Implementing Haskell's `take` function using `foldl` - list

Implementing Haskell's take and drop functions using foldl.
Any suggestions on how to implement take and drop functions using foldl ??
take x ls = foldl ???
drop x ls = foldl ???
i've tried these but it's showing errors:
myFunc :: Int -> [a] -> [a]
myFunc n list = foldl func [] list
where
func x y | (length y) > n = x : y
| otherwise = y
ERROR PRODUCED :
*** Expression : foldl func [] list
*** Term : func
*** Type : a -> [a] -> [a]
*** Does not match : [a] -> [a] -> [a]
*** Because : unification would give infinite type

Can't be done.
Left fold necessarily diverges on infinite lists, but take n does not. This is so because left fold is tail recursive, so it must scan through the whole input list before it can start the processing.
With the right fold, it's
ntake :: Int -> [a] -> [a]
ntake 0 _ = []
ntake n xs = foldr g z xs 0
where
g x r i | i>=n = []
| otherwise = x : r (i+1)
z _ = []
ndrop :: Int -> [a] -> [a]
ndrop 0 xs = xs
ndrop n xs = foldr g z xs 0 xs
where
g x r i xs#(_:t) | i>=n = xs
| otherwise = r (i+1) t
z _ _ = []
ndrop implements a paramorphism nicely and faithfully, up to the order of arguments to the reducer function g, giving it access to both the current element x and the current list node xs (such that xs == (x:t)) as well as the recursive result r. A catamorphism's reducer has access only to x and r.
Folds usually encode catamorphisms, but this shows that right fold can be used to code up a paramorphism just as well. It's universal that way. I think it is beautiful.
As for the type error, to fix it just switch the arguments to your func:
func y x | ..... = .......
The accumulator in the left fold comes as the first argument to the reducer function.
If you really want it done with the left fold, and if you're really sure the lists are finite, two options:
ltake n xs = post $ foldl' g (0,id) xs
where
g (i,f) x | i < n = (i+1, f . (x:))
| otherwise = (i,f)
post (_,f) = f []
rltake n xs = foldl' g id xs r n
where
g acc x = acc . f x
f x r i | i > 0 = x : r (i-1)
| otherwise = []
r _ = []
The first counts from the left straight up, potentially stopping assembling the prefix in the middle of the full list traversal that it does carry to the end nevertheless, being a left fold.
The second also traverses the list in full turning it into a right fold which then gets to work counting down from the left again, being able to actually stop working as soon as the prefix is assembled.
Implementing drop this way is bound to be (?) even clunkier. Could be a nice exercise.

I note that you never specified the fold had to be over the supplied list. So, one approach that meets the letter of your question, though probably not the spirit, is:
sillytake :: Int -> [a] -> [a]
sillytake n xs = foldl go (const []) [1..n] xs
where go f _ (x:xs) = x : f xs
go _ _ [] = []
sillydrop :: Int -> [a] -> [a]
sillydrop n xs = foldl go id [1..n] xs
where go f _ (_:xs) = f xs
go _ _ [] = []
These each use left folds, but over the list of numbers [1..n] -- the numbers themselves are ignored, and the list is just used for its length to build a custom take n or drop n function for the given n. This function is then applied to the original supplied list xs.
These versions work fine on infinite lists:
> sillytake 5 $ sillydrop 5 $ [1..]
[6,7,8,9,10]

Will Ness showed a nice way to implement take with foldr. The least repulsive way to implement drop with foldr is this:
drop n0 xs0 = foldr go stop xs0 n0
where
stop _ = []
go x r n
| n <= 0 = x : r 0
| otherwise = r (n - 1)
Take the efficiency loss and rebuild the whole list if you have no choice! Better to drive a nail in with a screwdriver than drive a screw in with a hammer.
Both ways are horrible. But this one helps you understand how folds can be used to structure functions and what their limits are.
Folds just aren't the right tools for implementing drop; a paramorphism is the right tool.

