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ifor_ :: (FoldableWithIndex i t, Applicative f) => t a -> (i -> a -> f b) -> f ()optics-extra Optics.Indexed Traverse elements with access to the index i, discarding the results (with the arguments flipped).
ifor_ ≡ flip itraverse_
When you don't need access to the index then for_ is more flexible in what it accepts.for_ a ≡ ifor_ a . const
transformByte :: Cfg -> Int -> String -> Stringpretty-hex Hexdump No documentation available.
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random-fu Data.Random A name for the "standard" uniform distribution over the type t, if one exists. See also stdUniform. For Integral and Enum types that are also Bounded, this is the uniform distribution over the full range of the type. For un-Bounded Integral types this is not defined. For Fractional types this is a random variable in the range [0,1) (that is, 0 to 1 including 0 but not including 1).
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random-fu Data.Random No documentation available.
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random-fu Data.Random A definition of a uniform distribution over the type t. See also uniform.
Uniform :: t -> t -> Uniform trandom-fu Data.Random A uniform distribution defined by a lower and upper range bound. For Integral and Enum types, the range is inclusive. For Fractional types the range includes the lower bound but not the upper.
stdUniform :: Distribution StdUniform a => RVar arandom-fu Data.Random Get a "standard" uniformly distributed variable. For integral types, this means uniformly distributed over the full range of the type (there is no support for Integer). For fractional types, this means uniformly distributed on the interval [0,1).
stdUniformT :: forall a (m :: Type -> Type) . Distribution StdUniform a => RVarT m arandom-fu Data.Random Get a "standard" uniformly distributed process. For integral types, this means uniformly distributed over the full range of the type (there is no support for Integer). For fractional types, this means uniformly distributed on the interval [0,1).
uniform :: Distribution Uniform a => a -> a -> RVar arandom-fu Data.Random No documentation available.
uniformT :: forall a (m :: Type -> Type) . Distribution Uniform a => a -> a -> RVarT m arandom-fu Data.Random No documentation available.