Is there a name for a recursion scheme that's like a catamorphism, but that allows peeking at the final result while it's still running? Here's a slighly contrived example:
toPercents :: Floating a => [a] -> [a]
toPercents xs = result
where
(total, result) = foldr go (0, []) xs
go x ~(t, r) = (x + t, 100*x/total:r)
{-
>>> toPercents [1,2,3]
[16.666666666666668,33.333333333333336,50.0]
-}
This example uses total
at each step of the fold, even though its value isn't known until the end. (Obviously, this relies on laziness to work.)
Though this is not necessarily what you were looking for, we can encode the laziness trick with a hylomorphism:
{-# LANGUAGE LambdaCase #-}
{-# LANGUAGE TupleSections #-}
{-# LANGUAGE DeriveFunctor #-}
{-# LANGUAGE DeriveFoldable #-}
{-# LANGUAGE DeriveTraversable #-}
{-# LANGUAGE TypeFamilies #-}
{-# LANGUAGE TemplateHaskell #-}
import Data.Functor.Foldable
import Data.Functor.Foldable.TH
data CappedList c a = Cap c | CCons a (CappedList c a)
deriving (Eq, Show, Ord, Functor, Foldable, Traversable)
makeBaseFunctor ''CappedList
-- The seq here has no counterpart in the implementation in the question.
-- It improves performance quite noticeably. Other seqs might be added for
-- some of the other "s", as well as for the percentage; the returns, however,
-- are diminishing.
toPercents :: Floating a => [a] -> [a]
toPercents = snd . hylo percAlg sumCal . (0,)
where
sumCal = \case
(s, []) -> CapF s
(s, a : as) -> s `seq` CConsF a (s + a, as)
percAlg = \case
CapF s -> (s, [])
CConsF a (s, as) -> (s, (a * 100 / s) : as)
This corresponds to the laziness trick because, thanks to hylo fusion, the intermediate CappedList
never actually gets built, and toPercents
consumes the input list in a single pass. The point of using CappedList
is, as moonGoose puts it, placing the sum at the bottom of the (virtual) intermediate structure, so that the list rebuilding being done with percAlg
can have access to it from the start.
(It is perhaps worth noting that, even though it is done in a single pass, it seems difficult to get nice-and-constant memory usage from this trick, be it with my version or with yours. Suggestions on this front are welcome.)
I don't think there's explicitly a scheme for allowing function 1 to peek at each step at the end result of function 2. It seems like a somewhat odd one to want though. I think that in the end, it's going to boil down to either 1) running function 2, then running function 1 with the known result of function 2 (ie. two passes, which I think is the only way to get constant memory in your example) or 2) running them side-by-side, creating a function thunk (or relying on laziness) to combine them at the end.
The lazy foldr
version you gave of course translates naturally into a catamorphism. Here's the functionalized catamorphism version,
{-# LANGUAGE LambdaCase #-}
import Data.Functor.Foldable
toPercents :: Floating a => [a] -> [a]
toPercents = uncurry ($) . cata alg
where
alg = \case
Nil -> (const [], 0)
Cons x (f,s) -> (\t -> 100*x / t : f t, s + x)
It doesn't seem nice stylistically to have to hand-parallelize the two catamorphisms though, particularly as then it doesn't encode the fact that neither stepwise-relies on the other. Hoogle finds bicotraverse, but it's unnecessarily general, so let's write our algebra-parallelization operator (&&&&)
,
import Control.Arrow
(&&&&) :: Functor f => (f a -> c) -> (f b -> d) -> f (a,b) -> (c,d)
f1 &&&& f2 = (f1 . fmap fst &&& f2 . fmap snd)
toPercents' :: Floating a => [a] -> [a]
toPercents' = uncurry ($) . cata (algList &&&& algSum)
algSum :: (Num a) => ListF a a -> a
algSum = \case
Nil -> fromInteger 0
Cons x !s -> s + x
algList :: (Fractional a) => ListF a (a -> [a]) -> (a -> [a])
algList = \case
Nil -> const []
Cons x s -> (\t -> 100*x / t : s t)
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