Using existential types
Tomasz Zielonka
t.zielonka at students.mimuw.edu.pl
Fri Oct 3 10:42:48 EDT 2003
On Thu, Oct 02, 2003 at 06:42:59PM -0700, oleg at pobox.com wrote:
>
> > data Datatype ex = forall vt . Datatype (DatatypeVal ex vt)
>
> In practice one rarely would write
> forall vt. Datatype (DatatypeVal ex vt)
> unless he is writing something like the ST monad.
> You can only pass vt to functions with the signature
> forall vt. vt -> C1 vt C2 C3 ...
>
> where C1, C2, C3 do not depend on vt in any way. For example,
> functions like 'id', (\vt x -> (vt,x)), (\x -> 1), etc. As you can
> notice these functions don't do anything with their vt argument. They
> merely pass it through or disregard. You can't do anything with the
> unconstrainedly quantified argument!
I think I have used unconstrained existentially quantified types in a
useful way. Below is a combinator library for calculating statistics
with aggregate functions (type Stat).
I use a datatype 'Stat i o' to represent an aggregate function that can be
fed with values of type 'i' and returns a result of type 'o'.
I use existentially quantified constructor to hide the internal state of
particular aggregate function. For example, avg's internal state is a
pair of numbers, but it is hidden, because users of the library
shouldn't have to know that.
However this approach has caveats. For example you can't store the state
of Stat and restart it later. All steps are done within one call to
runStat.
Example uses:
{- average of the list of values -}
runStat avg [1..20]
10.5
{- separate average for odd and even numbers -}
runStat
(fmap
fmToList
(categorize even
(projectInput fromIntegral avg)))
[1..20]
[(False,10.0),(True,11.0)]
{- word frequency -}
runStat rank (words "this is a test is a test")
[(2,"test"),(2,"is"),(2,"a"),(1,"this")]
{- group words by lengths -}
runStat
(fmap fmToList
(categorize length
(fold (flip (:)) [])))
(words "a aa ba wwww zz")
[(1,["a"]),(2,["zz","ba","aa"]),(4,["wwww"])]
... etc
Best regards,
Tom
----------------------------------------------------------------------
{-# OPTIONS -fglasgow-exts #-}
module Stat where
import Data.FiniteMap
import Prelude hiding (sum)
import List (sort)
data Stat i o = -- aggregate function taking i's on input and producing o
forall s. Stat
s -- init
(s -> i -> s) -- update
(s -> o) -- result
runStat :: Stat i o -> [i] -> o
runStat (Stat init update result) l = result (foldl update init l)
fold :: (a -> b -> a) -> a -> Stat b a
fold f i = Stat i f id
count :: Num n => Stat a n
count = fold (\s _ -> s+1) 0
sum :: Num n => Stat n n
sum = fold (+) 0
pair :: Stat a b -> Stat a c -> Stat a (b,c)
pair (Stat init1 update1 result1) (Stat init2 update2 result2) =
Stat
(init1, init2)
(\(s1,s2) x -> (update1 s1 x, update2 s2 x))
(\(s1,s2) -> (result1 s1, result2 s2))
instance Functor (Stat a) where
fmap f (Stat init update result) = (Stat init update (f . result))
projectInput :: (i -> j) -> Stat j a -> Stat i a
projectInput f (Stat init update result) =
Stat init (\s i -> update s (f i)) result
avg :: Fractional n => Stat n n
avg = fmap (\(s,c) -> if c /= 0 then s/c else 0) (pair sum count)
avgMaybe :: Fractional n => Stat n (Maybe n)
avgMaybe = fmap (\(s,c) -> if c /= 0 then Just (s/c) else Nothing) (pair sum count)
categorize :: Ord k => (a -> k) -> Stat a b -> Stat a (FiniteMap k b)
categorize fk (Stat init update result) =
Stat
emptyFM
(\fm a -> addToFM fm (fk a) (update (maybe init id (lookupFM fm (fk a))) a))
(mapFM (const result))
rank :: Ord k => Stat k [(Int,k)]
rank = fmap (reverse . sort . (map(\(k,c)->(c,k))) . fmToList) (categorize id count)
--
.signature: Too many levels of symbolic links
More information about the Haskell-Cafe
mailing list