You are not too far. Here are a pair of fixes.
First, note that func is passed the accumulator first (i.e. a list of a, in your case) and then the list element (an a). So, you need to swap the order of the arguments of func.
Then, if we want to mimic take, we need to add x when the length y is less than n, not greater!
So we get
myFunc :: Int -> [a] -> [a]
myFunc n list = foldl func [] list
where
func y x | (length y) < n = x : y
| otherwise = y
Test:
> myFunc 5 [1..10]
[5,4,3,2,1]
As you can see, this is reversing the string. This is because we add x at the front (x:y) instead of at the back (y++[x]). Or, alternatively, one could use reverse (foldl ....) to fix the order at the end.
Also, since foldl always scans the whole input list, myFunc 3 [1..1000000000] will take a lot of time, and myFunc 3 [1..] will fail to terminate. Using foldr would be much better.
drop is more tricky to do. I don't think you can easily do that without some post-processing like myFunc n xs = fst (foldl ...) or making foldl return a function which you immediately call (which is also a kind of post-processing).

Related

Breaking a list into sublists of a specified size using foldr

I'm taking a functional programming class and I'm having a hard time leaving the OOP mindset behind and finding answers to a lot of my questions.
I have to create a function that takes an ordered list and converts it into specified size sublists using a variation of fold.
This isn't right, but it's what I have:
splitList :: (Ord a) => Int -> [a] -> [[a]]
splitList size xs
| [condition] = foldr (\item subList -> item:subList) [] xs
| otherwise =
I've been searching and I found out that foldr is the variation that works better for what I want, and I think I've understood how fold works, I just don't know how I'll set up the guards so that when length sublist == size haskell resets the accumulator and goes on to the next list.
If I didn't explain myself correctly, here's the result I want:
> splitList 3 [1..10]
> [[1,2,3],[4,5,6],[7,8,9],[10]]
Thanks!
While Fabián's and chi's answers are entirely correct, there is actually an option to solve this puzzle using foldr. Consider the following code:
splitList :: Int -> [a] -> [[a]]
splitList n =
foldr (\el acc -> case acc of
[] -> [[el]]
(h : t) | length h < n -> (el : h) : t
_ -> [el] : acc
) []
The strategy here is to build up a list by extending its head as long as its length is lesser than desired. This solution has, however, two drawbacks:
It does something slightly different than in your example;
splitList 3 [1..10] produces [[1],[2,3,4],[5,6,7],[8,9,10]]
It's complexity is O(n * length l), as we measure length of up to n–sized list on each of the element which yields linear number of linear operations.
Let's first take care of first issue. In order to start counting at the beginning we need to traverse the list left–to–right, while foldr does it right–to–left. There is a common trick called "continuation passing" which will allow us to reverse the direction of the walk:
splitList :: Int -> [a] -> [[a]]
splitList n l = map reverse . reverse $
foldr (\el cont acc ->
case acc of
[] -> cont [[el]]
(h : t) | length h < n -> cont ((el : h) : t)
_ -> cont ([el] : acc)
) id l []
Here, instead of building the list in the accumulator we build up a function that will transform the list in the right direction. See this question for details. The side effect is reversing the list so we need to counter that by reverse application to the whole list and all of its elements. This goes linearly and tail-recursively tho.
Now let's work on the performance issue. The problem was that the length is linear on casual lists. There are two solutions for this:
Use another structure that caches length for a constant time access
Cache the value by ourselves
Because I guess it is a list exercise, let's go for the latter option:
splitList :: Int -> [a] -> [[a]]
splitList n l = map reverse . reverse . snd $
foldr (\el cont (countAcc, listAcc) ->
case listAcc of
[] -> cont (countAcc, [[el]])
(h : t) | countAcc < n -> cont (countAcc + 1, (el : h) : t)
(h : t) -> cont (1, [el] : (h : t))
) id l (1, [])
Here we extend our computational state with a counter that at each points stores the current length of the list. This gives us a constant check on each element and results in linear time complexity in the end.
A way to simplify this problem would be to split this into multiple functions. There are two things you need to do:
take n elements from the list, and
