I'm trying to do this exercise:
I'm not sure how to use Type in F#, in F# interactive, I wrote type term = Term of float *int, Then I tried to create a value of type term by let x: term = (3.5,8);;But it gives an error.
Then I tried let x: term = Term (3.5,8);; and it worked. So Why is that?
For the first function, I tried:
let multiplyPolyByTerm (x:term, p:poly)=
match p with
|[]->[]
But that gives an error on the line |[]->[] saying that the expression is expecting a type poly, but poly is a in fact a list right? So why is it wrong here? I fixed it by |Poly[]->Poly[]. Then I tried to finish the function by giving the recursive definition of multiplying each term of the polynomial by the given term: |Poly a::af-> This gives an error so I'm stuck on trying to break down the Poly list.
If anyone has suggestion on good readings about Type in F#, please share it.
I got all the methods now, However,I find myself unable to throw an exception when the polynomial is an empty list as the base case of my recursive function is an empty list. Also, I don't know how to group common term together, Please help, Here are my codes:
type poly=Poly of (float*int) list
type term = Term of float *int
exception EmptyList
(*
let rec mergeCommonTerm(p:poly)=
let rec iterator ((a: float,b: int ), k: (float*int) list)=
match k with
|[]->(a,b)
|ki::kf-> if b= snd ki then (a+ fst ki,b)
match p with
|Poly [] -> Poly []
|Poly (a::af)-> match af with
|[]-> Poly [a]
|b::bf -> if snd a =snd b then Poly (fst a +fst b,snd a)::bf
else
*)
let rec multiplyPolyByTerm (x:term, p:poly)=
match x with
| Term (coe,deg) -> match p with
|Poly[] -> Poly []
|Poly (a::af) -> match multiplyPolyByTerm (x,Poly af) with
|Poly recusivep-> Poly ((fst a *coe,snd a + deg)::recusivep)
let rec addTermToPoly (x:term, p:poly)=
match x with
|Term (coe, deg)-> match p with
|Poly[] -> Poly [(coe,deg)]
|Poly (a::af)-> if snd a=deg then Poly ((fst a+coe,deg)::af)
else match addTermToPoly (x,Poly af) with
|Poly recusivep-> Poly (a::recusivep)
let rec addPolys (x:poly, y: poly)=
match x with
|Poly []->y
|Poly (xh::xt)-> addPolys(Poly xt,addTermToPoly(Term xh, y))
let rec multPolys (x:poly,y:poly)=
match x with
|Poly []-> Poly[]
|Poly (xh::xt)->addPolys (multiplyPolyByTerm(Term xh,y),multPolys(Poly xt,y))
let evalTerm (values:float) (termmm : term) :float=
match termmm with
|Term (coe,deg)->coe*(values**float(deg))
let rec evalPoly (polyn : poly, v: float) :float=
match polyn with
|Poly []->0.0
|Poly (ph::pt)-> (evalTerm v (Term ph)) + evalPoly (Poly pt,v)
let rec diffPoly (p:poly) :poly=
match p with
|Poly []->Poly []
|Poly (ah::at)-> match diffPoly (Poly at) with
|Poly [] -> if snd ah = 0 then Poly []
else Poly [(float(snd ah)*fst ah,snd ah - 1)]
|Poly (bh::bt)->Poly ((float(snd ah)*fst ah,snd ah - 1)::bh::bt)
As I mentioned in a comment, reading https://fsharpforfunandprofit.com/posts/discriminated-unions/ will be very helpful for you. But let me give you some quick help to get you unstuck and starting to solve your immediate problems. You're on the right track, you're just struggling a little with the syntax (and operator precedence, which is part of the syntax).
First, load the MSDN operator precedence documentation in another tab while you read the rest of this answer. You'll want to look at it later on, but first I'll explain a subtlety of how F# treats discriminated unions that you probably haven't understood yet.
When you define a discriminated union type like poly, the name Poly acts like a constructor for the type. In F#, constructors are functions. So when you write Poly (something), the F# parser interprets this as "take the value (something) and pass it to the function named Poly". Here, the function Poly isn't one you had to define explicitly; it was implicitly defined as part of your type definition. To really make this clear, consider this example:
type Example =
| Number of int
| Text of string
5 // This has type int
Number 5 // This has type Example
Number // This has type (int -> Example), i.e. a function
"foo" // This has type string
Text "foo" // This has type Example
Text // This has type (string -> Example), i.e. a function
Now look at the operator precedence list that you loaded in another tab. Lowest precedence is at the top of the table, and highest precedence is at the bottom; in other words, the lower something is on the table, the more "tightly" it binds. As you can see, function application (f x, calling f with parameter x) binds very tightly, more tightly than the :: operator. So when you write f a::b, that is not read as f (a::b), but rather as (f a)::b. In other words, f a::b reads as "Item b is a list of some type which we'll call T, and the function call f a produces an item of type T that should go in front of list b". If you instead meant "take the list formed by putting item a at the head of list b, and then call f with the resulting list", then that needs parentheses: you have to write f (a::b) to get that meaning.
