Going through Project Euler trying to learn F#, I stumbled upon what appears to be a type inference problem while writing a solution for problem 3.
Here's what I wrote:
let rec findLargestPrimeFactor p n =
if n = 1 then p
else
if n % p = 0 then findLargestPrimeFactor p (n/p)
else findLargestPrimeFactor (p+1) n
let result = findLargestPrimeFactor 2 600851475143L
However, the compiler gives me the following error:
error FS0001: This expression was expected to have type int but here has type int64
Since I expect the types used in findLargestPrimeFactor to be inferred from usage, I'm quite surprised to find out the compiler seems to assume that parameter n be an int since in the only call to the function is done with an int64.
Could someone explain to me:
why the compiler appears to be confused about types
how to work around this limitation
The types in findLargestPrimeFactor are inferred from usage. The F# compiler performs type inference in a top-to-bottom manner, so the types of p and n (the parameters of findLargestPrimeFactor) are inferred from their usage in the function. By the time the compiler sees the let result = ..., the parameter types have already been inferred as int.
The easiest solution is to use the L suffix on all of your constant values, so the types will be inferred as int64:
let rec findLargestPrimeFactor p n =
if n = 1L then p
else
if n % p = 0L then findLargestPrimeFactor p (n/p)
else findLargestPrimeFactor (p + 1L) n
let result = findLargestPrimeFactor 2L 600851475143L
If you want a fancier solution, you can use the generic one and zero constants from the LanguagePrimitives module. This allows findLargestPrimeFactor to be generic(-ish) so it can be reused more easily with different numeric types:
open LanguagePrimitives
let rec findLargestPrimeFactor p n =
if n = GenericOne then p
else
if n % p = GenericZero then findLargestPrimeFactor p (n/p)
else findLargestPrimeFactor (p + GenericOne) n
(* You can use one of these, but not both at the same time --
now the types of the _arguments_ are used to infer the types
of 'p' and 'n'. *)
//let result = findLargestPrimeFactor 2L 600851475143L
let result = findLargestPrimeFactor 2 Int32.MaxValue
Per #kvb's suggestion, here's how you can write this function generically:
open LanguagePrimitives
let inline findLargestPrimeFactor p n =
let rec findLargestPrimeFactor p n =
if n = GenericOne then p
else
if n % p = GenericZero then findLargestPrimeFactor p (n/p)
else findLargestPrimeFactor (p + GenericOne) n
findLargestPrimeFactor p n
(* Now you can call the function with different argument types
as long as the generic constraints are satisfied. *)
let result = findLargestPrimeFactor 2L 600851475143L
let result' = findLargestPrimeFactor 2 Int32.MaxValue
Related
I want to solve this excercise: http://code.google.com/codejam/contest/351101/dashboard#s=p0 using F#.
I am new to functional programming and F# but I like the concept and the language a lot. And I love the codejam excercise too it looks so easy but real life. Could somebody point me out a solution?
At the moment I have written this code which is just plain imperative and looks ugly from the functional perspective:
(*
C - Credit
L - Items
I - List of Integer, wher P is single integer
How does the data look like inside file
N
[...
* Money
* Items in store
...]
*)
let lines = System.IO.File.ReadAllLines("../../../../data/A-small-practice.in")
let CBounds c = c >= 5 && c <= 1000
let PBounds p = p >= 1 && p <= 1000
let entries = int(lines.[0]) - 1
let mutable index = 1 (* First index is how many entries*)
let mutable case = 1
for i = 0 to entries do
let index = (i*3) + 1
let C = int(lines.[index])
let L = int(lines.[index+1])
let I = lines.[index+2]
let items = I.Split([|' '|]) |> Array.map int
// C must be the sum of some items
// Ugly imperative way which contains duplicates
let mutable nIndex = 0
for n in items do
nIndex <- nIndex + 1
let mutable mIndex = nIndex
for m in items.[nIndex..] do
mIndex <- mIndex + 1
if n + m = C then do
printfn "Case #%A: %A %A" case nIndex mIndex
case <- case + 1
I would like to find out items which add up to C value but not in a usual imperative way - I want functional approach.
