I am studying the code in the Data.List module and can't exactly wrap my head around this implementation of permutations:
permutations :: [a] -> [[a]]
permutations xs0 = xs0 : perms xs0 []
where
perms [] _ = []
perms (t:ts) is = foldr interleave (perms ts (t:is)) (permutations is)
where interleave xs r = let (_,zs) = interleave' id xs r in zs
interleave' _ [] r = (ts, r)
interleave' f (y:ys) r = let (us,zs) = interleave' (f . (y:)) ys r
in (y:us, f (t:y:us) : zs)
Can somebody explain in detail how these nested functions connect/work with each other?
Sorry about the late answer, it took a bit longer to write down than expected.
So, first of all to maximize lazyness in a list function like this there are two goals:
Now consider the permutation
function. Here maximal lazyness means:
n!
permutations after inspecting just n
elements of inputn!
permutations, the first n
elements should depend only on the first n
elements of the input.The first condition could be formalized as
length (take (factorial n) $ permutations ([1..n] ++ undefined))) `seq` () == ()
David Benbennick formalized the second condition as
map (take n) (take (factorial n) $ permutations [1..]) == permutations [1..n]
Combined, we have
map (take n) (take (factorial n) $ permutations ([1..n] ++ undefined)) == permutations [1..n]
Let's start with some simple cases. First permutation [1..]
. We must have
permutations [1..] = [1,???] : ???
And with two elements we must have
permutations [1..] = [1,2,???] : [2,1,???] : ???
Note that there is no choice about the order of the first two elements, we can't put [2,1,...]
first, since we already decided that the first permutation must start with 1
. It should be clear by now that the first element of permutations xs
must be equal to xs
itself.
Now on to the implementation.
First of all, there are two different ways to make all permutations of a list:
Selection style: keep picking elements from the list until there are none left
permutations [] = [[]]
permutations xxs = [(y:ys) | (y,xs) <- picks xxs, ys <- permutations xs]
where
picks (x:xs) = (x,xs) : [(y,x:ys) | (y,ys) <- picks xs]
Insertion style: insert or interleave each element in all possible places
permutations [] = [[]]
permutations (x:xs) = [y | p <- permutations xs, y <- interleave p]
where
interleave [] = [[x]]
interleave (y:ys) = (x:y:ys) : map (y:) (interleave ys)
Note that neither of these is maximally lazy. The first case, the first thing this function does is pick the first element from the entire list, which is not lazy at all. In the second case we need the permutations of the tail before we can make any permutation.
To start, note that interleave
can be made more lazy. The first element of interleave yss
list is [x]
if yss=[]
or (x:y:ys)
if yss=y:ys
. But both of these are the same as x:yss
, so we can write
interleave yss = (x:yss) : interleave' yss
interleave' [] = []
interleave' (y:ys) = map (y:) (interleave ys)
The implementation in Data.List continues on this idea, but uses a few more tricks.
It is perhaps easiest to go through the mailing list discussion. We start with David Benbennick's version, which is the same as the one I wrote above (without the lazy interleave). We already know that the first elment of permutations xs
should be xs
itself. So, let's put that in
permutations xxs = xxs : permutations' xxs
permutations' [] = []
permutations' (x:xs) = tail $ concatMap interleave $ permutations xs
where interleave = ..
The call to tail
is of course not very nice. But if we inline the definitions of permutations
and interleave
we get
permutations' (x:xs)
= tail $ concatMap interleave $ permutations xs
= tail $ interleave xs ++ concatMap interleave (permutations' xs)
= tail $ (x:xs) : interleave' xs ++ concatMap interleave (permutations' xs)
= interleave' xs ++ concatMap interleave (permutations' xs)
Now we have
permutations xxs = xxs : permutations' xxs
permutations' [] = []
permutations' (x:xs) = interleave' xs ++ concatMap interleave (permutations' xs)
where
interleave yss = (x:yss) : interleave' yss
interleave' [] = []
interleave' (y:ys) = map (y:) (interleave ys)
The next step is optimization. An important target would be to eliminate the (++) calls in interleave. This is not so easy, because of the last line, map (y:) (interleave ys)
. We can't immediately use the foldr/ShowS trick of passing the tail as a parameter. The way out is to get rid of the map. If we pass a parameter f
as the function that has to be mapped over the result at the end, we get
permutations' (x:xs) = interleave' id xs ++ concatMap (interleave id) (permutations' xs)
where
interleave f yss = f (x:yss) : interleave' f yss
interleave' f [] = []
interleave' f (y:ys) = interleave (f . (y:)) ys
Now we can pass in the tail,
permutations' (x:xs) = interleave' id xs $ foldr (interleave id) [] (permutations' xs)
where
interleave f yss r = f (x:yss) : interleave' f yss r
interleave' f [] r = r
interleave' f (y:ys) r = interleave (f . (y:)) ys r
This is starting to look like the one in Data.List, but it is not the same yet. In particular, it is not as lazy as it could be. Let's try it out:
*Main> let n = 4
*Main> map (take n) (take (factorial n) $ permutations ([1..n] ++ undefined))
[[1,2,3,4],[2,1,3,4],[2,3,1,4],[2,3,4,1]*** Exception: Prelude.undefined
Uh oh, only the first n
elements are correct, not the first factorial n
.
The reason is that we still try to place the first element (the 1
in the above example) in all possible locations before trying anything else.
