I been recently playing with F# . I was wondering instead of using a for loop to generate a sequence to element which are multiplied with every other element in the list how can I use a Seq map function or something similar to generate something like below.
So for e.g. I have a list [1..10] I would like to apply a fun which generates a result something like
[(1*1); (1*2);(1*3); (1*4); (1*5)......(2*1);(2*2);(2*3).....(3*1);(3*2)...]
How can i achieve this ?.
Many thanks for all you help.
let list = [1..10]
list |> List.map (fun v1 -> List.map (fun v2 -> (v1*v2)) list) |> List.collect id
The List.collect at the end flattens the list of lists.
It works the same with Seq instead of List, if you want a lazy sequence.
Or, using collect as the main iterator, as cfern suggested and obsessivley eliminating anonymous functions:
let flip f x y = f y x
let list = [1..10]
list |> List.collect ((*) >> ((flip List.map) list))
A list comprehension would be the easiest way to do this:
let allpairs L =
[for x in L do
for y in L -> (x*y)]
Or, without using any loops:
let pairs2 L = L |> List.collect (fun x -> L |> List.map (fun y -> (x*y)))
Edit in response to comment:
You could add a self-crossing extension method to a list like this:
type Microsoft.FSharp.Collections.List<'a> with
member L.cross f =
[for x in L do
for y in L -> f x y]
Example:
> [1;2;3].cross (fun x y -> (x,y));;
val it : (int * int) list =
[(1, 1); (1, 2); (1, 3); (2, 1); (2, 2); (2, 3); (3, 1); (3, 2); (3, 3)]
I wouldn't use an extension method in F# myself, is feels a bit C#'ish. But that's mostly because I don't feel that a fluent syntax is needed in F# because I usually chain my functions together with pipe (|>) operators.
My approach would be to extend the List module with a cross function, not the type itself:
module List =
let cross f L1 L2 =
[for x in L1 do
for y in L2 -> f x y]
If you do this, you can use the cross method like any other method of List:
> List.cross (fun x y -> (x,y)) [1;2;3] [1;2;3];;
val it : (int * int) list =
[(1, 1); (1, 2); (1, 3); (2, 1); (2, 2); (2, 3); (3, 1); (3, 2); (3, 3)]
> List.cross (*) [1;2;3] [1;2;3];;
val it : int list = [1; 2; 3; 2; 4; 6; 3; 6; 9]
Or we can implement a general cross product function:
let cross l1 l2 =
seq { for el1 in l1 do
for el2 in l2 do
yield el1, el2 };;
and use this function to get the job done:
cross [1..10] [1..10] |> Seq.map (fun (a,b) -> a*b) |> Seq.toList
To implement the same thing without for loops, you can use the solution using higher-order functions posted by Mau, or you can write the same thing explicitly using recursion:
let cross xs ys =
let rec crossAux ol2 l1 l2 =
match l1, l2 with
// All elements from the second list were processed
| x::xs, [] -> crossAux ol2 xs ol2
// Report first elements and continue looping after
// removing first element from the second list
| x::xs, y::ys -> (x, y)::(crossAux ol2 l1 ys)
// First list is empty - we're done
| [], _ -> []
crossAux ys xs ys
This may be useful if you're learning functional programming and recursion, however, the solution using sequence expressions is far more practically useful.
As a side-note, the first version by Mau can be made a bit nicer, because you can join the call to List.map with a call to List.collect id like this (you can pass the nested processing lambda directly as a parameter to collect). The cross function would look like this (Of course, you can modifiy this to take a parameter to apply to the two numbers instead of creating a tuple):
let cross xs ys =
xs |> List.collect (fun v1 ->
ys |> List.map (fun v2 -> (v1, v2)))
Incidentally, there is a free chapter from my book avaialable, which discusses how sequence expressions and List.collect functions work. It is worth noting, that for in sequence expressions directly corresponds to List.collect, so you can write the code just by using this higher order function:
let cross xs ys =
xs |> List.collect (fun v1 ->
ys |> List.collect (fun v2 -> [(v1, v2)] ))
However, see the free chapter for more information :-).
