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type Googol = {
number : float
power : float
result : float
}
let generatePowers (n:float) : list<Googol> =
let rec powerInner (n:float) (p:float) (acc : list<Googol>) =
match n with
| p when p <= 1.0 -> acc
| p when p > 1.0 -> powerInner n (p-1.0) ([{ number=n; power=p; result=n**p}]#acc)
let rec numberInner (n:float) (acc : list<Googol>) =
match n with
| n when n <=1.0 -> acc
| n when n >1.0 -> numberInner (n-1.0) ((powerInner n [])#acc)
numberInner n []
ProjectEuler.fsx(311,50): error FS0001: This expression was expected to have type
'Googol list'
but here has type
'Googol list -> Googol list'
I am trying to solve this problem -> https://projecteuler.net/problem=56 | but for this I need to generate powers below n < 100. When I try to concatenate [{ number=n; power=p; result=n**p}]#acc
these lists I get the error above. Explain please why error says 'Googol list -> Googol list' is in the function, does I plug a function as a parameter to the function or I plug the actual list when just after concatenation. Is # a function?
This looks like homework or practice, so first I'll give some hints to move on. Finally I'll show a version that seems to work, and then tell how I would approach the problem.
The task is to find the number a ** b, for a and b less than 100, that has the highest sum of its own digits.
The first problem is that float won't give us all the digits of a ** b, so that type is useless to solve the problem. To fix that, we turn to the BigInteger type, and the BigInteger.Pow function. Then we get a 1 followed by 200 zeroes if we run the following snippet, just like it says in the problem description.
let x: bigint = BigInteger.Pow (100I, 100)
let x: string = string x
printfn "s=%s" x
To get useful results, change the Googol type so that it uses bigint, except for power that should be an int.
Why are the functions powerInner and numberInner inside the function generatePowers? This doesn't seem to have a specific purpose, so I suggest moving them out to make this clearer.
The function powerInner do a match on n, but then goes on to name the results p, which shadows the p parameter so that it is unused. Ok, the intention here is probably to match on p rather than n, so just fix that, and then the shadowing of the p parameter is perfectly fine.
The tests first on <= 1 and then on > 1 causes incomplete matches. If the first line checks that the number is less or equal to one, then it must the greater than one in the next line. So just use n -> without the when to fix that. I also suspect you want to test <= 0 instead of 1.
This
[{ number=n; power=p; result=n**p}]#acc
can be just
{ number=n; power=p; result=n**p } :: acc
and here
(powerInner n [])
I suspect you just need a starting value for the power, which would be 99
(powerInner n 99 [])
SPOILER WARNING
After a bit of tinkering, this is what I ended up with, and it seems to print out a useful list of numbers. Note that in order to not run through all 99 by 99 results with printouts, I've used low starting numbers 3 and 5 for the countdowns here, so we get some simple printout we can study for analysis.
type Googol = { number: bigint; power: int; result: bigint }
let rec powerInner (n: bigint) (p: int) (acc: Googol list) =
match p with
| p when p <= 0 -> acc
| p ->
let newNumber = { number = n; power = p; result = n ** p }
printfn "newNumber=%0A" newNumber
powerInner n (p - 1) (newNumber :: acc)
let rec numberInner (n: bigint) (acc: Googol list) =
match n with
| n when n <= 0I -> acc
| n -> numberInner (n - 1I) ((powerInner n 5 []) # acc)
let generatePowers (n: bigint) : Googol list =
numberInner n []
let powers = generatePowers 3I
I'm not sure if this solution is correct. I'd do it differently anyway.
I would simply loop through a and b in two loops, one inside the other. For each a ** b I would convert the result to a string, and then sum the digits of the string. Then I'd simply use a mutable to hold on to whichever result is the highest. The same could be achieved in a more functional way with one of those fancy List functions.
You're missing a parameter here:
| n when n >1.0 -> numberInner (n-1.0) ((powerInner n [])#acc)
^^^^^^^^^^^^^^^
here
powerInner is defined with three parameters, but you're only passing two.
