A simple append function like this (in F#):
let rec app s t =
match s with
| [] -> t
| (x::ss) -> x :: (app ss t)
will crash when s becomes big, since the function is not tail recursive. I noticed that F#'s standard append function does not crash with big lists, so it must be implemented differently. So I wondered: How does a tail recursive definition of append look like? I came up with something like this:
let rec comb s t =
match s with
| [] -> t
| (x::ss) -> comb ss (x::t)
let app2 s t = comb (List.rev s) t
which works, but looks rather odd. Is there a more elegant definition?
Traditional (not tail-recursive)
let rec append a b =
match a, b with
| [], ys -> ys
| x::xs, ys -> x::append xs ys
With an accumulator (tail-recursive)
let append2 a b =
let rec loop acc = function
| [] -> acc
| x::xs -> loop (x::acc) xs
loop b (List.rev a)
With continuations (tail-recursive)
let append3 a b =
let rec append = function
| cont, [], ys -> cont ys
| cont, x::xs, ys -> append ((fun acc -> cont (x::acc)), xs, ys)
append(id, a, b)
Its pretty straight-forward to convert any non-tail recursive function to recursive with continuations, but I personally prefer accumulators for straight-forward readability.
In addition to what Juliet posted:
Using sequence expressions
Internally, sequence expressions generate tail-recursive code, so this works just fine.
let append xs ys =
[ yield! xs
yield! ys ]
Using mutable .NET types
David mentioned that F# lists can be mutated - that's however limited only to F# core libraries (and the feature cannot be used by users, because it breaks the functional concepts). You can use mutable .NET data types to implement a mutation-based version:
let append (xs:'a[]) (ys:'a[]) =
let ra = new ResizeArray<_>(xs)
for y in ys do ra.Add(y)
ra |> List.ofSeq
This may be useful in some scenarios, but I'd generally avoid mutation in F# code.
From a quick glance at the F# sources, it seems the tail is internally mutable. A simple solution would be to reverse the first list before consing its elements to the second list. That, along with reversing the list, are trivial to implement tail recursively.
Related
This is my code, when I enter a very large number I get stack overflow error does anyone know why? When i enter a very large number i get that error and im not really sure what is causing it, it is only with large numbers small ones work fine.....
//
// merge two sorted lists into one:
//
let rec merge L1 L2 =
if L1 = [] && L2 = [] then
[]
else if L1 = [] then
L2
else if L2 = [] then
L1
else if L1.Head <= L2.Head then
L1.Head :: merge L1.Tail L2
else
L2.Head :: merge L1 L2.Tail
//
// mergesort:
//
let rec mergesort L =
match L with
| [] -> []
| E::[] -> L
| _ ->
let mid = List.length L / 2
let (L1, L2) = List.splitAt mid L
merge (mergesort L1) (mergesort L2)
In both your functions you had the problem, that the last step you take is not the recursive call but some other thing:
in merge it is the :: operation
in mergesort it is the merge
So you have to get to a point where the very last thing is the recursive call!
One possibility in situations where you have more than one recursive call to make is to use continuations - the idea is to pass a function around that should be called with the result of the current step and then continue the computation from there.
this is a tail-recursive version of mergesort using this technique:
let mergesort xs =
let rec msort xs cont =
match xs with
| [] -> cont []
| [x] -> cont xs
| _ ->
let mid = List.length xs / 2
let (xs', xs'') = List.splitAt mid xs
msort xs' (fun ys' -> msort xs'' (fun ys'' -> cont (merge ys' ys'')))
msort xs id
as you can see the idea is not to hard - instead of first calling both recursive paths it starts with just one half but adds a continuation that basically says:
once I have the result of mergesort xs' I take the result ys' and continue by mergesorting xs'' and then merge those
of course the second step is done in just the same way (push the merge into the continuation)
the very first continuation is usually the identity as you can see in the very last line ;)
and here is something similar for your merge:
let merge xs ys =
let rec mrg xs ys cont =
match (xs, ys) with
| ([], ys) -> cont ys
| (xs, []) -> cont xs
| (x::xs', y::ys') ->
if x < y
then mrg xs' ys (fun rs -> cont (x::rs))
else mrg xs ys' (fun rs -> cont (y::rs))
mrg xs ys id
those will of course take as much space on the heap (probably more) - but that is usually no problem - your stack should be fine ;)
Each recursive call requires stack space. The more times mergesort calls itself, the more stack is used.
You avoid the stack overflow with recursive function by taking advantage of tail recursion. It simply means the last thing a function does is call itself, the call is removed and turns into a jump instead, saving stack space.
