I want to create a list of variations of applying a function to every element of a list. Here is a quick example of what I mean.
applyVar f [a, b, c]
>> [[(f a), b, c], [a, (f b), c], [a, b, (f c)]]
Essentially It applies a function to each element of a list individually and stores each possible application in an array.
I'm not too sure how to approach a problem like this without using indexes as I have heard they are not very efficient. This is assuming that the function f returns the same type as the input list.
Is there a pre-existing function to get this behavior? If not what would that function be?
To see if there's a pre-existing function, first figure out its type. In this case, it's (a -> a) -> [a] -> [[a]]. Searching for that type on Hoogle only returns a handful of matches, and by inspection, none of them do what you want.
To write it yourself, note that it operates on a list, and the best way to figure out how to write a function on a list is to define it inductively. This means you need to build two cases: one for an empty list, and one for a non-empty list that assumes you already know the answer for its tail:
applyVar f [] = _
applyVar f (x:xs) = _ -- use `applyVar f xs` somehow
Now we just need to fill in the two blanks. For the nil case, it's easy. For the cons case, note that the first sublist starts with f a, and the rest will all start with a. Then, note that the tails of the rest look an awful lot like the answer for the tail. From there, the pattern should become clear.
applyVar f [] = []
applyVar f (x:xs) = (f x:xs):map (x:) (applyVar f xs)
And here's a quick demo/test of it:
Prelude> applyVar (+10) [1,2,3]
[[11,2,3],[1,12,3],[1,2,13]]
Note that, as is often the case, lens contains some tools that provide this as a special case of some far more abstract tooling.
$ cabal repl -b lens,adjunctions
Resolving dependencies...
GHCi, version 8.10.3: https://www.haskell.org/ghc/ :? for help
> import Control.Lens
> import Control.Comonad.Representable.Store
> let updateEach f = map (peeks f) . holesOf traverse
> :t updateEach
updateEach :: Traversable t => (s -> s) -> t s -> [t s]
> updateEach negate [1..3]
[[-1,2,3],[1,-2,3],[1,2,-3]]
> import qualified Data.Map as M
> updateEach (*3) (M.fromList [('a', 1), ('b', 2), ('c', 4)])
[fromList [('a',3),('b',2),('c',4)],fromList [('a',1),('b',6),('c',4)],fromList [('a',1),('b',2),('c',12)]]
This is honestly way overkill, unless you start needing some of the ways lens gets more compositional, like so:
> let updateEachOf l f = map (peeks f) . holesOf l
> updateEachOf (traverse . filtered even) negate [1..5]
[[1,-2,3,4,5],[1,2,3,-4,5]]
> updateEachOf (traverse . ix 2) negate [[1,2],[3,4,5],[6,7,8,9],[10]]
[[[1,2],[3,4,-5],[6,7,8,9],[10]],[[1,2],[3,4,5],[6,7,-8,9],[10]]]
But whether you ever end up needing it or not, it's cool to know that the tools exist.
Yes. Two functions, inits and tails:
foo :: (a -> a) -> [a] -> [[a]]
foo f xs = [ a ++ [f x] ++ b | a <- inits xs
| (x:b) <- tails xs]
(with ParallelListComp extension; equivalent to using zip over two applications of the two functions, to the same input argument, xs, in the regular list comprehension).
Trying it out:
> foo (100+) [1..5]
[[101,2,3,4,5],[1,102,3,4,5],[1,2,103,4,5],[1,2,3,104,5],[1,2,3,4,105]]
Related
Say for example that I have a list like this
list = ["AC", "BA"]
I would like to add every unique combination of this list to a tuple so the result is like this:
[("AC", "AC"),("AC","BA"),("BA", "BA")]
where ("BA","AC") is excluded.
My first approach was to use a list comprehension like this:
ya = [(x,y) | x <- list, y <- list]
But I couldn't manage to get it to work, is there anyway to achieve my result by using list comprehensions?