In F# it is not technically illegal to pass fewer parameters than defined. If you do that, the result will be a function that "expects" the remaining parameters. For example:
let f : int -> int -> string
let x = f 42
// Here, x : int -> string
let y = x 5
// Here, y : string
So in your case omitting the last parameter makes the resulting type Googol list -> Googol list, which then turns out to be incompatible with the type Googol list expected by operator #. Which is what the compiler is telling you in the error message.
I am trying to write a program in sml that takes in the length of a list, the max number that will appear on the list and the list of course. It then calculates the length of the smallest "sub-list" that contains all numbers.
I have tried to use the sliding window approach , with two indexes , front and tail. The front scans first and when it finds a number it writes into a map how many times it has already seen this number. If the program finds all numbers then it calls the tail. The tail scans the list and if it finds that a number has been seen more times than 1 it takes it off.
The code I have tried so far is the following:
structure Key=
struct
type ord_key=int
val compare=Int.compare
end
fun min x y = if x>y then y else x;
structure mymap = BinaryMapFn ( Key );
fun smallest_sub(n,t,listall,map)=
let
val k=0
val front=0
val tail=0
val minimum= n;
val list1=listall;
val list2=listall;
fun increase(list1,front,k,ourmap)=
let
val number= hd list1
val elem=mymap.find(ourmap,number)
val per=getOpt(elem,0)+1
fun decrease(list2,tail,k,ourmap,minimum)=
let
val number=hd list2
val elem=mymap.find(ourmap,number)
val per=getOpt(elem,0)-1
val per1=getOpt(elem,0)
in
if k>t then
if (per1=1) then decrease(tl list2,tail+1,k-1,mymap.insert(ourmap,number,per),min minimum (front-tail))
else decrease(tl list2,tail+1,k,mymap.insert(ourmap,number,per),min minimum (front-tail))
else increase (list1, front,k,ourmap)
end
in
if t>k then
if (elem<>NONE) then increase (tl list1,front+1,k,mymap.insert(ourmap,number,per))
else increase(tl list1,front+1,k+1,mymap.insert(ourmap,number,per))
else (if (n>front) then decrease(list2,tail,k,ourmap,minimum) else minimum)
end
in
increase(list1,front,k,map)
end
fun solve (n,t,acc)= smallest_sub(n,t,acc,mymap.empty)
But when I call it with this smallest_sub(10,3,[1,3,1,3,1,3,3,2,2,1]); it does not work. What have I done wrong??
Example: if input is 1,3,1,3,1,3,3,2,2,1 the program should recognize that the parto of the list that contains all numbers and is the smallest is 1,3,3,2 and 3,2,2,1 so the output should be 4
This problem of "smallest sub-list that contains all values" seems to recur in
new questions without a successful answer. This is because it's not a minimal,
complete, and verifiable example.
Because you use a "sliding window" approach, indexing the front and the back
of your input, a list taking O(n) time to index elements is not ideal. You
really do want to use arrays here. If your input function must have a list, you
can convert it to an array for the purpose of the algorithm.
I'd like to perform a cleanup of the code before answering, because running
your current code by hand is a bit hard because it's so condensed. Here's an
example of how you could abstract out the book-keeping of whether a given
sub-list contains at least one copy of each element in the original list:
Edit: I changed the code below after originally posting it.
structure CountMap = struct
structure IntMap = BinaryMapFn(struct
type ord_key = int
val compare = Int.compare
end)
fun count (m, x) =
Option.getOpt (IntMap.find (m, x), 0)
fun increment (m, x) =
IntMap.insert (m, x, count (m, x) + 1)
fun decrement (m, x) =
let val c' = count (m, x)
in if c' <= 1
then NONE
else SOME (IntMap.insert (m, x, c' - 1))
end
fun flip f (x, y) = f (y, x)
val fromList = List.foldl (flip increment) IntMap.empty
end
That is, a CountMap is an int IntMap.map where the Int represents the
fixed key type of the map, being int, and the int parameter in front of it
represents the value type of the map, being a count of how many times this
value occurred.
When building the initialCountMap below, you use CountMap.increment, and
when you use the "sliding window" approach, you use CountMap.decrement to
produce a new countMap that you can test on recursively.
If you decrement the occurrence below 1, you're looking at a sub-list that
doesn't contain every element at least once; we rule out any solution by
letting CountMap.decrement return NONE.
