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1. 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
   

2. rfc822DateFormat :: String

   old-locale	System.Locale

   Format string according to RFC822.

3. data NumberFormat

   aeson-pretty	Data.Aeson.Encode.Pretty

   No documentation available.

4. confNumFormat :: Config -> NumberFormat

   aeson-pretty	Data.Aeson.Encode.Pretty

   No documentation available.

5. class Uniform a

   mwc-random	System.Random.MWC

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

6. class UniformRange a

   mwc-random	System.Random.MWC

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

7. uniform :: (Variate a, PrimMonad m) => Gen (PrimState m) -> m a

   mwc-random	System.Random.MWC

   Generate a single uniformly distributed random variate. The range of values produced varies by type:

   • For fixed-width integral types, the type's entire range is used.
   • For floating point numbers, the range (0,1] is used. Zero is explicitly excluded, to allow variates to be used in statistical calculations that require non-zero values (e.g. uses of the log function).
   To generate a Float variate with a range of [0,1), subtract 2**(-33). To do the same with Double variates, subtract 2**(-53).

8. 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]
   

9. 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.

10. 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)
    

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