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What is currying in F#? [duplicate]
(5 answers)
Closed 6 years ago.
I am new to F# and I need an example of currying.
Is it currying or partial application?
let multiplyByThree x =
let multiply y =
y * x
multiply 3
let result = multiplyByThree 3 // 9
Partial application is a process, well, of creating partially applied function, e.g.:
let sum x y = x + y // sum is a curried function, it's default in F#
let sum4 x = sum 4 x // partial application
Currying is an ability to represent a function with multiple arguments as a sequence of functions taking single argument and returning a function as well.
However, if you're working with .NET functions, they accept their arguments as tuples, e.g.:
let sum (x,y) = x + y
// let sum4 x = sum 4 x // can't do that!
let sum4 x = sum (4,x) // this is valid. passing a tuple
Related
in F# if I take a function that takes two arguments, for example, mod (%):
13 % 10
// val it : int = 3
which is the same as
(%) 13 10
// val it : int = 3
is there any way to write it in the pipe notation, currying the 13?
Obviously, the “two-argument function” is actually a one-argument function that returns an intermediate function. So can pipe
10 |> (%) 13
// val it : int = 3
However, I need the other way around, i.e. pipe the first argument 13, having the second argument 10 partially applied, but not the first one.
Is there anything in the language that helps to do that, without creating extra lambdas every time, i.e. to avoid the following?
13 |> (fun x -> x % 10)
There is no built-in, standard way to do this. Moreover, due to how function application works, it's impossible to do so: as soon as you write (%) 13, you've already applied the first argument, because function application has the highest and non-configurable precedence in F#.
You can, if course, make yourself a special function to produce a "weird" function application - one that would apply the second argument and leave a hole for the first:
let ap f x = fun y -> f y x
And then:
let x = 13 |> ap (%) 10
> x : int = 3
Incidentally, the function ap is a semi-standard occurrence in ML languages, and is usually called flip, because what it does is "flipping" the order of the arguments:
let flip f x y = f y x
Or, you can even make it into an operator:
let (-*-) = flip
And then:
let x = 13 |> (%) -*- 10
> x : int = 3
However, this sort of trickery gets unreadable very quickly. In practice, it is far more preferable to just declare a function that does what you need:
let mod10 x = x % 10
And then:
let x = 13 |> mod10
Or, if you really need it to be very general:
let mod' x y = y % x
And then:
let x = 13 |> mod' 10
You can write a combinator that will do this for any function of two arguments:
let inline flip f y x = f x y
This can be used as:
13 |> flip (%) 10
F# already contains an operator that will do what you want, namely <|:
10 |> (%) <| 13;;
val it : int = 10
This is equivalent to
(10 |> (%)) 13;;
val it : int = 10
K, you are looking for a flip
let flip f a b = f b a
I am a bit new to functional programming, and while I am somewhat familiar with F#, I am still learning about all the strange ways it works.
//I love my Rice and Curry'd functions
let add x =
let subFunction y =
x + y
subFunction
//explicit parameter
let add1 y = add 1 y
//implicit parameter
let add10 = add 10
//calling it with the parameter it doesn't show that it takes
let twenty = add10 10
So here add10 has implicit parameters by the fact that it is calling a function that returns a function that takes a parameter. Why is it accepted that I can declare it that way instead of the same way I declared add1?
It is really deceptive as judging by its declaration it, one would assume its just an int.
That's something coming from lambda calculus called eta-reduction
Basically it means that you can simplify your function/lambda by eliminating the last parameter on both sides of the expression when they are the same:
// instead of
let f x y = x + y
// in F# you can write
let f x y = (+) x y
// which is also the same as
let f x y = ((+) x) y
// then you can remove y
let f x = (+) x
// and then remove x
let f = (+)
In F# you can play with this as long as you don't reach the value restriction. So in your code let add1 y = add 1 y and let add10 = add 10 are equivalent. This is an example of how can you apply logic to reason about your code, applied to refactoring.