With all of this machinery abstracted out, the algorithm itself becomes much
easier to express. First, I'd like to convert the list to an array so that
indexing becomes O(1), because we'll be doing a lot of indexing.
fun smallest_sublist_length [] = 0
| smallest_sublist_length (xs : int list) =
let val arr = Array.fromList xs
val initialCountMap = CountMap.fromList xs
fun go countMap i j =
let val xi = Array.sub (arr, i)
val xj = Array.sub (arr, j)
val decrementLeft = CountMap.decrement (countMap, xi)
val decrementRight = CountMap.decrement (countMap, xj)
in
case (decrementLeft, decrementRight) of
(SOME leftCountMap, SOME rightCountMap) =>
Int.min (
go leftCountMap (i+1) j,
go rightCountMap i (j-1)
)
| (SOME leftCountMap, NONE) => go leftCountMap (i+1) j
| (NONE, SOME rightCountMap) => go rightCountMap i (j-1)
| (NONE, NONE) => j - i + 1
end
in
go initialCountMap 0 (Array.length arr - 1)
end
This appears to work, but...
Doing Int.min (go left..., go right...) incurs a cost of O(n^2) stack
memory (in the case where you cannot rule out either being optimal). This is a
good use-case for dynamic programming because your recursive sub-problems have a
common sub-structure, i.e.
go initialCountMap 0 10
|- go leftCountMap 1 10
| |- ...
| `- go rightCountMap 1 9 <-.
`- go rightCountMap 0 9 | possibly same sub-problem!
|- go leftCountMap 1 9 <-'
`- ...
So maybe there's a way to store the recursive sub-problem in a memory array and not
perform a recursive lookup if you know the result to this sub-problem. How to
do memoization in SML is a good question in and of itself. How to do purely
functional memoization in a non-lazy language is an even better one.
Another optimization you could make is that if you ever find a sub-list the
size of the number of unique elements, you need to look no further. This number
is incidentally the number of elements in initialCountMap, and IntMap
probably has a function for finding it.
I have two strings
a :: [String]
a = ["A1","A2","B3","C3"]
and
b :: [String]
b = ["A1","B2","B3","D5"]
And I want to calculate the difference between two strings based on the first character and second character and combination of two characters.
If the combination of two elements are the same, it would be calculate as 1
The function I declared is
calcP :: [String] -> [String] -> (Int,[String])
calcP (x:xs) (y:ys) = (a,b)
where
a = 0 in
???
b = ????
I know that I should have a increment variable to count the correct element, and where I should put it in? For now I totally have no idea about how to do that, can anyone give me some hint??
The desired result would be
(2,["B2","D5"])
How should I do that?
I assume that the lists have the same size.
The differences between the two lists
Let's focus on the main part of the problem:
Prelude> a=["A1","A2","B3","C3"]
Prelude> b=["A1","B2","B3","D5"]
First, notice that the zip method zips two lists. If you use it on a and b, you get:
Prelude> zip a b
[("A1","A1"),("A2","B2"),("B3","B3"),("C3","D5")]
Ok. It's now time to compare the terms one to one. There are many ways to do it.
Filter
Prelude> filter(\(x,y)->x/=y)(zip a b)
[("A2","B2"),("C3","D5")]
The lambda function returns True if the elements of the pair are different (/= operator). Thus, the filter keeps only the pairs that don't match.
It's ok, but you have to do a little more job to keep only the second element of each pair.
Prelude> map(snd)(filter(\(x,y)->x/=y)(zip a b))
["B2","D5"]
map(snd) applies snd, which keeps only the second element of a pair, to every discordant pair.
Fold
A fold is more generic, and may be used to implement a filter. Let's see how:
Prelude> foldl(\l(x,y)->if x==y then l else l++[y])[](zip a b)
["B2","D5"]
The lambda function takes every pair (x,y) and compares the two elements. If they have the same value, the accumulator list remains the identical, but if the values are different, the accumulator list is augmented by the second element.
List comprehension
This is more compact, and should seem obvious to every Python programmer:
Prelude> [y|(x,y)<-zip a b, x/=y] -- in Python [y for (x,y) in zip(a,b) if x!= y]
["B2","D5"]
The number of elements
You want a pair with the number of elements and the elements themselves.
