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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.
I'm new in haskell programming and I try to solve a problem by/not using list comprehensions.
The Problem is to find the index of an element in a list and return a list of the indexes (where the elements in the list was found.)
I already solved the problem by using list comprehensions but now i have some problems to solve the problem without using list comprehensions.
On my recursive way:
I tried to zip a list of [0..(length list)] and the list as it self.
then if the element a equals an element in the list -> make a new list with the first element of the Tupel of the zipped list(my index) and after that search the function on a recursive way until the list is [].
That's my list comprehension (works):
positions :: Eq a => a -> [a] -> [Int]
positions a list = [x | (x,y) <- zip [0..(length list)] list, a == y]
That's my recursive way (not working):
positions' :: Eq a => a -> [a] -> [Int]
positions' _ [] = []
positions' a (x:xs) =
let ((n,m):ns) = zip [0..(length (x:xs))] (x:xs)
in if (a == m) then n:(positions' a xs)
else (positions' a xs)
*sorry I don't know how to highlight words
but ghci says:
*Main> positions' 2 [1,2,3,4,5,6,7,8,8,9,2]
[0,0]
and it should be like that (my list comprehension):
*Main> positions 2 [1,2,3,4,5,6,7,8,8,9,2]
[1,10]
Where is my mistake ?
The problem with your attempt is simply that when you say:
let ((n,m):ns) = zip [0..(length (x:xs))] (x:xs)
then n will always be 0. That's because you are matching (n,m) against the first element of zip [0..(length (x:xs))] (x:xs), which will necessarily always be (0,x).
That's not a problem in itself - but it does mean you have to handle the recursive step properly. The way you have it now, positions _ _, if non-empty, will always have 0 as its first element, because the only way you allow it to find a match is if it's at the head of the list, resulting in an index of 0. That means that your result will always be a list of the correct length, but with all elements 0 - as you're seeing.
The problem isn't with your recursion scheme though, it's to do with the fact that you're not modifying the result to account for the fact that you don't always want 0 added to the front of the result list. Since each recursive call just adds 1 to the index you want to find, all you need to do is map the increment function (+1) over the recursive result:
positions' :: Eq a => a -> [a] -> [Int]
positions' _ [] = []
positions' a (x:xs) =
let ((0,m):ns) = zip [0..(length (x:xs))] (x:xs)
in if (a == m) then 0:(map (+1) (positions' a xs))
else (map (+1) (positions' a xs))
(Note that I've changed your let to be explicit that n will always be 0 - I prefer to be explicit this way but this in itself doesn't change the output.) Since m is always bound to x and ns isn't used at all, we can elide the let, inlining the definition of m:
positions' :: Eq a => a -> [a] -> [Int]
positions' _ [] = []
positions' a (x:xs) =
if a == x
then 0 : map (+1) (positions' a xs)
else map (+1) (positions' a xs)
You could go on to factor out the repeated map (+1) (positions' a xs) if you wanted to.
Incidentally, you didn't need explicit recursion to avoid a list comprehension here. For one, list comprehensions are basically a replacement for uses of map and filter. I was going to write this out explicitly, but I see #WillemVanOnsem has given this as an answer so I will simply refer you to his answer.
Another way, although perhaps not acceptable if you were asked to implement this yourself, would be to just use the built-in elemIndices function, which does exactly what you are trying to implement here.
We can make use of a filter :: (a -> Bool) -> [a] -> [a] and map :: (a -> b) -> [a] -> [b] approach, like:
positions :: Eq a => a -> [a] -> [Int]
positions x = map fst . filter ((x ==) . snd) . zip [0..]
We thus first construct tuples of the form (i, yi), next we filter such that we only retain these tuples for which x == yi, and finally we fetch the first item of these tuples.
For example:
Prelude> positions 'o' "foobaraboof"
[1,2,8,9]
Your
let ((n,m):ns) = zip [0..(length (x:xs))] (x:xs)
is equivalent to
== {- by laziness -}
let ((n,m):ns) = zip [0..] (x:xs)
== {- by definition of zip -}
let ((n,m):ns) = (0,x) : zip [1..] xs
== {- by pattern matching -}
let {(n,m) = (0,x)
; ns = zip [1..] xs }
== {- by pattern matching -}
let { n = 0
; m = x
; ns = zip [1..] xs }
but you never reference ns! So we don't need its binding at all:
positions' a (x:xs) =
let { n = 0 ; m = x } in
if (a == m) then n : (positions' a xs)
else (positions' a xs)
and so, by substitution, you actually have
positions' :: Eq a => a -> [a] -> [Int]
positions' _ [] = []
positions' a (x:xs) =
if (a == x) then 0 : (positions' a xs) -- NB: 0
else (positions' a xs)
And this is why all you ever produce are 0s. But you want to produce the correct index: 0, 1, 2, 3, ....
First, let's tweak your code a little bit further into
positions' :: Eq a => a -> [a] -> [Int]
positions' a = go xs
where
go [] = []
go (x:xs) | a == x = 0 : go xs -- NB: 0
| otherwise = go xs
This is known as a worker/wrapper transform. go is a worker, positions' is a wrapper. There's no need to pass a around from call to call, it doesn't change, and we have access to it anyway. It is in the enclosing scope with respect to the inner function, go. We've also used guards instead of the more verbose and less visually apparent if ... then ... else.
Now we just need to use something -- the correct index value -- instead of 0.
To use it, we must have it first. What is it? It starts as 0, then it is incremented on each step along the input list.
