Ocaml how to summing individual elements with tail recursion? - functional-programming

The thing is simple i think, the problem is:
With a given int list as example [25;30;45;60] return a int list with values [25;30+25;45+30+25;60+45+30+25].
I have 2 versions of the code (no one works).
let accu_weather lst =
let rec aux acc lst2 = function
| [] -> []
| h::t -> aux((acc+h) lst2::(h+acc)) lst
in 0 []
let accu_weather lst =
let rec accu lst2 = function
| [] -> []
| [x] -> x
| h::t -> (h+accu(t))::lst2
in accu List.rev(lst)
Someone knows the solution, and what im doing wrong??
Thanks!!

You wrote,
let accu_weather lst =
let rec aux acc lst2 = function
| [] -> []
| h::t -> aux((acc+h) lst2::(h+acc)) lst
in 0 []
First, here
in 0 []
You're applying 0 to an empty list. That doesn't make sense. There you should be making some call to your auxiliary function with the right arguments.
And here,
| h::t -> aux((acc+h) lst2::(h+acc)) lst
You are applying aux to ((acc+h) lst2::(h+acc)) and lst. What is the type of your first argument? and what is lst?
I'd suggest you start with a simpler exercise first. Such as just calculating the sum of the elements of the list (using an accumulator).

Try this:
let rec accu list =
match list with
|[] -> []
|l::[] -> [l]
|l::l1::r -> l::accu ((l1+l)::r);;

Related

F# - Traverse a tree defined not as a structure, but as a function: ls: 'a -> 'a seq

tldr; go to My Question
I believe that the problem presented here must not be at all new, but I have failed to find any directly corresponding discussion.
Let's say that I have the following function (in order to provide a deterministic substitute for a real-world function having the same structural properties, of type 'a -> 'a seq):
// I'm a function that looks suspiciously like a tree
let lsExample x =
match x with
| 0 -> seq { 1; 6; 7 }
| 1 -> seq { 2; 3 }
| 3 -> seq { 4; 5 }
| 7 -> seq { 8; 9 }
| _ -> Seq.empty
Now, I wish to have the following:
let lsAll: ('a -> 'a seq) -> 'a -> 'a seq
such that
lsAll lsExample 0
evaluates to
seq { 0 .. 9 }
I have found one long-winded solution to this, and one simple, but still not ideal, solution to a similar problem.
Solution 1
Convert the ls function to a Rose Tree, then do a pre-order dfs on the tree, as follows:
open FSharpx.Collections
module L = LazyList
module R = Experimental.RoseTree
let rec asRoseTree (ls: 'a -> seq<'a>) (item: 'a) =
let children = ls item
if (Seq.isEmpty children) then
R.singleton item
else
children
|> Seq.map (asRoseTree ls)
|> L.ofSeq
|> R.create item
let lsAll ls =
asRoseTree ls >> R.dfsPre
Solution 2
Having got the job done, I wanted a more elegant solution, so started with this approximation using 'a -> 'a list (lists offer structural pattern matching, whereas seqs don't... I hope no one ever uses this implementation):
let rec lsAll' (ls: 'a -> 'a list) (xs: 'a list) =
match xs with
| [] -> []
| [x] -> lsAll' ls (ls x) |> List.append [x]
| x :: tail -> lsAll' ls tail |> List.append (lsAll' ls [x])
let lsAll ls x = lsAll' ls [x]
I then got stumped trying to make this tail-recursive, even without the extra inconvenience of switching back to seq.
My question
How can we implement lsAll:
without resorting to constructing an intermediate, explicit tree structure;
with the desired types (seq, not list);
using tail recursion (a case for CPS?); and
without explicit self recursion (e.g. use a fold with accumulator/cps)?
Aside: Having got the job done and written this question up, I'm now thinking that getting the input function into a tree structure might not be a waste at all, and I should have made better use of it. That said, I'm still too curious to give up on this quest!
You can do this very nicely using F# sequence expressions and the yield and yield! constructs:
let rec lsAll ls x = seq {
yield x
for c in ls x do
yield! lsAll ls c }
lsAll lsExample 0
A sequence expression seq { .. } is a code block that generates a sequence. Inside this, you can use yield to add a single element to the sequence but also yield! to add all elements of some other sequence. Here, you can do this to include all values produced by a recursive call.
You could combine this with the approach in your solution 2 too:
let rec lsAll ls xs = seq {
match xs with
| [] -> ()
| x::xs ->
yield x
yield! lsAll ls (ls x)
yield! lsAll ls xs }
This requires lsAll to return a list - you could insert List.ofSeq on the line before the last, but I think it's probably best to leave this to the user. However, you can now turn this into tail-recursive version by using CPS where the continuation is "sequence of values to be produced after the current one is done":
let rec lsAll ls xs cont = seq {
match xs with
| [] -> yield! cont
| x::xs ->
yield x
yield! lsAll ls (ls x) (lsAll ls xs cont) }
lsAll (lsExample >> List.ofSeq) [0] Seq.empty
If I give this an infinite tree, it does not actually StackOverflow, but keeps allocating more and more memory, so I guess it works!