So when you write Poly a::af, that's interpreted as (Poly a)::af, which means "Here is a list. The first item is a Poly a, which means that a is a (float * int) list. The rest of the list will be called af". And since the value your passing into it is not a list, but rather a poly type, that is a type mismatch. (Note that items of type poly contain lists, but they are not themselves lists). What you needed to write was Poly (a::af), which would have meant "Here is an item of type poly that contains a list. That list should be split into the head, a, and the rest, af."
I hope that helped rather than muddle the waters further. If you didn't understand any part of this, let me know and I'll try to make it clearer.
P.S. Another point of syntax you might want to know: F# gives you many ways to signal an error condition (like an empty list in this assignment), but your professor has asked you to use exception EmptyList when invalid input is given. That means he expects your code to "throw" or "raise" an exception when you encounter an error. In C# the term is "throw", but in F# the term is "raise", and the syntax looks like this:
if someErrorCondition then
raise EmptyList
// Or ...
match listThatShouldNotBeEmpty with
| [] -> raise EmptyList
| head::rest -> // Do something with head, etc.
That should take care of the next question you would have needed to ask. :-)
Update 2: You've edited your question to clarify another issue you're having, where your recursive function boils down to an empty list as the base case — yet your professor asked you to consider an empty list as an invalid input. There are two ways to solve this. I'll discuss the more complicated one first, then I'll discuss the easier one.
The more complicated way to solve this is to have two separate functions, an "outer" one and an "inner" one, for each of the functions you have been asked to define. In each case, the "outer" one checks whether the input is an empty list and throws an exception if that's the case. If the input is not an empty list, then it passes the input to the "inner" function, which does the recursive algorithm (and does NOT consider an empty list to be an error). So the "outer" function is basically only doing error-checking, and the "inner" function is doing all the work. This is a VERY common approach in professional programming, where all your error-checking is done at the "edges" of your code, while the "inner" code never has to deal with errors. It's therefore a good approach to know about — but in your particular case, I think it's more complicated than you need.
The easier solution is to rewrite your functions to consider a single-item list as the base case, so that your recursive functions never go all the way to an empty list. Then you can always consider an empty list to be an error. Since this is homework I won't give you an example based on your actual code, but rather an example based on a simple "take the sum of a list of integers" exercise where an empty list would be considered an error:
let rec sumNonEmptyList (input : int list) : int =
match input with
| [] -> raise EmptyList
| [x] -> x
| x::rest -> x + sumNonEmptyList rest
The syntax [x] in a match expression means "This matches a list with exactly one item in it, and assigns the name x to the value of that item". In your case, you'd probably be matching against Poly [] to raise an exception, Poly [a] as the base case, and Poly (a::af) as the "more than one item" case. (That's as much of a clue as I think I should give you; you'll learn better if you work out the rest yourself).
Related
I'm trying to use pattern matching for an optional list of tuples but I could not write an exhaustive matching expression despite trying everything I can think of.
I'm struggling to understand why the F# compiler is insisting that my patterns in the following examples are not exhaustive.
module Mapper.PatternMatchingOddity
type A = A of string
type B = B of string
type ProblemType = ProblemType of (A * B) list option
//Incomplete pattern matches on this expression. Some ([_;_]) may indicate a case...
let matchProblem = function
|Some [(x:A,y:B)] -> []
|Some ([_,_]) -> [] //rider says this rule will never be matched
|None -> []
//same as before
let matchProblem1 = function
|Some [_,_] -> []
|Some [] -> []
//|Some _ -> []//this removes the warning but what is the case not covered by the previous two?
|None -> []
let matchProblem2 (input:ProblemType) =
match input with //same as before
|ProblemType (Some [(x:A,y:B)]) -> []
|ProblemType None -> []
How do I write the exhaustive matching and what am I missing above? Can you give an example for an input that would be accepted as a valid parameter to these functions and slip through the patterns?
Great question! I think many people that start out with F# grapple with how lists, options and tuples interact. Let me start by saying: the compiler is correct. The short answer is: you are only matching over singleton lists. Let me try to explain that a little deeper.
Your type is ('a * 'b) list option, essentially. In your case, 'a and 'b are themselves a single-case discriminated using of a string. Let's simplify this a bit and see what happens if we look at each part of your type in isolation (you may already know this, but it may help to put it in context):
First of all, your type is option. This has two values, None or Some 'a. To match over an option you can just do something like
match o with
| Some value -> value
| None -> failwith "nothing"`
Next, your type is a list. The items in a list are divided by semicolons ;. An empty list is [], a singleton list (one with a single item) is [x] and multiple items [x;y...]. To add something to the start of a list use ::. Lists are a special type of discriminated union and the syntax to match over them mimics the syntax of lists construction:
match myList with
| [] -> "empty"
| [x] -> printfn "one item: %A" x
| [x; y] -> printfn "two items: %A, %A" x y
| x::rest -> printfn "more items, first one: %A" x
Third, your list type is itself a tuple type. To deconstruct or match over a tuple type, you can use the comma ,, as with match (x, y) with 1, 2 -> "it's 1 and 2!" ....