Yitzchak Gale came up with a solution. Considered all ways to split the input into an initial part, a middle element, and a tail:
[1..n] == [] ++ 1 : [2..n]
== [1] ++ 2 : [3..n]
== [1,2] ++ 3 : [4..n]
If you haven't seen the trick to generate these before before, you can do this with zip (inits xs) (tails xs)
.
Now the permutations of [1..n]
will be
[] ++ 1 : [2..n]
aka. [1..n]
, or2
inserted (interleaved) somewhere into a permutation of [1]
, followed by [3..n]
. But not 2
inserted at the end of [1]
, since we already go that result in the previous bullet point.3
interleaved into a permutation of [1,2]
(not at the end), followed by [4..n]
.You can see that this is maximally lazy, since before we even consider doing something with 3
, we have given all permutations that start with some permutation of [1,2]
. The code that Yitzchak gave was
permutations xs = xs : concat (zipWith newPerms (init $ tail $ tails xs)
(init $ tail $ inits xs))
where
newPerms (t:ts) = map (++ts) . concatMap (interleave t) . permutations3
interleave t [y] = [[t, y]]
interleave t ys@(y:ys') = (t:ys) : map (y:) (interleave t ys')
Note the recursive call to permutations3
, which can be a variant that doesn't have to be maximally lazy.
As you can see this is a bit less optimized than what we had before. But we can apply some of the same tricks.
The first step is to get rid of init
and tail
. Let's look at what zip (init $ tail $ tails xs) (init $ tail $ inits xs)
actually is
*Main> let xs = [1..5] in zip (init $ tail $ tails xs) (init $ tail $ inits xs)
[([2,3,4,5],[1]),([3,4,5],[1,2]),([4,5],[1,2,3]),([5],[1,2,3,4])]
The init
gets rid of the combination ([],[1..n])
, while the tail
gets rid of the combination ([1..n],[])
. We don't want the former, because that would fail the pattern match in newPerms
. The latter would fail interleave
. Both are easy to fix: just add a case for newPerms []
and for interleave t []
.
permutations xs = xs : concat (zipWith newPerms (tails xs) (inits xs))
where
newPerms [] is = []
newPerms (t:ts) is = map (++ts) (concatMap (interleave t) (permutations is))
interleave t [] = []
interleave t ys@(y:ys') = (t:ys) : map (y:) (interleave t ys')
Now we can try to inline tails
and inits
. Their definition is
tails xxs = xxs : case xxs of
[] -> []
(_:xs) -> tails xs
inits xxs = [] : case xxs of
[] -> []
(x:xs) -> map (x:) (inits xs)
The problem is that inits
is not tail recursive. But since we are going to take a permutation of the inits anyway, we don't care about the order of the elements. So we can use an accumulating parameter,
inits' = inits'' []
where
inits'' is xxs = is : case xxs of
[] -> []
(x:xs) -> inits'' (x:is) xs
Now we make newPerms
a function of xxs
and this accumulating parameter, instead of tails xxs
and inits xxs
.
permutations xs = xs : concat (newPerms' xs [])
where
newPerms' xxs is =
newPerms xxs is :
case xxs of
[] -> []
(x:xs) -> newPerms' xs (x:is)
newPerms [] is = []
newPerms (t:ts) is = map (++ts) (concatMap (interleave t) (permutations3 is))
inlining newPerms
into newPerms'
then gives
permutations xs = xs : concat (newPerms' xs [])
where
newPerms' [] is = [] : []
newPerms' (t:ts) is =
map (++ts) (concatMap (interleave t) (permutations is)) :
newPerms' ts (t:is)
inlining and unfolding concat
, and moving the final map (++ts)
into interleave
,
permutations xs = xs : newPerms' xs []
where
newPerms' [] is = []
newPerms' (t:ts) is =
concatMap interleave (permutations is) ++
newPerms' ts (t:is)
where
interleave [] = []
interleave (y:ys) = (t:y:ys++ts) : map (y:) (interleave ys)
Then finally, we can reapply the foldr
trick to get rid of the (++)
:
permutations xs = xs : newPerms' xs []
where
newPerms' [] is = []
newPerms' (t:ts) is =
foldr (interleave id) (newPerms' ts (t:is)) (permutations is)
where
interleave f [] r = r
interleave f (y:ys) r = f (t:y:ys++ts) : interleave (f . (y:)) ys r
Wait, I said get rid of the (++)
. We got rid of one of them, but not the one in interleave
.
For that, we can see that we are always concatenating some tail of yys
to ts
. So, we can unfold the calculating (ys++ts)
along with the recursion of interleave
, and have the function interleave' f ys r
return the tuple (ys++ts, interleave f ys r)
. This gives
permutations xs = xs : newPerms' xs []
where
newPerms' [] is = []
newPerms' (t:ts) is =
foldr interleave (newPerms' ts (t:is)) (permutations is)
where
interleave ys r = let (_,zs) = interleave' id ys r in zs
interleave' f [] r = (ts,r)
interleave' f (y:ys) r =
let (us,zs) = interleave' (f . (y:)) ys r
in (y:us, f (t:y:us) : zs)
And there you have it, Data.List.permutations
in all its maximally lazy optimized glory.
Great write-up by Twan! I (@Yitz) will just add a few references:
The original email thread where Twan developed this algorithm, linked above by Twan, is fascinating reading.
Knuth classifies all possible algorithms that satisfy these criteria in Vol. 4 Fasc. 2 Sec. 7.2.1.2.
Twan's permutations3
is essentially the same as Knuth's "Algorithm P". As far as Knuth knows, that algorithm was first published by English church bell ringers in the 1600's.