keep taking from the list as much as possible.
Lets try taking first:
taking :: Int -> [a] -> [a]
taking n [] = undefined
taking n (x:xs) = undefined
If there are no elemensts then we cannot take any more elements so we can only return an empty list, on the other hand if we do have an element then we can think of taking n (x:xs) as x : taking (n-1) xs, we would only need to check that n > 0.
taking n (x:xs)
| n > 0 = x :taking (n-1) xs
| otherwise = []
Now, we need to do that multiple times with the remainder so we should probably also return whatever remains from taking n elements from a list, in this case it would be whatever remains when n = 0 so we could try to adapt it to
| otherwise = ([], x:xs)
and then you would need to modify the type signature to return ([a], [a]) and the other 2 definitions to ensure you do return whatever remained after taking n.
With this approach your splitList would look like:
splitList n [] = []
splitList n l = chunk : splitList n remainder
where (chunk, remainder) = taking n l
Note however that folding would not be appropriate since it "flattens" whatever you are working on, for example given a [Int] you could fold to produce a sum which would be an Int. (foldr :: (a -> b -> b) -> b -> [a] -> b or "foldr function zero list produces an element of the function return type")
You want:
splitList 3 [1..10]
> [[1,2,3],[4,5,6],[7,8,9],[10]]
Since the "remainder" [10] in on the tail, I recommend you use foldl instead. E.g.
splitList :: (Ord a) => Int -> [a] -> [[a]]
splitList size xs
| size > 0 = foldl go [] xs
| otherwise = error "need a positive size"
where go acc x = ....
What should go do? Essentially, on your example, we must have:
splitList 3 [1..10]
= go (splitList 3 [1..9]) 10
= go [[1,2,3],[4,5,6],[7,8,9]] 10
= [[1,2,3],[4,5,6],[7,8,9],[10]]
splitList 3 [1..9]
= go (splitList 3 [1..8]) 9
= go [[1,2,3],[4,5,6],[7,8]] 9
= [[1,2,3],[4,5,6],[7,8,9]]
splitList 3 [1..8]
= go (splitList 3 [1..7]) 8
= go [[1,2,3],[4,5,6],[7]] 8
= [[1,2,3],[4,5,6],[7,8]]
and
splitList 3 [1]
= go [] 1
= [[1]]
Hence, go acc x should
check if acc is empty, if so, produce a singleton list [[x]].
otherwise, check the last list in acc:
if its length is less than size, append x
otherwise, append a new list [x] to acc
Try doing this by hand on your example to understand all the cases.
This will not be efficient, but it will work.
You don't really need the Ord a constraint.
Checking the accumulator's first sublist's length would lead to information flow from the right and the first chunk ending up the shorter one, potentially, instead of the last. Such function won't work on infinite lists either (not to mention the foldl-based variants).
A standard way to arrange for the information flow from the left with foldr is using an additional argument. The general scheme is
subLists n xs = foldr g z xs n
where
g x r i = cons x i (r (i-1))
....
The i argument to cons will guide its decision as to where to add the current element into. The i-1 decrements the counter on the way forward from the left, instead of on the way back from the right. z must have the same type as r and as the foldr itself as a whole, so,
z _ = [[]]
This means there must be a post-processing step, and some edge cases must be handled as well,
subLists n xs = post . foldr g z xs $ n
where
z _ = [[]]
g x r i | i == 1 = cons x i (r n)
g x r i = cons x i (r (i-1))
....
cons must be lazy enough not to force the results of the recursive call prematurely.
I leave it as an exercise finishing this up.
For a simpler version with a pre-processing step instead, see this recent answer of mine.
Just going to give another answer: this is quite similar to trying to write groupBy as a fold, and actually has a couple gotchas w.r.t. laziness that you have to bear in mind for an efficient and correct implementation. The following is the fastest version I found that maintains all the relevant laziness properties:
splitList :: Int -> [a] -> [[a]]
splitList m xs = snd (foldr f (const ([],[])) xs 1)
where
f x a i
| i <= 1 = let (ys,zs) = a m in ([], (x : ys) : zs)
| otherwise = let (ys,zs) = a (i-1) in (x : ys , zs)
The ys and the zs gotten from the recursive processing of the rest of list indicate the first and the rest of the groups into which the rest of the list will be broken up, by said recursive processing. So we either prepend the current element before that first subgroup if it is still shorter than needed, or we prepend before the first subgroup when it is just right and start a new, empty subgroup.

