I am using the following fold to get the final monotonically decreasing sequence of a list.
foldl (\acc x -> if x<=(last acc) then acc ++ [x] else [x]) [(-1)] a
So [9,5,3,6,2,1] would return [6,2,1]
However, with foldl I needed to supply a start for the fold namely [(-1)]. I was trying to turn into to a foldl1 to be able to handle any range of integers as well as any Ord a like so:
foldl1 (\acc x -> if x<=(last acc) then acc ++ [x] else [x]) a
But I get there error:
cannot construct infinite type: a ~ [a]
in the second argument of (<=) namely last acc
I was under the impression that foldl1 was basically :
foldl (function) [head a] a
But I guess this isn't so? How would you go about making this fold generic for any Ord type?
I was under the impression that foldl1 was basically :
foldl (function) [head a] a
No, foldl1 is basically:
foldl function (head a) (tail a)
So the initial element is not a list of head a, but head a.
How would you go about making this fold generic for any Ord type?
Well a quick fix is:
foldl (\acc x -> if x<=(last acc) then acc ++ [x] else [x]) [head a] (tail a)
But there are still two problems:
in case a is an empty list, this function will error (while you probably want to return the empty list); and
the code is not terribly efficient since both last and (++) run in O(n).
The first problem can easily be addressed by using pattern matching to prevent that scenario. But for the latter you better would for instance use a reverse approach. Like for instance:
f :: Ord t => [t] -> [t]
f [] = [] -- case when the empty list is given
f a = reverse $ foldl (\acc#(ac:_) x -> if x <= ac then (x:acc) else [x]) [head a] (tail a)
Furthermore personally I am not a huge fan of if-then-else in functional programming, you can for instance define a helper function like:
f :: Ord t => [t] -> [t]
f [] = [] -- case when the empty list is given
f a = reverse $ foldl g [head a] (tail a)
where g acc#(ac:_) x | x <= ac = (x:acc)
| otherwise = [x]
Now reverse runs in O(n) but this is done only once. Furthermore the (:) construction runs in O(1) so all the actions in g run in O(1) (well given the comparison of course works efficient, etc.) making the algorithm itself O(n).
For your sample input it gives:
*Main> f [9,5,3,6,2,1]
[6,2,1]
The type of foldl1 is:
Foldable t => (a -> a -> a) -> t a -> a
Your function argument,
\acc x -> if x<=(last acc) then acc ++ [x] else [x]
has type:
(Ord a) => [a] -> a -> [a]
When Haskell's typechecker tries typechecking your function, it'll try unifying the type a -> a -> a (the type of the first argument of foldl1) with the type [a] -> a -> [a] (the type of your function).
To unify these types would require unifying a with [a], which would lead to the infinite type a ~ [a] ~ [[a]] ~ [[[a]]]... and so on.
The reason this works while using foldl is that the type of foldl is:
Foldable t => (b -> a -> b) -> b -> t a -> b
So [a] gets unified with b and a gets unified with the other a, leading to no problem at all.
foldl1 is limited in that it can only take functions which deal with only one type, or, in other terms, the accumulator needs to be the same type as the input list (for instance, when folding a list of Ints, foldl1 can only return an Int, while foldl can use arbitrary accumulators. So you can't do this using foldl1).
With regards to making this generic for all Ord values, one possible solution is to make a new typeclass for values which state their own "least-bound" value, which would then be used by your function. You can't make this function as it is generic on all Ord values because not all Ord values have sequence least bounds you can use.
class LowerBounded a where
lowerBound :: a
instance LowerBounded Int where
lowerBound = -1
finalDecreasingSequence :: (Ord a, LowerBounded a) => [a] -> [a]
finalDecreasingSequence = foldl buildSequence lowerBound
where buildSequence acc x
| x <= (last acc) = acc ++ [x]
| otherwise = [x]
You might also want to read a bit about how Haskell does its type inference, as it helps a lot in figuring out errors like the one you got.
