I have to split the given list into non-empty sub-lists each of which
is either in strictly ascending order, in strictly descending order, or contains all equal elements. For example, [5,6,7,2,1,1,1] should become [[5,6,7],[2,1],[1,1]].
Here is what I have done so far:
splitSort :: Ord a => [a] -> [[a]]
splitSort ns = foldr k [] ns
where
k a [] = [[a]]
k a ns'#(y:ys) | a <= head y = (a:y):ys
| otherwise = [a]:ns'
I think I am quite close but when I use it it outputs [[5,6,7],[2],[1,1,1]] instead of [[5,6,7],[2,1],[1,1]].
Here is a kinda ugly solution, with three reverse in one line of code :).
addElement :: Ord a => a -> [[a]] -> [[a]]
addElement a [] = [[a]]
addElement a (x:xss) = case x of
(x1:x2:xs)
| any (check a x1 x2) [(==),(<),(>)] -> (a:x1:x2:xs):xss
| otherwise -> [a]:(x:xss)
_ -> (a:x):xss
where
check x1 x2 x3 op = (x1 `op` x2) && (x2 `op` x3)
splitSort xs = reverse $ map reverse $ foldr addElement [] (reverse xs)
You can possibly get rid of all the reversing if you modify addElement a bit.
EDIT:
Here is a less reversing version (even works for infinite lists):
splitSort2 [] = []
splitSort2 [x] = [[x]]
splitSort2 (x:y:xys) = (x:y:map snd here):splitSort2 (map snd later)
where
(here,later) = span ((==c) . uncurry compare) (zip (y:xys) xys)
c = compare x y
EDIT 2:
Finally, here is a solution based on a single decorating/undecorating, that avoids comparing any two values more than once and is probably a lot more efficient.
splitSort xs = go (decorate xs) where
decorate :: Ord a => [a] -> [(Ordering,a)]
decorate xs = zipWith (\x y -> (compare x y,y)) (undefined:xs) xs
go :: [(Ordering,a)] -> [[a]]
go ((_,x):(c,y):xys) = let (here, later) = span ((==c) . fst) xys in
(x : y : map snd here) : go later
go xs = map (return . snd) xs -- Deal with both base cases
Every ordered prefix is already in some order, and you don't care in which, as long as it is the longest:
import Data.List (group, unfoldr)
foo :: Ord t => [t] -> [[t]]
foo = unfoldr f
where
f [] = Nothing
f [x] = Just ([x], [])
f xs = Just $ splitAt (length g + 1) xs
where
(g : _) = group $ zipWith compare xs (tail xs)
length can be fused in to make the splitAt count in unary essentially, and thus not be as strict (unnecessarily, as Jonas Duregård rightly commented):
....
f xs = Just $ foldr c z g xs
where
(g : _) = group $ zipWith compare xs (tail xs)
c _ r (x:xs) = let { (a,b) = r xs } in (x:a, b)
z (x:xs) = ([x], xs)
The initial try turned out to be lengthy probably inefficient but i will keep it striked for the sake of integrity with the comments. You best just skip to the end for the answer.
Nice question... but turns out to be a little hard candy. My approach is in segments, those of each i will explain;
import Data.List (groupBy)
splitSort :: Ord a => [a] -> [[a]]
splitSort (x:xs) = (:) <$> (x :) . head <*> tail $ interim
where
pattern = zipWith compare <$> init <*> tail
tuples = zipWith (,) <$> tail <*> pattern
groups = groupBy (\p c -> snd p == snd c) . tuples $ (x:xs)
interim = groups >>= return . map fst
*Main> splitSort [5,6,7,2,1,1,1]
[[5,6,7],[2,1],[1,1]]
The pattern function (zipWith compare <$> init <*> tail) is of type Ord a => [a] -> [Ordering] when fed with [5,6,7,2,1,1,1] compares the init of it by the tail of it by zipWith. So the result would be [LT,LT,GT,GT,EQ,EQ]. This is the pattern we need.
