I'm having a problem grouping these code lines into one function
sumFirstEven : int * int seq -> int
such that sumFirstEven (5, s) is the sum of the first 5 even elements of the sequence s
I've been told that I need to group my lines into one function that includes "let-in commands"
these are my lines for these func:
datatype 'a seq=null|SEQ of 'a*(unit->'a seq);
fun head(SEQ(x,_))=x
|head null=raise Empty;
fun tail(SEQ(_,xf))=xf()
|tail null=raise Empty;
fun sumFirstEven(0,_)=0
|sumFirstEven(n,null)=0
|sumFirstEven(n,xs)=if(head(xs) mod 2=0)then head(xs)+sumFirstEven(n-1,tail(xs))
else sumFirstEven(n,tail(xs));
fun seqFrom i=SEQ(i,fn()=>seqFrom(i+1));
val seqStart=seqFrom 1;
sumFirstEven(5,seqStart);
My function works fine but I dont know how to regroup all of these lines
correctly
The beauty of pattern matching is that it often obviates helper functions like head and tail.
fun sumFirstEven (0, _) = 0
| sumFirstEven (_, null) = 0
| sumFirstEven (n, SEQ (h, t)) =
case h mod 2
of 0 => h + sumFirstEven (n-1, t ())
| _ => sumFirstEven (n, t ())
Since the first two clauses didn't match, there's no need in the third clause to call a function with a failure condition like head... we already know the data is in the right form!
The pattern matching in the function clause serves the same role that a let-in-end expression (not command!) would.
Given your lazy list type,
datatype 'a seq = Null | Seq of 'a * (unit -> 'a seq)
you might want the helper function,
fun even n = n mod 2 = 0
and you might want to either recurse manually,
fun sumFirstEven (0, _) = 0
| sumFirstEven (_, Null) = 0
| sumFirstEven (n, Seq (x, seqf) =
if even x
then x + sumFirstEven (n-1, seqf ())
else sumFirstEven (n, seqf ())
or you may want to accumulate the result in a function parameter,
fun sumFirstEven (n, seq) =
let fun sfe (0, _, result) = result
| sfe (_, Null, result) = result
| sfe (n, Seq (x, seqf), result) =
if even x
then sfe (n-1, seqf (), result + x)
else sfe (n, seqf (), result)
in sfe (n, seq, 0) end
to make it tail-recursive (i.e. use a fixed amount of stack frames). More conveniently, you might want to extract the recursion part of the function into a separate higher-order fold combinator,
fun foldseqn _ e 0 _ = e
| foldseqn _ e _ Null = e
| foldseqn f e n (Seq (x, seqf)) =
case f (x, e) of
(e', true) => foldseqn f e' (n-1) (seqf ())
| (e', false) => foldseqn f e' n (seqf ())
fun sumFirstEven (n, seq) =
foldseqn (fn (x, sum) => if even x
then (sum + x, true)
else (sum, false)) 0 n seq
And a quick test,
fun nats n = Seq (n, fn () => nats (n+1))
val twelve = sumFirstEven (3, nats 1) (* 2+4+6 *)
Edit: Responded to Nick's comment, thanks.
Related
How to create a tuple list from one single list, like so:
[1; 2; 4; 6] -> [(1, 2); (4, 6)]
I want to do it using function List.fold_left since I'm trying to learn that currently but don't know how... Is there a way? Or should I leave it like that?
This is a working code that doesn't use List.fold_left:
let rec create_tuple acc l = match l with
| [] -> acc
| x :: y :: l' -> create_tuple (acc # [(x, y)]) l'
| _ -> acc
List.fold_left reads elements one by one. There is no direct way to make it read elements two by two.
It really is pointless complication (great for teaching, though), but if you absolutely want to use List.fold_left here, your accumulator needs to somehow record the state of the traversal:
either you have read an even number of elements so far,
or you have read an odd number and then you have to record what was the last element you read, so that, upon reading the following one, you can pair them.
Here is a way to do it. I use an algebraic datatype to represent the state.