This question already has answers here:
F# Functions vs. Values
(4 answers)
Closed 8 years ago.
Newby question f# related,
What is the difference between this definitions in f# ?
module s
let log p =
printfn "expression is %A" p
let loggedWorkflow =
let x = 42
log x
let y = 43
log y
let z = x + y
log z
z
s.loggedWorkflow
and this one
module s
let log p =
printfn "expression is %A" p
let loggedWorkflow() =
let x = 42
log x
let y = 43
log y
let z = x + y
log z
z
s.loggedWorkflow()
The first one does not call the inner log, only returns z value
Why it works this way?
Thanks :)
I take this sample from
http://fsharpforfunandprofit.com/posts/computation-expressions-intro/
let loggedWorkflow = ... is defining a value. The body is evaluated as soon as the definition is reached (typically when the module s is loaded), and the value of loggedWorkflow is remembered as the result of evaluating the body, and returned every time someone evaluates s.loggedWorkflow.
let loggedWorkflow() = ... is defining a function that takes a single argument of type unit - the only value of this type is (), also typically pronounced "unit". The body doesn't get evaluated straight away, but only when the function is actually called. Each time it is called by actually passing an argument of type unit, e.g. with s.loggedWorkflow(), the body is evaluated and the resulting value returned.
I'm trying to find if one set is a subset of the other. My code works perfectly if both sets are the same length.
For example,
My code will return true if
x = [a;b;c]
y = [a;b;c]
My code will return false if
x = [a;b;c]
y = [a;b;d]
However, my code will not even compile if I try
x = ['a';'b';'c']
y = ['a';'b';'c';'d']
It's supposed to return true, but I get the following error message:
Type mismatch.
Expecting a Set<char * char * char> but given a Set<char * char * char * char>
The tuples have differing lengths of 3 and 4
My code is below
let mySubList x y =
printfn "%A is a proper subset of %A: %b" x y (Set.isSubset x y)
let x = Set.empty.Add('a','b','c')
let y = Set.empty.Add('a','b','c', 'd')
let z = Set.empty.Add('a','x','a','y','c','e')
let found = mySubList x y
All your sets contain the same number of elements: they all contain exactly one element. However they contain elements of different types, which is why you can't compare. Namely x contains a 3-tuple (char * char * char), y contains a 4-tuple and z contains a 5 tuple.
The important thing to note here is that Add('a', 'b', 'c') doesn't call Add with multiple arguments - it calls it with one argument, which is a tuple. This will add a single tuple element to the set. To add multiple elements, use Add multiple times or just use the set on a list (i.e. set ['a'; 'b'; 'c']) instead of Add to avoid multiple function calls.
I am interested in learning an elegant way to use currying in a functional programming language to numerically evaluate multiple integrals. My language of choice is F#.
If I want to integrate f(x,y,z)=8xyz on the region [0,1]x[0,1]x[0,1] I start by writing down a triple integral of the differential form 8xyz dx dy dz. In some sense, this is a function of three ordered arguments: a (float -> float -> float -> float).
I take the first integral and the problem reduces to the double integral of 4xy dx dy on [0,1]x[0,1]. Conceptually, we have curried the function to become a (float -> float -> float).
After the second integral I am left to take the integral of 2x dx, a (float -> float), on the unit interval.
After three integrals I am left with the result, the number 1.0.
Ignoring optimizations of the numeric integration, how could I succinctly execute this? I would like to write something like:
let diffForm = (fun x y z -> 8 * x * y * z)
let result =
diffForm
|> Integrate 0.0 1.0
|> Integrate 0.0 1.0
|> Integrate 0.0 1.0
Is this doable, if perhaps impractical? I like the idea of how closely this would capture what is going on mathematically.
I like the idea of how closely this would capture what is going on mathematically.
