I have been working on a separate function that returns a list that inserts element x after each k elements of list l (counting from
the end of the list). For example, separate (1, 0, [1,2,3,4]) should return [1,0,2,0,3,0,4]. I finished the function and have it working as follows:
fun separate (k: int, x: 'a, l: 'a list) : 'a list =
let
fun kinsert [] _ = []
| kinsert ls 0 = x::(kinsert ls k)
| kinsert (l::ls) i = l::(kinsert ls (i-1))
in
List.rev (kinsert (List.rev l) k)
end
Im now trying to simplify the function using foldl/foldr without any recursion, but I cant seem to get it working right. Any tips/suggestions on how to approach this? Thank You!
These are more or less the thoughts I had when trying to write the function using foldl/foldr:
foldl/foldr abstracts away the list recursion from the logic that composes the end result.
Start by sketching out a function that has a much similar structure to your original program, but where foldr is used and kinsert instead of being a recursive function is the function given to foldr:
fun separate (k, x, L) =
let fun kinsert (y, ys) = ...
in foldr kinsert [] L
end
This isn't strictly necessary; kinsert might as well be anonymous.
You're using an inner helper function kinsert because you need a copy of k (i) that you gradually decrement and reset to k every time it reaches 0. So while the list that kinsert spits out is equivalent to the fold's accumulated variable, i is temporarily accumulated (and occasionally reset) in much the same way.
Change kinsert's accumulating variable to make room for i:
fun separate (k, x, L) =
let fun kinsert (y, (i, xs)) = ...
in foldr kinsert (?, []) L
end
Now the result of the fold becomes 'a * 'a list, which causes two problems: 1) We only really wanted to accumulate i temporarily, but it's part of the final result. This can be circumvented by discarding it using #2 (foldr ...). 2) If the result is now a tuple, I'm not sure what to put as the first i in place of ?.
Since kinsert is a separate function declaration, you can use pattern matching and multiple function bodies:
fun separate (k, x, L) =
let fun kinsert (y, (0, ys)) = ...
| kinsert (y, (i, ys)) = ...
in ... foldr kinsert ... L
end
Your original kinsert deviates from the recursion pattern that a fold performs in one way: In the middle pattern, when i matches 0, you're not chopping an element off ls, which a fold would otherwise force you to. So your 0 case will look slightly different from the original; you'll probably run into an off-by-one error.
Remember that foldr actually visits the last element in the list first, at which point i will have its initial value, where with the original kinsert, the initial value for i will be when you're at the first element.
Depending on whether you use foldl or foldr you'll run into different problems: foldl will reverse your list, but address items in the right order. foldr will keep the list order correct, but create a different result when k does not divide the length of L...
At this point, consider using foldl and reverse the list instead:
fun separate (k, x, L) =
let fun kinsert (y, (?, ys)) = ...
| kinsert (y, (i, ys)) = ...
in rev (... foldl kinsert ... L)
end
Otherwise you'll start to notice that separate (2, 0, [1,2,3,4,5]) should probably give [1,2,0,3,4,0,5] and not [1,0,2,3,0,5].
Related
fun p(L) =
[L] # p( tl(L) # [hd(L)] );
If L is [1,2,3] then I want to have a [ [1,2,3], [2,3,1], [3,1,2] ].
Since every time I append the first num to the end, then if L = [] then [] doesn't work here.
How to stop the function once it has the three lists?
You can have a parameter x in the function to keep track of how many levels deep in the recursion you are.
fun p(L, x) =
if x < length(L) then [L] # p(tl(L) # [hd(L)], x+1)
else [];
Then call the function with x=0.
p([1, 2, 3], 0)
And if you don't like the extra parameter, then as you probably know you can define another function and make it equal to the p function with the parameter forced to 0.
fun p0(L) = p(L, 0);
p0([1, 2, 3]); (* same result as p([1, 2, 3], 0); *)
Let me show some more implementation variants.
First of all, let's define an auxiliary function, which rotates a list 1 position to the left:
(* operates on non-empty lists only *)
fun rot1_left (h :: tl) = tl # [h]
Then the p function could be defined as follows:
fun p xs =
let
(* returns reversed result *)
fun loop [] _ _ = []
| loop xs n res =
if n = 0
then res
else loop (rot1_left xs) (n-1) (xs :: res)
in
List.rev (loop xs (length xs) [])
end
It's usually better (performance-wise) to add new elements at the beginning of the list and then reverse the resulting list once, than to append to the end many times. Note: this version does one spurious rotate at the end and I could have optimized it out, but didn't, to make code more clear.
