I want to write a function in haskell that takes a list of integers and an integer value as input and outputs a list of all the lists that contain combinations of elements that add up to the input integer.
For example:
myFunc [3,7,5,9,13,17] 30 = [[13,17],[3,5,9,13]]
Attempt:
myFunc :: [Integer] -> Integer -> [[Integer]]
myFunc list sm = case list of
[] -> []
[x]
| x == sm -> [x]
| otherwise -> []
(x : xs)
| x + myFunc xs == sm -> [x] ++ myFunc[xs]
| otherwise -> myFunc xs
My code produces just one combination and that combination must be consecutive, which is not what I want to achieve
Write a function to create all subsets
f [] = [[]]
f (x:xs) = f xs ++ map (x:) (f xs)
then use the filter
filter ((==30) . sum) $ f [3,7,5,9,13,17]
[[13,17],[3,5,9,13]]
as suggested by #Ingo you can prune the list while it's generated, for example
f :: (Num a, Ord a) => [a] -> [[a]]
f [] = [[]]
f (x:xs) = f xs ++ (filter ((<=30) . sum) $ map (x:) $ f xs)
should work faster than generating all 2^N elements.
You can use subsequences from Data.List to give you every possible combination of values, then filter based on your requirement that they add to 30.
myFunc :: [Integer] -> Integer -> [[Integer]]
myFunc list sm =
filter (\x -> sum x == sm) $ subsequences list
An alternative would be to use a right fold:
fun :: (Foldable t, Num a, Eq a) => t a -> a -> [[a]]
fun = foldr go $ \a -> if a == 0 then [[]] else []
where go x f a = f a ++ ((x:) <$> f (a - x))
then,
\> fun [3,7,5,9,13,17] 30
[[13,17],[3,5,9,13]]
\> fun [3,7,5,9,13,17] 12
[[7,5],[3,9]]
An advantage of this approach is that it does not create any lists unless it adds up to the desired value.
Whereas, an approach based on filtering, will create all the possible sub-sequence lists only to drop most of them during filtering step.
Here is an alternate solution idea: Generate a list of lists that sum up to the target number, i.e.:
[30]
[29,1]
[28,2]
[28,1,1]
...
and only then filter the ones that could be build from your given list.
Pro: could be much faster, especially if your input list is long and your target number comparatively small, such that the list of list of summands is much smaller than the list of subsets of your input list.
Con: does only work when 0 is not in the game.
Finally, you can it do both ways and write a function that decides which algorthm will be faster given some input list and the target number.
Related
So I already have a function that finds the number of occurrences in a list using maps.
occur :: [a] -> Map a a
occur xs = fromListWith (+) [(x, 1) | x <- xs]
For example if a list [1,1,2,3,3] is inputted, the code will output [(1,2),(2,1),(3,2)], and for a list [1,2,1,1] the output would be [(1,3),(2,1)].
I was wondering if there's any way I can change this function to use foldr instead to eliminate the use of maps.
You can make use of foldr where the accumulator is a list of key-value pairs. Each "step" we look if the list already contains a 2-tuple for the given element. If that is the case, we increment the corresponding value. If the item x does not yet exists, we add (x, 1) to that list.
Our function thus will look like:
occur :: Eq => [a] -> [(a, Int)]
occur = foldr incMap []
where incMap thus takes an item x and a list of 2-tuples. We can make use of recursion here to update the "map" with:
incMap :: Eq a => a -> [(a, Int)] -> [(a, Int)]
incMap x = go
where go [] = [(x, 1)]
go (y2#(y, ny): ys)
| x == y = … : ys
| otherwise = y2 : …
where I leave implementing the … parts as an exercise.
This algorithm is not very efficient, since it takes O(n) to increment the map with n the number of 2-tuples in the map. You can also implement incrementing the Map for the given item by using insertWith :: Ord k => (a -> a -> a) -> k -> a -> Map k a -> Map k a, which is more efficient.
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 playing around with Haskell, mostly trying to learn some new techniques to solve problems. Without any real application in mind I came to think about an interesting thing I can't find a satisfying solution to. Maybe someone has any better ideas?
The problem:
Let's say we want to generate a list of Ints using a starting value and a list of Ints, representing the pattern of numbers to be added in the specified order. So the first value is given, then second value should be the starting value plus the first value in the list, the third that value plus the second value of the pattern, and so on. When the pattern ends, it should start over.
For example: Say we have a starting value v and a pattern [x,y], we'd like the list [v,v+x,v+x+y,v+2x+y,v+2x+2y, ...]. In other words, with a two-valued pattern, next value is created by alternatingly adding x and y to the number last calculated.
If the pattern is short enough (2-3 values?), one could generate separate lists:
[v,v,v,...]
[0,x,x,2x,2x,3x, ...]
[0,0,y,y,2y,2y,...]
and then zip them together with addition. However, as soon as the pattern is longer this gets pretty tedious. My best attempt at a solution would be something like this:
generateLstByPattern :: Int -> [Int] -> [Int]
generateLstByPattern v pattern = v : (recGen v pattern)
where
recGen :: Int -> [Int] -> [Int]
recGen lastN (x:[]) = (lastN + x) : (recGen (lastN + x) pattern)
recGen lastN (x:xs) = (lastN + x) : (recGen (lastN + x) xs)
It works as intended - but I have a feeling there is a bit more elegant Haskell solution somewhere (there almost always is!). What do you think? Maybe a cool list-comprehension? A higher-order function I've forgotten about?
Separate the concerns. First look a just a list to process once. Get that working, test it. Hint: “going through the list elements with some accumulator” is in general a good fit for a fold.
Then all that's left to is to repeat the list of inputs and feed it into the pass-once function. Conveniently, there's a standard function for that purpose. Just make sure your once-processor is lazy enough to handle the infinite list input.