Fold
With a fold, it's easy but cumbersome: you will use a slightly more complicated accumulator, that stores simultaneously the differences (l) and the number of those differences (n).
Prelude> foldl(\(n,l)(x,y)->if x==y then (n,l) else (n+1,l++[y]))(0,[])$zip a b
(2,["B2","D5"])
Lambda
But you can use the fact that your output is redundant: you want a list preceeded by the length of that list. Why not apply a lambda that does the job?
Prelude> (\x->(length x,x))[1,2,3]
(3,[1,2,3])
With a list comprehension, it gives:
Prelude> (\x->(length x,x))[y|(x,y)<-zip a b, x/=y]
(2,["B2","D5"])
Bind operator
Finally, and for the fun, you don't need to build the lambda this way. You could do:
Prelude> ((,)=<<length)[y|(x,y)<-zip a b,x/=y]
(2,["B2","D5"])
What happens here? (,) is a operator that makes a pair from two elements:
Prelude> (,) 1 2
(1,2)
and ((,)=<<length) : 1. takes a list (technically a Foldable) and passes it to the length function; 2. the list and the length are then passed by =<< (the "bind" operator) to the (,) operator, hence the expected result.
Partial conclusion
"There is more than than one way to do it" (but it's not Perl!)
Haskell offers a lot of builtins functions and operators to handle this kind of basic manipulation.
What about doing it recursively? If two elements are the same, the first element of the resulting tuple is incremented; otherwise, the second element of the resulting tuple is appended by the mismatched element:
calcP :: [String] -> [String] -> (Int,[String])
calcP (x:xs) (y:ys)
| x == y = increment (calcP xs ys)
| otherwise = append y (calcP xs ys)
where
increment (count, results) = (count + 1, results)
append y (count, results) = (count, y:results)
calcP [] x = (0, x)
calcP x [] = (0, [])
a = ["A1","A2","B3","C3"]
b = ["A1","B2","B3","D5"]
main = print $ calcP a b
The printed result is (2,["B2","D5"])
Note, that
calcP [] x = (0, x)
calcP x [] = (0, [])
are needed to provide exhaustiveness for the pattern matching. In other words, you need to provide the case when one of the passed elements is an empty list. This also provides the following logic:
If the first list is greater than the second one on n elements, these n last elements are ignored.
If the second list is greater than the first one on n elements, these n last elements are appended to the second element of the resulting tuple.
I'd like to propose a very different method than the other folks: namely, compute a "summary statistic" for each pairing of elements between the two lists, and then combine the summaries into your desired result.
First some imports.
import Data.Monoid
import Data.Foldable
For us, the summary statistic is how many matches there are, together with the list of mismatches from the second argument:
type Statistic = (Sum Int, [String])
I've used Sum Int instead of Int to specify how statistics should be combined. (Other options here include Product Int, which would multiply together the values instead of adding them.) We can compute the summary of a single pairing quite simply:
summary :: String -> String -> Statistic
summary a b | a == b = (1, [ ])
| otherwise = (0, [b])
Combining the summaries for all the elements is just a fold:
calcP :: [String] -> [String] -> Statistic
calcP as bs = fold (zipWith summary as bs)
In ghci:
> calcP ["A1", "A2", "B3", "C3"] ["A1", "B2", "B3", "D5"]
(Sum {getSum = 2},["B2","D5"])
This general pattern (of processing elements one at a time into a Monoidal type) is frequently useful, and spotting where it's applicable can greatly simplify your code.
I have to iterate over 2 lists. One starts off as a list of empty sublists and the second one has the max length for each of the sublists that are in the first one.
Example; list1 = [[];[];[];]; list2 = [1;2;3]
I need to fill out the empty sublists in list1 ensuring that the length of the sublists never exceed the corresponding integer in list2. To that end, I wrote the following function, that given an element, elem and 2 two lists list and list, will fill out the sublists.
let mapfn elem list1 list2=
let d = ref 1 in
List.map2 (fun a b -> if ((List.length a) < b) && (!d=1)
then (incr d ; List.append a [elem])
else a )
list1 list2
;;
I can now call this function repeatedly on the elements of a list and get the final answer I need
This function works as expected. But I am little bothered by the need to use the int ref d.