(* This is the type that we’ll use for the accumulator;
the option component is the state of the traversal.
(None, acc) means that we have read an even number of elements so far;
(Some x, acc) means that we have read an odd number of elements so far,
the last of which being x. *)
type 'a accumulator = 'a option * ('a * 'a) list
let folder (state, acc) x =
match state with
| None -> (Some x, acc)
| Some y -> (None, (y,x)::acc)
let create_pairs l =
let (_, acc) = List.fold_left folder (None, []) l in
List.rev acc
Also notice how I avoid the complexity bug that I outlined in a comment: I add elements in reverse order (i.e. at the head of the accumulating list), and at the very end I reverse that list.
#Maëlan's answer is beautiful, but what if we want to get triples rather than pairs? Is there a way we can use List.fold_left to handle this more generically?
let chunks n lst =
let (_, _, acc) = List.fold_left
(fun (counter, chunk, lst') x ->
if counter = n - 1 then
(0, [], List.rev (x :: chunk) :: lst')
else
(counter + 1, x :: chunk, lst'))
(0, [], [])
lst
in
List.rev acc
Using this, chunks 2 [1; 2; 4; 6] returns [[1; 2]; [4; 6]]. We can map this to the result you're looking for with a very simple function that takes a list with two elements and creates a tuple with two elements.
chunks 2 [1; 2; 4; 6] |> List.map (fun [x; y] -> (x, y))
And we get:
[(1, 2), (4, 6)]
This could be used to implement a triples function.
let create_triples lst =
chunks 3 lst |> List.map (fun [x; y; z] -> (x, y, z));;
And now create_triples [1; 2; 3; 4; 5; 6; 7; 8; 9] returns [(1, 2, 3); (4, 5, 6); (7, 8, 9)].
I tried this question(using List.fold_left) and this is the best I could come up with:
type 'a node = First of 'a | Second of ('a * 'a)
let ans =
List.fold_left
(
fun a e ->
match a with
| [] -> (First e)::a
| (First f)::tl -> Second(f, e)::tl
| (Second n)::tl -> (First e)::(Second n)::tl
)
[]
[1; 2; 3; 4; 5; 6; ]
let () =
List.iter
(
fun e ->
match e with
| First f ->
print_endline(string_of_int f)
| Second (f, s) ->
Printf.printf "(%d, %d)" f s
)
(List.rev ans)
Just to make my answer all there...
type 'a node = One of 'a | Two of ('a * 'a)
let ans =
(List.map
(
fun e ->
match e with
| One _ -> failwith "Should only be Two's"
| Two (f, s) -> (f, s)
)
(List.filter
(
fun e ->
match e with
| One _ -> false
| Two _ -> true
)
(List.rev
(List.fold_left
(
fun a e ->
match a with
| [] -> (One e)::[]
| (One o)::tl -> (Two (o, e))::tl
| (Two t)::tl -> (One e)::(Two t)::tl
)
[]
(List.init 10 (fun x -> x + 1))
)
)
)
)
let () =
List.iter
(fun (f, s) -> Printf.printf "(%d, %d) " f s)
ans
I'm trying to get a list of primes of two digits by running these codes in LearnOcaml. The codes compile if I restrict the parameter of the listify method, which returns a list from a stream, to be less than 20. Otherwise, it either never halt or return "Exception: Js_of_ocaml__Js.Error _.". I don't think the code is semantically wrong. So I'm
wondering if anyone can help resolve the problem?
type 'a stream = Eos | StrCons of 'a*(unit -> 'a stream)
(*integers from n onwards*)
let rec nums_from n =
StrCons(n,fun () -> nums_from (n+1))
let rec filterStr (test : 'a -> bool) (s: 'a stream) =
match s with
|Eos -> Eos
|StrCons(q,w) -> if test q then StrCons(q,fun ()-> filterStr test (w ()))
else filterStr test (w ())
(*Remove all numbers mod p*)
let sift p =
filterStr (fun x -> x mod p <> 0)
(*Sieves*)
let rec sieves s =
match s with
|Eos ->Eos
|StrCons(x,g) -> StrCons(x, fun ()-> sieves (sift x (g ())))
(*primes*)
let allprimes = sieves (nums_from 2)
let rec listify s n=
if n =0 then [] else
match s with
|Eos -> []
|StrCons(q,w) -> q::(listify (w ()) (n-1))
let twodigitsprimes = filterStr (fun x -> x > 10&& x<100) allprimes
let twodigitsprimeslist= listify twodigitsprimes 21
It appears that filterStr is looping while trying to create the StrCons that represents the next element after the 21st. Since there are only 21 2-digit primes, this will loop forever.