This is tricky to do in your case because you have to call mergesort twice. Only one of them can be last. The solution is to use a continuation. You only call mergesort once, but pass it a function to call, which will call mergesort the second time.
Search the internet for F# examples of a merge sort that uses continuations.
I'm trying to write a function in F# to get the powersets of a set. So far I have written :
let rec powerset = function
|[] -> [[]]
| [x] -> [[x]; []]
|x::xs -> [x] :: (List.map (fun n -> [x; n]) xs) # powerset xs;;
but this isn't returning the cases that have 3 or more elements, only the pairs, the single elements, and the empty set.
You are on the right track, here is a working solution:
let rec powerset =
function
| [] -> [[]]
| (x::xs) ->
let xss = powerset xs
List.map (fun xs' -> x::xs') xss # xss
See you only have to use this trick:
for each element x you there half of the elements of the powerset will include x and half will not
so you recursively generate the powerset of the remaining elements xss and concat the two parts (List.map (fun xs' -> x::xs') xss will prepend the x to each of those)
But please note that this is not tail recursive and will blow the stack for bigger lists - you can take this idea and try to implement it with seq or make a tail-recursive version if you like
Using seq
Here is a version that uses seq and the bijection between the binary representation of natural numbers (a subset of those) and the subsets of a set (you map the elements to digits and set 1 if the corresponding element is in the subset and 0 if not):
let powerset (xs : 'a seq) : 'a seq seq =
let digits (n : bigint) : bool seq =
Seq.unfold (fun n ->
if n <= 0I
then None
else Some (n &&& 1I = 1I, n >>> 1))
n
let subsetBy (i : bigint) : 'a seq =
Seq.zip xs (digits i)
|> Seq.choose (fun (x,b) -> if b then Some x else None)
seq { 0I .. 2I**(Seq.length xs)-1I }
|> Seq.map subsetBy
this will work for things like powerset [1..100] but it might take a long time to enumerate them all ;) (but it should not take to much memory...)
I understand and wrote a typical power set function in F# (similar to the Algorithms section in Wikipedia)
Later I found this implementation of powerset which seems nice and compact, expect that I do not understand it.
let rec powerset = function
| [] -> [[]]
| h::t -> List.fold (fun xs t -> (h::t)::t::xs) [] (powerset t);
I broke this down to a 1 step non-recursive function to find the powerset of [1;2] and hardcoded the value of power set of 2 at the end [[2]; []]
let right = function
| [] -> [[]]
| h::t -> List.fold (fun acc t -> (h::t)::t::acc) [] [[2]; []];
The output is [[1]; []; [1; 2]; [2]] which is correct.
However I was expecting List.Fold to output [[1; 2]; []; [1; 2]; [2]].
Since I was not certain about the 't', I modified the variable names, and I did get what I had expected. Of course this is not the correct powerset of [1;2].
let wrong = function
| [] -> [[]]
| h::t -> List.fold (fun acc data -> (h::t)::data::acc) [] [[2]; []];
For me 't' (the one withing fun and not the h::t) is simply a name for the second argument to 'fun' but that is obviously not the case. So what is the difference in the "right" and "wrong" F# functions I have written ? And what exactly does 't' here refer to ?
Thank you ! (I am new to F#)
In your "right" example, t is originally the name of the value bound in the pattern match, but it is hidden by the parameter t in the lambda expression passed to List.fold. Whereas in your "wrong" example, t is captured as a closure in the lambda expression. I think maybe you don't intend this capture, instead you want:
//now it works as you expect, replaced "t" with "data" in your lambda expression.
let wrong = function
| [] -> [[]]
| h::t -> List.fold (fun acc data -> (h::data)::data::acc) [] [[2]; []];
let rec powerset = function
| [] -> [[]]
| h::t -> List.fold (fun xs t -> (h::t)::t::xs) [] (powerset t);
here is the understanding/english translation of the code:
if the list (you want to power) is empty, then return a list, which contains an empty list in it
if the list is h::t (with head h and the rest as t, so h is an element and t is a list). then:
A. (powerset t): calculate the power set of t
B. (fun xs t -> (h::t)::t::xs) means that you apply/fold this function to the (powerset t). more details: xs is an accumulator, it is initialized to []. xxx::xs means you add something to an existing powerest xs. Here xxx is (h::t)::t, which are two elements to be added to the head of xs. (h::t) means add head to t and t means each element in (powerset t). <- the confusing part lies in t, the t in (powerset t) is the rest of the list, while the other t means an element in (powerset t).
here is an imperative translation of the fold function :
let h::t = list
let setfort = powerset t
xs <- []
foreach s in setfort do
xs <- xs.add(t) // t is a valid subset of list
xs <- xs.add(h::t) // t with h is also a valid subset of list
t is a variable bound by pattern matching. List.fold is a fancy way of avoiding explicit looping. Now, go and read some introductory tutorials about F#.