The tuples function will take the tail of our list and will tuple up it's elements with the corresponding elements from the result of pattern. So we will end up with something like [(6,LT),(7,LT),(2,GT),(1,GT),(1,EQ),(1,EQ)].
The groups function utilizes Data.List.groupBy over the second items of the tuples and generates the required sublists such as [[(6,LT),(7,LT)],[(2,GT),(1,GT)],[(1,EQ),(1,EQ)]]
Interim is where we monadically get rid of the Ordering type values and tuples. The result of interim is [[6,7],[2,1],[1,1]].
Finally at the main function body (:) <$> (x :) . head <*> tail $ interim appends the first item of our list (x) to the sublist at head (it has to be there whatever the case) and gloriously present the solution.
Edit: So investigating the [0,1,0,1] resulting [[0,1],[0],[1]] problem that #Jonas Duregård discovered, we can conclude that in the result there shall be no sub lists with a length of 1 except for the last one when singled out. I mean for an input like [0,1,0,1,0,1,0] the above code produces [[0,1],[0],[1],[0],[1],[0]] while it should [[0,1],[0,1],[0,1],[0]]. So I believe adding a squeeze function at the very last stage should correct the logic.
import Data.List (groupBy)
splitSort :: Ord a => [a] -> [[a]]
splitSort [] = []
splitSort [x] = [[x]]
splitSort (x:xs) = squeeze $ (:) <$> (x :) . head <*> tail $ interim
where
pattern = zipWith compare <$> init <*> tail
tuples = zipWith (,) <$> tail <*> pattern
groups = groupBy (\p c -> snd p == snd c) $ tuples (x:xs)
interim = groups >>= return . map fst
squeeze [] = []
squeeze [y] = [y]
squeeze ([n]:[m]:ys) = [n,m] : squeeze ys
squeeze ([n]:(m1:m2:ms):ys) | compare n m1 == compare m1 m2 = (n:m1:m2:ms) : squeeze ys
| otherwise = [n] : (m1:m2:ms) : squeeze ys
squeeze (y:ys) = y : squeeze s
*Main> splitSort [0,1, 0, 1, 0, 1, 0]
[[0,1],[0,1],[0,1],[0]]
*Main> splitSort [5,6,7,2,1,1,1]
[[5,6,7],[2,1],[1,1]]
*Main> splitSort [0,0,1,0,-1]
[[0,0],[1,0,-1]]
Yes; as you will also agree the code has turned out to be a little too lengthy and possibly not so efficient.
The Answer: I have to trust the back of my head when it keeps telling me i am not on the right track. Sometimes, like in this case, the problem reduces down to a single if then else instruction, much simpler than i had initially anticipated.
runner :: Ord a => Maybe Ordering -> [a] -> [[a]]
runner _ [] = []
runner _ [p] = [[p]]
runner mo (p:q:rs) = let mo' = Just (compare p q)
(s:ss) = runner mo' (q:rs)
in if mo == mo' || mo == Nothing then (p:s):ss
else [p] : runner Nothing (q:rs)
splitSort :: Ord a => [a] -> [[a]]
splitSort = runner Nothing
My test cases
*Main> splitSort [0,1, 0, 1, 0, 1, 0]
[[0,1],[0,1],[0,1],[0]]
*Main> splitSort [5,6,7,2,1,1,1]
[[5,6,7],[2,1],[1,1]]
*Main> splitSort [0,0,1,0,-1]
[[0,0],[1,0,-1]]
*Main> splitSort [1,2,3,5,2,0,0,0,-1,-1,0]
[[1,2,3,5],[2,0],[0,0],[-1,-1],[0]]
For this solution I am making the assumption that you want the "longest rally". By that I mean:
splitSort [0, 1, 0, 1] = [[0,1], [0,1]] -- This is OK
splitSort [0, 1, 0, 1] = [[0,1], [0], [1]] -- This is not OK despite of fitting your requirements
Essentially, There are two pieces:
Firstly, split the list in two parts: (a, b). Part a is the longest rally considering the order of the two first elements. Part b is the rest of the list.