I'm afraid your premise is false: The pipe operator threads a value through a chain of functions and is closely related to function composition. Integrating over an n-dimensional domain however is analogous to n nested loops, i.e. in your case something like
for x in x_grid_nodes do
for y in y_grid_nodes do
for z in z_grid_nodes do
integral <- integral + ... // details depend on integration scheme
You cannot easily map that to a chain of three independet calls to some Integrate function and thus the composition integrate x1 x2 >> integrate y1 y2 >> integrate z1 z2 is actually not what you do when you integrate f. That is why Tomas' solution—if I understood it correctly (and I am not sure about that...)—essentially evaluates your function on an implicitly defined 3D grid and passes that to the integration function. I suspect that is as close as you can get to your original question.
You did not ask for it, but if you do want to evaluate a n-dimensional integral in practice, look into Monte Carlo integration, which avoids another problem commonly known as the "curse of dimensionality", i.e. that fact that the number of required sample points grows exponentially with n with classic integration schemes.
Update
You can implement iterated integration, but not with a single integrate function, because the type of the function to be integrated is different for each step of the integration (i.e. each step turns an n-ary function to an (n - 1)-ary one):
let f = fun x y z -> 8.0 * x * y * z
// numerically integrate f on [x1, x2]
let trapRule f x1 x2 = (x2 - x1) * (f x1 + f x2) / 2.0
// uniform step size for simplicity
let h = 0.1
// integrate an unary function f on a given discrete grid
let integrate grid f =
let mutable integral = 0.0
for x1, x2 in Seq.zip grid (Seq.skip 1 grid) do
integral <- integral + trapRule f x1 x2
integral
// integrate a 3-ary function f with respect to its last argument
let integrate3 lower upper f =
let grid = seq { lower .. h .. upper }
fun x y -> integrate grid (f x y)
// integrate a 2-ary function f with respect to its last argument
let integrate2 lower upper f =
let grid = seq { lower .. h .. upper }
fun x -> integrate grid (f x)
// integrate an unary function f on [lower, upper]
let integrate1 lower upper f =
integrate (seq { lower .. h .. upper }) f
With your example function f
f |> integrate3 0.0 1.0 |> integrate2 0.0 1.0 |> integrate1 0.0 1.0
yields 1.0.
I'm not entirely sure how you would implement this in a normal way, so this might not fully solve the problem, but here are some ideas.
To do the numerical integration, you'll (I think?) need to call the original function diffForm at various points as specified by the Integrate calls in the pipeline - but you actually need to call it at a product of the ranges - so if I wanted to call it only at the borders, I would still need to call it 2x2x2 times to cover all possible combinations (diffForm 0 0 0, diffForm 0 0 1, diffForm 0 1 0 etc.) and then do some calcualtion on the 8 results you get.
The following sample (at least) shows how to write similar code that calls the specified function with all combinations of the argument values that you specify.
The idea is to use continuations which can be called multiple times (and so when we get a function, we can call it repeatedly at multiple different points).
// Our original function
let diffForm x y z = 8.0 * x * y * z
// At the first step, we just pass the function to a continuation 'k' (once)
let diffFormK k = k diffForm
// This function takes a function that returns function via a continuation
// (like diffFormK) and it fixes the first argument of the function
// to 'lo' and 'hi' and calls its own continuation with both options
let range lo hi func k =
// When called for the first time, 'f' will be your 'diffForm'
// and here we call it twice with 'lo' and 'hi' and pass the
// two results (float -> float -> float) to the next in the pipeline
func (fun f -> k (f lo))
func (fun f -> k (f hi))
// At the end, we end up with a function that takes a continuation
// and it calls the continuation with all combinations of results
// (This is where you need to do something tricky to aggregate the results :-))
let integrate result =
result (printfn "%f")
// Now, we pass our function to 'range' for every argument and
// then pass the result to 'integrate' which just prints all results
let result =
diffFormK
|> range 0.0 1.0
|> range 0.0 1.0
|> range 0.0 1.0
|> integrate
This might be pretty confusing (because continuations take a lot of time to get used to), but perhaps you (or someone else here?) can find a way to turn this first attempt into a real numerical integration :-)