Get index of next smallest element in the list in Haskell

I m a newbie to Haskell. I am pretty good with Imperative languages but not with functional. Haskell is my first as a functional language.
I am trying to figure out, how to get the index of the smallest element in the list where the minimum element is defined by me.
Let me explain by examples.
For example :
Function signature
minList :: x -> [x]
let x = 2
let list = [2,3,5,4,6,5,2,1,7,9,2]
minList x list --output 1 <- is index
This should return 1. Because the at list[1] is 3. It returns 1 because 3 is the smallest element after x (=2).
let x = 1
let list = [3,5,4,6,5,2,1,7,9,2]
minList x list -- output 9 <- is index
It should return 9 because at list[9] is 2 and 2 is the smallest element after 1. x = 1 which is defined by me.
What I have tried so far.
minListIndex :: (Ord a, Num a) => a -> [a] -> a
minListIndex x [] = 0
minListIndex x (y:ys)
| x > y = length ys
| otherwise = m
where m = minListIndex x ys
When I load the file I get this error
• Couldn't match expected type ‘a’ with actual type ‘Int’
‘a’ is a rigid type variable bound by
the type signature for:
minListIndex :: forall a. (Ord a, Num a) => a -> [a] -> a
at myFile.hs:36:17
• In the expression: 1 + length ys
In an equation for ‘minListIndex’:
minListIndex x (y : ys)
| x > y = 1 + length ys
| otherwise = 1 + m
where
m = minListIndex x ys
• Relevant bindings include
m :: a (bound at myFile.hs:41:19)
ys :: [a] (bound at myFile.hs:38:19)
y :: a (bound at myFile.hs:38:17)
x :: a (bound at myFile.hs:38:14)
minListIndex :: a -> [a] -> a (bound at myFile.hs:37:1)
When I modify the function like this
minListIndex :: (Ord a, Num a) => a -> [a] -> a
minListIndex x [] = 0
minListIndex x (y:ys)
| x > y = 2 -- <- modified...
| otherwise = 3 -- <- modifiedd
where m = minListIndex x ys
I load the file again then it compiles and runs but ofc the output is not desired.
What is the problem with
| x > y = length ys
| otherwise = m
?
In short: Basically, I want to find the index of the smallest element but higher than the x which is defined by me in parameter/function signature.
Thanks for the help in advance!
minListIndex :: (Ord a, Num a) => a -> [a] -> a
The problem is that you are trying to return result of generic type a but it is actually index in a list.
Suppose you are trying to evaluate your function for a list of doubles. In this case compiler should instantiate function's type to Double -> [Double] -> Double which is nonsense.
Actually compiler notices that you are returning something that is derived from list's length and warns you that it is not possible to match generic type a with concrete Int.
length ys returns Int, so you can try this instead:
minListIndex :: Ord a => a -> [a] -> Int
Regarding your original problem, seems that you can't solve it with plain recursion. Consider defining helper recursive function with accumulator. In your case it can be a pair (min_value_so_far, its_index).
First off, I'd separate the index type from the list element type altogether. There's no apparent reason for them to be the same. I will use the BangPatterns extension to avoid a space leak without too much notation; enable that by adding {-# language BangPatterns #-} to the very top of the file. I will also import Data.Word to get access to the Word64 type.
There are two stages: first, find the index of the given element (if it's present) and the rest of the list beyond that point. Then, find the index of the minimum of the tail.
-- Find the 0-based index of the first occurrence
-- of the given element in the list, and
-- the rest of the list after that element.
findGiven :: Eq a => a -> [a] -> Maybe (Word64, [a])
findGiven given = go 0 where
go !_k [] = Nothing --not found
go !k (x:xs)
| given == xs = Just (k, xs)
| otherwise = go (k+1) xs
-- Find the minimum (and its index) of the elements of the
-- list greater than the given one.
findMinWithIndexOver :: Ord a => a -> [a] -> Maybe (Word64, a)
findMinWithIndexOver given = go 0 Nothing where
go !_k acc [] = acc
go !k acc (x : xs)
| x <= given = go (k + 1) acc xs
| otherwise
= case acc of
Nothing -> go (k + 1) (Just (k, x)) xs
Just (ix_min, curr_min)
| x < ix_min = go (k + 1) (Just (k, x)) xs
| otherwise = go (k + 1) acc xs
You can now put these functions together to construct the one you seek. If you want a general Num result rather than a Word64 one, you can use fromIntegral at the very end. Why use Word64? Unlike Int or Word, it's (practically) guaranteed not to overflow in any reasonable amount of time. It's likely substantially faster than using something like Integer or Natural directly.
It is not clear for me what do you want exactly. Based on examples I guess it is: find the index of the smallest element higher than x which appears after x. In that case, This solution is plain Prelude. No imports
minList :: Ord a => a -> [a] -> Int
minList x l = snd . minimum . filter (\a -> x < fst a) . dropWhile (\a -> x /= fst a) $ zip l [0..]
The logic is:
create the list of pairs, [(elem, index)] using zip l [0..]
drop elements until you find the input x using dropWhile (\a -> x /= fst a)
discards elements less than x using filter (\a -> x < fst a)
find the minimum of the resulting list. Tuples are ordered using lexicographic order so it fits your problem
take the index using snd
Your function can be constructed out of ready-made parts as
import Data.Maybe (listToMaybe)
import Data.List (sortBy)
import Data.Ord (comparing)
foo :: (Ord a, Enum b) => a -> [a] -> Maybe b
foo x = fmap fst . listToMaybe . take 1
. dropWhile ((<= x) . snd)
. sortBy (comparing snd)
. dropWhile ((/= x) . snd)
. zip [toEnum 0..]
This Maybe finds the index of the next smallest element in the list above the given element, situated after the given element, in the input list. As you've requested.
You can use any Enum type of your choosing as the index.
Now you can implement this higher-level executable specs as direct recursion, using an efficient Map data structure to hold your sorted elements above x seen so far to find the next smallest, etc.
Correctness first, efficiency later!
Efficiency update: dropping after the sort drops them sorted, so there's a wasted effort there; indeed it should be replaced with the filtering (as seen in the answer by Luis Morillo) before the sort. And if our element type is in Integral (so it is a properly discrete type, unlike just an Enum, thanks to #dfeuer for pointing this out!), there's one more opportunity for an opportunistic optimization: if we hit on a succ minimal element by pure chance, there's no further chance of improvement, and so we should bail out at that point right there:
bar :: (Integral a, Enum b) => a -> [a] -> Maybe b
bar x = fmap fst . either Just (listToMaybe . take 1
. sortBy (comparing snd))
. findOrFilter ((== succ x).snd) ((> x).snd)
. dropWhile ((/= x) . snd)
. zip [toEnum 0..]
findOrFilter :: (a -> Bool) -> (a -> Bool) -> [a] -> Either a [a]
findOrFilter t p = go
where go [] = Right []
go (x:xs) | t x = Left x
| otherwise = fmap ([x | p x] ++) $ go xs
Testing:
> foo 5 [2,3,5,4,6,5,2,1,7,9,2] :: Maybe Int
Just 4
> foo 2 [2,3,5,4,6,5,2,1,7,9,2] :: Maybe Int
Just 1
> foo 1 [3,5,4,6,5,2,1,7,9,2] :: Maybe Int
Just 9

