I want to write the function residue l n which calculates the residue of n by l by making an iterative calculation starting with n and using the items in the list in order. The calculation is as follows:
-initially the residue is the value of n
-each element e of l (taken in the order of the list) changes the residue in the following way:
if e and the residue are of the same parity (both even or both odd) then the new residue is the sum of r and e, otherwise it is the difference between r and e (r-e).
-the last residue is the result of the game.
Example: residu [1;3] 7 returns 5 as a result of the following calculations:
7 + 1 (same parity +) = 8
8 - 3 (parité différente -) = 5
This is my code but it doesn't seem to be working:
let rec residue l n =
if l = [] then 0 else
if (((List.hd l) mod 2 <> 0) && (n mod 2 <> 0 )) || (((List.hd l) mod 2 == 0) && (n mod 2 == 0 ))
then
(List.hd l) + residue (List.tl l) ((List.hd l)+ n) else
n - (List.hd l) - residue (List.tl l) (n - (List.hd l));;
residu [1;3] 7;;
- : int = 6 (The correct result should be 5)
Thank you for your help.
Here is my stab at it.
let rec residue l n =
let parity a b =
if ((a mod 2 <> 0) && (b mod 2 <> 0)) ||
((a mod 2 == 0) && (b mod 2 == 0)) then true else false in
match l, n with
| [], n -> n
| (x::xs), n -> if parity x n then residue xs (n+x) else residue xs (n-x)
Hope it helps for figuring out the problem.
Related
How to compute the sum of each element of a list multiplied by it's index position in OCaml? example: for [4;7;9] the result is 45 (4x1 + 7x2 + 9x3 = 45). the only authorized functions are List.hd, List.tl et List.length.
I can do it in the other direction with this code:
let rec sum l =
let n = (List.length l) + 1 in
if l = [] then 0 else
((List.hd l)*(n-1))+ (sum(List.tl l)) ;;
sum [4;7;9];;
- : int = 35 (4x3 + 7x2 + 9x1 = 35)
But the expected result is 45 (4x1 + 7x2 + 9x3 = 45).
thank you for your help.
Personally, I'd probably do something like this..
let rec new_sum l n =
match l with
| [] -> 0
| head::tail -> (head * n) + new_sum tail (n+1)
let sum l =
new_sum l 1;;
sum [4;7;9]
...if you don't like the guards for pattern matching, and prefer List.hd, List.tl, List.length then you could use...
let rec new_sum l n =
if (List.length l == 0) then 0
else ((List.hd l) * n) + new_sum (List.tl l) (n+1)
let sum l =
new_sum l 1;;
sum [4;7;9];
Can I get a brief explanation why this proof effort fails?
In my studies I'm trying to recognize simple patterns in generated lists of integers.
The generator below produces a list of alternating 0s and 1s. I'd like to prove that items at even indexes are 0.
val evenb : nat -> bool
let rec evenb n =
match n with
| 0 -> true
| 1 -> false
| n -> evenb (n - 2)
val nth_item : ls: list nat {length ls > 0} -> n: nat {n < length ls} -> nat
let rec nth_item ls n =
match ls with
| [h] -> h
| h :: t -> if n = 0 then h else nth_item t (n - 1)
val gen_01 : lng: nat {lng >= 2 && evenb lng} -> ls: list nat {length ls = lng}
let rec gen_01 lng =
match lng with
| 2 -> [0; 1]
| _ -> [0; 1] # gen_01 (lng - 2)
let rec lemma_01 (lng: nat {lng >= 2 && evenb lng}) :
Lemma (forall (n: nat {n <= lng - 2 && evenb n}) . (nth_item (gen_01 lng) n) = 0) =
match lng with
| 2 -> ()
| _ -> lemma_01 (lng - 2)
FStar returns 'could not prove post-condition'.
I'd appreciate any help regarding the approach.
F* should also report a secondary error location pointing to the conjunct in the postcondition that was not provable---in this case, it's just the nth_item (gen_01 lng) n = 0 goal.
One way to diagnose this is to consider one branch of the proof at a time. E.g. if you add an admit(); in the second branch, then you'll see that the first branch is easily provable. So, what's going wrong is the inductive case. You don't have a strong enough induction hypothesis to prove the property you want.