My preferred solution uses a list comprehension
f :: [t] -> [(t, t)]
f list = [ (a,b) | theTail#(a:_) <- tails list , b <- theTail ]
I find this to be quite readable: first you choose (non-deterministically) a suffix theTail, starting with a, and then you choose (non-deterministically) an element b of the suffix. Finally, the pair (a,b) is produced, which clearly ranges over the wanted pairs.
It should also be optimally efficient: every time you demand an element from it, that is produced in constant time.
ThreeFx's answer will work, but it adds the constraint that you elements must be orderable. Instead, you can get away with functions in Prelude and Data.List to implement this more efficiently and more generically:
import Data.List (tails)
permutations2 :: [a] -> [(a, a)]
permutations2 list
= concat
$ zipWith (zip . repeat) list
$ tails list
It doesn't use list comprehensions, but it works without having to perform potentially expensive comparisons and without any constraints on what kind of values you can put through it.
To see how this works, consider that if you had the list [1, 2, 3], you'd have the groups
[(1, 1), (1, 2), (1, 3),
(2, 2), (2, 3),
(3, 3)]
This is equivalent to
[(1, [1, 2, 3]),
(2, [2, 3]),
(3, [3])]
since it doesn't contain any extra or any less information. The transformation from this form to our desired output is to map the function f (x, ys) = map (\y -> (x, y)) ys over each tuple, then concat them together. Now we just need to figure out how to get the second element of those tuples. Quite clearly, we see that all its doing is dropping successive elements off the front of the list. Luckily, this is already implemented for us by the tails function in Data.List. The first element in each of these tuples is just makes up the original list, so we know we can use a zip. Initially, you could implement this with
> concatMap (\(x, ys) -> map (\y -> (x, y)) ys) $ zip list $ tails list
But I personally prefer zips, so I'd turn the inner function into one that doesn't use lambdas more than necessary:
> concatMap (\(x, ys) -> zip (repeat x) ys) $ zip list $ tails list
And since I prefer zipWith f over map (uncurry f) . zip, I'd turn this into
> concat $ zipWith (\x ys -> zip (repeat x) ys) list $ tails list
Now, we can reduce this further:
> concat $ zipWith (\x -> zip (repeat x)) list $ tails list
> concat $ zipWith (zip . repeat) list $ tails list
thanks the eta-reduction and function composition. We could make this entirely pointfree where
> permutations2 = concat . ap (zipWith (zip . repeat)) tails
But I find this pretty hard to read and understand, so I think I'll stick with the previous version.
Just use a list comprehension:
f :: (Ord a) => [a] -> [(a, a)]
f list = [ (a, b) | a <- list, b <- list, a <= b ]
Since Haskell's String is in the Ord typeclass, which means it can be ordered, you first tell Haskell to get all possible combinations and then exclude every combination where b is greater than a which removes all "duplicate" combinations.
Example output:
> f [1,2,3,4]
[(1,1),(1,2),(1,3),(1,4),(2,2),(2,3),(2,4),(3,3),(3,4),(4,4)]
I'm trying to write a function that given a list of numbers, returns a list where every 2nd number is doubled in value, starting from the last element. So if the list elements are 1..n, n-th is going to be left as-is, (n-1)-th is going to be doubled in value, (n-2)-th is going to be left as-is, etc.
So here's how I solved it:
MyFunc :: [Integer] -> [Integer]
MyFunc xs = reverse (MyFuncHelper (reverse xs))
MyFuncHelper :: [Integer] -> [Integer]
MyFuncHelper [] = []
MyFuncHelper (x:[]) = [x]
MyFuncHelper (x:y:zs) = [x,y*2] ++ MyFuncHelper zs
And it works:
MyFunc [1,1,1,1] = [2,1,2,1]
MyFunc [1,1,1] = [1,2,1]
However, I can't help but think there has to be a simpler solution than reversing the list, processing it and then reversing it again. Could I simply iterate the list backwards? If yes, how?