Secondly, apply splitSort on b and put all list into one list of list
Taking the longest rally is surprisingly messy but straight. Given the list x:y:xs: by construction x and y will belong to the rally. The elements in xs belonging to the rally depends on whether or not they follow the Ordering of x and y. To check this point, you zip every element with the Ordering is has compared against its previous element and split the list when the Ordering changes. (edge cases are pattern matched) In code:
import Data.List
import Data.Function
-- This function split the list in two (Longest Rally, Rest of the list)
splitSort' :: Ord a => [a] -> ([a], [a])
splitSort' [] = ([], [])
splitSort' (x:[]) = ([x],[])
splitSort' l#(x:y:xs) = case span ( (o ==) . snd) $ zip (y:xs) relativeOrder of
(f, s) -> (x:map fst f, map fst s)
where relativeOrder = zipWith compare (y:xs) l
o = compare y x
-- This applies the previous recursively
splitSort :: Ord a => [a] -> [[a]]
splitSort [] = []
splitSort (x:[]) = [[x]]
splitSort (x:y:[]) = [[x,y]]
splitSort l#(x:y:xs) = fst sl:splitSort (snd sl)
where sl = splitSort' l
I wonder whether this question can be solve using foldr if splits and groups a list from
[5,6,7,2,1,1,1]
to
[[5,6,7],[2,1],[1,1]]
instead of
[[5,6,7],[2],[1,1,1]]
The problem is in each step of foldr, we only know the sorted sub-list on right-hand side and a number to be processed. e.g. after read [1,1] of [5,6,7,2,1,1,1] and next step, we have
1, [[1, 1]]
There are no enough information to determine whether make a new group of 1 or group 1 to [[1,1]]
And therefore, we may construct required sorted sub-lists by reading elements of list from left to right, and why foldl to be used. Here is a solution without optimization of speed.
EDIT:
As the problems that #Jonas Duregård pointed out on comment, some redundant code has been removed, and beware that it is not a efficient solution.
splitSort::Ord a=>[a]->[[a]]
splitSort numList = foldl step [] numList
where step [] n = [[n]]
step sublists n = groupSublist (init sublists) (last sublists) n
groupSublist sublists [n1] n2 = sublists ++ [[n1, n2]]
groupSublist sublists sortedList#(n1:n2:ns) n3
| isEqual n1 n2 = groupIf (isEqual n2 n3) sortedList n3
| isAscen n1 n2 = groupIfNull isAscen sortedList n3
| isDesce n1 n2 = groupIfNull isDesce sortedList n3
| otherwise = mkNewGroup sortedList n3
where groupIfNull check sublist#(n1:n2:ns) n3
| null ns = groupIf (check n2 n3) [n1, n2] n3
| otherwise = groupIf (check (last ns) n3) sublist n3
groupIf isGroup | isGroup = addToGroup
| otherwise = mkNewGroup
addToGroup gp n = sublists ++ [(gp ++ [n])]
mkNewGroup gp n = sublists ++ [gp] ++ [[n]]
isEqual x y = x == y
isAscen x y = x < y
isDesce x y = x > y
My initial thought looks like:
ordruns :: Ord a => [a] -> [[a]]
ordruns = foldr extend []
where
extend a [ ] = [ [a] ]
extend a ( [b] : runs) = [a,b] : runs
extend a (run#(b:c:etc) : runs)
| compare a b == compare b c = (a:run) : runs
| otherwise = [a] : run : runs
This eagerly fills from the right, while maintaining the Ordering in all neighbouring pairs for each sublist. Thus only the first result can end up with a single item in it.
The thought process is this: an Ordering describes the three types of subsequence we're looking for: ascending LT, equal EQ or descending GT. Keeping it the same every time we add on another item means it will match throughout the subsequence. So we know we need to start a new run whenever the Ordering does not match. Furthermore, it's impossible to compare 0 or 1 items, so every run we create contains at least 1 and if there's only 1 we do add the new item.
We could add more rules, such as a preference for filling left or right. A reasonable optimization is to store the ordering for a sequence instead of comparing the leading two items twice per item. And we could also use more expressive types. I also think this version is inefficient (and inapplicable to infinite lists) due to the way it collects from the right; that was mostly so I could use cons (:) to build the lists.