Is there a better way for me to do this.
I always find it worthwhile to split the problem into byte-sized pieces that can be composed together to form a solution. You want to pad or truncate lists to a given length; this is easy to do in two steps, first pad, then truncate:
let all x = let rec xs = x :: xs in xs
let rec take n = function
| [] -> []
| _ when n = 0 -> []
| x :: xs -> x :: take (pred n) xs
all creates an infinite list by repeating a value, while take extracts the prefix sublist of at most the given length. With these two, padding and truncating is very straightforwad:
let pad_trim e n l = take n (l # all e)
(it might be a bit surprising that this actually works in a strict language like OCaml). With that defined, your required function is simply:
let mapfn elem list1 list2 = List.map2 (pad_trim elem) list2 list1
that is, taking the second list as a list of specified lengths, pad each of the lists in the first list to that length with the supplied padding element. For instance, mapfn 42 [[];[];[]] [1;2;3] gives [[42]; [42; 42]; [42; 42; 42]]. If this is not what you need, you can tweak the parts and their assembly to suit your requirements.
Are you looking for something like that?
let fill_list elem lengths =
let rec fill acc = function
| 0 -> acc
| n -> fill (elem :: acc) (n - 1) in
let accumulators = List.map (fun _ -> []) lengths in
List.map2 fill accumulators lengths
(* toplevel test *)
# let test = fill_list 42 [1; 3];;
val test : int list list = [[42]; [42; 42; 42]]
(I couldn't make sense of the first list of empty lists in your question, but I suspect it may be the accumulators for the tail-rec fill function.)
I'm really new to F#, and I need a bit of help with an F# problem.
I need to implement a cut function that splits a list in half so that the output would be...
cut [1;2;3;4;5;6];;
val it : int list * int list = ([1; 2; 3], [4; 5; 6])
I can assume that the length of the list is even.
I'm also expected to define an auxiliary function gencut(n, xs) that cuts xs into two pieces, where n gives the size of the first piece:
gencut(2, [1;3;4;2;7;0;9]);;
val it : int list * int list = ([1; 3], [4; 2; 7; 0; 9])
I wouldn't normally ask for exercise help here, but I'm really at a loss as to where to even start. Any help, even if it's just a nudge in the right direction, would help.
Thanks!
Since your list has an even length, and you're cutting it cleanly in half, I recommend the following (psuedocode first):
Start with two pointers: slow and fast.
slow steps through the list one element at a time, fast steps two elements at a time.
slow adds each element to an accumulator variable, while fast moves foward.
When the fast pointer reaches the end of the list, the slow pointer will have only stepped half the number of elements, so its in the middle of the array.
Return the elements slow stepped over + the elements remaining. This should be two lists cut neatly in half.
The process above requires one traversal over the list and runs in O(n) time.
Since this is homework, I won't give a complete answer, but just to get you partway started, here's what it takes to cut the list cleanly in half:
let cut l =
let rec cut = function
| xs, ([] | [_]) -> xs
| [], _ -> []
| x::xs, y::y'::ys -> cut (xs, ys)
cut (l, l)
Note x::xs steps 1 element, y::y'::ys steps two.
This function returns the second half of the list. It is very easy to modify it so it returns the first half of the list as well.
You are looking for list slicing in F#. There was a great answer by #Juliet in this SO Thread: Slice like functionality from a List in F#
Basically it comes down to - this is not built in since there is no constant time index access in F# lists, but you can work around this as detailed. Her approach applied to your problem would yield a (not so efficient but working) solution:
let gencut(n, list) =
let firstList = list |> Seq.take n |> Seq.toList
let secondList = list |> Seq.skip n |> Seq.toList
(firstList, secondList)
(I didn't like my previous answer so I deleted it)
The first place to start when attacking list problems is to look at the List module which is filled with higher order functions which generalize many common problems and can give you succinct solutions. If you can't find anything suitable there, then you can look at the Seq module for solutions like #BrokenGlass demonstrated (but you can run into performance issues there). Next you'll want to consider recursion and pattern matching. There are two kinds of recursion you'll have to consider when processing lists: tail and non-tail. There are trade-offs. Tail-recursive solutions involve using an accumulator to pass state around, allowing you to place the recursive call in the tail position and avoid stack-overflows with large lists. But then you'll typically end up with a reversed list! For example,
Tail-recursive gencut solution:
let gencutTailRecursive n input =
let rec gencut cur acc = function
| hd::tl when cur < n ->
gencut (cur+1) (hd::acc) tl
| rest -> (List.rev acc), rest //need to reverse accumulator!