Here's one proof of it ... there are probably many others.
First, I proved this:
let rec access_2n (l:nat{l >= 2 && evenb l}) (n:nat{2 * n < l})
: Lemma (ensures nth_item (gen_01 l) (2 * n) = 0)
= match n with
| 0 -> ()
| _ -> access_2n (l - 2) (n - 1)
Notice the induction on the pair l, n so that the length and the access index decrease together.
This is pretty much the property you wanted to prove, stated slightly differently. To massage it into the form you want, I did this:
First, a lemma to interpret evenb arithmetically:
[Edit: I added an open FStar.Mul to bring the * symbol into scope for multiplication]
open FStar.Mul
let rec evenb_is_even (n:nat{evenb n})
: Lemma (2 * (n / 2) = n)
= match n with
| 0 -> ()
| _ -> evenb_is_even (n - 2)
Then to prove something very like your lemma, but for an explicit n.
let lemma_01_aux (lng: nat {lng >= 2 && evenb lng}) (n:nat{n <= lng - 2 && evenb n})
: Lemma (nth_item (gen_01 lng) n = 0)
= access_2n lng (n / 2); evenb_is_even n
And finally to universally quantify over n using a library that turns lemmas into quantified postconditions.
let lemma_01 (lng: nat {lng >= 2 && evenb lng})
: Lemma (forall (n: nat {n <= lng - 2 && evenb n}) . (nth_item (gen_01 lng) n) = 0)
= FStar.Classical.forall_intro_2 lemma_01_aux
So I have to make a decimal number into binary list like so: intToBitString 4 = [1,0,0].
Which i have done like so:
intToBitString n = reverse (helper n)
helper 0 = []
helper n
| n `mod` 2 == 1 = 1 : helper (n `div` 2)
| n `mod` 2 == 0 = 0 : helper(n `div` 2)
But then I also have to make a function called intToByte, which pads out the list with 0-s until it's length is 8 elements long. (so making it a bytestring) Like this:
intToByte 7 = [0, 0, 0, 0, 0, 1, 1, 1]
I have tried so many things, but they never work. I am a beginner, so I only know the "if" loop the way I showed above, and recursion, but I dont know anything fancy. One of my tries:
intToByte 0 = [0]
intToByte n
| eight n == helper2 n = reverse (helper2 n)
| otherwise = eight n
helper2 0 = []
helper2 n
| n `mod` 2 == 1 = 1 : helper2 (n `div` 2)
| n `mod` 2 == 0 = 0 : helper2 (n `div` 2)
eight n
| length (helper2 n) < 8 = 0 : eight n
| otherwise = helper2 n
I have been working on this for so many hours that i'm getting confused by it. But this is part of an important assignment, so help would be very appreciated!
First of all, you can simplify your code with:
helper2 :: Integral i => i -> [i]
helper2 0 = []
helper2 n = r : helper2 q
where (q,r) = quotRem n 2
Secondly, the above is a big endian representation [wiki]. Indeed, 7 is represented as [1,1,1], whereas 14 is for example represented as [0,1,1,1]. If we want to revers this, we can work with an accumulator:
helper2 :: Integral i => i -> [i]
helper2 = go []
where go rs 0 = rs
go rs n = go (r:rs) q
where (q,r) = quotRem n 2
This thus maps 7 to [1,1,1] and 14 to [1,1,1,0]. But now we still need to add leading zeros. We can do that for example by maintaing the number of elements already added to the list:
eight :: Integral i => i -> [i]
eight = go [] 0
where go rs l 0 = replicate (8-l) 0 ++ rs
go rs l n = go (r:rs) (l+1) q
where (q,r) = quotRem n 2
Padding can be as simple as computing how many additional elements to push to the list and then have those elements produced using the function replicate from the Prelude:
padLeft :: Int -> a -> [a] -> [a]
padLeft n x xs = replicate (n - length xs) x ++ xs
For instance:
> padLeft 8 0 [1, 1, 0]
[0,0,0,0,0,1,1,0]
One approach would be to define a function bits such that bits k converts its argument to a bit string of length k:
bits :: Int -> Int -> [Int]
bits 0 _n = []
bits k n | n < 0 = error "bits: negative"
| n > 2 * m - 1 = error "bits: overflow"
| otherwise = let (i, j) = n `divMod` m in i : bits (k - 1) j
where m = 2 ^ (k - 1)
Your function eight is then easily written as
eight :: Int -> [Int]
eight = bits 8
This gives:
> eight 4
[0,0,0,0,0,1,0,0]
> eight 7
[0,0,0,0,0,1,1,1]
This F# code is an attempt to solve Project Euler problem #58:
let inc = function
| n -> n + 1
let is_prime = function
| 2 -> true
| n when n < 2 || n%2=0-> false
| n ->
[3..2..(int (sqrt (float n)))]
|> List.tryFind (fun i -> n%i=0)
|> Option.isNone
let spir = Seq.initInfinite (fun i ->
let n = i%4
let a = 2 * (i/4 + 1)
(a*n) + a + (a-1)*(a-1))
let rec accum se p n =
match se with
| x when p*10 < n && p <> 0 -> 2*(n/4) + 1
| x when is_prime (Seq.head x) -> accum (Seq.tail x) (inc p) (inc n)
| x -> accum (Seq.tail x) p (inc n)
| _ -> 0
printfn "%d" (accum spir 0 1)
I do not know the running time of this program because I refused to wait for it to finish. Instead, I wrote this code imperatively in C++:
#include "stdafx.h"
#include "math.h"
#include <iostream>
using namespace std;
int is_prime(int n)
{
if (n % 2 == 0) return 0;
for (int i = 3; i <= sqrt(n); i+=2)
{
if (n%i == 0)
{
return 0;
}
}
return 1;
}
int spir(int i)
{
int n = i % 4;
int a = 2 * (i / 4 + 1);
return (a*n) + a + ((a - 1)*(a - 1));
}
int main()
{
int n = 1, p = 0, i = 0;
cout << "start" << endl;
while (p*10 >= n || p == 0)
{
p += is_prime(spir(i));
n++; i++;
}
cout << 2*(i/4) + 1;
return 0;
}
The above code runs in less than 2 seconds and gets the correct answer.
What is making the F# code run so slowly? Even after using some of the profiling tools mentioned in an old Stackoverflow post, I still cannot figure out what expensive operations are happening.
Edit #1
With rmunn's post, I was able to come up with a different implementation that gets the answer in a little under 30 seconds:
let inc = function
| n -> n + 1
let is_prime = function
| 2 -> true
| n when n < 2 || n%2=0-> false
| n ->
[3..2..(int (sqrt (float n)))]
|> List.tryFind (fun i -> n%i=0)
|> Option.isNone
let spir2 =
List.unfold (fun state ->
let p = fst state
let i = snd state
let n = i%4
let a = 2 * (i/4 + 1)
let diag = (a*n) + a + (a-1)*(a-1)
if p*10 < (i+1) && p <> 0 then
printfn "%d" (2*((i+1)/4) + 1)
None
elif is_prime diag then
Some(diag, (inc p, inc i))
else Some(diag, (p, inc i))) (0, 0)
Edit #2
With FuleSnabel's informative post, his is_prime function makes the above code run in under a tenth of a second, making it faster than the C++ code:
let inc = function
| n -> n + 1
let is_prime = function
| 1 -> false
| 2 -> true
| v when v % 2 = 0 -> false
| v ->
let stop = v |> float |> sqrt |> int
let rec loop vv =
if vv <= stop then
if (v % vv) <> 0 then
loop (vv + 2)
else
false
else
true
loop 3
let spir2 =
List.unfold (fun state ->
let p = fst state
let i = snd state
let n = i%4
let a = 2 * (i/4 + 1)
let diag = (a*n) + a + (a-1)*(a-1)
if p*10 < (i+1) && p <> 0 then
printfn "%d" (2*((i+1)/4) + 1)
None
elif i <> 3 && is_prime diag then
Some(diag, (inc p, inc i))
else Some(diag, (p, inc i))) (0, 0)
There is no Seq.tail function in the core F# library (UPDATE: Yes there is, see comments), so I assume you're using the Seq.tail function from FSharpx.Collections. If you're using a different implementation of Seq.tail, it's probably similar -- and it's almost certainly the cause of your problems, because it's not O(1) like you think it is. Getting the tail of a List is O(1) because of how List is implemented (as a series of cons cells). But getting the tail of a Seq ends up creating a brand new Seq from the original enumerable, discarding one item from it, and returning the rest of its items. When you go through your accum loop a second time, you call Seq.tail on that "skip 1 then return" seq. So now you have a Seq which I'll call S2, which asks S1 for an IEnumerable, skips the first item of S1, and returns the rest of it. S1, when asked for its first item, asks S0 (the original Seq) for an enumerable, skips its first item, then returns the rest of it. So for S2 to skip two items, it had to create two seqs. Now on your next run through when you ask for the Seq.tail of S2, you create S3 that asks S2 for an IEnumerable, which asks S1 for an IEnumerable, which asks S0 for an IEnumerable... and so on. This is effectively O(N^2), when you thought you were writing an O(N) operation.