Reverse first k elements of a list

I'd like to reverse the first k elements of a list efficiently.
This is what I came up with:
reverseFirst :: Int -> [a] -> [a] -> [a]
reverseFirst 0 xs rev = rev ++ xs
reverseFirst k (x:xs) rev = reverseFirst (k-1) xs (x:rev)
reversed = reverseFirst 3 [1..5] mempty -- Result: [3,2,1,4,5]
It is fairly nice, but the (++) bothers me. Or should I maybe consider using another data structure? I want to do this many million times with short lists.
Let's think about the usual structure of reverse:
reverse = rev [] where
rev acc [] = acc
rev acc (x : xs) = rev (x : acc) xs
It starts with the empty list and tacks on elements from the front of the argument list till it's done. We want to do something similar, except we want to tack the elements onto the front of the portion of the list that we don't reverse. How can we do that when we don't have that un-reversed portion yet?
The simplest way I can think of to avoid traversing the front of the list twice is to use laziness:
reverseFirst :: Int -> [a] -> [a]
reverseFirst k xs = dis where
(dis, dat) = rf dat k xs
rf acc 0 ys = (acc, ys)
rf acc n [] = (acc, [])
rf acc n (y : ys) = rf (y : acc) (n - 1) ys
dat represents the portion of the list that is left alone. We calculate it in the same helper function rf that does the reversing, but we also pass it to rf in the initial call. It's never actually examined in rf, so everything just works. Looking at the generated core (using ghc -O2 -ddump-simpl -dsuppress-all -dno-suppress-type-signatures) suggests that the pairs are compiled away into unlifted pairs and the Ints are unboxed, so everything should probably be quite efficient.
Profiling suggests that this implementation is about 1.3 times as fast as the difference list one, and allocates about 65% as much memory.
Well, usually I'd just write splitAt 3 >>> first reverse >>> uncurry(++) to achieve the goal.
If you're anxious about performance, you can consider a difference list:
reverseFirstN :: Int -> [a] -> [a]
reverseFirstN = go id
where go rev 0 xs = rev xs
go rev k (x:xs) = go ((x:).rev) (k-1) xs
but frankly I wouldn't expect this to be a lot faster: you need to traverse the first n elements either way. Actual performance will depend a lot on what the compiler is able to fuse away.