Related
Given a condition, I want to search through a list of elements and return the first element that reaches the condition, and the previous one.
In C/C++ this is easy :
int i = 0;
for(;;i++) if (arr[i] == 0) break;
After we get the index where the condition is met, getting the previous element is easy, through "arr[i-1]"
In Haskell:
dropWhile (/=0) list gives us the last element I want
takeWhile (/=0) list gives us the first element I want
But I don't see a way of getting both in a simple manner. I could enumerate the list and use indexing, but that seems messy. Is there a proper way of doing this, or a way of working around this?
I would zip the list with its tail so that you have pairs of elements
available. Then you can just use find on the list of pairs:
f :: [Int] -> Maybe (Int, Int)
f xs = find ((>3) . snd) (zip xs (tail xs))
> f [1..10]
Just (3,4)
If the first element matches the predicate this will return
Nothing (or the second match if there is one) so you might need to special-case that if you want something
different.
As Robin Zigmond says break can also work:
g :: [Int] -> (Int, Int)
g xs = case break (>3) xs of (_, []) -> error "not found"
([], _) -> error "first element"
(ys, z:_) -> (last ys, z)
(Or have this return a Maybe as well, depending on what you need.)
But this will, I think, keep the whole prefix ys in memory until it
finds the match, whereas f can start garbage-collecting the elements
it has moved past. For small lists it doesn't matter.
I would use a zipper-like search:
type ZipperList a = ([a], [a])
toZipperList :: [a] -> ZipperList a
toZipperList = (,) []
moveUntil' :: (a -> Bool) -> ZipperList a -> ZipperList a
moveUntil' _ (xs, []) = (xs, [])
moveUntil' f (xs, (y:ys))
| f y = (xs, (y:ys))
| otherwise = moveUntil' f (y:xs, ys)
moveUntil :: (a -> Bool) -> [a] -> ZipperList a
moveUntil f = moveUntil' f . toZipperList
example :: [Int]
example = [2,3,5,7,11,13,17,19]
result :: ZipperList Int
result = moveUntil (>10) example -- ([7,5,3,2], [11,13,17,19])
The good thing about zippers is that they are efficient, you can access as many elements near the index you want, and you can move the focus of the zipper forwards and backwards. Learn more about zippers here:
http://learnyouahaskell.com/zippers
Note that my moveUntil function is like break from the Prelude but the initial part of the list is reversed. Hence you can simply get the head of both lists.
A non-awkward way of implementing this as a fold is making it a paramorphism. For general explanatory notes, see this answer by dfeuer (I took foldrWithTails from it):
-- The extra [a] argument f takes with respect to foldr
-- is the tail of the list at each step of the fold.
foldrWithTails :: (a -> [a] -> b -> b) -> b -> [a] -> b
foldrWithTails f n = go
where
go (a : as) = f a as (go as)
go [] = n
boundary :: (a -> Bool) -> [a] -> Maybe (a, a)
boundary p = foldrWithTails findBoundary Nothing
where
findBoundary x (y : _) bnd
| p y = Just (x, y)
| otherwise = bnd
findBoundary _ [] _ = Nothing
Notes:
If p y is true we don't have to look at bnd to get the result. That makes the solution adequately lazy. You can check that by trying out boundary (> 1000000) [0..] in GHCi.
This solution gives no special treatment to the edge case of the first element of the list matching the condition. For instance:
GHCi> boundary (<1) [0..9]
Nothing
GHCi> boundary even [0..9]
Just (1,2)
There's several alternatives; either way, you'll have to implement this yourself. You could use explicit recursion:
getLastAndFirst :: (a -> Bool) -> [a] -> Maybe (a, a)
getLastAndFirst p (x : xs#(y:ys))
| p y = Just (x, y)
| otherwise = getLastAndFirst p xs
getLastAndFirst _ [] = Nothing
Alternately, you could use a fold, but that would look fairly similar to the above, except less readable.