You don't specify how you would solve the problem, so it's hard to give advices.
Regarding reading inputs, you can express it as a series of transformation on Seq. High-order functions from Seq module are very handy:
let data =
"../../../../data/A-small-practice.in"
|> System.IO.File.ReadLines
|> Seq.skip 1
|> Seq.windowed 3
|> Seq.map (fun lines -> let C = int(lines.[0])
let L = int(lines.[1])
let items = lines.[2].Split([|' '|]) |> Array.map int
(C, L, items))
UPDATE:
For the rest of your example, you could use sequence expression. It is functional enough and easy to express nested computations:
let results =
seq {
for (C, _, items) in data do
for j in 1..items.Length-1 do
for i in 0..j-1 do
if items.[j] + items.[i] = C then yield (i, j)
}
Seq.iteri (fun case (i, j) -> printfn "Case #%A: %A %A" case i j) results
I have a sequence of prime number divisors that I want to iterate over for each prime candidate. I use GetEnumerator() MoveNext() and Current. I can't reinitialize the enumerator to start from the beginning. I tried Reset(), which compiled, but gives a runtime error of not implemented.
I am using F# 2.0 Interactive build 4.0.40219.1
Any suggestions?
Regards,
Doug
To clarify the problem: For each prime candidate N I want to iterate thru the prime divisors sequence (up to approx sqrt N) and completely factor N or determine if it is prime. Using the GetEnumerator, MoveNext, Current approach works for the first prime candidate, but on the second prime candidate I want to iterate on my divisors sequence from the beginning. It appears that the only way to do this is to create a new iterator (which is awkward for a large number of prime candidates) or create a new prime sequence (which I don't want to do).
The suggestion of using something like "divisors in seqPrimes" appears to exhaust all divisors before stopping, but I want to stop as soon as a prime divisor divides the prime candidate.
If there is an error in my logic in the above statements, please let me know.
I investigated Seq.cache, and this worked for me. The resulting code follows:
// Recursive isprime function (modified from MSDN)
let isPrime n =
let rec check i =
i > n/2 || (n % i <> 0 && check (i + 2))
if n = 2 then true
elif (n%2) = 0 then false
else check 3
let seqPrimes = seq { for n in 2 .. 100000 do if isPrime n then yield n }
// Cache the sequence to avoid recomputing the sequence elements.
let cachedSeq = Seq.cache seqPrimes
// find the divisors of n (or determine prime) using the seqEnum enumerator
let rec testPrime n (seqEnum:System.Collections.Generic.IEnumerator<int>) =
if n = 1 then printfn "completely factored"
else
let nref = ref n
if seqEnum.MoveNext() then
let divisor = seqEnum.Current
//printfn "trial divisor %A" divisor
if divisor*divisor > n then printfn "prime %A" !nref
else
while ((!nref % divisor) = 0) do
printfn "divisor %A" divisor
nref := !nref / divisor
testPrime !nref seqEnum
// test
for x = 1000000 to 1000010 do
printfn "\ndivisors of %d = " x
let seqEnum = cachedSeq.GetEnumerator()
testPrime x seqEnum
seqEnum.Dispose() // not needed
If you mean that the cause of your attempt to reset the Enumerator is the high cost of regenerating your sequence of primes you may consider caching your sequence. This manner of using your sequence would be idiomatic to F#. To show you how to do this I refer you to the following snippet taken from this context:
let rec primes =
Seq.cache <| seq { yield 2; yield! Seq.unfold nextPrime 3 }
and nextPrime n =
if isPrime n then Some(n, n + 2) else nextPrime(n + 2)
and isPrime n =
if n >= 2 then
primes
|> Seq.tryFind (fun x -> n % x = 0 || x * x > n)
|> fun x -> x.Value * x.Value > n
else false
You may play with this snippet to see that the penalty of re-enumeration here gets negligible.
