[...] a pair of functions tofun : int -> ('a -> 'a) and fromfun : ('a -> 'a) ->
int such that (fromfun o tofun) n evaluates to n for every n : int.
Anyone able to explain to me what this is actually asking for? I'm looking for more of an explanation of that than an actual solution to this.
What this is asking for is:
1) A higher-order function tofun which when given an integer returns a polymorphic function, one which has type 'a->'a, meaning that it can be applied to values of any type, returning a value of the same type. An example of such a function is:
- fun id x = x;
val id = fn : 'a -> 'a
for example, id "cat" = "cat" and id () = (). The later value is of type unit, which is a type with only 1 value. Note that there is only 1 total function from unit to unit (namely, id or something equivalent). This underscores the difficulty with coming up with defining tofun: it returns a function of type 'a -> 'a, and other than the identity function it is hard to think of other functions. On the other hand -- such functions can fail to terminate or can raise an error and still have type 'a -> 'a.
2) fromfun is supposed to take a function of type 'a ->'a and return an integer. So e.g. fromfun id might evaluate to 0 (or if you want to get tricky it might never terminate or it might raise an error)
3) These are supposed to be inverses of each other so that, e.g. fromfun (tofun 5) needs to evaluate to 5.
Intuitively, this should be impossible in a sufficiently pure functional language. If it is possible in SML, my guess is that it would be by using some of the impure features of SML (which allow for side effects) to violate referential transparency. Or, the trick might involve raising and handling errors (which is also an impure feature of SML). If you find an answer which works in SML it would be interesting to see if it could be translated to the annoyingly pure functional language Haskell. My guess is that it wouldn't translate.
You can devise the following property:
fun prop_inverse f g n = (f o g) n = n
And with definitions for tofun and fromfun,
fun tofun n = ...
fun fromfun f = ...
You can test that they uphold the property:
val prop_test_1 =
List.all
(fn i => prop_inverse fromfun tofun i handle _ => false)
[0, ~1, 1, valOf Int.maxInt, valOf Int.minInt]
And as John suggests, those functions must be impure. I'd also go with exceptions.
Related
A function can be a highly nested structure:
function a(x) {
return b(c(x), d(e(f(x), g())))
}
First, wondering if a function has an instance. That is, the evaluation of the function being the instance of the function. In that sense, the type is the function, and the instance is the evaluation of it. If it can be, then how to model a function as a type (in some type-theory oriented language like Haskell or Coq).
It's almost like:
type a {
field: x
constructor b {
constructor c {
parameter: x
},
...
}
}
But I'm not sure if I'm not on the right track. I know you can say a function has a [return] type. But I'm wondering if a function can be considered a type, and if so, how to model it as a type in a type-theory-oriented language, where it models the actual implementation of the function.
I think the problem is that types based directly on the implementation (let's call them "i-types") don't seem very useful, and we already have good ways of modelling them (called "programs" -- ha ha).
In your specific example, the full i-type of your function, namely:
type a {
field: x
constructor b {
constructor c {
parameter: x
},
constructor d {
constructor e {
constructor f {
parameter: x
}
constructor g {
}
}
}
}
is just a verbose, alternative syntax for the implementation itself. That is, we could write this i-type (in a Haskell-like syntax) as:
itype a :: a x = b (c x) (d (e (f x) g))
On the other hand, we could convert your function implementation to Haskell term-level syntax directly to write it as:
a x = b (c x) (d (e (f x) g))
and the i-type and the implementation are exactly the same thing.
How would you use these i-types? The compiler might use them by deriving argument and return types to type-check the program. (Fortunately, there are well known algorithms, such as Algorithm W, for simultaneously deriving and type-checking argument and return types from i-types of this sort.) Programmers probably wouldn't use i-types directly -- they're too complicated to use for refactoring or reasoning about program behavior. They'd probably want to look at the types derived by the compiler for the arguments and return type.