Note that when listify is called with n = 0, the StrCons has already been constructed; it just isn't examined. But the StrCons for this case diverges (and OCaml is a strict language).
You can get things to work using this version of listify:
let rec listify s n =
if n = 0 then []
else
match s with
| Eos -> []
| StrCons (q, w) ->
if n = 1 then [q] else q :: listify (w ()) (n - 1)
I'm a beginner in OCaml and algorithms.
I'm trying to get the number of 5 digits numbers with no repeating digits bigger than 12345.
Here is what I did in OCaml, I tried to make as tail recursive as possible, and I also used streams. But still, due to size, it stack overflowed:
type 'a stream = Eos | StrCons of 'a * (unit -> 'a stream)
let rec numberfrom n= StrCons (n, fun ()-> numberfrom (n+1))
let nats = numberfrom 1
let rec listify st n f=
match st with
|Eos ->f []
|StrCons (m, a) ->if n=1 then f [m] else listify (a ()) (n-1) (fun y -> f (m::y))
let rec filter (test: 'a-> bool) (s: 'a stream) : 'a stream=
match s with
|Eos -> Eos
|StrCons(q,w) -> if test q then StrCons(q, fun ()->filter test (w ()))
else filter test (w ())
let rec check_dup l=
match l with
| [] -> false
| h::t->
let x = (List.filter (fun x -> x = h) t) in
if (x == []) then
check_dup t
else
true;;
let digits2 d =
let rec dig acc d =
if d < 10 then d::acc
else dig ((d mod 10)::acc) (d/10) in
dig [] d
let size a=
let rec helper n aa=
match aa with
|Eos-> n
|StrCons (q,w) -> helper (n+1) (w())
in helper 0 a
let result1 = filter (fun x -> x<99999 && x>=12345 && (not (check_dup (digits2 x)))) nats
(* unterminating : size result1 *)
(*StackOverflow: listify result1 10000 (fun x->x) *)
I can't reproduce your reported problem. When I load up your code I see this:
# List.length (listify result1 10000 (fun x -> x));;
- : int = 10000
# List.length (listify result1 26831 (fun x -> x));;
- : int = 26831
It's possible your system is more resource constrained than mine.
Let me just say that the usual way to code a tail recursive function is to build the list up in reverse, then reverse it at the end. That might look something like this:
let listify2 st n =
let rec ilist accum st k =
match st with
| Eos -> List.rev accum
| StrCons (m, a) ->
if k = 1 then List.rev (m :: accum)
else ilist (m :: accum) (a ()) (k - 1)
in
if n = 0 then []
else ilist [] st n
You still have the problem that listify doesn't terminate if you ask for more elements than there are in the stream. It might be better to introduce a method to detect the end of the stream and return Eos at that point. For example, the filter function might accept a function that returns three possible values (the element should be filtered out, the element should not be filtered out, the stream should end).
The problem is that the size of your stream result1 is undefined.
Indeed, nats is an never-ending stream: it never returns Eos.
However, filtering a never-ending stream results in another never-ending stream
since a filtered stream only returns Eos after the underlying stream does so:
let rec filter (test: 'a-> bool) (s: 'a stream) : 'a stream=
match s with
| Eos -> Eos
| StrCons(q,w) -> if test q then StrCons(q, fun ()->filter test (w ()))
else filter test (w ())
Consequently, size result1 is stuck trying to reach the end of integers.
Note also that, in recent version of the standard library, your type stream is called Seq.node.