Talking of Reset() method of IEnumerator, I recall that it is not implemented in current F#, i.e. throws System.NotSupportedException. See MSDN reference for justification.
ADDITION:
In order to test it with the test you've suggested below:
for x in [1000000..1000010] do
printfn "\ndivisors of %d" x
primes
|> Seq.takeWhile ((>) (int(sqrt(float x))))
|> Seq.iter (fun n -> if x%n = 0 then printf "%d " n)
On my laptop test execution takes mere 3ms.
I have this bit of code:
let rec h n z = if n = 0 then z
else <# (fun x -> %(h (n - 1) <# x + %z #>)) n #>
converted from a MetaOcaml example in http://www.cs.rice.edu/~taha/publications/journal/dspg04a.pdf
In the paper there is explained that the above example will yield the following with the parameters 3 and .<1>. (in MetaOcaml notation):
.<(fun x_1 -> (fun x_2 -> (fun x_3 -> x_3 + (x_2 + (x_1 + 1))) 1) 2) 3>.
As you can see the x´s gets replaced by x_1, x_2 etc. because the x would otherwise only refer to the x in the innermost fun.
But in F# this isn't allowed. I get the compile-time error: "The variable 'x' is bound in a quotation but is used as part of a spliced expression. This is not permitted since it may escape its scope." So the question is: how can this be changed so it will compile and have the same semantic as the MetaOcaml output?
Update to comment: I use the PowerPack to actually evaluating the quotation. But I don't think this have anything to do with it because the error is at compile-time. So far QuotationEvaluation works. However, I do know it may not be the most efficient implementation.
Update to Tomas´ answer:
I really don't want the x to be global, or to escape scope. But I want is the equivalent to
let rec h n z = if n = 0 then z
else (fun x -> (h (n - 1) (x + z))) n
with quotations. Your answer gives (h 3 <# 1 #>).Eval() = 4 where the above yields h 3 1 = 7. And here, I want 7 to be the answer.
F# quotation syntax doesn't support variables that could potentially escape the scope, so you'll need to construct the tree explicitly using the Expr operations. Something like this should do the trick:
open Microsoft.FSharp.Quotations
let rec h n (z:Expr<int>) =
if n = 0 then z
else
let v = new Var("x", typeof<int>)
let ve = Expr.Var(v)
Expr.Cast<int>
(Expr.Application( Expr.Lambda(v, h (n - 1) <# %%ve + %z #>),
Expr.Value(n)))
However, this is quite artificial example (to demonstrate variable capturing in MetaOCaml, which isn't available in F#). It just generates expression like (2 + (1 + ...)). You can get the same result by writing something like this:
let rec h n (z:Expr<int>) =
if n = 0 then z
else h (n - 1) <# n + %z #>
Or even better:
[ 1 .. 4 ] |> List.fold (fun st n -> <# n + %st #>) <# 0 #>
I also came accross this limitation in F# quotations and it would be nice if this was supported. However, I don't think it is such a big problem in practice, because F# quotations are not used for staged meta-programming. They are more useful for analyzing existing F# code than for generating code.
I am trying to learn F# so I paid a visit to Project Euler and I am currently working on Problem 3.
The prime factors of 13195 are 5, 7,
13 and 29.
What is the largest prime
factor of the number 600851475143?
Some things to consider:
My first priority is to learn good functional habits.
My second priority is I would like it to be fast and efficient.
Within the following code I have marked the section this question is regarding.
let isPrime(n:int64) =
let rec check(i:int64) =
i > n / 2L or (n % i <> 0L && check(i + 1L))
check(2L)
let greatestPrimeFactor(n:int64) =
let nextPrime(prime:int64):int64 =
seq { for i = prime + 1L to System.Int64.MaxValue do if isPrime(i) then yield i }
|> Seq.skipWhile(fun v -> n % v <> 0L)
|> Seq.hd
let rec findNextPrimeFactor(number:int64, prime:int64):int64 =
if number = 1L then prime else
//************* No variable
(fun p -> findNextPrimeFactor(number / p, p))(nextPrime(prime))
//*************
//************* Variable
let p = nextPrime(prime)
findNextPrimeFactor(number / p, p)
//*************
findNextPrimeFactor(n, 2L)
Update
Based off some of the feedback I have refactored the code to be 10 times faster.