What you describe is
foo :: Num a => a -> [a] -> [a]
foo v pattern = scanl (+) v (cycle pattern)
which would normally be written even as just
foo :: Num a => a -> [a] -> [a]
foo v = scanl (+) v . cycle
scanl (+) v xs is the standard way to calculate the partial sums of (v:xs), and cycle is the standard way to repeat a given list cyclically. This is what you describe.
This works for a pattern list of any positive length, as you wanted.
Your way of generating it is inventive, but it's almost too clever for its own good (i.e. it seems overly complicated). It can be expressed with some list comprehensions, as
foo v pat =
let -- the lists, as you describe them:
lists = repeat v :
[ replicate i 0 ++
[ y | x <- [p, p+p ..]
, y <- map (const x) pat ]
| (p,i) <- zip pat [1..] ]
in
-- OK, so what do we do with that? How do we zipWith
-- over an arbitrary amount of lists?
-- with a fold!
foldr (zipWith (+)) (repeat 0) lists
map (const x) pat is a "clever" way of writing replicate (length pat) x. It can be further shortened to x <$ pat since (<$) x xs == map (const x) xs by definition. It might seem obfuscated, until you've become accustomed to it, and then it seems clear and obvious. :)
Surprised noone's mentioned the silly way yet.
mylist x xs = x : zipWith (+) (mylist x xs) (cycle xs)
(If you squint a bit you can see the connection to scanl answer).
When it is about generating series my first approach would be iterate or unfoldr. iterate is for simple series and unfoldr is for those who carry kind of state but without using any State monad.
In this particular case I think unfoldr is ideal.
series :: Int -> [Int] -> [Int]
series s [x,y] = unfoldr (\(f,s) -> Just (f*x + s*y, (s+1,f))) (s,0)
λ> take 10 $ series 1 [1,1]
[1,2,3,4,5,6,7,8,9,10]
λ> take 10 $ series 3 [1,1]
[3,4,5,6,7,8,9,10,11,12]
λ> take 10 $ series 0 [1,2]
[0,1,3,4,6,7,9,10,12,13]
It is probably better to implement the lists separately, for example the list with x can be implement with:
xseq :: (Enum a, Num a) => a -> [a]
xseq x = 0 : ([x, x+x ..] >>= replicate 2)
Whereas the sequence for y can be implemented as:
yseq :: (Enum a, Num a) => a -> [a]
yseq y = [0,y ..] >>= replicate 2
Then you can use zipWith :: (a -> b -> c) -> [a] -> [b] -> [c] to add the two lists together and add v to it:
mylist :: (Enum a, Num a) => a -> a -> a -> [a]
mylist v x y = zipWith ((+) . (v +)) (xseq x) (yseq y)
So for v = 1, x = 2, and y = 3, we obtain:
Prelude> take 10 (mylist 1 2 3)
[1,3,6,8,11,13,16,18,21,23]
An alternative is to see as pattern that we each time first add x and then y. We thus can make an infinite list [(x+), (y+)], and use scanl :: (b -> a -> b) -> b -> [a] -> [b] to each time apply one of the functions and yield the intermediate result:
mylist :: Num a => a -> a -> a -> [a]
mylist v x y = scanl (flip ($)) v (cycle [(x+), (y+)])
this yields the same result:
Prelude> take 10 $ mylist 1 2 3
[1,3,6,8,11,13,16,18,21,23]
Now the only thing left to do is to generalize this to a list. So for example if the list of additions is given, then you can impelement this as:
mylist :: Num a => [a] -> [a]
mylist v xs = scanl (flip ($)) v (cycle (map (+) xs))
or for a list of functions:
mylist :: Num a => [a -> a] -> [a]
mylist v xs = scanl (flip ($)) v (cycle (xs))
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 am dealing with small program with Haskell. Probably the answer is really simple but I try and get no result.
So one of the part in my program is the list:
first = [(3,3),(4,6),(7,7),(5,43),(9,9),(32,1),(43,43) ..]
and according to that list I want to make new one with element that are equal in the () =:
result = [3,7,9,43, ..]
Even though you appear to have not made the most minimal amount of effort to solve this question by yourself, I will give you the answer because it is so trivial and because Haskell is a great language.
Create a function with this signature:
findIdentical :: [(Int, Int)] -> [Int]
It takes a list of tuples and returns a list of ints.
Implement it like this:
findIdentical [] = []
findIdentical ((a,b) : xs)
| a == b = a : (findIdentical xs)
| otherwise = findIdentical xs
As you can see, findIdentical is a recursive function that compares a tuple for equality between both items, and then adds it to the result list if there is found equality.
You can do this for instance with list comprehension. We iterate over every tuple f,s) in first, so we write (f,s) <- first in the right side of the list comprehension, and need to filter on the fact that f and s are equal, so f == s. In that case we add f (or s) to the result. So:
result = [ f | (f,s) <- first, f == s ]
We can turn this into a function that takes as input a list of 2-tuples [(a,a)], and compares these two elements, and returns a list [a]:
f :: Eq a => [(a,a)] -> [a]
f dat = [f | (f,s) <- dat, f == s ]
An easy way to do this is to use the Prelude's filter function, which has the type definition:
filter :: (a -> Bool) -> [a] -> [a]
All you need to do is supply predicate on how to filter the elements in the list, and the list to filter. You can accomplish this easily below:
filterList :: (Eq a) => [(a, a)] -> [a]
filterList xs = [x | (x, y) <- filter (\(a, b) -> a == b) xs]
Which behaves as expected:
*Main> filterList [(3,3),(4,6),(7,7),(5,43),(9,9),(32,1),(43,43)]
[3,7,9,43]