A third option is to use break, as suggested in the comments:
getLastAndFirst' :: (a -> Bool) -> [a] -> Maybe (a,a)
getLastAndFirst' p l =
case break p l of
(xs#(_:_), (y:_)) -> Just (last xs, y)
_ -> Nothing
(\(xs, ys) -> [last xs, head ys]) $ break (==0) list
Using break as Robin Zigmond suggested ended up short and simple, not using Maybe to catch edge-cases, but I could replace the lambda with a simple function that used Maybe.
I toyed a bit more with the solution and came up with
breakAround :: Int -> Int -> (a -> Bool) -> [a] -> [a]
breakAround m n cond list = (\(xs, ys) -> (reverse (reverse take m (reverse xs))) ++ take n ys) $ break (cond) list
which takes two integers, a predicate, and a list of a, and returns a single list of m elements before the predicate and n elements after.
Example: breakAround 3 2 (==0) [3,2,1,0,10,20,30] would return [3,2,1,0,10]
I need to implement a function that replaces elements in a list -- the
index to replace at is the fst in the tuple, and the snd in the tuple
is what to replace it with. and I am asked to use foldr or map function.
for example:
setElements [(1, 'a'), (-4, 't'), (3, 'b')] "#####" = "#a#b#"
the setElements function doesn't compile:
my code:
setElement :: Int -> a -> [a] -> [a]
setElement n x xs = if ((n < length xs) && n >= 0)
then (take n xs) ++ [x] ++ (drop (n + 1) xs)
else xs
setElements :: [(Int, a)] -> [a] -> [a]
setElements = foldr (\t l-> setElement (fst t) (snd t) l) []
I get:
• Couldn't match type ‘[a]’ with ‘[a] -> [a]’
Expected type: [(Int, a)] -> [a] -> [a]
Actual type: [(Int, a)] -> [a]
• Possible cause: ‘foldr’ is applied to too many arguments
In the expression: foldr (\ t l -> setElement (fst t) (snd t) l) []
In an equation for ‘setElements’:
setElements = foldr (\ t l -> setElement (fst t) (snd t) l) []
• Relevant bindings include
setElements :: [(Int, a)] -> [a] -> [a]
(bound at hw3.hs:79:1)
|
79 | setElements = foldr (\t l-> setElement (fst t) (snd t) l) []
|
How can I fix the error?
Let's look at your function:
setElements :: [(Int, a)] -> [a] -> [a]
setElements = foldr (\t l-> setElement (fst t) (snd t) l) []
and recall the type of foldr:
foldr :: (a -> b -> b) -> b -> [a] -> b
In your use of foldr, you have a as (Int, a) and b as [a]. And you only give it the first 2 arguments. So foldr (\t l-> setElement (fst t) (snd t) l) [] has type [(Int, a)] -> [a] - whereas setElements is supposed to have type [(Int, a)] -> [a] -> [a]. Note how these match exactly with the "actual type" and "expected type" reported by GHC in the error message.
To fix this, I would actually take a step backwards. Folding is the right idea - your setElement function already modifies the original list (its third argument) based on an index and new value, and what you want is to take a list of pairs encoding this data, and keep on applying this function to update the original list repeatedly. (Of course this is Haskell so data is immutable - you're not literally updating it in place, but simply returning a new list each time. But sometimes talking loosely like this is easier.)
That's exactly what a fold is. Let's try to write it out, without trying to be too fancy with a "point-free" approach, but instead fully applying it:
setElements :: [(Int, a)] -> [a] -> [a]
setElements ps as = foldr myFunction as ps
where myFunction = undefined
The undefined here is just a placeholder - it will cause a runtime error if you try to use the function (but won't cause a compilation error), and I've put it there because we need to think about that, the fold function usually being the trickiest part of implementing a fold. But let's check we understand what the other terms are doing: the list we are actually "walking along" is the list of (Int, a) terms that tell us what to insert and where - that's what I've called ps (the p is for "pair"). And because we are starting with the list of as - which I've logically called as here - then that should be the starting accumulator value, which is the second argument to foldr.