In particular, "modelling" these i-types at the type level in Haskell doesn't seem productive. Haskell can already model them at the term level. Just write your i-types as a Haskell program:
a x = b (c x) (d (e (f x) g))
b s t = sqrt $ fromIntegral $ length (s ++ t)
c = show
d = reverse
e c ds = show (sum ds + fromIntegral (ord c))
f n = if even n then 'E' else 'O'
g = [1.5..5.5]
and don't run it. Congratulations, you've successfully modelled these i-types! You can even use GHCi to query derived argument and return types:
> :t a
a :: Floating a => Integer -> a -- "a" takes an Integer and returns a float
>
Now, you are perhaps imagining that there are situations where the implementation and i-type would diverge, maybe when you start introducing literal values. For example, maybe you feel like the function f above:
f n = if even n then 'E' else 'O'
should be assigned a type something like the following, that doesn't depend on the specific literal values:
type f {
field: n
if_then_else {
constructor even { -- predicate
parameter: n
}
literal Char -- then-branch
literal Char -- else-branch
}
Again, though, you'd be better off defining an arbitrary term-level Char, like:
someChar :: Char
someChar = undefined
and modeling this i-type at the term-level:
f n = if even n then someChar else someChar
Again, as long as you don't run the program, you've successfully modelled the i-type of f, can query its argument and return types, type-check it as part of a bigger program, etc.
I'm not clear exactly what you are aiming at, so I'll try to point at some related terms that you might want to read about.
A function has not only a return type, but a type that describes its arguments as well. So the (Haskell) type of f reads "f takes an Int and a Float, and returns a List of Floats."
f :: Int -> Float -> [Float]
f i x = replicate i x
Types can also describe much more of the specification of a function. Here, we might want the type to spell out that the length of the list will be the same as the first argument, or that every element of the list will be the same as the second argument. Length-indexed lists (often called Vectors) are a common first example of Dependent Types.
You might also be interested in functions that take types as arguments, and return types. These are sometimes called "type-level functions". In Coq or Idris, they can be defined the same way as more familiar functions. In Haskell, we usually implement them using Type Families, or using Type Classes with Functional Dependencies.
Returning to the first part of your question, Beta Reduction is the process of filling in concrete values for each of the function's arguments. I've heard people describe expressions as "after reduction" or "fully reduced" to emphasize some stage in this process. This is similar to a function Call Site, but emphasizes the expression & arguments, rather than the surrounding context.
Hello I started to write in sml and I have some difficulty in understanding a particular function.
I have this function:
fun isInRow (r:int) ((x,y)) = x=r;
I would be happy to get explain to some points:
What the function accepts and what it returns.
What is the relationship between (r: int) ((x, y)).
Thanks very much !!!
The function isInRow has two arguments. The first is named r. The second is a pair (x, y). The type ascription (r: int) says that r must be an int.
This function is curried, which is a little unusual for SML. What this means roughly speaking is that it accepts arguments given separately rather than supplied as a pair.
So, the function accepts an int and a pair whose first element is an int. These are accepted as separate arguments. It returns a boolean value (the result of the comparison x = r).
A call to the function would look like this:
isInRow 3 (3, 4)
There is more to say about currying (which is kind of cool), but I hope this is enough to get you going.
In addition to what Jeffrey has said,
You don't need the extra set of parentheses:
fun isInRow (r:int) (x,y) = x=r;
You don't need to specify the type :int. If you instead write:
fun isInRow r (x,y) = x=r;
then the function's changes type from int → (int • 'a) → bool into ''a → (''a • 'b) → bool, meaning that r and x can have any type that can be compared for equality (not just int), and y can still be anything since it is still disregarded.
Polymorphic functions are one of the strengths of typed, functional languages like SML.
You could even refrain from giving y a name:
fun isInRow r (x,_) = x=r;
Imagine I have a custom type and two functions:
type MyType = Int -> Bool
f1 :: MyType -> Int
f3 :: MyType -> MyType -> MyType
I tried to pattern match as follows:
f1 (f3 a b i) = 1
But it failed with error: Parse error in pattern: f1. What is the proper way to do the above?? Basically, I want to know how many f3 is there (as a and b maybe f3 or some other functions).