Related
I have a situation where I'm parsing a file and I need to know both:
the current line
the previous line
before the previous line requirements, I was doing something like:
myData
|> List.mapi (fun i data -> parse i data)
but now I need access to the previous line, so scan is ideal for that, but then I loose the index.
so, I need a List.scani function :) is it something that could be built easily in an idiomatic way?
You could define scani as follows:
let scani (f:int->'S->'T->'S) (state:'S) (list:'T list) =
list
|>List.scan (fun (i,s) x -> (i+1,f i s x)) (0,state)
|>List.map snd
Creating a tuple with the original state and a counter initialized with (0,state). The state is manipulated as usual with the folder function f (that now takes an extra i parameter) and the counter incremented by one. Finally, we remove the counter from the state by taking the second element of the state.
You could use it as follows, where i is the index, s is the state, and x the element.
[1;2;3]
|> scani (fun i s x -> s + i*x) 0
|> should equal [0;0;2;8]
It may not be the most efficient way to do it, but it seems to work (I called it scanl given that you want access to the previous element, or line):
let scanl f s l =
List.scan (fun (acc,elem0) elem1 -> (f acc elem0 elem1),elem1) (s,List.head l) l
|> List.map fst
Examples of usage:
let l = [1..5]
scanl (fun acc elem0 elem1 -> elem0,elem1) (0,0) l
//result: [(0, 0); (1, 1); (1, 2); (2, 3); (3, 4); (4, 5)]
The usual List.scan would give this:
List.scan (fun acc elem -> elem) 0 l
//result [0; 1; 2; 3; 4; 5]
Let's say I have an array
let arr = [|1;2;3;4;5;6|]
I would like to convert it to something like
[|(1,2);(3,4);(5,6)|]
I've seen Seq.window but this one is going to generate something like
[|(1,2);(2,3);(3,4);(4,5);(5,6)|]
which is not what I want
You can use Array.chunkBySize and then map each sub-array into tuples:
let input = [|1..10|]
Array.chunkBySize 2 list |> Array.map (fun xs -> (xs.[0], xs.[1]))
#Slugart's accepted answer is the best approach (IMO) assuming you know that the array has an even number of elements, but here's another approach that doesn't throw an exception if there does happen to be an odd number (it just omits the last trailing element):
let arr = [|1;2;3;4;5|]
seq { for i in 0 .. 2 .. arr.Length - 2 -> (arr.[i], arr.[i+1]) } |> Seq.toArray
You could use Seq.pairwise, as long as you filter out every other tuple. The filtering needs to pass a state through the iteration, which is usually effected by the scan function.
[|1..10|]
|> Seq.pairwise
|> Seq.scan (fun s t ->
match s with None -> Some t | _ -> None )
None
|> Seq.choose id
|> Seq.toArray
// val it : (int * int) [] = [|(1, 2); (3, 4); (5, 6); (7, 8); (9, 10)|]
But then it's also possible to have scan generate the tuples directly, on penalty of an intermediate array.
[|1..10|]
|> Array.scan (function
| Some x, _ -> fun y -> None, Some(x, y)
| _ -> fun x -> Some x, None )
(None, None)
|> Array.choose snd
Use Seq.pairwise to turn a sequence into tuples
[|1;2;3;4;5;6|]
|> Seq.pairwise
|> Seq.toArray
val it : (int * int) [] = [|(1, 2); (2, 3); (3, 4); (4, 5); (5, 6)|]
Should be:
let rec slice =
function
| [] -> []
| a::b::rest -> (a,b) :: slice (rest)
| _::[] -> failwith "cannot slice uneven list"
I am interested to implement fold3, fold4 etc., similar to List.fold and List.fold2. e.g.