The under reversed f xs idiom from the lens library will apply f to xs in reverse order:
under reversed (take 5) [1..100] => [96,97,98,99,100]
When you need to process the list from the end, usually foldr works pretty well. Here is a solution for you without reversing the whole list twice:
doubleOdd :: Num a => [a] -> [a]
doubleOdd = fst . foldr multiplyCond ([], False)
where multiplyCond x (rest, flag) = ((if flag then (x * 2) else x) : rest, not flag)
The multiplyCond function takes a tuple with a flag and the accumulator list. The flag constantly toggles on and off to track whether we should multiply the element or not. The accumulator list simply gathers the resulting numbers. This solution may be not so concise, but avoids extra work and doesn't use anything but prelude functions.
myFunc = reverse
. map (\(b,x) -> if b then x*2 else x)
. zip (cycle [False,True])
. reverse
But this isn't much better. Your implementation is sufficiently elegant.
The simplest way to iterate the list backwards is to reverse the list. I don't think you can really do much better than that; I suspect that if you have to traverse the whole list to find the end, and remember how to get back up, you might as well just reverse it. If this is a big deal, maybe you should be using some other data structure instead of lists—Vector or Seq might be good choices.
Another way to write your helper function is to use Traversable:
import Control.Monad.State
import Data.Traversable (Traversable, traverse)
toggle :: (Bool -> a -> b) -> a -> State Bool b
toggle f a =
do active <- get
put (not active)
return (f active a)
doubleEvens :: (Num a, Traversable t) => t a -> t a
doubleEvens xs = evalState (traverse (toggle step) xs) False
where step True x = 2*x
step False x = x
yourFunc :: Num a => [a] -> [a]
yourFunc = reverse . doubleEvens
Or if we go a bit crazy with Foldable and Traversable, we can try this:
Use Foldable's foldl to extract a reverse-order list from any of its instances. For some types this will be more efficient than reversing a list.
Then we can use traverse and State to map each element of the original structure to its counterpart in the reversed order.
Here's how to do it:
import Control.Monad.State
import Data.Foldable (Foldable)
import qualified Data.Foldable as F
import Data.Traversable (Traversable, traverse)
import Data.Map (Map)
import qualified Data.Map as Map
toReversedList :: Foldable t => t a -> [a]
toReversedList = F.foldl (flip (:)) []
reverse' :: Traversable t => t a -> t a
reverse' ta = evalState (traverse step ta) (toReversedList ta)
where step _ = do (h:t) <- get
put t
return h
yourFunc' :: (Traversable t, Num a) => t a -> t a
yourFunc' = reverse' . doubleEvens
-- >>> yourFunc' $ Map.fromList [(1, 1), (2, 1), (3, 1), (4, 1)]
-- fromList [(1,2),(2,1),(3,2),(4,1)]
-- >>> yourFunc' $ Map.fromList [(1, 1), (2, 1), (3, 1)]
-- fromList [(1,1),(2,2),(3,1)]
There's probably a better way to do this, though...
func xs = zipWith (*) xs $ reverse . (take $ length xs) $ cycle [1,2]
Say I have any list like this:
[4,5,6,7,1,2,3,4,5,6,1,2]
I need a Haskell function that will transform this list into a list of lists which are composed of the segments of the original list which form a series in ascending order. So the result should look like this:
[[4,5,6,7],[1,2,3,4,5,6],[1,2]]
Any suggestions?
You can do this by resorting to manual recursion, but I like to believe Haskell is a more evolved language. Let's see if we can develop a solution that uses existing recursion strategies. First some preliminaries.
{-# LANGUAGE NoMonomorphismRestriction #-}
-- because who wants to write type signatures, amirite?
import Data.List.Split -- from package split on Hackage
Step one is to observe that we want to split the list based on a criteria that looks at two elements of the list at once. So we'll need a new list with elements representing a "previous" and "next" value. There's a very standard trick for this:
previousAndNext xs = zip xs (drop 1 xs)
However, for our purposes, this won't quite work: this function always outputs a list that's shorter than the input, and we will always want a list of the same length as the input (and in particular we want some output even when the input is a list of length one). So we'll modify the standard trick just a bit with a "null terminator".
pan xs = zip xs (map Just (drop 1 xs) ++ [Nothing])
Now we're going to look through this list for places where the previous element is bigger than the next element (or the next element doesn't exist). Let's write a predicate that does that check.
