I'm trying to write a haskell function that takes in two lists of integers and generates a list with elements that have been taken alternatingly from the two lists.
I have the function:
blend xs ys
An example:
blend [1,2,3] [4,5,6]
should return
[1,4,2,5,3,6]
My logic is to zip the two lists together, generating the pairs of alternate elements, then somehow remove them from their tuples.
It's removing them from their tuples that I can't figure out how to implement.
How about exchanging the arguments during recursion-descend?
blend (x:xs) ys = x:(blend ys xs)
blend _ _ = []
You can even generalise this approach for any number of lists (I'll leave this to you) or take the remaining elements of a list if the other is empty:
blend _ ys = ys
If you want to zip, generate lists instead of tuples:
concat $ zipWith (\x y -> [x,y]) [1,2,3] [4,5,6]
Some pointless fun:
concat $ zipWith ((flip(:)).(:[])) [1,2,3] [4,5,6]
Probably the easiest way:
import Data.List
concat $ transpose [[1,2,3],[4,5,6]]
I will assume that this is homework. Provided that you can create the following list (as you said):
[(1,4),(2,5),(3,6)]
... you can solve it with 2 functions:
You need to convert a tuple (a, b) into a list [a, b]. Try using pattern matching! This function needs to be applied (aka. mapped) over all elements of the list you have.
You will have a list of lists, like [[1,4],[2,5],[3,6]], so you need a function for concatenating the sublists into one big list.
There are of course other, maybe superior, ways to solve this problem, but it might be a good idea to continue with your original approach.
A solution without using concat or explicit recursion:
blend l = foldr($)[] . zipWith(.) (map(:)l) . map(:)
We can make also make this point-free
blend' = (foldr($)[].) . (.map(:)) . zipWith(.) . map(:)
How it works: first decorate both lists with cons operators
\[1,2,3] [4,5,6] -> [1:, 2:, 3:] [4:, 5:, 6:]
then we zip this together with function composition
-> [(1:).(4:), (2:).(5:), (3:).(6:)]
and finally fold the application of all these compositions from the right to the empty list
-> (1:).(4:) $ (2:).(5:) $ (3:).(6:) $ [] = 1:4:2:5:3:6:[] = [1,4,2,5,3,6]
Your blend function seems to be a limited version of flatZip. The flatZip function is similar but works for any number of lists of varying lengths. Using flatZip to implement blend will cause blend to also support varying lengths by default. Therefore, using a flatZip based approach may not be the way to go in situations where trimming the input lists to equal length is part of the desired behaviour.
The name flatZip refers to "a zipish way of flattening". Note the -ish part though. We can implement the function by composing concat with transpose. We can add blend on top of flatZip as syntactic sugar to verify that our implementation matches the desired behaviour.
import Data.List
flatZip = concat . transpose
flatZip([[1,2],[3],[4,5,6]]) --[1,3,4,2,5,6]
blend xs ys = flatZip [xs, ys]
blend [1,2,3] [4,5,6] --[1,4,2,5,3,6]
Related
I'm trying to learn OCaml since I'm new to the language and I stumbled across this problem where I can't seem to find a way to see, in a function where I need to merge 2 kinds of these lists, if there is already an element with a key, and if so how to join the elements that come after. Would appreciate any guidance.
For example if I have:
l1: [(k, [e]); (ka, [])]
l2: [(k, [f; g])]
How can I end up with:
fl: [(k, [e; f; g]); (ka, [])]
Basically, how can I filter the key k from both lists while making their elements combine.
There are functions in the standard OCaml library for dealing with lists of pairs where the first element of each pair is a key. You will find them described here: https://ocaml.org/releases/4.12/api/List.html under Association lists.
I will repeat what #ivg says. This is not how you want to solve your problem if you have more than just a few pairs to work with.
First of all, using lists as mappings is a bad idea. It is much better to use dedicated data structures such as maps and hash tables.
Answering your question directly, you can concatenate two lists using the (#) operator, e.g.,
# [1;2;3] # [4;5;6];;
- : int list = [1; 2; 3; 4; 5; 6]
If you don't want repetitive elements when you merge then, and I feel like I repeat myself, it is bad to use lists for sets, it is better to use dedicated data structures such as sets and hash sets. But if you want to continue, then you can merge two lists without repetitions by checking if an element is already in the list before prepending to it. Easy to implement but hard to run, in a sense that it takes quadratic time to merge two lists this way.