// TESTCASE
let polynomial (x:double) a b c = a*x + b*x*x + c*x*x*x
let A = [2.0; 3.0; 4.0; 5.0]
let B = [1.5; 1.0; 0.5; 0.2]
let C = [0.8; 0.01; 0.001; 0.0001]
let result = fold3 polynomial 0.7 A B C
// 2.0 * (0.7 ) + 1.5 * (0.7 )^2 + 0.8 * (0.7 )^3 -> 2.4094
// 3.0 * (2.4094) + 1.0 * (2.4094)^2 + 0.01 * (2.4094)^3 -> 13.173
// 4.0 * (13.173) + 0.5 * (13.173)^2 + 0.001 * (13.173)^3 -> 141.75
// 5.0 * (141.75) + 0.2 * (141.75)^2 + 0.0001 * (141.75)^3 -> 5011.964
//
// Output: result = 5011.964
My first method is grouping the 3 lists A, B, C, into a list of tuples, and then apply list.fold
let fold3 f x A B C =
List.map3 (fun a b c -> (a,b,c)) A B C
|> List.fold (fun acc (a,b,c) -> f acc a b c) x
// e.g. creates [(2.0,1.5,0.8); (3.0,1.0,0.01); ......]
My second method is to declare a mutable data, and use List.map3
let mutable result = 0.7
List.map3 (fun a b c ->
result <- polynomial result a b c // Change mutable data
// Output intermediate data
result) A B C
// Output from List.map3: [2.4094; 13.17327905; 141.7467853; 5011.963942]
// result mutable: 5011.963942
I would like to know if there are other ways to solve this problem. Thank you.
For fold3, you could just do zip3 and then fold:
let polynomial (x:double) (a, b, c) = a*x + b*x*x + c*x*x*x
List.zip3 A B C |> List.fold polynomial 0.7
But if you want this for the general case, then you need what we call "applicative functors".
First, imagine you have a list of functions and a list of values. Let's assume for now they're of the same size:
let fs = [ (fun x -> x+1); (fun x -> x+2); (fun x -> x+3) ]
let xs = [3;5;7]
And what you'd like to do (only natural) is to apply each function to each value. This is easily done with List.map2:
let apply fs xs = List.map2 (fun f x -> f x) fs xs
apply fs xs // Result = [4;7;10]
This operation "apply" is why these are called "applicative functors". Not just any ol' functors, but applicative ones. (the reason for why they're "functors" is a tad more complicated)
So far so good. But wait! What if each function in my list of functions returned another function?
let f1s = [ (fun x -> fun y -> x+y); (fun x -> fun y -> x-y); (fun x -> fun y -> x*y) ]
Or, if I remember that fun x -> fun y -> ... can be written in the short form of fun x y -> ...
let f1s = [ (fun x y -> x+y); (fun x y -> x-y); (fun x y -> x*y) ]
What if I apply such list of functions to my values? Well, naturally, I'll get another list of functions:
let f2s = apply f1s xs
// f2s = [ (fun y -> 3+y); (fun y -> 5+y); (fun y -> 7+y) ]
Hey, here's an idea! Since f2s is also a list of functions, can I apply it again? Well of course I can!
let ys = [1;2;3]
apply f2s ys // Result: [4;7;10]
Wait, what? What just happened?
I first applied the first list of functions to xs, and got another list of functions as a result. And then I applied that result to ys, and got a list of numbers.
We could rewrite that without intermediate variable f2s:
let f1s = [ (fun x y -> x+y); (fun x y -> x-y); (fun x y -> x*y) ]
let xs = [3;5;7]
let ys = [1;2;3]
apply (apply f1s xs) ys // Result: [4;7;10]
For extra convenience, this operation apply is usually expressed as an operator:
let (<*>) = apply
f1s <*> xs <*> ys
See what I did there? With this operator, it now looks very similar to just calling the function with two arguments. Neat.
But wait. What about our original task? In the original requirements we don't have a list of functions, we only have one single function.
Well, that can be easily fixed with another operation, let's call it "apply first". This operation will take a single function (not a list) plus a list of values, and apply this function to each value in the list:
let applyFirst f xs = List.map f xs
Oh, wait. That's just map. Silly me :-)
For extra convenience, this operation is usually also given an operator name:
let (<|>) = List.map
And now, I can do things like this:
let f x y = x + y
let xs = [3;5;7]
let ys = [1;2;3]
f <|> xs <*> ys // Result: [4;7;10]
Or this:
let f x y z = (x + y)*z
let xs = [3;5;7]
let ys = [1;2;3]
let zs = [1;-1;100]
f <|> xs <*> ys <*> zs // Result: [4;-7;1000]
Neat! I made it so I can apply arbitrary functions to lists of arguments at once!