bigger (x, y) = maybe False (x >) y
Now let's write the function that actually does the split. Our "delimiters" will be values that satisfy bigger; and we never want to throw them away, so let's keep them.
ascendingTuples = split . keepDelimsR $ whenElt bigger
The final step is just to throw together the bit that constructs the tuples, the bit that splits the tuples, and a last bit of munging to throw away the bits of the tuples we don't care about:
ascending = map (map fst) . ascendingTuples . pan
Let's try it out in ghci:
*Main> ascending [4,5,6,7,1,2,3,4,5,6,1,2]
[[4,5,6,7],[1,2,3,4,5,6],[1,2]]
*Main> ascending [7,6..1]
[[7],[6],[5],[4],[3],[2],[1]]
*Main> ascending []
[[]]
*Main> ascending [1]
[[1]]
P.S. In the current release of split, keepDelimsR is slightly stricter than it needs to be, and as a result ascending currently doesn't work with infinite lists. I've submitted a patch that makes it lazier, though.
ascend :: Ord a => [a] -> [[a]]
ascend xs = foldr f [] xs
where
f a [] = [[a]]
f a xs'#(y:ys) | a < head y = (a:y):ys
| otherwise = [a]:xs'
In ghci
*Main> ascend [4,5,6,7,1,2,3,4,5,6,1,2]
[[4,5,6,7],[1,2,3,4,5,6],[1,2]]
This problem is a natural fit for a paramorphism-based solution. Having (as defined in that post)
para :: (a -> [a] -> b -> b) -> b -> [a] -> b
foldr :: (a -> b -> b) -> b -> [a] -> b
para c n (x : xs) = c x xs (para c n xs)
foldr c n (x : xs) = c x (foldr c n xs)
para c n [] = n
foldr c n [] = n
we can write
partition_asc xs = para c [] xs where
c x (y:_) ~(a:b) | x<y = (x:a):b
c x _ r = [x]:r
Trivial, since the abstraction fits.
BTW they have two kinds of map in Common Lisp - mapcar
(processing elements of an input list one by one)
and maplist (processing "tails" of a list). With this idea we get
import Data.List (tails)
partition_asc2 xs = foldr c [] . init . tails $ xs where
c (x:y:_) ~(a:b) | x<y = (x:a):b
c (x:_) r = [x]:r
Lazy patterns in both versions make it work with infinite input lists
in a productive manner (as first shown in Daniel Fischer's answer).
update 2020-05-08: not so trivial after all. Both head . head . partition_asc $ [4] ++ undefined and the same for partition_asc2 fail with *** Exception: Prelude.undefined. The combining function g forces the next element y prematurely. It needs to be more carefully written to be productive right away before ever looking at the next element, as e.g. for the second version,
partition_asc2' xs = foldr c [] . init . tails $ xs where
c (x:ys) r#(~(a:b)) = (x:g):gs
where
(g,gs) | not (null ys)
&& x < head ys = (a,b)
| otherwise = ([],r)
(again, as first shown in Daniel's answer).
You can use a right fold to break up the list at down-steps:
foldr foo [] xs
where
foo x yss = (x:zs) : ws
where
(zs, ws) = case yss of
(ys#(y:_)) : rest
| x < y -> (ys,rest)
| otherwise -> ([],yss)
_ -> ([],[])
(It's a bit complicated in order to have the combining function lazy in the second argument, so that it works well for infinite lists too.)
One other way of approaching this task (which, in fact lays the fundamentals of a very efficient sorting algorithm) is using the Continuation Passing Style a.k.a CPS which, in this particular case applied to folding from right; foldr.
As is, this answer would only chunk up the ascending chunks however, it would be nice to chunk up the descending ones at the same time... preferably in reverse order all in O(n) which would leave us with only binary merging of the obtained chunks for a perfectly sorted output. Yet that's another answer for another question.
chunks :: Ord a => [a] -> [[a]]
chunks xs = foldr go return xs $ []
where
go :: Ord a => a -> ([a] -> [[a]]) -> ([a] -> [[a]])
go c f = \ps -> let (r:rs) = f [c]
in case ps of
[] -> r:rs
[p] -> if c > p then (p:r):rs else [p]:(r:rs)
*Main> chunks [4,5,6,7,1,2,3,4,5,6,1,2]
[[4,5,6,7],[1,2,3,4,5,6],[1,2]]
*Main> chunks [4,5,6,7,1,2,3,4,5,4,3,2,6,1,2]
[[4,5,6,7],[1,2,3,4,5],[4],[3],[2,6],[1,2]]
In the above code c stands for current and p is for previous and again, remember we are folding from right so previous, is actually the next item to process.