So all that remains is the fold function - which takes a pair and a list, and updates the list according to the values in the pair. Well this is the function you're already using:
\t l-> setElement (fst t) (snd t) l
or, rewritten with pattern matching (which I find much more readable, and for this reason I think is preferred by most Haskell developers):
\(i, a) as -> setElement i a as
So, substituting this in, we arrive at the following definition:
setElements :: [(Int, a)] -> [a] -> [a]
setElements ps as = foldr myFunction as ps
where myFunction = \(i, a) as -> setElement i a as
This now will compile and work correctly. But it's always worth taking a step back when you have a working function, and seeing if you can simplify its definition. In fact myFunction can be simplified quite a bit:
\(i, a) as -> setElement i a as
can first be "eta-reduced" to
\(i, a) -> setElement i a
which, using a standard library function, is simply uncurry setElement.
At this stage we clearly don't need a where clause any more (in fact we never did before, but imo it aids readability for any lambda which isn't fairly trivial), and can just write:
setElements :: [(Int, a)] -> [a] -> [a]
setElements ps as = foldr (uncurry setElement) as ps
In fact, while I wouldn't necessarily recommend it, if we're playing code golf you can even go a step further and just write:
setElements = flip . foldr . uncurry $ setElement
I personally think the ability to be able to express relatively complex functions in a concise way, as above, is definitely part of the allure of Haskell. But, rather than try to write something like this straight away, in my opinion it's always best to start with something very concrete showing how you want to transform your data - and, only after getting that working, look for a more concise representation if you want to.
I'm trying to convert basic functions into higher order functions (specifically map, filter, or foldr). I was wondering if there are any simple concepts to apply where I could see old functions I've written using guards and turn them into higher order.
I'm working on changing a function called filterFirst that removes the first element from the list (second argument) that does not satisfy a given predicate function (first argument).
filterFirst :: (a -> Bool) -> [a] -> [a]
filterFirst _ [] = []
filterFirst x (y:ys)
| x y = y : filterFirst x ys
| otherwise = ys
For an example:
greaterOne :: Num a=>Ord a=>a->Bool
greaterOne x = x > 1
filterFirst greaterOne [5,-6,-7,9,10]
[5,-7,9,10]
Based on the basic recursion, I was wondering if there might be a way to translate this (and similar functions) to higher order map, filter, or foldr. I'm not very advanced and these functions are new to me.
There is a higher-order function that's appropriate here, but it's not in the base library. What's the trouble with foldr? If you just fold over the list, you'll end up rebuilding the whole thing, including the part after the deletion.
A more appropriate function for the job is para from the recursion-schemes package (I've renamed one of the type variables):
para :: Recursive t => (Base t (t, r) -> r) -> t -> r
In the case of lists, this specializes to
para :: (ListF a ([a], r) -> r) -> [a] -> r
where
data ListF a b = Nil | Cons a b
deriving (Functor, ....)
This is pretty similar to foldr. The recursion-schemes equivalent of foldr is
cata :: Recursive t => (Base t r -> r) -> t -> r
Which specializes to
cata :: (ListF a r -> r) -> [a] -> r
Take a break here and figure out why the type of cata is basically equivalent to that of foldr.