Second thought: I could collect the lists from the left using plain recursion.
ordruns :: Ord a => [a] -> [[a]]
ordruns [] = []
ordruns [a] = [[a]]
ordruns (a1:a2:as) = run:runs
where
runs = ordruns rest
order = compare a1 a2
run = a1:a2:runcontinuation
(runcontinuation, rest) = collectrun a2 order as
collectrun _ _ [] = ([], [])
collectrun last order (a:as)
| order == compare last a =
let (more,rest) = collectrun a order as
in (a:more, rest)
| otherwise = ([], a:as)
More exercises. What if we build the list of comparisons just once, for use in grouping?
import Data.List
ordruns3 [] = []
ordruns3 [a] = [[a]]
ordruns3 xs = unfoldr collectrun marked
where
pairOrder = zipWith compare xs (tail xs)
marked = zip (head pairOrder : pairOrder) xs
collectrun [] = Nothing
collectrun ((o,x):xs) = Just (x:map snd markedgroup, rest)
where (markedgroup, rest) = span ((o==).fst) xs
And then there's the part where there's a groupBy :: (a -> a -> Bool) -> [a] -> [[a]] but no groupOn :: Eq b => (a -> b) -> [a] -> [[a]]. We can use a wrapper type to handle that.
import Data.List
data Grouped t = Grouped Ordering t
instance Eq (Grouped t) where
(Grouped o1 _) == (Grouped o2 _) = o1 == o2
ordruns4 [] = []
ordruns4 [a] = [[a]]
ordruns4 xs = unmarked
where
pairOrder = zipWith compare xs (tail xs)
marked = group $ zipWith Grouped (head pairOrder : pairOrder) xs
unmarked = map (map (\(Grouped _ t) -> t)) marked
Of course, the wrapper type's test can be converted into a function to use groupBy instead:
import Data.List
ordruns5 [] = []
ordruns5 [a] = [[a]]
ordruns5 xs = map (map snd) marked
where
pairOrder = zipWith compare xs (tail xs)
marked = groupBy (\a b -> fst a == fst b) $
zip (head pairOrder : pairOrder) xs
These marking versions arrive at the same decoration concept Jonas Duregård applied.
I'm fairly new to Haskell and trying to figure out how I would write a Function to do this and after combing Google for a few hours I'm at a loss on how to do it.
Given the following two lists in Haskell
[(500,False),(400,False),(952,True),(5,False),(42,False)]
[0,2,3]
How would I change the Boolean of the First list at each location given by the second list to a Value of True for an Output of
[(500,True),(400,False),(952,True),(5,True),(42,False)]
This is how I would do it (assumes the list of indexes to replace is sorted).
First we add an index list alongside the list of indexes to replace and the original list.
Then we recurse down the list and when we hit the next index to replace we replace the boolean and recurse on the tail of both all three lists. If this is not an index to
replace we recurse on the entire replacement index list and the tail of the other two lists.
setTrue :: [Int] -> [(a, Bool)] -> [(a, Bool)]
setTrue is xs = go is xs [0..] -- "Index" the list with a list starting at 0.
where
go [] xs _ = xs -- If we're out of indexes to replace return remaining list.
go _ [] _ = [] -- If we run out of list return the empty list.
go indexes#(i:is) (x:xs) (cur:cs)
| i == cur = (fst x, True) : go is xs cs -- At the next index to replace.
| otherwise = x : go indexes xs cs -- Otherwise, keep the current element.