If you still want to stick with the list of pairs, then you will find that the List.assoc function is useful, as it finds a value by key. The overall algorithm would be, given two lists, xs and ys, fold over elements of ys using xs as the initial value acc, and for each (ky,y) in ys if ky is already in acc, find the associated with ky value x and remove (List.remove_assoc) it, then merge x and y and prepend the merged value with the acc list, otherwise (if it is not in acc) just prepend (ky,y) to acc`. Note that this algorithm doesn't preserve order, so if it matters you need something more complex. Also, if your keys are sorted you can make it a little bit more efficient and easier to implement.
I guess you're doing this to practice with list.
What I would do is store the already found keys in an accumulator
let mergePairs yourList =
let rec aux accKeys = function
| [] -> []
| x :: xs -> let k,v = x in if (* k in accKeys *) then aux accKeys xs (*we suppress already
existing keys*)
else (k, v # (* get all the list of the other pairs with key = k in xs*))
:: aux (k::accKeys) xs
in aux [] yourList;;
I have a list of (String, Int) pairs and am struggling to figure out how to sort the list by the snd field (Int). I am not allowed to use higher order functions or recursion which makes it more difficult.
For example, I have
[("aaaaa", 5),("bghdfe", 6),("dddr",4)]
and would like to sort it into
[("dddr",4),("aaaaa", 5),("bghdfe", 6)].
Edit:
I understand that the sort may not be possible without higher order functions, what I really need is to find the element with the minimum length (the snd field), so is there a way to find the minimum number and then take the fst field of the list's element at that index? If that way works better I am unsure about how to find the index of that minimum number however.
The task seems to be impossible, since you can't write a sort without recursion in Haskell. This means, you must use sort, which is usually something like sortBy compare and thus you have it.
But if you are allowed to use sort you can do it by first reversing all tuples, sorting the resulting list and reversing the tuples in the result again. This should be possible to do in a few nested list comprehension, so technically no higher order functions are needed.
After you have given more details, I'd do
homework list = snd (minimum [ (s,f) | (f,s) <- list ])
Without higher order functions or recursion all you have left, technically, is list comprehensions. Thus we define
-- sortBy (comparing snd) >>> take 1 >>> listToMaybe >>> fmap fst
-- ~= minimumBy (comparing snd) >>> fst
foo :: Ord b => [(a,b)] -> Maybe a
foo xs = case [ a | (a,b) <- xs
, null [ () | (_c,d) <- xs, d < b]]
of (a:_) -> Just a
[] -> Nothing
I am trying to understand this piece of code which returns the all possible combinations of [a] passed to it:
-- Infinite list of all combinations for a given value domain
allCombinations :: [a] -> [[a]]
allCombinations [] = [[]]
allCombinations values = [] : concatMap (\w -> map (:w) values)
(allCombinations values)
Here i tried this sample input:
ghci> take 7 (allCombinations [True,False])
[[],[True],[False],[True,True],[False,True],[True,False],[False,False]]
Here it doesn't seems understandable to me which is that how the recursion will eventually stops and will return [ [ ] ], because allCombinations function certainly doesn't have any pointer which moves through the list, on each call and when it meets the base case [ ] it returns [ [ ] ]. According to me It will call allCombinations function infinite and will never stop on its own. Or may be i am missing something?
On the other hand, take only returns the first 7 elements from the final list after all calculation is carried out by going back after completing recursive calls. So actually how recursion met the base case here?
Secondly what is the purpose of concatMap here, here we could also use Map function here just to apply function to the list and inside function we could arrange the list? What is actually concatMap doing here. From definition it concatMap tells us it first map the function then concatenate the lists where as i see we are already doing that inside the function here?
Any valuable input would be appreciated?
Short answer: it will never meet the base case.
However, it does not need to. The base case is most often needed to stop a recursion, however here you want to return an infinite list, so no need to stop it.
On the other hand, this function would break if you try to take more than 1 element of allCombination [] -- have a look at #robin's answer to understand better why. That is the only reason you see a base case here.
The way the main function works is that it starts with an empty list, and then append at the beginning each element in the argument list. (:w) does that recursively. However, this lambda alone would return an infinitely nested list. I.e: [],[[True],[False]],[[[True,True],[True,False] etc. Concatmap removes the outer list at each step, and as it is called recursively this only returns one list of lists at the end. This can be a complicated concept to grasp so look for other example of the use of concatMap and try to understand how they work and why map alone wouldn't be enough.