I'm afraid I don't have time right now to figure out a solution for you; using List.tail won't help since you need an infinite sequence. But perhaps just knowing about the Seq.tail gotcha is enough to get you started, so I'll post this answer now even though it's not complete.
If you need more help, comment on this answer and I'll come back to it when I have time -- but that might not be for several days, so hopefully others will also answer your question.
Writing performant F# is very possible but requires some knowledge of patterns that have high relative CPU cost in a tight loop. I recommend using tools like ILSpy to find hidden overhead.
For instance one could imagine F# exands this expression into an effective for loop:
[3..2..(int (sqrt (float n)))]
|> List.tryFind (fun i -> n%i=0)
|> Option.isNone
However it currently doesn't. Instead it creates a List that spans the range using intrinsic operators and passes that to List.tryFind. This is expensive when compared to the actual work we like to do (the modulus operation). ILSpy decompiles the code above into something like this:
public static bool is_prime(int _arg1)
{
switch (_arg1)
{
case 2:
return true;
default:
return _arg1 >= 2 && _arg1 % 2 != 0 && ListModule.TryFind<int>(new Program.Original.is_prime#10(_arg1), SeqModule.ToList<int>(Operators.CreateSequence<int>(Operators.OperatorIntrinsics.RangeInt32(3, 2, (int)Math.Sqrt((double)_arg1))))) == null;
}
}
These operators aren't as performant as they could be (AFAIK this is currently being improved) but no matter how effecient allocating a List and then search it won't beat a for loop.
This means the is_prime is not as effective as it could be. Instead one could do something like this:
let is_prime = function
| 1 -> false
| 2 -> true
| v when v % 2 = 0 -> false
| v ->
let stop = v |> float |> sqrt |> int
let rec loop vv =
if vv <= stop then
(v % vv) <> 0 && loop (vv + 2)
else
true
loop 3
This version of is_prime relies on tail call optimization in F# to expand the loop into an efficient for loop (you can see this using ILSpy). ILSpy decompile the loop into something like this:
while (vv <= stop)
{
if (_arg1 % vv == 0)
{
return false;
}
int arg_13_0 = _arg1;
int arg_11_0 = stop;
vv += 2;
stop = arg_11_0;
_arg1 = arg_13_0;
}
This loop doesn't allocate memory and is just a rather efficient loop. One see some non-sensical assignments but hopefully the JIT:er eliminate those. I am sure is_prime can be improved even further.
When using Seq in performant code one have to keep in mind it's lazy and it doesn't use memoization by default (see Seq.cache). Therefore one might easily end up doing the same work over and over again (see #rmunn answer).
In addition Seq isn't especially effective because of how IEnumerable/IEnumerator are designed. Better options are for instance Nessos Streams (available on nuget).
In case you are interested I did a quick implementation that relies on a simple Push Stream which seems decently performant:
// Receiver<'T> is a callback that receives a value.
// Returns true if it wants more values, false otherwise.
type Receiver<'T> = 'T -> bool
// Stream<'T> is function that accepts a Receiver<'T>
// This means Stream<'T> is a push stream (as opposed to Seq that uses pull)
type Stream<'T> = Receiver<'T> -> unit
// is_prime returns true if the input is prime, false otherwise
let is_prime = function
| 1 -> false
| 2 -> true
| v when v % 2 = 0 -> false
| v ->
let stop = v |> float |> sqrt |> int
let rec loop vv =
if vv <= stop then
(v % vv) <> 0 && loop (vv + 2)
else
true
loop 3
// tryFind looks for the first value in the input stream for f v = true.