You can't pattern match on a function. For (almost) any given function, there are an infinite number of ways to define the same function. And it turns out to be mathematically impossible for a computer to always be able to say whether a given definition expresses the same function as another definition. This also means that Haskell would be unable to reliably tell whether a function matches a pattern; so the language simply doesn't allow it.
A pattern must be either a single variable or a constructor applied to some other patterns. Remembering that constructor start with upper case letters and variables start with lower case letters, your pattern f3 a n i is invalid; the "head" of the pattern f3 is a variable, but it's also applied to a, n, and i. That's the error message you're getting.
Since functions don't have constructors, it follows that the only pattern that can match a function is a single variable; that matches all functions (of the right type to be passed to the pattern, anyway). That's how Haskell enforces the "no pattern matching against functions" rule. Basically, in a higher order function there's no way to tell anything at all about the function you've been given except to apply it to something and see what it does.
The function f1 has type MyType -> Int. This is equivalent to (Int -> Bool) -> Int. So it takes a single function argument of type Int -> Bool. I would expect an equation for f1 to look like:
f1 f = ...
You don't need to "check" whether it's an Int -> Bool function by pattern matching; the type guarantees that it will be.
You can't tell which one it is; but that's generally the whole point of taking a function as an argument (so that the caller can pick any function they like knowing that you'll use them all the same way).
I'm not sure what you mean by "I want to know how many f3 is there". f1 always receives a single function, and f3 is not a function of the right type to be passed to f1 at all (it's a MyType -> MyType -> MyType, not a MyType).
Once a function has been applied its syntactic form is lost. There is now way, should I provide you 2 + 3 to distinguish what you get from just 5. It could have arisen from 2 + 3, or 3 + 2, or the mere constant 5.
If you need to capture syntactic structure then you need to work with syntactic structure.
data Exp = I Int | Plus Exp Exp
justFive :: Exp
justFive = I 5
twoPlusThree :: Exp
twoPlusThree = I 2 `Plus` I 3
threePlusTwo :: Exp
threePlusTwo = I 2 `Plus` I 3
Here the data type Exp captures numeric expressions and we can pattern match upon them:
isTwoPlusThree :: Exp -> Bool
isTwoPlusThree (Plus (I 2) (I 3)) = True
isTwoPlusThree _ = False
But wait, why am I distinguishing between "constructors" which I can pattern match on and.... "other syntax" which I cannot?
Essentially, constructors are inert. The behavior of Plus x y is... to do nothing at all, to merely remain as a box with two slots called "Plus _ _" and plug the two slots with the values represented by x and y.
On the other hand, function application is the furthest thing from inert! When you apply an expression to a function that function (\x -> ...) replaces the xes within its body with the applied value. This dynamic reduction behavior means that there is no way to get a hold of "function applications". They vanish into thing air as soon as you look at them.
I'm learning F# and I cannot figure out what the difference between let, fun and function is, and my text book doesn't really explain that either. As an example:
let s sym = function
| V x -> Map.containsKey x sym
| A(f, es) -> Map.containsKey f sym && List.forall (s sym) es;;
Couldn't I have written this without the function keyword? Or could I have written that with fun instead of function? And why do I have to write let when I've seen some examples where you write
fun s x =
...
What's the difference really?
I guess you should really ask MSDN, but in a nutshell:
let binds a value with a symbol. The value can be a plain type like an int or a string, but it can also be a function. In FP functions are values and can be treated in the same way as those types.
fun is a keyword that introduces an anonymous function - think lambda expression if you're familiar with C#.
Those are the two important ones, in the sense that all the others usages you've seen can be thought as syntax sugar for those two. So to define a function, you can say something like this:
let myFunction =
fun firstArg secondArg ->
someOperation firstArg secondArg
And that's very clear way of saying it. You declare that you have a function and then bind it to the myFunction symbol.
