import qualified Data.Vector.Generic as G

import qualified Data.Vector.Generic.Mutable as M

import qualified Data.Vector.Unboxed as U

+import qualified Data.Vector as V

import Data.Vector.Generic (Vector)

+-- | Lookup table for arbitrary discrete distributions. It allows to

+-- generate random variates in /O(1)/. Note that probability is

+-- quantized in @1/2^32@ units and all distributions with infinite

+-- support (e.g. Poisson) should be truncated.

data CondensedTable v a =

{-# UNPACK #-} !Word64 !(v a) -- Lookup limit and first table

{-# UNPACK #-} !Word64 !(v a) -- Third table

+-- Implementation note. We have to store lookup limit in Word64 since

+-- we need to accomodate two cases. First is when we have no values in

+-- lookup table, second is when all elements are there

+-- Both are pretty easy to realize. For first one probability of every

+-- outcome should be less then 1/256, latter arise when probabilities

+-- of two outcomes are [0.5,0.5]

+-- | 'CondensedTable' which uses unboxed vectors

+type CondensedTableU = CondensedTable U.Vector

+-- | 'CondensedTable' which uses boxed vector and able to hold any element

+type CondensedTableV = CondensedTable V.Vector

+-- | Generate random value using condensed table

genFromTable :: (PrimMonad m, Vector v a) => CondensedTable v a -> Gen (PrimState m) -> m a

{-# INLINE genFromTable #-}

genFromTable table gen = do

at arr j = (G.!) arr (fromIntegral j)

----------------------------------------------------------------

----------------------------------------------------------------

## System/Random/MWC/CondensedTable.hs