Now, finally, you can apply this to your original problem:
let polynomial a b c (x:double) = a*x + b*x*x + c*x*x*x
let A = [2.0; 3.0; 4.0; 5.0]
let B = [1.5; 1.0; 0.5; 0.2]
let C = [0.8; 0.01; 0.001; 0.0001]
let ps = polynomial <|> A <*> B <*> C
let result = ps |> List.fold (fun x f -> f x) 0.7
The list ps consists of polynomial instances that are partially applied to corresponding elements of A, B, and C, and still expecting the final argument x. And on the next line, I simply fold over this list of functions, applying each of them to the result of the previous.
You could check the implementation for ideas:
https://github.com/fsharp/fsharp/blob/master/src/fsharp/FSharp.Core/array.fs
let fold<'T,'State> (f : 'State -> 'T -> 'State) (acc: 'State) (array:'T[]) =
checkNonNull "array" array
let f = OptimizedClosures.FSharpFunc<_,_,_>.Adapt(f)
let mutable state = acc
for i = 0 to array.Length-1 do
state <- f.Invoke(state,array.[i])
state
here's a few implementations for you:
let fold2<'a,'b,'State> (f : 'State -> 'a -> 'b -> 'State) (acc: 'State) (a:'a array) (b:'b array) =
let mutable state = acc
Array.iter2 (fun x y->state<-f state x y) a b
state
let iter3 f (a: 'a[]) (b: 'b[]) (c: 'c[]) =
let f = OptimizedClosures.FSharpFunc<_,_,_,_>.Adapt(f)
if a.Length <> b.Length || a.Length <> c.Length then failwithf "length"
for i = 0 to a.Length-1 do
f.Invoke(a.[i], b.[i], c.[i])
let altIter3 f (a: 'a[]) (b: 'b[]) (c: 'c[]) =
if a.Length <> b.Length || a.Length <> c.Length then failwithf "length"
for i = 0 to a.Length-1 do
f (a.[i]) (b.[i]) (c.[i])
let fold3<'a,'b,'State> (f : 'State -> 'a -> 'b -> 'c -> 'State) (acc: 'State) (a:'a array) (b:'b array) (c:'c array) =
let mutable state = acc
iter3 (fun x y z->state<-f state x y z) a b c
state
NB. we don't have an iter3, so, implement that. OptimizedClosures.FSharpFunc only allow up to 5 (or is it 7?) params. There are a finite number of type slots available. It makes sense. You can go higher than this, of course, without using the OptimizedClosures stuff.
... anyway, generally, you don't want to be iterating too many lists / arrays / sequences at once. So I'd caution against going too high.
... the better way forward in such cases may be to construct a record or tuple from said lists / arrays, first. Then, you can just use map and iter, which are already baked in. This is what zip / zip3 are all about (see: "(array1.[i],array2.[i],array3.[i])")
let zip3 (array1: _[]) (array2: _[]) (array3: _[]) =
checkNonNull "array1" array1
checkNonNull "array2" array2
checkNonNull "array3" array3
let len1 = array1.Length
if len1 <> array2.Length || len1 <> array3.Length then invalidArg3ArraysDifferent "array1" "array2" "array3" len1 array2.Length array3.Length
let res = Microsoft.FSharp.Primitives.Basics.Array.zeroCreateUnchecked len1
for i = 0 to res.Length-1 do
res.[i] <- (array1.[i],array2.[i],array3.[i])
res
I'm working with arrays at the moment, so my solution pertained to those. Sorry about that. Here's a recursive version for lists.
let fold3 f acc a b c =
let mutable state = acc
let rec fold3 f a b c =
match a,b,c with
| [],[],[] -> ()
| [],_,_
| _,[],_
| _,_,[] -> failwith "length"
| ahead::atail, bhead::btail, chead::ctail ->
state <- f state ahead bhead chead
fold3 f atail btail ctail
fold3 f a b c
i.e. we define a recursive function within a function which acts upon/mutates/changes the outer scoped mutable acc variable (a closure in functional speak). Finally, this gets returned.