// If found tryFind returns Some v, None otherwise
let tryFind f (s : Stream<'T>) : 'T option =
let res = ref None
s (fun v -> if f v then res := Some v; false else true)
!res
// diagonals generates a tuple stream of all diagonal values
// The first value is the side length, the second value is the diagonal value
let diagonals : Stream<int*int> =
fun r ->
let rec loop side v =
let step = side - 1
if r (side, v + 1*step) && r (side, v + 2*step) && r (side, v + 3*step) && r (side, v + 4*step) then
loop (side + 2) (v + 4*step)
if r (1, 1) then loop 3 1
// ratio computes the streaming ratio for f v = true
let ratio f (s : Stream<'T>) : Stream<float*'T> =
fun r ->
let inc r = r := !r + 1.
let acc = ref 0.
let count = ref 0.
s (fun v -> (inc count; if f v then inc acc); r (!acc/(!count), v))
let result =
diagonals
|> ratio (snd >> is_prime)
|> tryFind (fun (r, (_, v)) -> v > 1 && r < 0.1)
I'm a complete newbie in OCaml and trying to create a simple console program.
(*let k = read_int()
let l = read_int()
let m = read_int()
let n = read_int()
let d = read_int()*)
let k = 5
let l = 2
let m = 3
let n = 4
let d = 42
let rec total: int -> int -> int = fun i acc ->
if i > d then
acc
else
if (i mod k) == 0 || (i mod l) == 0 || (i mod m) == 0 || (i mod n) == 0 then
total (i + 1) (acc + 1)
else
total (i + 1) acc;
print_int (total 1 0)
But if I try to compile it, it fails:
PS C:\Users\user> ocamlc -g .\a148.ml
File ".\a148.ml", line 14, characters 2-180:
Warning S: this expression should have type unit.
File ".\a148.ml", line 22, characters 0-21:
Error: This expression has type unit but is here used with type int
So, looks like if expression cannot return value here (why?). I've added let binding
let k = 5
let l = 2
let m = 3
let n = 4
let d = 42
let rec total: int -> int -> int = fun i acc ->
let x' = if i > d then
acc
else
if (i mod k) == 0 || (i mod l) == 0 || (i mod m) == 0 || (i mod n) == 0 then
total (i + 1) (acc + 1)
else
total (i + 1) acc;
x'
print_int (total 1 0)
and it works, but raises another error:
File ".\a148.ml", line 23, characters 0-0:
Error: Syntax error
Line 23 is the next to print_int statement and empty, so it seems like compiler wants something else from me, but I don't know what.
UPD: ok, the working code:
let k = 5 in
let l = 2 in
let m = 3 in
let n = 4 in
let d = 42 in
let rec total i acc =
if i > d then
acc
else
if (i mod k) == 0 || (i mod l) == 0 || (i mod m) == 0 || (i mod n) == 0 then
total (i + 1) (acc + 1)
else
total (i + 1) acc
in let x = total 1 0 in
print_int x;
The problem is the misuse of semicolon (;).
Semicolon intends to be the sequence composition of two expressions. S1 ; S2 means that the compiler expects S1 to be unit type, computes S1 and S2 in that order and returns the result of S2.
Here you mistakenly use ;, so OCaml expects the second if...then...else to return unit and wants you to provide one more expression. Removing ; and adding necessary in(s) should make the function compile:
let k = 5 in
let l = 2 in
let m = 3 in
let n = 4 in
let d = 42 in
let rec total: int -> int -> int = fun i acc ->
if i > d then
acc
else
if (i mod k) == 0 || (i mod l) == 0 || (i mod m) == 0 || (i mod n) == 0 then
total (i + 1) (acc + 1)
else
total (i + 1) acc
Regarding your second function, you should replace ; by in to indicate that x' is used to compute the return value.
BTW, your total function looks weird since you use lambda expression in the function body. Explicit declaration is more readable:
let rec total i acc =
if i > d then
acc
else if i mod k = 0 || i mod l = 0 || i mod m = 0 || i mod n = 0 then
total (i + 1) (acc + 1)
else
total (i + 1) acc
I have also changed reference equality (==) to structural equality (=) though there is no difference among them in integer.