This obviously only works because of Haskell lazy evaluation. Similarly, you know in a foldr you need to pass it the base case, however when your function is supposed to only take infinite lists, you can have undefined as the base case to make it more clear that finite lists should not be used. For example, foldr f undefined could be used instead of foldr f []
#Lorenzo has already explained the key point - that the recursion in fact never ends, and therefore this generates an infinite list, which you can still take any finite number of elements from because of Haskell's laziness. But I think it will be helpful to give a bit more detail about this particular function and how it works.
Firstly, the [] : at the start of the definition tells you that the first element will always be []. That of course is the one and only way to make a 0-element list from elements of values. The rest of the list is concatMap (\w -> map (:w) values) (allCombinations values).
concatMap f is as you observe simply the composition concat . (map f): it applies the given function to every element of the list, and concatenates the results together. Here the function (\w -> map (:w) values) takes a list, and produces the list of lists given by prepending each element of values to that list. For example, if values == [1,2], then:
(\w -> map (:w) values) [1,2] == [[1,1,2], [2,1,2]]
if we map that function over a list of lists, such as
[[], [1], [2]]
then we get (still with values as [1,2]):
[[[1], [2]], [[1,1], [2,1]], [[1,2], [2,2]]]
That is of course a list of lists of lists - but then the concat part of concatMap comes to our rescue, flattening the outermost layer, and resulting in a list of lists as follows:
[[1], [2], [1,1], [2,1], [1,2], [2,2]]
One thing that I hope you might have noticed about this is that the list of lists I started with was not arbitrary. [[], [1], [2]] is the list of all combinations of size 0 or 1 from the starting list [1,2]. This is in fact the first three elements of allCombinations [1,2].
Recall that all we know "for sure" when looking at the definition is that the first element of this list will be []. And the rest of the list is concatMap (\w -> map (:w) [1,2]) (allCombinations [1,2]). The next step is to expand the recursive part of this as [] : concatMap (\w -> map (:w) [1,2]) (allCombinations [1,2]). The outer concatMap
then can see that the head of the list it's mapping over is [] - producing a list starting [1], [2] and continuing with the results of appending 1 and then 2 to the other elements - whatever they are. But we've just seen that the next 2 elements are in fact [1] and [2]. We end up with
allCombinations [1,2] == [] : [1] : [2] : concatMap (\w -> map (:w) values) [1,2] (tail (allCombinations [1,2]))
(tail isn't strictly called in the evaluation process, it's done by pattern-matching instead - I'm trying to explain more by words than explicit plodding through equalities).
And looking at that we know the tail is [1] : [2] : concatMap .... The key point is that, at each stage of the process, we know for sure what the first few elements of the list are - and they happen to be all 0-element lists with values taken from values, followed by all 1-element lists with these values, then all 2-element lists, and so on. Once you've got started, the process must continue, because the function passed to concatMap ensures that we just get the lists obtained from taking every list generated so far, and appending each element of values to the front of them.
If you're still confused by this, look up how to compute the Fibonacci numbers in Haskell. The classic way to get an infinite list of all Fibonacci numbers is:
fib = 1 : 1 : zipWith (+) fib (tail fib)
This is a bit easier to understand that the allCombinations example, but relies on essentially the same thing - defining a list purely in terms of itself, but using lazy evaluation to progressively generate as much of the list as you want, according to a simple rule.
It is not a base case but a special case, and this is not recursion but corecursion,(*) which never stops.
Maybe the following re-formulation will be easier to follow:
allCombs :: [t] -> [[t]]
-- [1,2] -> [[]] ++ [1:[],2:[]] ++ [1:[1],2:[1],1:[2],2:[2]] ++ ...
allCombs vals = concat . iterate (cons vals) $ [[]]
where
cons :: [t] -> [[t]] -> [[t]]
cons vals combs = concat [ [v : comb | v <- vals]
| comb <- combs ]
-- iterate :: (a -> a ) -> a -> [a]
-- cons vals :: [[t]] -> [[t]]
-- iterate (cons vals) :: [[t]] -> [[[t]]]
-- concat :: [[ a ]] -> [ a ]
-- concat . iterate (cons vals) :: [[t]]
Looks different, does the same thing. Not just produces the same results, but actually is doing the same thing to produce them.(*) The concat is the same concat, you just need to tilt your head a little to see it.
