad m, StatefulGen g m, Uniform a, Vector v a) => g -> Int -> m (v a)

   mwc-random	System.Random.MWC

   Generate a vector of pseudo-random variates. This is not necessarily faster than invoking uniform repeatedly in a loop, but it may be more convenient to use in some situations.

5. uniformPermutation :: (StatefulGen g m, PrimMonad m, Vector v Int) => Int -> g -> m (v Int)

   mwc-random	System.Random.MWC.Distributions

   Random variate generator for uniformly distributed permutations. It returns random permutation of vector [0 .. n-1]. This is the Fisher-Yates shuffle

6. uniformShuffle :: (StatefulGen g m, PrimMonad m, Vector v a) => v a -> g -> m (v a)

   mwc-random	System.Random.MWC.Distributions

   Random variate generator for a uniformly distributed shuffle (all shuffles are equiprobable) of a vector. It uses Fisher-Yates shuffle algorithm.

7. uniformShuffleM :: (StatefulGen g m, PrimMonad m, MVector v a) => v (PrimState m) a -> g -> m ()

   mwc-random	System.Random.MWC.Distributions

   In-place uniformly distributed shuffle (all shuffles are equiprobable)of a vector.

8. iso8601DateFormat :: Maybe String -> String

   old-locale	System.Locale

   Construct format string according to ISO-8601. The Maybe String argument allows to supply an optional time specification. E.g.:

   iso8601DateFormat Nothing            == "%Y-%m-%d"           -- i.e. YYYY-MM-DD
   iso8601DateFormat (Just "%H:%M:%S")  == "%Y-%m-%dT%H:%M:%S"  -- i.e. YYYY-MM-DDTHH:MM:SS
   

9. rfc822DateFormat :: String

   old-locale	System.Locale

   Format string according to RFC822.

10. data NumberFormat

    aeson-pretty	Data.Aeson.Encode.Pretty

    No documentation available.

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