I want to reuse a set of local assignments in the let form of different functions. Let's say
(def common-assign
[x 10
y 20])
one way to do it is with eval:
(eval `(defn ~'foo []
(let [~#common-assign
~'hello "world"])
balala))
The problem is that now you have to quote all other symbols, which is cumbersome.
Is there any other clean way to do what I want?
(defmacro with-common [& body]
`(let ~'[x 10, y 20]
~#body))
(with-common (+ x y))
(def common-assign
['x 10
'y 20])
(defmacro defn-common [name args & body]
`(defn ~name ~args (let ~common-assign ~#body)))
(defn-common foo [a b c] (+ a b c x y))
You can use a closure for this.
(let [x 10
y 20]
(defn foo
[]
(let [hello "world"]
...)))
(defn bar
[]
...))
But, why not just refer to the values in the namespace?
(def x 10)
(def y 20)
(defn foo
[]
(let [hello "world"]
...))
(defn bar
[]
...)
Related
Suppose I have a collection like [ "a"; "b"; "c" ] and I want to test every element against every other element.
I could generate all pairs like this:
let combinations xs =
Seq.allPairs xs xs
|> Seq.filter (fun (x, y) -> x <> y)
|> Seq.toList
combinations [ "a"; "b"; "c" ]
// [("a", "b"); ("a", "c"); ("b", "a"); ("b", "c"); ("c", "a"); ("c", "b")]
But for my test, I always know that f x y = f y x (since f is symmetric), so I want to trim the number of combinations tested:
let combinations xs =
Seq.allPairs xs xs
|> Seq.filter (fun (x, y) -> x <> y && x < y)
|> Seq.toList
combinations [ "a"; "b"; "c" ]
// [("a", "b"); ("a", "c"); ("b", "c")]
But this:
Doesn't seem like an efficient way to generate the test cases
Requires that x : comparison, which I don't think should be necessary
How should I implement this in F#?
Don't know about efficient - this looks like you need to cache the pairs already generated and filter on their presence in the cache.
The library implementation of Seq.allPairs goes along these lines:
let allPairs source1 source2 =
source1 |> Seq.collect (fun x -> source2 |> Seq.map (fun y -> x, y))
// val allPairs : source1:seq<'a> -> source2:seq<'b> -> seq<'a * 'b>
Then you integrate the caching and filtering into this, constraining both sequences to type seq<'a> and introducing the equality constraint.
let allPairs1 source1 source2 =
let h = System.Collections.Generic.HashSet()
source1 |> Seq.collect (fun x ->
source2 |> Seq.choose (fun y ->
if x = y || h.Contains (x, y) || h.Contains (y, x) then None
else h.Add (x, y) |> ignore; Some (x, y) ) )
// val allPairs1 :
// source1:seq<'a> -> source2:seq<'a> -> seq<'a * 'a> when 'a : equality
Test
allPairs1 [1..3] [2..4] |> Seq.toList
// val it : (int * int) list = [(1, 2); (1, 3); (1, 4); (2, 3); (2, 4); (3, 4)]
Because f is commutative, the simplest way to get all combinations is to project each item into a pair with the remainder of the list.
let rec combinations = function
| [] -> []
| x::xs -> (xs |> List.map (fun y -> (x, y))) # (combinations xs)
We don't need any comparison constraint.
let xs = [1; 2; 3; 4;]
combinations xs // [(1, 2); (1, 3); (1, 4); (2, 3); (2, 4); (3, 4)]
Checking the results with #kaefer's method:
combinations xs = (allPairs1 xs xs |> Seq.toList) // true
Another solution that assumes all elements are distinct (it uses position as identity):
let allSymmetricPairs xs =
seq {
let xs = Seq.toArray xs
for i = 0 to Array.length xs - 2 do
for j = i + 1 to Array.length xs - 1 do
yield xs.[i], xs.[j]
}
We can also pre-allocate the array, which may be faster if you plan to pull the whole sequence:
let allSymmetricPairs xs =
let xs = Seq.toArray xs
let n = Array.length xs
let result = Array.zeroCreate (n * (n - 1) / 2)
let mutable k = 0
for i = 0 to n - 2 do
for j = i + 1 to n - 1 do
result.[k] <- xs.[i], xs.[j]
k <- k + 1
result
Given a simple function, where we do pattern matching on the result of a recursive call, such as:
let rec sumProd = function
| [] -> (0,1)
| x::rest -> let (rSum,rProd) = sumProd rest
(x + rSum,x * rProd)
sumProd [2;5] //Expected (7, 10)
How would I go about changing it into something using higher order functions, e.g. foldBack?
let sumProdHigherOrder lst =
List.foldBack (fun x acc -> (acc + x, acc * x)) lst (0,0)
The above seemed almost like the way to do it, but calling it gives the error: The type 'int' does not match the type 'int * int'
sumProdHigherOrder [2;5] //Expected (7, 10)
What am I missing?
Your missing the tuple functions fst and snd:
List.foldBack (fun x acc -> (fst acc + x, snd acc * x)) [2;5] (0,1)
// val it : int * int = (7, 10)
Or even better, decomposing the tuple at the lambda. I see you just found it:
List.foldBack (fun x (s, m) -> (s + x, m * x)) [2;5] (0,1)
Also note that since the operations are commutative you can do a straight fold:
List.fold (fun (s, m) x -> (s + x, m * x)) (0,1) [2;5]
It will be more efficient.
Right! Of course it shouldn't be the same accumulator that gets passed through the list. After staring intensely at the code for some minutes, I figured it out:
let sumProdHigherOrder lst =
List.foldBack (fun x (acc,acc') -> (acc + x, acc' * x)) lst (0,1)
How can I simplify the Boolean expression obtained as a result of evaluating an uninterpreted function?
For instance, in the example: http://rise4fun.com/Z3/G8sL,
(eval (f x y))
yields (not (and (not x) (not y)))
I want to instead get the expression (or x y).
(simplify (eval (f x y))
gives an error.
This is not supported in the SMT-LIB 2.0 front-end.
You should consider one the programmatic front-ends for Z3.
For example, here is how to do it using the Z3 Python front-end (also available here):
B = BoolSort()
f = Function('f', B, B, B)
x, y = Bools('x y')
b1, b2 = Bools('b1 b2')
s = Solver()
s.add(ForAll([b1, b2], Implies(Or(b1, b2), f(b1, b2))))
s.add(Exists([b1, b2], Not(f(b1, b2))))
print(s.check())
m = s.model()
print(m.evaluate(f(x, y)))
print(simplify(m.evaluate(f(x, y)), elim_and=True))
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 (+))
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 :-).