I am new to F# and was reading about tail recursive functions and was hoping someone could give me two different implementations of a function foo - one that is tail recursive and one that isn't so that I can better understand the principle.
Start with a simple task, like mapping items from 'a to 'b in a list. We want to write a function which has the signature
val map: ('a -> 'b) -> 'a list -> 'b list
Where
map (fun x -> x * 2) [1;2;3;4;5] == [2;4;6;8;10]
Start with non-tail recursive version:
let rec map f = function
| [] -> []
| x::xs -> f x::map f xs
This isn't tail recursive because function still has work to do after making the recursive call. :: is syntactic sugar for List.Cons(f x, map f xs).
The function's non-recursive nature might be a little more obvious if I re-wrote the last line as | x::xs -> let temp = map f xs; f x::temp -- obviously its doing work after the recursive call.
Use an accumulator variable to make it tail recursive:
let map f l =
let rec loop acc = function
| [] -> List.rev acc
| x::xs -> loop (f x::acc) xs
loop [] l
Here's we're building up a new list in a variable acc. Since the list gets built up in reverse, we need to reverse the output list before giving it back to the user.
If you're in for a little mind warp, you can use continuation passing to write the code more succinctly:
let map f l =
let rec loop cont = function
| [] -> cont []
| x::xs -> loop ( fun acc -> cont (f x::acc) ) xs
loop id l
Since the call to loop and cont are the last functions called with no additional work, they're tail-recursive.
This works because the continuation cont is captured by a new continuation, which in turn is captured by another, resulting in a sort of tree-like data structure as follows:
(fun acc -> (f 1)::acc)
((fun acc -> (f 2)::acc)
((fun acc -> (f 3)::acc)
((fun acc -> (f 4)::acc)
((fun acc -> (f 5)::acc)
(id [])))))
which builds up a list in-order without requiring you to reverse it.
For what its worth, start writing functions in non-tail recursive way, they're easier to read and work with.
If you have a big list to go through, use an accumulator variable.
If you can't find a way to use an accumulator in a convenient way and you don't have any other options at your disposal, use continuations. I personally consider non-trivial, heavy use of continuations hard to read.
An attempt at a shorter explanation than in the other examples:
let rec foo n =
match n with
| 0 -> 0
| _ -> 2 + foo (n-1)
let rec bar acc n =
match n with
| 0 -> acc
| _ -> bar (acc+2) (n-1)
Here, foo is not tail-recursive, because foo has to call foo recursively in order to evaluate 2+foo(n-1) and return it.
However, bar ís tail-recursive, because bar doesn't have to use the return value of the recursive call in order to return a value. It can just let the recursively called bar return its value immediately (without returning all the way up though the calling stack). The compiler sees this and optimized this by rewriting the recursion into a loop.
Changing the last line in bar into something like | _ -> 2 + (bar (acc+2) (n-1)) would again destroy the function being tail-recursive, since 2 + leads to an action that needs to be done after the recursive call is finished.
Here is a more obvious example, compare it to what you would normally do for a factorial.
let factorial n =
let rec fact n acc =
match n with
| 0 -> acc
| _ -> fact (n-1) (acc*n)
fact n 1
This one is a bit complex, but the idea is that you have an accumulator that keeps a running tally, rather than modifying the return value.
Additionally, this style of wrapping is usually a good idea, that way your caller doesn't need to worry about seeding the accumulator (note that fact is local to the function)
I'm learning F# too.
The following are non-tail recursive and tail recursive function to calculate the fibonacci numbers.
Non-tail recursive version
let rec fib = function
| n when n < 2 -> 1
| n -> fib(n-1) + fib(n-2);;
Tail recursive version
let fib n =
let rec tfib n1 n2 = function
| 0 -> n1
| n -> tfib n2 (n2 + n1) (n - 1)
tfib 0 1 n;;
Note: since the fibanacci number could grow really fast you could replace last line tfib 0 1 n to
tfib 0I 1I n to take advantage of Numerics.BigInteger Structure in F#
Also, when testing, don't forget that indirect tail recursion (tailcall) is turned off by default when compiling in Debug mode. This can cause tailcall recursion to overflow the stack in Debug mode but not in Release mode.
I need to generate permutations on a given list. I managed to do it like this
let rec Permute (final, arr) =
if List.length arr > 0 then
for x in arr do
let n_final = final # [x]
let rest = arr |> List.filter (fun a -> not (x = a))
Permute (n_final, rest)
else
printfn "%A" final
let DoPermute lst =
Permute ([], lst)
DoPermute lst
There are obvious issues with this code. For example, list elements must be unique. Also, this is more-less a same approach that I would use when generating straight forward implementation in any other language. Is there any better way to implement this in F#.