The difference between cata and para is that para passes the folding function not only the result of folding over the tail of the list, but also the tail of the list itself. That gives us an easy and efficient way to produce the rest of the list after we've found the first non-matching element:
filterFirst :: (a -> Bool) -> [a] -> [a]
filterFirst f = para go
where
--go :: ListF a ([a], [a]) -> [a]
go (Cons a (tl, r))
| f a = a : r
| otherwise = tl
go Nil = []
para is a bit awkward for lists, since it's designed to fit into a more general context. But just as cata and foldr are basically equivalent, we could write a slightly less awkward function specifically for lists.
foldrWithTails
:: (a -> [a] -> b -> b)
-> b -> [a] -> b
foldrWithTails f n = go
where
go (a : as) = f a as (go as)
go [] = n
Then
filterFirst :: (a -> Bool) -> [a] -> [a]
filterFirst f = foldrWithTails go []
where
go a tl r
| f a = a : r
| otherwise = tl
First, let's flip the argument order of your function. This will make a few steps easier, and we can flip it back when we're done. (I'll call the flipped version filterFirst'.)
filterFirst' :: [a] -> (a -> Bool) -> [a]
filterFirst' [] _ = []
filterFirst' (y:ys) x
| x y = y : filterFirst' ys x
| otherwise = ys
Note that filterFirst' ys (const True) = ys for all ys. Let's substitute that in place:
filterFirst' :: [a] -> (a -> Bool) -> [a]
filterFirst' [] _ = []
filterFirst' (y:ys) x
| x y = y : filterFirst' ys x
| otherwise = filterFirst' ys (const True)
Use if-else instead of a guard:
filterFirst' :: [a] -> (a -> Bool) -> [a]
filterFirst' [] _ = []
filterFirst' (y:ys) x = if x y then y : filterFirst' ys x else filterFirst' ys (const True)
Move the second argument to a lambda:
filterFirst' :: [a] -> (a -> Bool) -> [a]
filterFirst' [] = \_ -> []
filterFirst' (y:ys) = \x -> if x y then y : filterFirst' ys x else filterFirst' ys (const True)
And now this is something we can turn into a foldr. The pattern we were going for is that filterFirst' (y:ys) can be expressed in terms of filterFirst' ys, without using ys otherwise, and we're now there.
filterFirst' :: Foldable t => t a -> (a -> Bool) -> [a]
filterFirst' = foldr (\y f -> \x -> if x y then y : f x else f (const True)) (\_ -> [])
Now we just need to neaten it up a bit:
filterFirst' :: Foldable t => t a -> (a -> Bool) -> [a]
filterFirst' = foldr go (const [])
where go y f x
| x y = y : f x
| otherwise = f (const True)
And flip the arguments back:
filterFirst :: Foldable t => (a -> Bool) -> t a -> [a]
filterFirst = flip $ foldr go (const [])
where go y f x
| x y = y : f x
| otherwise = f (const True)
And we're done. filterFirst implemented in terms of foldr.
Addendum: Although filter isn't strong enough to build this, filterM is when used with the State monad:
{-# LANGUAGE FlexibleContexts #-}
import Control.Monad.State
filterFirst :: (a -> Bool) -> [a] -> [a]
filterFirst x ys = evalState (filterM go ys) False
where go y = do
alreadyDropped <- get
if alreadyDropped || x y then
return True
else do
put True
return False
If we really want, we can write filterFirst using foldr, since foldr is kind of "universal" -- it allows any list transformation we can perform using recursion. The main downside is that the resulting code is rather counter-intuitive. In my opinion, explicit recursion is far better in this case.
Anyway here's how it is done. This relies on what I consider to be an antipattern, namely "passing four arguments to foldr". I call this an antipattern since foldr is usually called with three arguments only, and the result is not a function taking a fourth argument.
filterFirst :: (a->Bool)->[a]->[a]
filterFirst p xs = foldr go (\_ -> []) xs True
where
go y ys True
| p y = y : ys True
| otherwise = ys False
go y ys False = y : ys False
Clear? Not very much. The trick here is to exploit foldr to build a function Bool -> [a] which returns the original list if called with False, and the filtered-first list if called with True. If we craft that function using
foldr go baseCase xs
the result is then obviously
foldr go baseCase xs True
Now, the base case must handle the empty list, and in such case we must return a function returning the empty list, whatever the boolean argument is. Hence, we arrive at
foldr go (\_ -> []) xs True
Now, we need to define go. This takes as arguments:
a list element y
the result of the "recursion" ys (a function Bool->[a] for the rest of the list)
and must return a function Bool->[a] for the larger list. So let's also consider
a boolean argument
and finally make go return a list. Well, if the boolean is False we must return the list unchanged, so
go y ys False = y : ys False
Note that ys False means "the tail unchanged", so we are really rebuilding the whole list unchanged.