I have a chained list like
["root", "foo", "bar", "blah"]
And I'd like to convert it to a list of tuples, using adjacent pairs. Like so
[("root", "foo"), ("foo", "bar"), ("bar", "blah")]
At the moment, I'm using this to do it:
zipAdj x = tail (zip ("":x) (x++[""]))
However, I don't really like this method. Can anyone think of a better way? If it's glaringly obvious I apologise, I'm fairly new to Haskell.
Okay, here's the comment as an answer:
Just zipAdj x = zip x $ tail x will suffice. zip stops upon reaching the end of the shorter of the two lists, so this simply pairs each item in the list with its successor, which seems to be all you want.
And for the sake of explaining the pointless version: zip <*> tail uses the Applicative instance for "functions from some type", which basically amounts to a lightweight inline Reader monad--in this case the list is the "environment" for the Reader. Usually this just obfuscates matters but in this case it almost makes it clearer, assuming you know to read (<*>) here as "apply both of these to a single argument, then apply the first to the second".
One possible solution:
pairs [] = []
pairs (x:[]) = []
pairs (x:y:zs) = (x, y) : pairs (y : zs)
Definitely not as small as yours, and can probably be optimized quite a bit.
It's possible to generalize the zipAdj in the question to work with arbitrary Traversable containers. Here's how we'd do it if we wanted the extra element on the front end:
import Data.Traversable
pairDown :: Traversable t => a -> t a -> t (a, a)
pairDown x = snd . mapAccumL (\old new -> (new, (old,new))) x
*Pairing> take 10 $ pairDown 0 [1..]
[(0,1),(1,2),(2,3),(3,4),(4,5),(5,6),(6,7),(7,8),(8,9),(9,10)]
*Pairing> pairDown 0 [1..10]
[(0,1),(1,2),(2,3),(3,4),(4,5),(5,6),(6,7),(7,8),(8,9),(9,10)]
To stick the extra element on the end, we can use mapAccumR:
import Data.Traversable
pairUp :: Traversable t => t a -> a -> t (a, a)
pairUp xs x = snd $ mapAccumR (\old new -> (new, (new,old))) x xs
This effectively traverses the container backwards.
*Pairing> pairUp [0..10] 11
[(0,1),(1,2),(2,3),(3,4),(4,5),(5,6),(6,7),(7,8),(8,9),(9,10),(10,11)]
*Pairing> take 10 $ pairUp [0..] undefined
[(0,1),(1,2),(2,3),(3,4),(4,5),(5,6),(6,7),(7,8),(8,9),(9,10)]
It's impossible to generalize the apparently-desired function in quite this fashion, but it's possible to generalize it a bit differently:
import Data.Foldable
import Prelude hiding (foldr)
pairAcross :: Foldable f => f a -> [(a,a)]
pairAcross xs = foldr go (const []) xs Nothing
where
go next r Nothing = r (Just next)
go next r (Just prev) = (prev, next) : r (Just next)
This gives
*Pairing> pairAcross [1..10]
[(1,2),(2,3),(3,4),(4,5),(5,6),(6,7),(7,8),(8,9),(9,10)]
Creating the permutations of a list or set is simple enough. I need to apply a function to each element of all subsets of all elements in a list, in the order in which they occur. For instance:
apply f [x,y] = { [x,y], [f x, y], [x, f y], [f x, f y] }
The code I have is a monstrous pipeline or expensive computations, and I'm not sure how to proceed, or if it's correct. I'm sure there must be a better way to accomplish this task - perhaps in the list monad - but I'm not sure. This is my code:
apply :: Ord a => (a -> Maybe a) -> [a] -> Set [a]
apply p xs = let box = take (length xs + 1) . map (take $ length xs) in
(Set.fromList . map (catMaybes . zipWith (flip ($)) xs) . concatMap permutations
. box . map (flip (++) (repeat Just)) . flip iterate []) ((:) p)
The general idea was:
(1) make the list
[[], [f], [f,f], [f,f,f], ... ]
(2) map (++ repeat Just) over the list to obtain
[[Just, Just, Just, Just, ... ],
[f , Just, Just, Just, ... ],
[f , f , Just, Just, ... ],
... ]
(3) find all permutations of each list in (2) shaved to the length of the input list
(4) apply the permuted lists to the original list, garnering all possible applications
of the function f to each (possibly empty) subset of the original list, preserving
the original order.