This also shows why the concat is needed here. Each step = cons vals is producing a new batch of combinations, with length increasing by 1 on each step application, and concat glues them all together into one list of results.
The length of each batch is the previous batch length multiplied by n where n is the length of vals. This also shows the need to special case the vals == [] case i.e. the n == 0 case: 0*x == 0 and so the length of each new batch is 0 and so an attempt to get one more value from the results would never produce a result, i.e. enter an infinite loop. The function is said to become non-productive, at that point.
Incidentally, cons is almost the same as
== concat [ [v : comb | comb <- combs]
| v <- vals ]
== liftA2 (:) vals combs
liftA2 :: Applicative f => (a -> b -> r) -> f a -> f b -> f r
So if the internal order of each step results is unimportant to you (but see an important caveat at the post bottom) this can just be coded as
allCombsA :: [t] -> [[t]]
-- [1,2] -> [[]] ++ [1:[],2:[]] ++ [1:[1],1:[2],2:[1],2:[2]] ++ ...
allCombsA [] = [[]]
allCombsA vals = concat . iterate (liftA2 (:) vals) $ [[]]
(*) well actually, this refers to a bit modified version of it,
allCombsRes vals = res
where res = [] : concatMap (\w -> map (: w) vals)
res
-- or:
allCombsRes vals = fix $ ([] :) . concatMap (\w -> map (: w) vals)
-- where
-- fix g = x where x = g x -- in Data.Function
Or in pseudocode:
Produce a sequence of values `res` by
FIRST producing `[]`, AND THEN
from each produced value `w` in `res`,
produce a batch of new values `[v : w | v <- vals]`
and splice them into the output sequence
(by using `concat`)
So the res list is produced corecursively, starting from its starting point, [], producing next elements of it based on previous one(s) -- either in batches, as in iterate-based version, or one-by-one as here, taking the input via a back pointer into the results previously produced (taking its output as its input, as a saying goes -- which is a bit deceptive of course, as we take it at a slower pace than we're producing it, or otherwise the process would stop being productive, as was already mentioned above).
But. Sometimes it can be advantageous to produce the input via recursive calls, creating at run time a sequence of functions, each passing its output up the chain, to its caller. Still, the dataflow is upwards, unlike regular recursion which first goes downward towards the base case.
The advantage just mentioned has to do with memory retention. The corecursive allCombsRes as if keeps a back-pointer into the sequence that it itself is producing, and so the sequence can not be garbage-collected on the fly.
But the chain of the stream-producers implicitly created by your original version at run time means each of them can be garbage-collected on the fly as n = length vals new elements are produced from each downstream element, so the overall process becomes equivalent to just k = ceiling $ logBase n i nested loops each with O(1) space state, to produce the ith element of the sequence.
This is much much better than the O(n) memory requirement of the corecursive/value-recursive allCombsRes which in effect keeps a back pointer into its output at the i/n position. And in practice a logarithmic space requirement is most likely to be seen as a more or less O(1) space requirement.
This advantage only happens with the order of generation as in your version, i.e. as in cons vals, not liftA2 (:) vals which has to go back to the start of its input sequence combs (for each new v in vals) which thus must be preserved, so we can safely say that the formulation in your question is rather ingenious.
And if we're after a pointfree re-formulation -- as pointfree can at times be illuminating -- it is
allCombsY values = _Y $ ([] :) . concatMap (\w -> map (: w) values)
where
_Y g = g (_Y g) -- no-sharing fixpoint combinator
So the code is much easier understood in a fix-using formulation, and then we just switch fix with the semantically equivalent _Y, for efficiency, getting the (equivalent of the) original code from the question.
The above claims about space requirements behavior are easily tested. I haven't done so, yet.
See also:
Why does GHC make fix so confounding?
Sharing vs. non-sharing fixed-point combinator
I want to generate all possible combinations of a 6 element list [x1,x2,x3,x4,x5,x6] with each xi being a number between 0 and 20.
I want to generate all possible combinations of such list, apply a function (takes the list as input and outputs a magical Int) to each list, then output the results to a list of tuples. So the list of tuples looks like
[([x11,x21,x31,x41,x51,x61],Int1), ([x12,x22,x32,x42,x52,x62],Int2), ...]