module Problem3
module private Internal =
let execute(number:int64):int64 =
let rec isPrime(value:int64, current:int64) =
current > value / 2L or (value % current <> 0L && isPrime(value, current + 1L))
let rec nextPrime(prime:int64):int64 =
if number % prime = 0L && isPrime(prime, 2L) then prime else nextPrime(prime + 1L)
let rec greatestPrimeFactor(current:int64, prime:int64):int64 =
if current = 1L then prime else nextPrime(prime + 1L) |> fun p -> greatestPrimeFactor(current / p, p)
greatestPrimeFactor(number, 2L)
let execute() = Internal.execute(600851475143L)
Update
I would like to thank everyone for there advice. This latest version is a compilation of all the advice I received.
module Problem3
module private Internal =
let largestPrimeFactor number =
let rec isPrime value current =
current > value / 2L || (value % current <> 0L && isPrime value (current + 1L))
let rec nextPrime value =
if number % value = 0L && isPrime value 2L then value else nextPrime (value + 1L)
let rec find current prime =
match current / prime with
| 1L -> prime
| current -> nextPrime (prime + 1L) |> find current
find number (nextPrime 2L)
let execute() = Internal.largestPrimeFactor 600851475143L
Functional programming becomes easier and more automatic with practice, so don't sweat it if you don't get it absolutely right on the first try.
With that in mind, let's take your sample code:
let rec findNextPrimeFactor(number:int64, prime:int64):int64 =
if number = 1L then prime else
//************* No variable
(fun p -> findNextPrimeFactor(number / p, p))(nextPrime(prime))
//*************
//************* Variable
let p = nextPrime(prime)
findNextPrimeFactor(number / p, p)
//*************
Your no variable version is just weird, don't use it. I like your version with the explicit let binding.
Another way to write it would be:
nextPrime(prime) |> fun p -> findNextPrimeFactor(number / p, p)
Its ok and occasionally useful to write it like this, but still comes across as a little weird. Most of the time, we use |> to curry values without needing to name our variables (in "pointfree" style). Try to anticipate how your function will be used, and if possible, re-write it so you can use it with the pipe operator without explicit declared variables. For example:
let rec findNextPrimeFactor number prime =
match number / prime with
| 1L -> prime
| number' -> nextPrime(prime) |> findNextPrimeFactor number'
No more named args :)
Ok, now that we have that out of the way, let's look at your isPrime function:
let isPrime(n:int64) =
let rec check(i:int64) =
i > n / 2L or (n % i <> 0L && check(i + 1L))
check(2L)
You've probably heard to use recursion instead of loops, and that much is right. But, wherever possible, you should abstract away recursion with folds, maps, or higher order functions. Two reasons for this:
its a little more readable, and
improperly written recursion will result in a stack overflow. For example, your function is not tail recursive, so it'll blow up on large values of n.
I'd rewrite isPrime like this:
let isPrime n = seq { 2L .. n / 2L } |> Seq.exists (fun i -> n % i = 0L) |> not
Most of the time, if you can abstract away your explicit looping, then you're just applying transformations to your input sequence until you get your results:
let maxFactor n =
seq { 2L .. n - 1L } // test inputs
|> Seq.filter isPrime // primes
|> Seq.filter (fun x -> n % x = 0L) // factors
|> Seq.max // result
We don't even have intermediate variables in this version. Coolness!
My second priority is I would like it
to be fast and efficient.
Most of the time, F# is going to be pretty comparable with C# in terms of speed, or it's going to be "fast enough". If you find your code takes a long time to execute, it probably means you're using the wrong data structure or a bad algorithm. For a concrete example, read the comments on this question.