I'm sure there's a better way to do it, though. I just don't know it. This way is expensive, messy, and rather prone to error. The Justs are there because of the intended application.
To do this, you can leverage the fact that lists represent non-deterministic values when using applicatives and monads. It then becomes as simple as:
apply f = mapM (\x -> [x, f x])
It basically reads as follows: "Map each item in a list to itself and the result of applying f to it. Finally, return a list of all the possible combinations of these two values across the whole list."
If I understand your problem correctly, it's best not to describe it in terms of permutations. Rather, it's closer to generating powersets.
powerset (x:xs) = let pxs = powerset xs in pxs ++ map (x :) pxs
powerset [] = [[]]
Each time you add another member to the head of the list, the powerset doubles in size. The second half of the powerset is exactly like the first, but with x included.
For your problem, the choice is not whether to include or exclude x, but whether to apply or not apply f.
powersetapp f (x:xs) = let pxs = powersetapp f xs in map (x:) pxs ++ map (f x:) pxs
powersetapp f [] = [[]]
This does what your "apply" function does, modulo making a Set out of the result.
Paul's and Heatsink's answers are good, but error out when you try to run them on infinite lists.
Here's a different method that works on both infinite and finite lists:
apply _ [] = [ [] ]
apply f (x:xs) = (x:ys):(x':ys):(double yss)
where x' = f x
(ys:yss) = apply f xs
double [] = []
double (ys:yss) = (x:ys):(x':ys):(double yss)
This works as expected - though you'll note it produces a different order to the permutations than Paul's and Heatsink's
ghci> -- on an infinite list
ghci> map (take 4) $ take 16 $ apply (+1) [0,0..]
[[0,0,0,0],[1,0,0,0],[0,1,0,0],[1,1,0,0],[0,0,1,0],...,[1,1,1,1]]
ghci> -- on a finite list
ghci> apply (+1) [0,0,0,0]
[[0,0,0,0],[1,0,0,0],[0,1,0,0],[1,1,0,0],[0,0,1,0],...,[1,1,1,1]]
Here is an alternative phrasing of rampion's infinite-input-handling solution:
-- sequence a list of nonempty lists
sequenceList :: [[a]] -> [[a]]
sequenceList [] = [[]]
sequenceList (m:ms) = do
xs <- nonempty (sequenceList ms)
x <- nonempty m
return (x:xs)
where
nonempty ~(x:xs) = x:xs
Then we can define apply in Paul's idiomatic style:
apply f = sequenceList . map (\x -> [x, f x])
Contrast sequenceList with the usual definition of sequence:
sequence :: (Monad m) => [m a] -> m [a]
sequence [] = [[]]
sequence (m:ms) = do
x <- m
xs <- sequence ms
return (x:xs)
The order of binding is reversed in sequenceList so that the variations of the first element are the "inner loop", i.e. we vary the head faster than the tail. Varying the end of an infinite list is a waste of time.
The other key change is nonempty, the promise that we won't bind an empty list. If any of the inputs were empty, or if the result of the recursive call to sequenceList were ever empty, then we would be forced to return an empty list. We can't tell in advance whether any of inputs is empty (because there are infinitely many of them to check), so the only way for this function to output anything at all is to promise that they won't be.
Anyway, this is fun subtle stuff. Don't stress about it on your first day :-)