Taking out the last occurrence of a certain element in a list in Haskell

I'm having trouble writing this function that takes a predicate and a list of integers, then eliminates the last occurrence of the integer that satisfies the predicate in the list. I was able to take out the first occurrence of the predicate in the list with my function below:
fun :: (Int -> Bool) -> [Int] -> [Int]
fun check (s:ss)
|check s = ss
|otherwise = s : fun check ss
What I need help on is how I should modify this function to take out the last occurrence of the integer, instead of the first. For example, fun (<2) [3,4,1,5,0,-3,9] would return [3,4,1,5,0,9].
(I couldn't use where due to some indentation problems)
removeLast :: (a -> Bool) -> [a] -> [a]
removeLast p xs =
let
go c [] = tail (c [])
go c (x:xs)
| p x = c (go (x:) xs)
| otherwise = go (c . (x:)) xs
in case break p xs of
(ok, []) -> ok
(ok, x:xs) -> ok ++ go (x:) xs
go collects elements for which the predicate doesn't hold in a difference list and prepends this list to the result once a new satisfying the predicate element is found. Pattern matching on break p xs ensures that difference lists always start with an element that satisfies the predicate and we can drop it if it's the last.
Works with infinite lists:
main = do
print $ removeLast (< 2) [3,4,1,5,0,-3,9] -- [3,4,1,5,0,9]
print $ removeLast (== 2) [1,3] -- [1,3]
print $ take 10 $ removeLast (< 2) (cycle [1,3]) -- [1,3,1,3,1,3,1,3,1,3]
Here is an obfuscated version:
removeLast :: (a -> Bool) -> [a] -> [a]
removeLast p xs = case break p xs of
(ok, []) -> ok
(ok, x:xs) -> ok ++ foldr step (tail . ($[])) xs (x:) where
step x r c = if p x then c (r (x:)) else r (c . (x:))
If you want to have fun with it, try this version.
removeLast :: (a -> Bool) -> [a] -> [a]
removeLast p = fst . foldr go ([], False) where
go x ~(r, more)
| p x = (if more then x : r else r, True)
| otherwise = (x : r, more)
This seems to be almost as lazy as it can be, and it gets to the point pretty quickly. It could produce the list spine more lazily with some effort, but it produces list elements maximally lazily.
After some more thought, I realize that there is some tension between different aspects of laziness in this case. Consider
removeLast p (x : xs)
There are two ways we can try to find out whether to produce a [] or (:) constructor.
We can check xs; if xs is not [], then we can produce (:).
We can check p x. If p x is False, then we can produce (:).
These are the only ways to do it, and their strictness is not comparable. The only "maximally lazy" approach would be to use parallelism to try it both ways, which is not the most practical approach.
How about this:
fun :: (Num a) => (a -> Bool) -> [a] -> [a]
fun check (s:ss)
|check s = ss
|otherwise = s : fun check ss
Then, apply your fun function like this:
reverse $ fun (\ x -> x `mod` 3 == 0) (reverse [1..10])
HTH