If instead the boolean is true, we query the predicate as in p y. If that is false, we discard y, and return the list tail unchanged
go y ys True
| p y = -- TODO
| otherwise = ys False
If p y is true, we keep y and we return the list tail filtered.
go y ys True
| p y = y : ys True
| otherwise = ys False
As a final note, we cold have used a pair ([a], [a]) instead of a function Bool -> [a], but that approach does not generalize as well to more complex cases.
So, that's all. This technique is something nice to know, but I do not recommend it in real code which is meant to be understood by others.
Joseph and chi's answers already show how to derive a foldr implementation, so I'll try to aid intuition.
map is length-preserving, filterFirst is not, so trivially map must be unsuited for implementing filterFirst.
filter (and indeed map) are memoryless - the same predicate/function is applied to each element of the list, regardless of the result on other elements. In filterFirst, behaviour changes once we see the first non-satisfactory element and remove it, so filter (and map) are unsuited.
foldr is used to reduce a structure to a summary value. It's very general, and it might not be immediately obvious without experience what sorts of things this may cover. filterFirst is in fact such an operation, though. The intuition is something like, "can we build it in a single pass through the structure, building it up as we go(, with additional state stored as required)?". I fear Joseph's answer obfuscates a little, as foldr with 4 parameters, it may not be immediately obvious what's going on, so let's try it a little differently.
filterFirst p xs = snd $ foldr (\a (deleted,acc) -> if not deleted && not (p a) then (True,acc) else (deleted,a:acc) ) (False,[]) xs
Here's a first attempt. The "extra state" here is obviously the bool indicating whether or not we've deleted an element yet, and the list accumulates in the second element of the tuple. At the end we call snd to obtain just the list. This implementation has the problem, however, that we delete the rightmost element not satisfying the predicate, because foldr first combines the rightmost element with the neutral element, then the second-rightmost, and so on.
filterFirst p xs = snd $ foldl (\(deleted,acc) a -> if not deleted && not (p a) then (True,acc) else (deleted,a:acc) ) (False,[]) xs
Here, we try using foldl. This does delete the leftmost non-satisfactory element, but has the side-effect of reversing the list. We can stick a reverse at the front, and this would solve the problem, but is somewhat unsatisfactory due to the double-traversal.
Then, if you go back to foldr, having realized that (basically) if you want transform a list whilst preserving order that foldr is the correct variant, you play with it for a while and end up writing what Joseph suggested. I do however agree with chi that straightforward recursion is the best solution here.
Your function can also be expressed as an unfold, or, more specifically, as an apomorphism. Allow me to begin with a brief explanatory note, before the solution itself.
The apomorphism is the recursion scheme dual to the paramorphism (see dfeuer's answer for more about the latter). Apomorphisms are examples of unfolds, which generate a structure from a seed. For instance, Data.List offers unfoldr, a list unfold.
unfoldr :: (b -> Maybe (a, b)) -> b -> [a]
The function given to unfoldr takes a seed and either produces a list element and a new seed (if the maybe-value is a Just) or terminates the list generation (if it is Nothing). Unfolds are more generally expressed by the ana function from recursion-schemes ("ana" is short for "anamorphism").
ana :: Corecursive t => (a -> Base t a) -> a -> t
Specialised to lists, this becomes...
ana #[_] :: (b -> ListF a b) -> b -> [a]
... which is unfoldr in different clothing.