But you can save yourself some typing by just conflating anonymous function declaration and binding it to a symbol with let:
let myFunction firstArg secondArg =
someOperation firstArg secondArg
What function does is a bit trickier - you combine an anonymous single-argument function declaration with a match expression, by matching on an implicit argument. So these two are equivalent:
let myFunction firstArg secondArg =
match secondArg with
| "foo" -> firstArg
| x -> x
let myFunction firstArg = function
| "foo" -> firstArg
| x -> x
If you're just starting on F#, I'd steer clear of that one. It has its uses (mainly for providing succinct higher order functions for maps/filters etc.), but results in code less readable at a glance.
These things are sort of shortcuts to each other.
The most fundamental thing is let. This keyword gives names to stuff:
let name = "stuff"
Speaking more technically, the let keyword defines an identifier and binds it to a value:
let identifier = "value"
After this, you can use words name and identifier in your program, and the compiler will know what they mean. Without the let, there wouldn't be a way to name stuff, and you'd have to always write all your stuff inline, instead of referring to chunks of it by name.
Now, values come in different flavors. There are strings "some string", there are integer numbers 42, floating point numbers 5.3, Boolean values true, and so on. One special kind of value is function. Functions are also values, in most respects similar to strings and numbers. But how do you write a function? To write a string, you use double quotes, but what about function?
Well, to write a function, you use the special word fun:
let squareFn = fun x -> x*x
Here, I used the let keyword to define an identifier squareFn, and bind that identifier to a value of the function kind. Now I can use the word squareFn in my program, and the compiler will know that whenever I use it I mean a function fun x -> x*x.
This syntax is technically sufficient, but not always convenient to write. So in order to make it shorter, the let binding takes an extra responsibility upon itself and provides a shorter way to write the above:
let squareFn x = x*x
That should do it for let vs fun.
Now, the function keyword is just a short form for fun + match. Writing function is equivalent to writing fun x -> match x with, period.
For example, the following three definitions are equivalent:
let f = fun x ->
match x with
| 0 -> "Zero"
| _ -> "Not zero"
let f x = // Using the extra convenient form of "let", as discussed above
match x with
| 0 -> "Zero"
| _ -> "Not zero"
let f = function // Using "function" instead of "fun" + "match"
| 0 -> "Zero"
| _ -> "Not zero"
How many functions are present in this expression? :
'a -> 'a -> ('a*'a)
Also, how would you implement a function to return this type? I've created functions that have for example:
'a -> 'b -> ('a * b)
I created this by doing:
fun function x y = (x,y);
But I've tried using two x inputs and I get an error trying to output the first type expression.
Thanks for the help!
To be able to have two inputs of the same alpha type, I have to specify the type of both inputs to alpha.
E.g
fun function (x:'a) (y:'a) = (x, y);
==>
a' -> 'a -> (a' * 'a)
Assuming this is homework, I don't want to say too much. -> in a type expression represents a function. 'a -> 'a -> ('a * 'a) has two arrows, so 2 might be the answer for your first question, though I find that particular question obscure. An argument could be made that each fun defines exactly one function, which might happen to return a function for its output. Also, you ask "how many functions are present in the expression ... " but then give a string which literally has 0 functions in it (type descriptions describe functions but don't contain functions), so maybe the answer is 0.
If you want a natural example of int -> int -> int * int, you could implement the functiondivmod where divmod x y returns a tuple consisting of the quotient and remainder upon dividing x by y. For example, you would want divmod 17 5 to return (3,2). This is a built-in function in Python but not in SML, but is easily defined in SML using the built-in operators div and mod. The resulting function would have a type of the form 'a -> 'a -> 'a*'a -- but for a specific type (namely int). You would have to do something which is a bit less natural (such as what you did in your answer to your question) to come up with a polymorphic example.