It's pretty cool how much type information gets inferred about these functions. In the array examples above, mostly I was explicit with 'a 'b 'c. This time, we let type inference kick in. It knows we're dealing with lists from the :: operator. That's kind of neat.
NB. the compiler will probably unwind this tail-recursive approach so that it is just a loop behind-the-scenes. Generally, get a correct answer before optimising. Just mentioning this, though, as food for later thought.
I think the existing answers provide great options if you want to generalize folding, which was your original question. However, if I simply wanted to call the polynomial function on inputs specified in A, B and C, then I would probably do not want to introduce fairly complex constructs like applicative functors with fancy operators to my code base.
The problem becomes a lot easier if you transpose the input data, so that rather than having a list [A; B; C] with lists for individual variables, you have a transposed list with inputs for calculating each polynomial. To do this, we'll need the transpose function:
let rec transpose = function
| (_::_)::_ as M -> List.map List.head M :: transpose (List.map List.tail M)
| _ -> []
Now you can create a list with inputs, transpose it and calculate all polynomials simply using List.map:
transpose [A; B; C]
|> List.map (function
| [a; b; c] -> polynomial 0.7 a b c
| _ -> failwith "wrong number of arguments")
There are many ways to solve this problem. Few are mentioned like first zip3 all three list, then run over it. Using Applicate Functors like Fyodor Soikin describes means you can turn any function with any amount of arguments into a function that expects list instead of single arguments. This is a good general solution that works with any numbers of lists.
While this is a general good idea, i'm sometimes shocked that so few use more low-level tools. In this case it is a good idea to use recursion and learn more about recursion.
Recursion here is the right-tool because we have immutable data-types. But you could consider how you would implement it with mutable lists and looping first, if that helps. The steps would be:
You loop over an index from 0 to the amount of elements in the lists.
You check if every list has an element for the index
If every list has an element then you pass this to your "folder" function
If at least one list don't have an element, then you abort the loop
The recursive version works exactly the same. Only that you don't use an index to access the elements. You would chop of the first element from every list and then recurse on the remaining list.
Otherwise List.isEmpty is the function to check if a List is empty. You can chop off the first element with List.head and you get the remaining list with the first element removed by List.tail. This way you can just write:
let rec fold3 f acc l1 l2 l3 =
let h = List.head
let t = List.tail
let empty = List.isEmpty
if (empty l1) || (empty l2) && (empty l3)
then acc
else fold3 f (f acc (h l1) (h l2) (h l3)) (t l1) (t l2) (t l3)
The if line checks if every list has at least one element. If that is true
it executes: f acc (h l1) (h l2) (h l3). So it executes f and passes it the first element of every list as an argument. The result is the new accumulator of
the next fold3 call.
Now that you worked on the first element of every list, you must chop off the first element of every list, and continue with the remaining lists. You achieve that with List.tail or in the above example (t l1) (t l2) (t l3). Those are the next remaining lists for the next fold3 call.
Creating a fold4, fold5, fold6 and so on isn't really hard, and I think it is self-explanatory. My general advice is to learn a little bit more about recursion and try to write recursive List functions without Pattern Matching. Pattern Matching is not always easier.
Some code examples:
fold3 (fun acc x y z -> x + y + z :: acc) [] [1;2;3] [10;20;30] [100;200;300] // [333;222;111]
fold3 (fun acc x y z -> x :: y :: z :: acc) [] [1;2;3] [10;20;30] [100;200;300] // [3; 30; 300; 2; 20; 200; 1; 10; 100]
Does groupBy guarantee that sort order is preserved in code like the following?
x
|> Seq.sortBy (fun (x, y) -> y)
|> Seq.groupBy (fun (x, y) -> x)
By preserving sort order, I mean can we guarantee that within each grouping by x, the result is still sorted by y.
This is true for simple examples,
[(1, 3);(2, 1);(1, 1);(2, 3)]
|> Seq.sortBy (fun (x, y) -> y)
|> Seq.groupBy (fun (x, y) -> x)
// seq [(2, seq [(2, 1); (2, 3)]); (1, seq [(1, 1); (1, 3)])]
I want to make sure there are no weird edge cases.