An apomorphism is an unfold in which the generation of the structure can be short-circuited at any point of the process, by producing, instead of a new seed, the rest of the structure in a fell swoop. In the case of lists, we have:
apo #[_] :: (b -> ListF a (Either [a] b)) -> b -> [a]
Either is used to trigger the short-circuit: with a Left result, the unfold short-circuits, while with a Right it proceeds normally.
The solution in terms of apo is fairly direct:
{-# LANGUAGE LambdaCase #-}
import Data.Functor.Foldable
filterFirst :: (a -> Bool) -> [a] -> [a]
filterFirst p = apo go
where
go = \case
[] -> Nil
a : as
| p a -> Cons a (Right as)
| otherwise -> case as of
[] -> Nil
b : bs -> Cons b (Left bs)
It is somewhat more awkward than dfeuer's para-based solution, because if we want to short-circuit without an empty list for a tail we are compelled to emit one extra element (the b in the short-circuiting case), and so we have to look one position ahead. This awkwardness would grow by orders of magnitude if, rather than filterFirst, we were to impĺement plain old filter with an unfold, as beautifully explained in List filter using an anamorphism.
This answer is inspired by a comment from luqui on a now-deleted question.
filterFirst can be implemented in a fairly direct way in terms of span:
filterFirst :: (a -> Bool) -> [a] -> [a]
filterFirst p = (\(yeas, rest) -> yeas ++ drop 1 rest) . span p
span :: (a -> Bool) -> [a] -> ([a], [a]) splits the list in two at the first element for which the condition doesn't hold. After span, we drop the first element of the second part of the list (with drop 1 rather than tail so that we don't have to add a special case for []), and reassemble the list with (++).
As an aside, there is a near-pointfree spelling of this implementation which I find too pretty not to mention:
filterFirst :: (a -> Bool) -> [a] -> [a]
filterFirst p = uncurry (++) . second (drop 1) . span p
While span is a higher order function, it would be perfectly understandable if you found this implementation disappointing in the context of your question. After all, span is not much more fundamental than filterFirst itself. Shouldn't we try going a little deeper, to see if we can capture the spirit of this solution while expressing it as a fold, or as some other recursion scheme?
I believe functions like filterFirst can be fine demonstrations of hylomorphisms. A hylomorphism is an unfold (see my other answer for more on that) that generates an intermediate data structure followed by a fold which turns this data structure into something else. Though it might look like that would require two passes to get a result (one through the input structure, and another through the intermediate one), if the hylomorphism implemented properly (as done in the hylo function of recursion-schemes) it can be done in a single pass, with the fold consuming pieces of the intermediate structure as they are generated by the unfold (so that we don't have to actually build it all only to tear it down).
Before we start, here is the boilerplate needed to run what follows:
{-# LANGUAGE LambdaCase #-}
{-# LANGUAGE DeriveFunctor #-}
{-# LANGUAGE DeriveFoldable #-}
{-# LANGUAGE DeriveTraversable #-}
{-# LANGUAGE TypeFamilies #-}
{-# LANGUAGE TemplateHaskell #-}
import Data.Functor.Foldable
import Data.Functor.Foldable.TH
The strategy here is picking an intermediate data structure for the hylomorphism that expresses the essence of what we want to achieve. In this case, we will use this cute thing:
data BrokenList a = Broken [a] | Unbroken a (BrokenList a)
-- I won't actually use those instances here,
-- but they are nice to have if you want to play with the type.
deriving (Eq, Show, Functor, Foldable, Traversable)
makeBaseFunctor ''BrokenList
BrokenList is very much like a list (Broken and Unbroken mirror [] and (:), while the makeBaseFunctor incantation generates a BrokenListF base functor analogous to ListF, with BrokenF and UnbrokenF constructors), except that it has another list attached at its end (the Broken constructor). It expresses, in a quite literal way, the idea of a list being divided in two parts.