Thanks!
Here's the solution I gave in my book F# for Scientists (page 166-167):
let rec distribute e = function
| [] -> [[e]]
| x::xs' as xs -> (e::xs)::[for xs in distribute e xs' -> x::xs]
let rec permute = function
| [] -> [[]]
| e::xs -> List.collect (distribute e) (permute xs)
For permutations of small lists, I use the following code:
let distrib e L =
let rec aux pre post =
seq {
match post with
| [] -> yield (L # [e])
| h::t -> yield (List.rev pre # [e] # post)
yield! aux (h::pre) t
}
aux [] L
let rec perms = function
| [] -> Seq.singleton []
| h::t -> Seq.collect (distrib h) (perms t)
It works as follows: the function "distrib" distributes a given element over all positions in a list, example:
distrib 10 [1;2;3] --> [[10;1;2;3];[1;10;2;3];[1;2;10;3];[1;2;3;10]]
The function perms works (recursively) as follows: distribute the head of the list over all permutations of its tail.
The distrib function will get slow for large lists, because it uses the # operator a lot, but for lists of reasonable length (<=10), the code above works fine.
One warning: if your list contains duplicates, the result will contain identical permutations. For example:
perms [1;1;3] = [[1;1;3]; [1;1;3]; [1;3;1]; [1;3;1]; [3;1;1]; [3;1;1]]
The nice thing about this code is that it returns a sequence of permutations, instead of generating them all at once.
Of course, generating permutations with an imperative array-based algorithm will be (much) faster, but this algorithm has served me well in most cases.
Here's another sequence-based version, hopefully more readable than the voted answer.
This version is similar to Jon's version in terms of logic, but uses computation expressions instead of lists. The first function computes all ways to insert an element x in a list l. The second function computes permutations.
You should be able to use this on larger lists (e.g. for brute force searches on all permutations of a set of inputs).
let rec inserts x l =
seq { match l with
| [] -> yield [x]
| y::rest ->
yield x::l
for i in inserts x rest do
yield y::i
}
let rec permutations l =
seq { match l with
| [] -> yield []
| x::rest ->
for p in permutations rest do
yield! inserts x p
}
It depends on what you mean by "better". I'd consider this to be slightly more elegant, but that may be a matter of taste:
(* get the list of possible heads + remaining elements *)
let rec splitList = function
| [x] -> [x,[]]
| x::xs -> (x, xs) :: List.map (fun (y,l) -> y,x::l) (splitList xs)
let rec permutations = function
| [] -> [[]]
| l ->
splitList l
|> List.collect (fun (x,rest) ->
(* permute remaining elements, then prepend head *)
permutations rest |> List.map (fun l -> x::l))
This can handle lists with duplicate elements, though it will result in duplicated permutations.
In the spirit of Cyrl's suggestion, here's a sequence comprehension version
let rec permsOf xs =
match xs with
| [] -> List.toSeq([[]])
| _ -> seq{ for x in xs do
for xs' in permsOf (remove x xs) do
yield (x::xs')}
where remove is a simple function that removes a given element from a list
let rec remove x xs =
match xs with [] -> [] | (x'::xs')-> if x=x' then xs' else x'::(remove x xs')
IMHO the best solution should alleviate the fact that F# is a functional language so imho the solution should be as close to the definition of what we mean as permutation there as possible.
So the permutation is such an instance of list of things where the head of the list is somehow added to the permutation of the rest of the input list.
The erlang solution shows that in a pretty way:
permutations([]) -> [[]];
permutations(L) -> [[H|T] H<- L, T <- permutations( L--[H] ) ].
taken fron the "programming erlang" book
There is a list comprehension operator used, in solution mentioned here by the fellow stackoverflowers there is a helper function which does the similar job
basically I'd vote for the solution without any visible loops etc, just pure function definition
I'm like 11 years late, but still in case anyone needs permutations like I did recently. Here's Array version of permutation func, I believe it's more performant:
[<RequireQualifiedAccess>]
module Array =
let private swap (arr: _[]) i j =
let buf = arr.[i]
arr.[i] <- arr.[j]
arr.[j] <- buf
let permutations arr =
match arr with
| null | [||] -> [||]
| arr ->
let last = arr.Length - 1
let arr = Array.copy arr
let rec perm arr k =
let arr = Array.copy arr
[|
if k = last then
yield arr
else
for i in k .. last do
swap arr k i
yield! perm arr (k + 1)
|]
perm arr 0