What do you mean by preserving sort order? Seq.groupBy changes the type of the sequence, so how can you even meaningfully compare before and after?
For a given xs of the type seq<'a * 'b>, the type of the expression xs |> Seq.sortBy snd is seq<'a * 'b>, whereas the type of the expression xs |> Seq.sortBy snd |> Seq.groupBy fst is seq<'a * seq<'a * 'b>>. Thus, whether or not the answer to the question is yes or no depends on what you mean by preserving the sort order.
As #Petr wrote in the comments, it's easy to test this. If you're worried about special cases, write a Property using FsCheck and see if it generalises:
open FsCheck.Xunit
open Swensen.Unquote
[<Property>]
let isSortOrderPreserved (xs : (int * int) list) =
let actual = xs |> Seq.sortBy snd |> Seq.groupBy fst
let expected = xs |> Seq.sortBy snd |> Seq.toList
expected =! (actual |> Seq.map snd |> Seq.concat |> Seq.toList)
In this property, I've interpreted the property of sort order preservation to mean that if you subsequently concatenate the grouped sequences, the sort order is preserved. Your definition may be different.
Given this particular definition, however, running the property clearly demonstrates that the property doesn't hold:
Falsifiable, after 6 tests (13 shrinks) (StdGen (1448745695,296088811)):
Original:
[(-3, -7); (4, -7); (4, 0); (-4, 0); (-4, 7); (3, 7); (3, -1); (-5, -1)]
Shrunk:
[(3, 1); (3, 0); (0, 0)]
---- Swensen.Unquote.AssertionFailedException : Test failed:
[(3, 0); (0, 0); (3, 1)] = [(3, 0); (3, 1); (0, 0)]
false
Here we see that if the input is [(3, 1); (3, 0); (0, 0)], the grouped sequence doesn't preserve the sort order (which isn't surprising to me).
Based on the updated question, here's a property that examines that question:
[<Property(MaxTest = 10000)>]
let isSortOrderPreservedWithEachGroup (xs : (int * int) list) =
let actual = xs |> Seq.sortBy snd |> Seq.groupBy fst
let expected =
actual
|> Seq.map (fun (k, vals) -> k, vals |> Seq.sort |> Seq.toList)
|> Seq.toList
expected =!
(actual |> Seq.map (fun (k, vals) -> k, Seq.toList vals) |> Seq.toList)
This property does, indeed, hold:
Ok, passed 10000 tests.
You should still consider carefully whether you want to rely on behaviour that isn't documented, since it could change in later incarnations of F#. Personally, I'd adopt a piece of advice from the Zen of Python:
Explicit is better than implicit.
BTW, the reason for all that conversion to F# lists is because lists have structural equality, while sequences don't.
The documentation doesn't say explicitly (except through the example), but the implementation does preserve the order of the original sequence. It would be quite surprising if it didn't: the equivalent functions in other languages that I am aware of do.
Who cares. Instead of sorting and then grouping, just group and then sort and the ordering is guaranteed even if the F# implementation of groupBy eventually changes:
x
|> Seq.groupBy (fun (x, y) -> x)
|> Seq.map (fun (k, v) -> k, v |> Seq.sortBy (fun (x, y) -> y))
Hullo all.
I am a C# programmer, exploring F# in my free time. I have written the following little program for image convolution in 2D.
open System
let convolve y x =
y |> List.map (fun ye -> x |> List.map ((*) ye))
|> List.mapi (fun i l -> [for q in 1..i -> 0] # l # [for q in 1..(l.Length - i - 1) -> 0])
|> List.reduce (fun r c -> List.zip r c |> List.map (fun (a, b) -> a + b))
let y = [2; 3; 1; 4]
let x = [4; 1; 2; 3]
printfn "%A" (convolve y x)
My question is: Is the above code an idiomatic F#? Can it be made more concise? (e.g. Is there some shorter way to generate a filled list of 0's (I have used list comprehension in my code for this purpose)). Any changes that can improve its performance?
Any help would be greatly appreciated. Thanks.