With BrokenList at hand, we can write the hylomorphism. coalgSpan is the operation used for the unfold, and algWeld, the one used for the fold.
filterFirst p = hylo algWeld coalgSpan
where
coalgSpan = \case
[] -> BrokenF []
x : xs
| p x -> UnbrokenF x xs
| otherwise -> BrokenF xs
algWeld = \case
UnbrokenF x yeas -> x : yeas
BrokenF rest -> rest
coalgSpan breaks the list upon hitting a x element such that p x doesn't hold. Not adding that element to the second part of the list (BrokenF xs rather than BrokenF (x : xs)) takes care of the filtering. As for algWeld, it is used to concatenate the two parts (it is very much like what we would use to implement (++) using cata).
(For a similar example of BrokenList in action, see the breakOn implementation in Note 5 of this older answer of mine. It suggests what it would take to implement span using this strategy.)
There are at least two good things about this hylo-based implementation. Firstly, it has good performance (casual testing suggests that, if compiled with optimisations, it is at least as good as, and possibly slightly faster than, the most efficient implementations in other answers here). Secondly, it reflects very closely your original, explicitly recursive implementation of filterFirst (or, at any rate, more closely than the fold-only and unfold-only implementations).
I just wanted to multiply two lists element by element, so I'd pass (*) as the first argument to that function:
apply :: Num a => (a -> a -> a) -> [a] -> [a] -> [a]
apply f xs ys = [f (xs !! i) (ys !! i) | i <- [0..(length xs - 1)]]
I may be asking a silly question, but I actually googled a lot for it and just couldn't find. Thank you, guys!
> :t zipWith
zipWith :: (a -> b -> c) -> [a] -> [b] -> [c]
> zipWith (*) [1,2,3] [4,5,6]
[4,10,18]
It's the eighth result provided by Hoogle when queried with your type
(a -> a -> a) -> [a] -> [a] -> [a]
Moreover, when you need to implement your own function, use list !! index only as a last resort, since it usually leads to a bad performance, having a cost of O(index). Similarly, length should be used only when necessary, since it needs to scan the whole list.
In the zipWith case, you can avoid both and proceed recursively in a natural way: it is roughly implemented as
zipWith _ [] _ = []
zipWith _ _ [] = []
zipWith f (x:xs) (y:ys) = f x y : zipWith f xs ys
Note that this will only recurse as much as needed to reach the end of the shortest list. The remaining part of the longer list will be discarded.
I was reading through the paper A tutorial on the universality and
expressiveness of fold, and am stuck on the section about generating tuples. After showing of how the normal definition of dropWhile cannot be defined in terms of fold, an example defining dropWhile using tuples was proved:
dropWhile :: (a -> Bool) -> [a] -> [a]
dropWhile p = fst . (dropWhilePair p)
dropWhilePair :: (a -> Bool) -> [a] -> ([a], [a])
dropWhilePair p = foldr f v
where
f x (ys,xs) = (if p x then ys else x : xs, x : xs)
v = ([], [])
The paper states:
In fact, this result is an instance of a
general theorem (Meertens, 1992) that states that any function on finite lists that is
defined by pairing the desired result with the argument list can always be redefined
in terms of fold, although not always in a way that does not make use of the original
(possibly recursive) definition for the function.
I looked at Meerten's Paper but do not have the background (category theory? type theory?) and did not quite find how this was proved.
Is there a relatively simple "proof" why this is the case? Or just a simple explanation as to why we can redefine all functions on finite lists in terms of fold if we pair the results with the original list.
Given the remark that you can / may need to use the original function inside, the claim as stated in your question seems trivial to me:
rewriteAsFold :: ([a] -> (b, [a])) -> [a] -> (b, [a])
rewriteAsFold g = foldr f v where
f x ~(ys,xs) = (fst (g (x:xs)), x:xs)
v = (fst (g []), [])
EDIT: Added the ~, after which it seems to work for infinite lists as well.