We have calculated the length of the given list to make its rotated "copies", but we don't have to traverse xs beforehand, we can do it as we rotate it. So, we can use xs as a kind of counter, recursively calling the loop helper function on the tail of the xs list.
fun p xs =
let
(* returns reversed result *)
fun loop [] _ _ = []
| loop xs [] res = res
| loop xs (_::tl) res =
loop (rot1_left xs) tl (xs :: res)
in
List.rev (loop xs xs [])
end
Having done that, we are now closer to implementing p as a foldl function:
fun p xs =
(List.rev o #1)
(List.foldl
(fn (_, (res, rot)) => (rot::res, rot1_left rot))
([], xs)
xs)
The second argument to the List.foldl function is our "accumulator", which is represented here as a pair of the current (partial) result as in the previous implementations and the current rotated list. That explains (List.rev o #1) part: we need to take the first component of the accumulator and reverse it. And as for the ([], xs) part -- the current result is empty at the beginning (hence []) and we start rotating the initial xs list. Also, the _ in (_, (res, rot)) means the current element of the given xs, which we don't care about, since it just serves as a counter (see the prev. variant).
Note: o stands for function composition in Standard ML.
I'm trying to write a method that splits a list into two. The function should return a tuple of the two lists and the arguments that the function takes are the # of items on the first list, and then the list. Here's what I mean
list [1,2,3,4]
split(1,list)-> ([1],[2,3,4])
split (3,list) -> ([1,2,3],[4])
Here's what I have so far:
let rec mysplit = function
|(n,[])->([],[])
|(1,x::xs)->(x::[],xs)
|(n,x::xs)-> mysplit(n-1,xs)
I'm not exactly sure how to "catch" the tuple back from the recursive call. Not sure where to have an extra let statement in there to temporarily save the list I'm building up. New to the language so a couple of different approaches would be good to learn.
Skip and take are your friends here. I don't think you need to do any sort of matches or recursive calls when there's a direct approach.
let split n l = (l |> Seq.take n, l |> Seq.skip n)
As for possible edge cases, skip will return an empty sequence if there are > n elements in the list, and take will return the first n elements if there are < n elements in the sequence.
Tried it in TryFharp.org with your examples and it works as expected.
A straightforward implementation would be:
let rec mysplit = function
|(n,[])->([],[])
|(1,x::xs)->(x::[],xs)
|(n,x::xs)-> let (f, s) = mysplit(n-1,xs) in (x::f, s)
You could also write a tail-recursive version:
let mysplit (n, l) =
let rec mysplit' n' (f, s) = function
| [] -> (f, s)
| (x::xs) as l' -> if n' = 0 then (f, l') else mysplit' (n'-1) (x::f, xs) xs
let (f', s) = mysplit' n ([], []) l in (List.rev f', s)
Lee's answer shows you a working solution, but to answer your specific question, you can capture values returned to you in a tuple like so:
let before, after = mysplit (2, [1;2;3;4;5])
You can also use this trick to declare multiple variables in a single let statement:
let i, j, k = (1, 2, 3)
So i'm new to sml and am trying to understand the ins/out out of it. Recently i tried creating a filter which takes two parameters: a function (that returns a boolean), and a list of values to run against the function. What the filter does is it returns the list of values which return true against the function.
Code:
fun filter f [] = [] |
filter f (x::xs) =
if (f x)
then x::(filter f xs)
else (filter f xs);
So that works. But what i'm trying to do now is just a return a tuple that contains the list of true values, and false. I'm stuck on my conditional and I can't really see another way. Any thoughts on how to solve this?
Code:
fun filter2 f [] = ([],[]) |
filter2 f (x::xs) =
if (f x)
then (x::(filter2 f xs), []) (* error *)
else ([], x::(filter2 f xs)); (* error *)
I think there are several ways to do this.
Reusing Filter
For instance, we could use a inductive approach based on the fact that your tuple would be formed by two elements, the first is the list of elements that satisfy the predicate and the second the list of elements that don't. So, you could reuse your filter function as:
fun partition f xs = (filter f xs, filter (not o f) xs)
This is not the best approach, though, because it evaluates the lists twice, but if the lists are small, this is quite evident and very readable.
Folding
Another way to think about this is in terms of fold. You could think that you are reducing your list to a tuple list, and as you go, you split your items depending on a predicate. Somwewhat like this:
fun parition f xs =
let
fun split x (xs,ys) =
if f x
then (x::xs,ys)
else (xs, x::ys)
val (trueList, falseList) = List.foldl (fn (x,y) => split x y)
([],[]) xs
in
(List.rev trueList, List.rev falseList)
end
Parition
You could also implement your own folding algorithm in the same way as the List.parition method of SML does:
fun partition f xs =
let
fun iter(xs, (trueList,falseList)) =
case xs of
[] => (List.rev trueList, List.rev falseList)
| (x::xs') => if f x
then iter(xs', (x::trueList,falseList))
else iter(xs', (trueList,x::falseList))
in
iter(xs,([],[]))
end
Use SML Basis Method
And ultimately, you can avoid all this and use SML method List.partition whose documentation says:
partition f l
applies f to each element x of l, from left to right, and returns a
pair (pos, neg) where pos is the list of those x for which f x
evaluated to true, and neg is the list of those for which f x
evaluated to false. The elements of pos and neg retain the same
relative order they possessed in l.