So, the code I've written is "elegant" in the sense that its concise, gives the correct results, and doesn't rely on any trickery. Unfortunately, its not very fast. For start:
it uses trial division to create a sequence of primes, when the Sieve of Eratosthenes would be much faster. [Edit: I wrote a somewhat naive version of this sieve which didn't work for numbers larger than Int32.MaxValue, so I've removed the code.]
read Wikipedia's article on the prime counting function, it'll give you pointers on calculating the first n primes as well as estimating the upper and lower bounds for the nth prime.
[Edit: I included some code with a somewhat naive implementation of a sieve of eratosthenes. It only works for inputs less than int32.MaxValue, so it probably isn't suitable for project euler.]
Concerning "good functional habit" or rather good practice I see three minor things. Using the yield in your sequence is a little harder to read than just filter. Unnecessary type annotations in a type inferred language leads to difficult refactoring and makes the code harder to read. Don't go overboard and try to remove every type annotation though if you're finding it difficult. Lastly making a lambda function which only takes a value to use as a temp variable reduces readability.
As far as personal style goes I prefer more spaces and only using tupled arguments when the data makes sense being grouped together.
I'd write your original code like this.
let isPrime n =
let rec check i =
i > n / 2L || (n % i <> 0L && check (i + 1L))
check 2L
let greatestPrimeFactor n =
let nextPrime prime =
seq {prime + 1L .. System.Int64.MaxValue}
|> Seq.filter isPrime
|> Seq.skipWhile (fun v -> n % v <> 0L)
|> Seq.head
let rec findNextPrimeFactor number prime =
if number = 1L then
prime
else
let p = nextPrime(prime)
findNextPrimeFactor (number / p) p
findNextPrimeFactor n 2L
Your updated code is optimal for your approach. You would have to use a different algorithm like Yin Zhu answer to go faster. I wrote a test to check to see if F# makes the "check" function tail recursive and it does.
the variable p is actually a name binding, not a variable. Using name binding is not a bad style. And it is more readable. The lazy style of nextPrime is good, and it actually prime-test each number only once during the whole program.
My Solution
let problem3 =
let num = 600851475143L
let rec findMax (n:int64) (i:int64) =
if n=i || n<i then
n
elif n%i=0L then
findMax (n/i) i
else
findMax n (i+1L)
findMax num 2L
I basically divides num from 2, 3, 4.. and don't consider any prime numbers. Because if we divides all 2 from num, then we won't be able to divide it by 4,8, etc.
on this number, my solution is quicker:
> greatestPrimeFactor 600851475143L;;
Real: 00:00:01.110, CPU: 00:00:00.702, GC gen0: 1, gen1: 1, gen2: 0
val it : int64 = 6857L
>
Real: 00:00:00.001, CPU: 00:00:00.000, GC gen0: 0, gen1: 0, gen2: 0
val problem3 : int64 = 6857L
I think that the code with the temporary binding is significantly easier to read. It's pretty unusual to create an anonymous function and then immediately apply it to a value as you do in the other case. If you really want to avoid using a temporary value, I think that the most idiomatic way to do that in F# would be to use the (|>) operator to pipe the value into the anonymous function, but I still think that this isn't quite as readable.
I've been trying to work my way through Problem 27 of Project Euler, but this one seems to be stumping me. Firstly, the code is taking far too long to run (a couple of minutes maybe, on my machine, but more importantly, it's returning the wrong answer though I really can't spot anything wrong with the algorithm after looking through it for a while.
Here is my current code for the solution.
/// Checks number for primality.
let is_prime n =
[|1 .. 2 .. sqrt_int n|] |> Array.for_all (fun x -> n % x <> 0)
/// Memoizes a function.
let memoize f =
let cache = Dictionary<_, _>()
fun x ->
let found, res = cache.TryGetValue(x)
if found then
res
else
let res = f x
cache.[x] <- res
res
/// Problem 27
/// Find a quadratic formula that produces the maximum number of primes for consecutive values of n.