When do we make a step along the input list? At the recursive call:
positions' :: Eq a => a -> [a] -> [Int]
positions' a = go xs 0
where
go [] _ = []
go (x:xs) i | a == x = 0 : go xs (i+1) -- NB: 0
| otherwise = go xs (i+1)
_ as a pattern means we don't care about the argument's value -- it's there but we're not going to use it.
Now all that's left for us to do is to use that i in place of that 0.
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).
I have seen some similar questions, but nothing that really helped me. Basically the title says it all. Using SML I want to take a string that I have, and make a list containing each letter found in the string. Any help would be greatly appreciated.
One possibility is to use the basic logic of quicksort to sort the letters while removing duplicates at the same time. Something like:
fun distinctChars []:char list = []
| distinctChars (c::cs) =
let val smaller = List.filter (fn x => x < c) cs
val bigger = List.filter (fn x => x > c) cs
in distinctChars smaller # [c] # distinctChars bigger
end
If the < and > in the definitions of smaller and bigger were to be replaced by <= and >= then it would simply be an implementation of quicksort (although not the most efficient one since it makes two passes over cs when a suitably defined auxiliary function could split into smaller and bigger in just one pass). The strict inequalities have the effect of throwing away duplicates.
To get what you want from here, do something like explode the string into a list of chars, remove non-alphabetical characters from the resulting list, while simultaneously converting to lower case, then invoke the above function -- ideally first refined so that it uses a custom split function rather than List.filter twice.
On Edit: # is an expensive operator and probably results in the naïve SML quicksort not being all that quick. You can use the above idea of a modified sort, but one that modifies mergesort instead of quicksort:
fun split ls =
let fun split' [] (xs,ys) = (xs,ys)
| split' (a::[]) (xs, ys) = (a::xs,ys)
| split' (a::b::cs) (xs, ys) = split' cs (a::xs, b::ys)
in split' ls ([],[])
end
fun mergeDistinct ([], ys) = ys:char list
| mergeDistinct (xs, []) = xs
| mergeDistinct (x::xs, y::ys) =
if x < y then x::mergeDistinct(xs,y::ys)
else if x > y then y::mergeDistinct(x::xs,ys)
else mergeDistinct(x::xs, ys)
fun distinctChars [] = []
| distinctChars [c] = [c]
| distinctChars chars =
let val (xs,ys) = split chars
in mergeDistinct (distinctChars xs, distinctChars ys)
end
You can get a list of all the letters in a few different ways:
val letters = [#"a",#"b",#"c",#"d",#"e",#"f",#"g",#"h",#"i",#"j",#"k",#"l",#"m",#"n",#"o",#"p",#"q",#"r",#"s",#"t",#"u",#"v",#"w",#"x",#"y",#"z"]
val letters = explode "abcdefghijklmnopqrstuvwxyz"
val letters = List.tabulate (26, fn i => chr (i + ord #"a"))
Update: Looking at your question and John's answer, I might have misunderstood your intention. An efficient way to iterate over a string and gather some result (e.g. a set of characters) could be to write a "foldr for strings":
fun string_foldr f acc0 s =
let val len = size s
fun loop i acc = if i < len then loop (i+1) (f (String.sub (s, i), acc)) else acc
in loop 0 acc0 end
Given an implementation of sets with at least setEmpty and setInsert, one could then write:
val setLetters = string_foldr (fn (c, ls) => setInsert ls c) setEmpty "some sentence"
The simplest solution I can think of:
To get the distinct elements of a list:
Take the head
Remove that value from the tail and get the distinct elements of the result.
Put 1 and 2 together.
In code:
(* Return the distinct elements of a list *)
fun distinct [] = []
| distinct (x::xs) = x :: distinct (List.filter (fn c => x <> c) xs);
(* All the distinct letters, in lower case. *)
fun letters s = distinct (List.map Char.toLower (List.filter Char.isAlpha (explode s)));
(* Variation: "point-free" style *)
val letters' = distinct o (List.map Char.toLower) o (List.filter Char.isAlpha) o explode;
This is probably not the most efficient solution, but it's uncomplicated.
The point of the following function is to take in a list and split the list into a tuple of 2 lists. The first list will maintain even indexed items and the second will maintain odd indexed items. "Pos" is the position currently at. (0 is being passed in on function call). The initial tuple of lists passed in is ([],[])
split :: [Integer] -> ([Integer],[Integer]) -> Integer -> ([Integer], [Integer])
split [] (x,y) _ = (x,y)
split (x:xs) ((y:ys),(z:zs)) pos
| pos `mod` 2 == 0 = doSplit xs ((y:ys) ++ [x], (z:zs)) (pos + 1)
| otherwise = doSplit xs ((y:ys), (z:zs) ++ [x]) (pos + 1)
Haskell is reporting
*** Exception: split.hs:(113,1)-(116,73): Non-exhaustive patterns in function split
I understand that it believes that I have not covered "some case" that should be covered, however I feel I have covered all cases.
If the list is empty -> return the tuple of lists that was passed in
Otherwise -> tack x onto one of the lists and recurse on xs.
From my point of view, this function is strictly decreasing until xs becomes [] in which case it stops.
Am I missing something?
There is no match when the first list is nonempty but one (or both) of the lists in the tuple argument are empty e.g.
split [1] ([], [])
however your second clause doesn't seem to require that either list in the tuple is non-empty so you could change it to:
split (x:xs) (ys,zs) pos
| pos `mod` 2 == 0 = doSplit xs (ys ++ [x], zs) (pos + 1)
| otherwise = doSplit xs (ys, zs ++ [x]) (pos + 1)