This method is implemented as the previous example.
So I will show a good way to do it, and a better way to do it (IMO). But the 'better way' is just for future reference when you learn:
fun filter2 f [] = ([], [])
| filter2 f (x::xs) = let
fun ftuple f (x::xs) trueList falseList =
if (f x)
then ftuple f xs (x::trueList) falseList
else ftuple f xs trueList (x::falseList)
| ftuple _ [] trueList falseList = (trueList, falseList)
in
ftuple f (x::xs) [] []
end;
The reason why yours does not work is because when you call x::(filter2 f xs), the compiler is naively assuming that you are building a single list, it doesn't assume that it is a tuple, it is stepping into the scope of your function call. So while you think to yourself result type is tuple of lists, the compiler gets tunnel vision and thinks result type is list. Here is the better version in my opinion, you should look up the function foldr if you are curious, it is much better to employ this technique since it is more readable, less verbose, and much more importantly ... more predictable and robust:
fun filter2 f l = foldr (fn(x,xs) => if (f x) then (x::(#1(xs)), #2(xs)) else (#1(xs), x::(#2(xs)))) ([],[]) l;
The reason why the first example works is because you are storing default empty lists that accumulate copies of the variables that either fit the condition, or do not fit the condition. However, you have to explicitly tell SML compiler to make sure that the type rules agree. You have to make absolutely sure that SML knows that your return type is a tuple of lists. Any mistake in this chain of command, and this will result in failure to execute. Hence, when working with SML, always study your type inferences. As for the second one, you can see that it is a one-liner, but I will leave you to research that one on your own, just google foldr and foldl.
With a list of integers such as:
[1;2;3;4;5;6;7;8;9]
How can I create a list of list of ints from the above, with all new lists the same specified length?
For example, I need to go from:
[1;2;3;4;5;6;7;8;9] to [[1;2;3];[4;5;6];[7;8;9]]
with the number to split being 3?
Thanks for your time.
So what you actually want is a function of type
val split : int list -> int -> int list list
that takes a list of integers and a sub-list-size. How about one that is even more general?
val split : 'a list -> int -> 'a list list
Here comes the implementation:
let split xs size =
let (_, r, rs) =
(* fold over the list, keeping track of how many elements are still
missing in the current list (csize), the current list (ys) and
the result list (zss) *)
List.fold_left (fun (csize, ys, zss) elt ->
(* if target size is 0, add the current list to the target list and
start a new empty current list of target-size size *)
if csize = 0 then (size - 1, [elt], zss # [ys])
(* otherwise decrement the target size and append the current element
elt to the current list ys *)
else (csize - 1, ys # [elt], zss))
(* start the accumulator with target-size=size, an empty current list and
an empty target-list *)
(size, [], []) xs
in
(* add the "left-overs" to the back of the target-list *)
rs # [r]
Please let me know if you get extra points for this! ;)
The code you give is a way to remove a given number of elements from the front of a list. One way to proceed might be to leave this function as it is (maybe clean it up a little) and use an outer function to process the whole list. For this to work easily, your function might also want to return the remainder of the list (so the outer function can easily tell what still needs to be segmented).
It seems, though, that you want to solve the problem with a single function. If so, the main thing I see that's missing is an accumulator for the pieces you've already snipped off. And you also can't quit when you reach your count, you have to remember the piece you just snipped off, and then process the rest of the list the same way.
If I were solving this myself, I'd try to generalize the problem so that the recursive call could help out in all cases. Something that might work is to allow the first piece to be shorter than the rest. That way you can write it as a single function, with no accumulators
(just recursive calls).
I would probably do it this way:
let split lst n =
let rec parti n acc xs =
match xs with
| [] -> (List.rev acc, [])
| _::_ when n = 0 -> (List.rev acc, xs)
| x::xs -> parti (pred n) (x::acc) xs
in let rec concat acc = function
| [] -> List.rev acc
| xs -> let (part, rest) = parti n [] xs in concat (part::acc) rest
in concat [] lst
Note that we are being lenient if n doesn't divide List.length lst evenly.
Example:
split [1;2;3;4;5] 2 gives [[1;2];[3;4];[5]]
Final note: the code is very verbose because the OCaml standard lib is very bare bones :/ With a different lib I'm sure this could be made much more concise.
let rec split n xs =
let rec take k xs ys = match k, xs with
| 0, _ -> List.rev ys :: split n xs
| _, [] -> if ys = [] then [] else [ys]
| _, x::xs' -> take (k - 1) xs' (x::ys)
in take n xs []
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 :-)