I tried to this by hand by quickly realised that there are too many combinations and it is practically impossible to do by hand.
The combinations are like [0,0,0,0,0,0], [1,7,0,10,11,6], [7,7,7,7,6,6], [20,20,20,20,20,20] and so on.
I know how to generate all combinations of a list and put them in a list of lists (because I asked this before)
foo [] = [[]]
foo (x:xs) = foo xs ++ map (x:) (foo xs)
What I want to achieve this time is different because I am not trying to generate the different combinations within a particular list, I am trying to generate all 6 element lists.
As far as I can tell, you want a cartesian product (denoted by × here) of 6 lists [0..20].
So essentially, something like this:
[0..20]×[0..20]×[0..20]×[0..20]×[0..20]×[0..20]
That's a lot of elements (85,766,121 to be exact). But, it could be done.
Perhaps an easier to understand version is as follows.
Let us define a function, cart, that would do something like a cartesian product over a list and a list of lists:
let cart xs ls = [x:l | x <- xs, l <- ls]
This function will take all elements from xs, and all elements from ls and build a list of lists with all possible concatenations.
Now, we need a base case. Suppose you wanted a list of lists of a single element instead of six. How would you apply our cart function? Well, since it adds each element from first argument to every element in second argument, we can pass a list of a single empty list as a second argument, and [0..20] as first argument:
cart [0..20] [[]]
We get
[[0],[1],[2],[3],[4],[5],[6],[7],[8],[9],[10],[11],[12],[13],[14],[15],[16],[17],[18],[19],[20]]
Great. Now we just apply it 6 times to its own result, starting with [[]]:
foldr ($) [[]] $ replicate 6 (cart [0..20])
($) is function application.
replicateM from Control.Monad (defined as sequence of n monadic actions: replicateM n x = sequence (replicate n x)) basically does the same when applied to lists (see e.g. Why does application of `sequence` on List of Lists lead to computation of its Cartesian Product? for why exactly that is) So shorter answer would be like this:
replicateM 6 [0..20]
You can map over those after this, e.g.
map (\x -> (x, magicFunction x)) $ replicateM 6 [0..20]
foo f xs = map (\ys -> (ys,f ys)) (replicateM (length xs) xs)
Here replicateM (length xs) xs will generate all combinations of the elements in xs. Then you just map over it.
Results in GHCI:
>import Control.Monad
>let foo f xs = map (\ys -> (ys,f ys)) (replicateM (length xs) xs)
>foo sum [1,2]
[([1,1],2),([1,2],3),([2,1],3),([2,2],4)]
Is there a straight-forward combination of standard higher-order functions to count the unique elements in a list?
For example the result for
[1, 1, 4, 0, 4, 4]
would be something like
[(1,2), (4,3), (0,1)]
Using Data.Map and tuple sections:
count = Map.fromListWith (+) . map (, 1)
(Add Map.toList if you need a list.)
If order is not important this works:
map (\xs#(x:_) -> (x, length xs)) . group . sort
group . sort will give you a list of lists where all elements that are equal to each other are grouped into the same sublist (without sort, only consecutive equal elements would be grouped together). The map then turns each sublist into a (element, lengthOfSublist)-tuple.
If you want to order the result by first occurrence, you can use zip before the sort to add an index to each element, then, after grouping, sort again by that index and then remove the index.
The simplest thing would be to sort the items into order, use "group" to put them into sub-lists of equal elements, and then count the items in each sub-list.
map (\xs -> (head xs, length xs)) . group . sort
If the list contains only integers, you could also use
import qualified Data.IntMap as I
countElems1 :: [Int] -> [(Int, Int)]
countElems1 = I.toList . foldr (\k -> I.insertWith (+) k 1) I.empty
(Remember to compile with optimization though, otherwise this will be 2x slower than the group . sort method. With -O2 it is slightly faster by 14%.)
You could also use one of the multiset packages which makes the function as simple as
import qualified Math.Combinatorics.Multiset as S
countElems4 = S.toCounts . S.fromList
but being less efficient.
All of the above solutions ignore the original order.
What your talking about is just run length encoding on sorted data: the free online book Real World Haskell has a great example of this. You will want to sort the list before you put it through the runLengthEncoder.