This is basically the same as Andrew's approach, but it doesn't use an additional index list, and is a little bit more inspired by the traditional map. Note that unlike map, the provided function must be a -> a and cannot be a -> b.
restrictedMap :: (a -> a) -> [Int] -> [a] -> [a]
restrictedMap f is xs = go f is xs 0
where
go f [] xs _ = xs
go f _ [] _ = []
go f ind#(i:is) (x:xs) n
| i == n = f x : go f is xs (n+1)
| otherwise = x : go f ind xs (n+1)
setTrue = restrictedMap (\(x,_) -> (x, True))
Straightforward translation from the description will be:
setIndexTrue f a = [(x, p || i `elem` f) | (i, (x,p)) <- zip [0..] a]
Or using the fantastic lens library:
setTrue :: [(a,Bool)] -> Int -> [(a,Bool)]
setTrue xs i = xs & ix i . _2 .~ True
setTrues :: [(a,Bool)] -> [Int] -> [(a,Bool)]
setTrues = foldl setTrue
Since the approach I would use is not listed:
setTrue spots values = let
pattern n = replicate n False ++ [True] ++ Repeat False
toSet = foldl1 (zipWith (||)) $ map pattern spots
in zipWith (\s (v,o) -> (v, o || s)) toSet values
I come from a C++ background so I'm not sure if I'm even going about this properly. But what I'm trying to do is write up quick sort but fallback to insertion sort if the length of a list is less than a certain threshold. So far I have this code:
insertionSort :: (Ord a) => [a] -> [a]
insertionSort [] = []
insertionSort (x:xs) = insert x (insertionSort xs)
quickSort :: (Ord a) => [a] -> [a]
quickSort x = qsHelper x (length x)
qsHelper :: (Ord a) => [a] -> Int -> [a]
qsHelper [] _ = []
qsHelper (x:xs) n
| n <= 10 = insertionSort xs
| otherwise = qsHelper before (length before) ++ [x] ++ qsHelper after (length after)
where
before = [a | a <- xs, a < x]
after = [a | a <- xs, a >= x]
Now what I'm concerned about is calculating the length of each list every time. I don't fully understand how Haskell optimizes things or the complete effects of lazy evaluation on code like the above. But it seems like calculating the length of the list for each before and after list comprehension is not a good thing? Is there a way for you to extract the number of matches that occurred in a list comprehension while performing the list comprehension?
I.e. if we had [x | x <- [1,2,3,4,5], x > 3] (which results in [4,5]) could I get the count of [4,5] without using a call to length?
Thanks for any help/explanations!
Short answer: no.
Less short answer: yes, you can fake it. import Data.Monoid, then
| otherwise = qsHelper before lenBefore ++ [x] ++ qsHelper after lenAfter
where
(before, Sum lenBefore) = mconcat [([a], Sum 1) | a <- xs, a < x]
(after, Sum lenAfter) = mconcat [([a], Sum 1) | a <- xs, a >= x]
Better answer: you don't want to.
Common reasons to avoid length include:
its running time is O(N)
but it costs us O(N) to build the list anyway
it forces the list spine to be strict
but we're sorting the list: we have to (at least partially) evaluate each element in order to know which is the minimum; the list spine is already forced to be strict
if you don't care how long the list is, just whether it's shorter/longer than another list or a threshold, length is wasteful: it will walk all the way to the end of the list regardless
BINGO
isLongerThan :: Int -> [a] -> Bool
isLongerThan _ [] = False
isLongerThan 0 _ = True
isLongerThan n (_:xs) = isLongerThan (n-1) xs
quickSort :: (Ord a) => [a] -> [a]
quickSort [] = []
quickSort (x:xs)
| not (isLongerThan 10 (x:xs)) = insertionSort xs
| otherwise = quickSort before ++ [x] ++ quickSort after
where
before = [a | a <- xs, a < x]
after = [a | a <- xs, a >= x]
The real inefficiency here though is in before and after. They both step through the entire list, comparing each element against x. So we are stepping through xs twice, and comparing each element against x twice. We only have to do it once.
(before, after) = partition (< x) xs
partition is in Data.List.