I want to write a function that gives the cartesiant product of two sequences that's what i did but i thought that it can be interesting to have less complexity with I want to browsing once the first sequence s1 and n times the second using map and then append all the results:
`let cartesian_product a b =
let na = length a in
let nb = length b in
init
(na * nb)
(fun j -> let i = j / nb in
at a i, at b (j - i*nb))
`
that's what i did for the moment :
`let rec cartesian_product a b =
let rec aux x b () = match b () with
| Nil -> Nil
| Cons(e, b) -> Cons ((x, e), aux x b)
in
match a () with
| Nil -> nil
| Cons (x, a) -> append (aux x b) (cartesian_product a b)`
but i didn't use map (is there a better way for doing that)??
Your aux function is essentially a specific case of map so you can write:
let rec cartesian_product a b = match a () with
| Nil -> Nil
| Cons (x, a) -> append (map (fun e -> (x, e)) b) (cartesian_product a b)
As a rule of thumb when you feel the need to write a function called aux, take a step back and think whether you can use map or fold. In fact, you could improve my code by using a fold instead of deconstructing the sequence yourself.
Here an example of the algorithm with a structure of list :
let cartesian_product a b =
let open List in
let mk_tuple l n = map (fun x -> (n,x)) l in
a |> map (mk_tuple b) |> fold_left append []
This will give you :
cartesian_product [0;1] [2;3];;
- : (int * int) list = [(0, 2); (0, 3); (1, 2); (1, 3)]
I'm trying to make a function which can return the specific nth element of lazylist.
Here is what I made:
datatype 'a lazyList = nullList
| cons of 'a * (unit -> 'a lazyList)
fun Nth(lazyListVal, n) = (* lazyList * int -> 'a option *)
let fun iterator (laztListVal, cur, target) =
case lazyListVal of
nullList => NONE
| cons(value, tail) => if cur = target
then SOME value
else iterator (tail(), cur+1, target)
in
iterator(lazyListVal,1,n)
end
I expected the result that as recusing proceeds, eventually the variable cur gets same as the variable target, and then the function iterator returns SOME value so it will return the final nth element.
But when I compile it and run, it only returns the very first element however I test with the lazylist objects.
Please figure what is the problem. I have no idea...
cf) I made another function which is relevant to this problem, the function that transforms lazylist into SML original list containing the first N values. Codes above:
fun firstN (lazyListVal, n) = (* lazyList * int -> 'a list *)
let fun iterator (lazyListVal, cur, last) =
case lazyListVal of
nullList => []
| cons(value, tail) => if cur = last
then []
else value::iterator(tail(),cur+1,last)
in
iterator(lazyListVal,0,n)
end
The strange thing is the function firstN is properly working.
The problem is that your iterator function does case lazyListVal of ..., but the recursive tail is called laztListVal, so for every iteration, it keeps looking at the first list. Use better variable names to avoid this kind of "invisible" bug.
For a simpler definition of nth:
datatype 'a lazyList = NullList | Cons of 'a * (unit -> 'a lazyList)
fun nth (NullList, _) = NONE
| nth (Cons (x, xs), 0) = SOME x
| nth (Cons (_, xs), n) = nth (xs (), n-1)
val nats = let fun nat n = Cons (n, fn () => nat (n+1)) in nat 0 end
val ten = nth (nats, 10)
Edit: While function pattern matching is ideal here, you could also have used a case ... of ... here. A helper function seems unnecessary, though, since you can simply use the input argument n as the iterator:
fun nth (L, n) =
case (L, n) of
(NullList, _) => NONE
| (Cons (x, xs), 0) => SOME x
| (Cons (_, xs), n) => nth (xs (), n-1)
You may however want to make the function more robust:
fun nth (L, n) =
let fun nth' (NullList, _) = NONE
| nth' (Cons (x, xs), 0) = SOME x
| nth' (Cons (_, xs), n) = nth' (xs (), n-1)
in if n < 0 then NONE else nth' (L, n) end
Here having a helper function ensures that n < 0 is only checked once.
(You could also raise Domain, since negative indices are not well-defined.)