F# adding lists

How would I go about adding sub-lists.
For example, [ [10;2;10]; [10;50;10]] ----> [20;52;20] that is 10+10, 2+50 and 10+10. Not sure how to start this.
Fold is a higher order function:
let input = [[10;2;10]; [10;50;10]]
input |> Seq.fold (fun acc elem -> acc + (List.nth elem 1)) 0
val it : int = 52
Solution 1: Recursive version
We need a helper function to add two lists by summing elements one-to-one. It is recursive and assumes that both lists are of the same length:
let rec sum2Lists (l1:List<int>) (l2:List<int>) =
match (l1,l2) with
| ([],[]) -> []
| (x1::t1, x2::t2) -> (x1+x2)::sum2Lists t1 t2
Then the following recursive function can process a list of lists, using our helper function :
let rec sumLists xs =
match xs with
| [] -> [] // empty list
| x1::[] -> x1 // a single sublist
| xh::xt -> sum2Lists xh (sumLists xt) // add the head to recursion on tail
let myres = sumLists mylist
Solution 2: higher order function
Our helper function can be simplified, using List.map2:
let sum2hfLists (l1:List<int>) (l2:List<int>) = List.map2 (+) l1 l2
We can then use List.fold to create an on the flow accumulator using our helper function:
let sumhfList (l:List<List<int>>) =
match l with
| [] -> [] // empty list of sublist
| h::[] -> h // list with a single sublist
| h::t -> List.fold (fun a x -> sum2hfLists a x) h t
The last match case is applied only for lists of at least two sublists. The trick is to take the first sublist as starting point of the accumulator, and let fold execute on the rest of the list.

ERLANG, map for infinite list

I wanted to write a map for an infinite list.
This is, what I have so far:
-module(map).
-export([ints/0,take/2,map/2, double_int/1]).
ints() -> ints_from(0).
take(0, _) -> [];
take(N, [H|LazyT]) -> [H | take(N-1, LazyT())].
double_int(N) -> 2 * N.
map(_, []) -> [];
map(F, [H | T]) -> [F(H) | map(F, T())].
ints_from(N) -> [N | fun () -> ints_from(N+1) end].
The problem is, that with the call
> L = map:ints().
[0|#Fun<map.0.104601022>]
> R = map:map(fun map:double_int/1, L).
I get a never ending process. I guess, the map is proceeding through the whole infinite list and therefore never ending.
What am I doing wrong?
Since you represent lazy lists as lists whose tail is a function, your definition of map needs to return such a value as well:
map(_, []) -> [];
map(F, [H | T]) -> [F(H) | fun() -> map(F, T()) end].