No, there is no way to use list comprehensions to simultaneously do a filter and count the number of found elements. But if you are worried about this performance hit, you should not be using the list comprehensions the way you are in the first place: You are filtering the list twice, hence applying the predicate <x and its negation to each element. A better variant would be
(before, after) = partition (< x) xs
Starting from that it is not hard to write a function
partitionAndCount :: (a -> Bool) -> [a] -> (([a],Int), ([a],Int))
that simultaneously partitions and counts the list and counts the elements in each of the returned list:
((before, lengthBefore), (after, lengthAfter)) = partitionAndCount (< x) xs
Here is a possible implementation (with a slightly reordered type):
{-# LANGUAGE BangPatterns #-}
import Control.Arrow
partitionAndCount :: (a -> Bool) -> [a] -> (([a], [a]), (Int, Int))
partitionAndCount p = go 0 0
where go !c1 !c2 [] = (([],[]),(c1,c2))
go !c1 !c2 (x:xs) = if p x
then first (first (x:)) (go (c1 + 1) c2 xs)
else first (second (x:)) (go c1 (c2 + 1) xs)
And here you can see it in action:
*Main> partitionAndCount (>=4) [1,2,3,4,5,3,4,5]
(([4,5,4,5],[1,2,3,3]),(4,4))
I want to write a function which takes a list of elements l, a list of indices i, and a list of replacement values v. The function will replace the values in l corresponding to the indices in i with the corresponding value in v.
Example:
If l = [1,2,3,4,5,6], i = [0,2], and v = [166,667], then
replaceValues l i v == [166,2,667,4,5,6]
My function:
--Replace the values in list l at indices in i with the
-- corresponding value in v
replaceValues :: [a] -> [Int] -> [a] -> [a]
replaceValues l [] [] = l
replaceValues l i v = x ++ [head v] ++ (replaceValues (tail y) shiftedIndices (tail v))
where
(x,y) = splitAt (head i) l
--The indices must be shifted because we are changing the list
shiftedIndices = map ((-)((head i) + 1)) (tail i)
This function manages to correctly replace the value at the first index in i, but it misplaces all of the following values. In the example above, it would give the output [166,667,3,4,5,6].
The problem with your implementation is that you aren't keeping track of which index you're currently at.
First of all, you're better off considering using [(Int,a)] rather than [Int] and [a] arguments separate to ensure that the "lists" are equal in length.
An alternate implementation is as follows:
import Data.Maybe(fromMaybe)
import qualified Data.IntMap as M
replaceValues :: [a] -> [(Int,a)] -> [a]
replaceValues as rs = map rep $ zip [0..] as
where
rsM = M.fromList rs
rep (i,a) = fromMaybe a $ M.lookup i rsM
What's happening here:
Tag each value with its index
See if there's a replacement value for that index: if there is, use it; otherwise, use the original value.
The first thing that springs to mind is that you should use a list of tuples to specify the replacement, that is, work with
l = [1,2,3,4,5,6]
r = [(0,166),(2,667)]
... you can use zip to convert your two lists into that format. Then I'm going to stipulate that that list is sorted by the first element of the tuple (sortBy), and that there are no duplicate indices in it (nubBy). The rest is a simple recursion, replacing as you go, with linear complexity and being maximally lazy:
replaceValues :: [a] -> [(Int, a)] -> [a]
replaceValues xs rs = f 0 xs rs
where
f _ xs [] = xs
f _ [] _ = []
f n (x:xs) is#((i,r):is')
| n < i = x:f (n+1) xs is
| n == i = r:f (n+1) xs is'
| otherwise = error "Can't happen"
Beware of the code, though, I have only proven it to be correct, not actually tried it.
Using a map works too, of course, but then you're dealing with an complexity of O(m log m + n log m) (construct map + n times lookup) instead of O(n), or, taking sorting into account, O(n + m log m), as well as lose the capability of being lazy in case your list is already sorted and have the replacements incrementally garbage collected while you traverse.
nubBy from the library has quadratic complexity, but as the list is sorted it can be dealt with in linear time, too, just replace the call to error with a recursive call throwing away superfluous (i,r)s.
as said before, use tuples - but don't forget about pattern matching. Or use Map if you are not dealing with large collections
replaceValues :: [a] -> [Int] -> [a] ->[a]
replaceValues a b i = map fst $ f (zip a [0..]) (zip b i)
where
f [] _ = []
f xs [] = xs
f ((x,i):xs) s2#((j,y):ys) | i == j = (y,i) : f xs ys
| otherwise = (x,i) : f xs s2