gencut 0 [] input
Non-tail-recursive gencut solution:
let gencutNonTailRecursive n input =
let rec gencut cur = function
| hd::tl when cur < n ->
let x, y = gencut (cur+1) tl //stackoverflow with big lists!
hd::x, y
| rest -> [], rest
gencut 0 input
Once you have your gencut solution, it's really easy to define cut:
let cut input = gencut ((List.length input)/2) input
Here's yet another way to do it using inbuilt library functions, which may or may not be easier to understand than some of the other answers. This solution also only requires one traversal across the input. My first thought after I looked at your problem was that you want something along the lines of List.partition, which splits a list into two lists based on a given predicate. However, in your case this predicate would be based on the index of the current element, which partition cannot handle, short of looking up the index for each element.
We can accomplish creating our own equivalent of this behavior using a fold or foldBack. I will use foldBack here as it means you won't have to reverse the lists afterward (see Stephens excellent answer). What we are going to do here is use the fold to provide our own index, along with the two output lists, all as the accumulator. Here is the generic function that will split your list into two lists based on n index:
let gencut n input =
//calculate the length of the list first so we can work out the index
let inputLength = input |> List.length
let results =
List.foldBack( fun elem acc->
let a,b,index = acc //decompose accumulator
if (inputLength - index) <= n then (elem::a,b,index+1)
else (a,elem::b,index+1) ) input ([],[],0)
let a,b,c = results
(a,b) //dump the index, leaving the two lists as output.
So here you see we start the foldBack with an initial accumulator value of ([],[],0). However, because we are starting at the end of the list, the 0 representing the current index needs to be subtracted from the total length of the list to get the actual index of the current element.
Then we simply check if the current index falls within the range of n. If it does, we update the accumulator by adding the current element to list a, leave list b alone, and increase the index by 1 : (elem::a,b,index+1). In all other cases, we do exactly the same but add the element to list b instead: (a,elem::b,index+1).
Now you can easily create your function that splits a list in half by creating another function over this one like so:
let cut input =
let half = (input |> List.length) / 2
input |> gencut half
I hope that can help you somewhat!
> cut data;;
val it : int list * int list = ([1; 2; 3], [4; 5; 6])
> gencut 5 data;;
val it : int list * int list = ([1; 2; 3; 4; 5], [6])
EDIT: you could avoid the index negation by supplying the length as the initial accumulator value and negating it on each cycle instead of increasing it - probably simpler that way :)
let gencut n input =
let results =
List.foldBack( fun elem acc->
let a,b,index = acc //decompose accumulator
if index <= n then (elem::a,b,index-1)
else (a,elem::b,index-1) ) input ([],[],List.length input)
let a,b,c = results
(a,b) //dump the index, leaving the two lists as output.
I have the same Homework, this was my solution. I'm just a student and new in F#
let rec gencut(n, listb) =
let rec cut n (lista : int list) (listb : int list) =
match (n , listb ) with
| 0, _ -> lista, listb
| _, [] -> lista, listb
| _, b :: listb -> cut (n - 1) (List.rev (b :: lista )) listb
cut n [] listb
let cut xs = gencut((List.length xs) / 2, xs)
Probably is not the best recursive solution, but it works. I think
You can use List.nth for random access and list comprehensions to generate a helper function:
let Sublist x y data = [ for z in x..(y - 1) -> List.nth data z ]
This will return items [x..y] from data. Using this you can easily generate gencut and cut functions (remember to check bounds on x and y) :)
check this one out:
let gencut s xs =
([for i in 0 .. s - 1 -> List.nth xs i], [for i in s .. (List.length xs) - 1 -> List.nth xs i])
the you just call
let cut xs =
gencut ((List.length xs) / 2) xs
with n durationn only one iteration split in two