let problem27 n =
let is_prime_mem = memoize is_prime
let range = [|-(n - 1) .. n - 1|]
let natural_nums = Seq.init_infinite (fun i -> i)
range |> Array.map (fun a -> (range |> Array.map (fun b ->
let formula n = n * n + a * n + b
let num_conseq_primes = natural_nums |> Seq.map (fun n -> (n, formula n))
|> Seq.find (fun (n, f) -> not (is_prime_mem f)) |> fst
(a * b, num_conseq_primes)) |> Array.max_by snd)) |> Array.max_by snd |> fst
printn_any (problem27 1000)
Any tips on how to a) get this algorithm actually returning the right answer (I think I'm at least taking a workable approach) and b) improve the performance, as it clearly exceeds the "one minute rule" set out in the Project Euler FAQ. I'm a bit of a newbie to functional programming, so any advice on how I might consider the problem with a more functional solution in mind would also be appreciated.
Two remarks:
You may take advantage of the fact that b must be prime. This follows from the fact that the problem asks for the longest sequence of primes for n = 0, 1, 2, ...
So, formula(0) must be prime to begin with , but formula(0) = b, therefore, b must be prime.
I am not an F# programmer, but it seems to me that the code does not try n= 0 at all. This, of course, does not meet the problem's requirement that n must start from 0, therefore there are neglectable chances a correct answer could be produced.
Right, after a lot of checking that all the helper functions were doing what they should, I've finally reached a working (and reasonably efficient) solution.
Firstly, the is_prime function was completely wrong (thanks to Dimitre Novatchev for making me look at that). I'm not sure quite how I arrived at the function I posted in the original question, but I had assumed it was working since I'd used it in previous problems. (Most likely, I had just tweaked it and broken it since.) Anyway, the working version of this function (which crucially returns false for all integers less than 2) is this:
/// Checks number for primality.
let is_prime n =
if n < 2 then false
else [|2 .. sqrt_int n|] |> Array.for_all (fun x -> n % x <> 0)
The main function was changed to the following:
/// Problem 27
/// Find a quadratic formula that produces the maximum number of primes for consecutive values of n.
let problem27 n =
let is_prime_mem = memoize is_prime
let set_b = primes (int64 (n - 1)) |> List.to_array |> Array.map int
let set_a = [|-(n - 1) .. n - 1|]
let set_n = Seq.init_infinite (fun i -> i)
set_b |> Array.map (fun b -> (set_a |> Array.map (fun a ->
let formula n = n * n + a * n + b
let num_conseq_primes = set_n |> Seq.find (fun n -> not (is_prime_mem (formula n)))
(a * b, num_conseq_primes))
|> Array.max_by snd)) |> Array.max_by snd |> fst
The key here to increase speed was to only generate the set of primes between 1 and 1000 for the values of b (using the primes function, my implementation of the Sieve of Eratosthenes method). I also managed to make this code slightly more concise by eliminating the unnecessary Seq.map.
So, I'm pretty happy with the solution I have now (it takes just under a second), though of course any further suggestions would still be welcome...
You could speed up your "is_prime" function by using a probabilistic algorithm. One of the easiest quick algorithms for this is the Miller-Rabin algorithm.
to get rid of half your computations you could also make the array of possible a´s only contain odd numbers
my superfast python solution :P
flag = [0]*204
primes = []
def ifc(n): return flag[n>>6]&(1<<((n>>1)&31))
def isc(n): flag[n>>6]|=(1<<((n>>1)&31))
def sieve():
for i in xrange(3, 114, 2):
if ifc(i) == 0:
for j in xrange(i*i, 12996, i<<1): isc(j)
def store():
primes.append(2)
for i in xrange(3, 1000, 2):
if ifc(i) == 0: primes.append(i)
def isprime(n):
if n < 2: return 0
if n == 2: return 1
if n & 1 == 0: return 0
if ifc(n) == 0: return 1
return 0
def main():
sieve()
store()
mmax, ret = 0, 0
for b in primes:
for a in xrange(-999, 1000, 2):
n = 1
while isprime(n*n + a*n + b): n += 1
if n > mmax: mmax, ret = n, a * b
print ret
main()