EDIT:
Thanks Brian. I didn't get your first suggestion. Here's how my code looks after applying your second suggestion. (I also abstracted out the list-fill operation.)
open System
let listFill howMany withWhat = [for i in 1..howMany -> withWhat]
let convolve y x =
y |> List.map (fun ye -> x |> List.map ((*) ye))
|> List.mapi (fun i l -> (listFill i 0) # l # (listFill (l.Length - i - 1) 0))
|> List.reduce (List.map2 (+))
let y = [2; 3; 1; 4]
let x = [4; 1; 2; 3]
printfn "%A" (convolve y x)
Anything else can be improved? Awaiting more suggestions...
As Brian mentioned, the use of # is generally problematic, because the operator cannot be efficiently implemented for (simple) functional lists - it needs to copy the entire first list.
I think Brians suggestion was to write a sequence generator that would generate the list at once, but that's a bit more complicated. You'd have to convert the list to array and then write something like:
let convolve y x =
y |> List.map (fun ye -> x |> List.map ((*) ye) |> Array.ofList)
|> List.mapi (fun i l -> Array.init (2 * l.Length - 1) (fun n ->
if n < i || n - i >= l.Length then 0 else l.[n - i]))
|> List.reduce (Array.map2 (+))
In general, if performance is an important concern, then you'll probably need to use arrays anyway (because this kind of problem can be best solved by accessing elements by index). Using arrays is a bit more difficult (you need to get the indexing right), but perfectly fine approach in F#.
Anyway, if you want to write this using lists, then here ara some options. You could use sequence expressions everywhere, which would look like this:
let convolve y (x:_ list) =
[ for i, v1 in x |> List.zip [ 0 .. x.Length - 1] ->
[ yield! listFill i 0
for v2 in y do yield v1 * v2
yield! listFill (x.Length - i - 1) 0 ] ]
|> List.reduce (List.map2 (+))
... or you can also combine the two options and use a nested sequence expression (with yield! to generate zeros and lists) in the lambda function that you're passing to List.mapi:
let convolve y x =
y |> List.map (fun ye -> x |> List.map ((*) ye))
|> List.mapi (fun i l ->
[ for _ in 1 .. i do yield 0
yield! l
for _ in 1 .. (l.Length - i - 1) do yield 0 ])
|> List.reduce (List.map2 (+))
The idiomatic solution would be to use arrays and loops just as you would in C. However, you may be interested in the following alternative solution that uses pattern matching instead:
let dot xs ys =
Seq.map2 (*) xs ys
|> Seq.sum
let convolve xs ys =
let rec loop vs xs ys zs =
match xs, ys with
| x::xs, ys -> loop (dot ys (x::zs) :: vs) xs ys (x::zs)
| [], _::(_::_ as ys) -> loop (dot ys zs :: vs) [] ys zs
| _ -> List.rev vs
loop [] xs ys []
convolve [2; 3; 1; 4] [4; 1; 2; 3]
Regarding the zeroes, how about e.g.
[for q in 0..l.Length-1 -> if q=i then l else 0]
(I haven't tested to verify that is exactly right, but hopefully the idea is clear.) In general, any use of # is a code smell.
Regarding overall performance, for small lists this is probably fine; for larger ones, you might consider using Seq rather than List for some of the intermediate computations, to avoid allocating as many temporary lists along the way.
It looks like maybe the final zip-then-map could be replaced by just a call to map2, something like
... fun r c -> (r,c) ||> List.map2 (+)
or possibly even just
... List.map2 (+)
but I'm away from a compiler so haven't double-checked it.
(fun ye -> x |> List.map ((*) ye))
Really ?
I'll admit |> is pretty, but you could just wrote :
(fun ye -> List.map ((*) ye) x)
Another thing that you could do is fuse the first two maps. l |> List.map f |> List.mapi g = l |> List.mapi (fun i x -> g i (f x)), so incorporating Tomas and Brian's suggestions, you can get something like:
let convolve y x =
let N = List.length x
y
|> List.mapi (fun i ye ->
[for _ in 1..i -> 0
yield! List.map ((*) ye) x
for _ in 1..(N-i-1) -> 0])
|> List.reduce (List.map2 (+))