Replace an element in a list only once - Haskell

I want to replace an element in a list with a new value only at first time occurrence.
I wrote the code below but using it, all the matched elements will change.
replaceX :: [Int] -> Int -> Int -> [Int]
replaceX items old new = map check items where
check item | item == old = new
| otherwise = item
How can I modify the code so that the changing only happen at first matched item?
Thanks for helping!
The point is that map and f (check in your example) only communicate regarding how to transform individual elements. They don't communicate about how far down the list to transform elements: map always carries on all the way to the end.
map :: (a -> b) -> [a] -> [b]
map _ [] = []
map f (x:xs) = f x : map f xs
Let's write a new version of map --- I'll call it mapOnce because I can't think of a better name.
mapOnce :: (a -> Maybe a) -> [a] -> [a]
There are two things to note about this type signature:
Because we may stop applying f part-way down the list, the input list and the output list must have the same type. (With map, because the entire list will always be mapped, the type can change.)
The type of f hasn't changed to a -> a, but to a -> Maybe a.
Nothing will mean "leave this element unchanged, continue down the list"
Just y will mean "change this element, and leave the remaining elements unaltered"
So:
mapOnce _ [] = []
mapOnce f (x:xs) = case f x of
Nothing -> x : mapOnce f xs
Just y -> y : xs
Your example is now:
replaceX :: [Int] -> Int -> Int -> [Int]
replaceX items old new = mapOnce check items where
check item | item == old = Just new
| otherwise = Nothing
You can easily write this as a recursive iteration like so:
rep :: Eq a => [a] -> a -> a -> [a]
rep items old new = rep' items
where rep' (x:xs) | x == old = new : xs
| otherwise = x : rep' xs
rep' [] = []
A direct implementation would be
rep :: Eq a => a -> a -> [a] -> [a]
rep _ _ [] = []
rep a b (x:xs) = if x == a then b:xs else x:rep a b xs
I like list as last argument to do something like
myRep = rep 3 5 . rep 7 8 . rep 9 1
An alternative using the Lens library.
>import Control.Lens
>import Control.Applicative
>_find :: (a -> Bool) -> Simple Traversal [a] a
>_find _ _ [] = pure []
>_find pred f (a:as) = if pred a
> then (: as) <$> f a
> else (a:) <$> (_find pred f as)
This function takes a (a -> Bool) which is a function that should return True on an type 'a' that you wan to modify.
If the first number greater then 5 needs to be doubled then we could write:
>over (_find (>5)) (*2) [4, 5, 3, 2, 20, 0, 8]
[4,5,3,2,40,0,8]
The great thing about lens is that you can combine them together by composing them (.). So if we want to zero the first number <100 in the 2th sub list we could:
>over ((element 1).(_find (<100))) (const 0) [[1,2,99],[101,456,50,80,4],[1,2,3,4]]
[[1,2,99],[101,456,0,80,4],[1,2,3,4]]
To be blunt, I don't like most of the answers so far. dave4420 presents some nice insights on map that I second, but I also don't like his solution.
Why don't I like those answers? Because you should be learning to solve problems like these by breaking them down into smaller problems that can be solved by simpler functions, preferably library functions. In this case, the library is Data.List, and the function is break:
break, applied to a predicate p and a list xs, returns a tuple where first element is longest prefix (possibly empty) of xs of elements that do not satisfy p and second element is the remainder of the list.
Armed with that, we can attack the problem like this:
Split the list into two pieces: all the elements before the first occurence of old, and the rest.
The "rest" list will either be empty, or its first element will be the first occurrence of old. Both of these cases are easy to handle.
So we have this solution:
import Data.List (break)
replaceX :: Eq a => a -> a -> [a] -> [a]
replaceX old new xs = beforeOld ++ replaceFirst oldAndRest
where (beforeOld, oldAndRest) = break (==old) xs
replaceFirst [] = []
replaceFirst (_:rest) = new:rest
Example:
*Main> replaceX 5 7 ([1..7] ++ [1..7])
[1,2,3,4,7,6,7,1,2,3,4,5,6,7]
So my advice to you:
Learn how to import libraries.
Study library documentation and learn standard functions. Data.List is a great place to start.
Try to use those library functions as much as you can.
As a self study exercise, you can pick some of the standard functions from Data.List and write your own versions of them.
When you run into a problem that can't be solved with a combination of library functions, try to invent your own generic function that would be useful.
EDIT: I just realized that break is actually a Prelude function, and doesn't need to be imported. Still, Data.List is one of the best libraries to study.
Maybe not the fastest solution, but easy to understand:
rep xs x y =
let (left, (_ : right)) = break (== x) xs
in left ++ [y] ++ right
[Edit]
As Dave commented, this will fail if x is not in the list. A safe version would be:
rep xs x y =
let (left, right) = break (== x) xs
in left ++ [y] ++ drop 1 right
[Edit]
Arrgh!!!
rep xs x y = left ++ r right where
(left, right) = break (== x) xs
r (_:rs) = y:rs
r [] = []
replaceValue :: Int -> Int -> [Int] -> [Int]
replaceValue a b (x:xs)
|(a == x) = [b] ++ xs
|otherwise = [x] ++ replaceValue a b xs
Here's an imperative way to do it, using State Monad:
import Control.Monad.State
replaceOnce :: Eq a => a -> a -> [a] -> [a]
replaceOnce old new items = flip evalState False $ do
forM items $ \item -> do
replacedBefore <- get
if item == old && not replacedBefore
then do
put True
return new
else
return old