F# Cutting a list in half using functional programming

I am trying to input a list into the function and it send me a list with the first half of the elements taken away using f# with the below recursion but I keep running into a base case problem that I just cant figure out. any thoughts? I am using the second shadow list to count how far I need to go until I am half way into the list (by removing two elements at a time)
let rec dropHalf listToDrop shadowList =
match shadowList with
| [] -> listToDrop
| shadowHead2::shadowHead1::shadowTail -> if shadowTail.Length<=1 then listToDrop else
match listToDrop with
|[] -> listToDrop
|listToDropHead::listToDropTail -> dropHalf listToDropTail shadowTail
let rec dropHalf listToDrop shadowList =
match shadowList with
| [] -> listToDrop
| shadowHead2::[] -> listToDrop (* odd number! *)
| shadowHead1::shadowHead2::shadowTail ->
match listToDrop with
| [] -> listToDrop (* should never happen? *)
| listToDropHead::listToDropTail -> dropHalf listToDropTail shadowTail
i'm afraid i don't use F#, but it's similar to ocaml, so hopefully the following is close to what you're looking for (maybe the comment format has changed?!). the idea is that when you exhaust the shadow you're done. your code was almost there, but the test for length on the shadow tail made no sense.
i want to emphasize that this isn't anything like anyone would write "in real life", but it sounds like you're battling with some weird requirements.
Because you use the shadow list with the same length as the original list and remove elements from these lists with different rates, it's better to create an auxiliary function:
let dropHalf xs =
let rec dropHalf' ys zs =
match ys, zs with
| _::_::ys', _::zs' -> dropHalf' ys' zs'
| _, zs' -> zs' (* One half of the shadow list ys *)
dropHalf' xs xs
If you don't care to traverse the list twice, the following solution is simpler:
let rec drop n xs =
match xs, n with
| _ when n < 0 -> failwith "n should be greater or equals to 0"
| [], _ -> []
| _, 0 -> xs
| _::xs', _ -> drop (n-1) xs'
let dropHalf xs =
xs |> drop (List.length xs/2)
and another simple solution needs some extra space but doesn't have to use recursion:
let dropHalf xs =
let xa = Array.ofList xs
xa.[xa.Length/2..] |> List.ofArray
As a general rule of thumb, if you're calling Length on a list, then there is most likely a better way to do what you're doing. Length has to iterate the entire list and is therefore O(n).
let secondHalf list =
let rec half (result : 'a list) = function
| a::b::sx -> half result.Tail sx
// uncomment to remove odd value from second half
// | (a::sx) -> result.Tail
| _ -> result
half list list
Here is a sample does what you described.
open System
open System.Collections.Generic
let items = seq { 1 .. 100 } |> Seq.toList
let getBackOfList ( targetList : int list) =
if (targetList.Length = 0) then
targetList
else
let len = targetList.Length
let halfLen = len / 2
targetList |> Seq.skip halfLen |> Seq.toList
let shortList = items |> getBackOfList
("Len: {0}", shortList.Length) |> Console.WriteLine
let result = Console.ReadLine()
Hope this helps

Recursive lambdas in F#

Take this example code (ignore it being horribly inefficient for the moment)
let listToString (lst:list<'a>) = ;;' prettify fix
let rec inner (lst:list<'a>) buffer = ;;' prettify fix
match List.length lst with
| 0 -> buffer
| _ -> inner (List.tl lst) (buffer + ((List.hd lst).ToString()))
inner lst ""
This is a common pattern I keep coming across in F#, I need to have an inner function who recurses itself over some value - and I only need this function once, is there in any way possible to call a lambda from within it self (some magic keyword or something) ? I would like the code to look something like this:
let listToString2 (lst:list<'a>) = ;;' prettify fix
( fun
(lst:list<'a>) buffer -> match List.length lst with ;;' prettify fix
| 0 -> buffer
| _ -> ##RECURSE## (List.tl lst) (buffer + ((List.hd lst).ToString()))
) lst ""
But as you might expect there is no way to refer to the anonymous function within itself, which is needed where I put ##RECURSE##
Yes, it's possible using so called y-combinators (or fixed-point combinators). Ex:
let rec fix f x = f (fix f) x
let fact f = function
| 0 -> 1
| x -> x * f (x-1)
let _ = (fix fact) 5 (* evaluates to "120" *)
I don't know articles for F# but this haskell entry might also be helpful.
But: I wouldn't use them if there is any alternative - They're quite hard to understand.
Your code (omit the type annotations here) is a standard construct and much more expressive.
let listToString lst =
let rec loop acc = function
| [] -> acc
| x::xs -> loop (acc ^ (string x)) xs
loop "" lst
Note that although you say you use the function only once, technically you refer to it by name twice, which is why it makes sense to give it a name.

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