Combine all this, we must match over an option (outer) then list (middle) then tuple. Something like Some [] for an empty list and None for the absence of a list and Some [a, b] for a singleton list and Some (a,b)::rest for a list with one or more items.
Now that we have the theory out of the way, let's see if we can tackle your code. First let's have a look at the warning messages:
Incomplete pattern matches on this expression. Some ([_;_]) may indicate a case...
This is correct, the item in your code is separated by , denoting the tuple, and the message says Some [something; something] (underscore means "anything"), which is a list of two items. But it wouldn't help you much to add it, because the list can still be longer than 2.
rider says this rule will never be matched
Rider is correct (which calls the FSC compiler services underneath). The rule above that line is Some [(x:A,y:B)] (the :A and :B are not needed here), which matches any Some singleton array with a tuple. Some [_,_] does the same, except that it doesn't catch the values in a variable.
this removes the warning but what is the case not covered by the previous two?
It removes the warning because Some _ means Some with anything, as _ means just that: it is a placeholder for anything. In this case, it matches the empty list, the 2-item list, the 3-item list the n-item list (the only one your match is the 1-item list in that example).
Can you give an example for an input that would be accepted as a valid parameter
Yes. Valid input that you were not matching is Some [] (empty list), Some [A "a", B "x"; A "2", B "2"] (list of two items) etc.
Let's take your first example. You had this:
let matchProblem = function
|Some [(x:A,y:B)] -> [] // matching a singleton list
|Some ([_,_]) -> [] // matches a singleton list (will never match, see before)
|None -> [] // matches None
Here's what you (probably) need:
let notAProblemAnymore = function
// first match all the 'Some' matches:
| Some [] -> "empty" // an empty list
| Some [x,y] -> "singleton" // a list with one item that is a tuple
| Some [_,a;_,b] -> "2-item list" // a list with two tuples, ignoring the first half of each tuple
| Some ((x,y)::rest) -> "multi-item list"
// a list with at least one item, and 'rest' as the
// remaining list, which can be empty (but won't,
// here it has at least three items because of the previous matches)
| None -> "Not a list at all" // matching 'None' for absence of a list
To sum it up: you were matching over a list that had only one item and the compiler complained that you missed lists of other lengths (empty lists and lists that have more than one item).
Usually it is not necessary to use option with a list, because the empty list already means the absence of data. So whenever you find yourself writing the type option list consider whether just list would suffice. It will make the matching easier.
You are struggling because your example is too “example”.
Let’s convert your example to a more meaningful one: check the input, so that
If it is none then print “nothing”, otherwise:
If it has zero element then print “empty”
If it has only one element then print “ony one element: ...”
If it has two elements then print “we have two elements: ...”
If it has three elements then print “there are three elements: ...”
If it has more than three elements then print “oh man, the first element is ..., the second element is ..., the third element is ..., and N elements more”
Now you can see that your code only covers the first 3 cases. So the F# compiler was correct.
To rewrite the code:
let matchProblem (ProblemType input) =
match input with
| None -> printfn "nothing"
| Some [] -> ...
| Some [(x, y)] -> ...
| Some [(x1, y1); (x2, y2)] -> ...
| Some [(x1, y1); (x2, y2); (x3, y3)] -> ...
| Some (x1, y1) :: (x2, y2) :: (x3, y3) :: rest -> // access rest.Length to print the number of more elements
Notice that I’m using pattern matching on the parameter ProblemType input so that I can extract the input in a convenient way. This makes the later patterns simpler.
Personally, when I learned F#, I didn’t understand many features/syntax until I used them in production code.
Upon covering the predefined datatypes in f# (i.e lists) and how to sum elements of a list or a sequence, I'm trying to learn how I can work with user defined datatypes. Say I create a data type, call it list1:
type list1 =
A
| B of int * list1
Where:
A stands for an empty list
B builds a new list by adding an int in front of another list
so 1,2,3,4, will be represented with the list1 value:
B(1, B(2, B(3, B(4, A))))
From the wikibook I learned that with a list I can sum the elements by doing:
let List.sum [1; 2; 3; 4]
But how do I go about summing the elements of a user defined datatype? Any hints would be greatly appreciated.
Edit: I'm able to take advantage of the match operator:
let rec sumit (l: ilist) : int =
match l with
| (B(x1, A)) -> x1
| (B(x1, B(x2, A))) -> (x1+x2)
sumit (B(3, B(4, A)))
I get:
val it : int = 7
How can I make it so that if I have more than 2 ints it still sums the elemets (i.e. (B(3, B(4, B(5, A)))) gets 12?
One good general approach to questions like this is to write out your algorithm in word form or pseudocode form, then once you've figured out your algorithm, convert it to F#. In this case where you want to sum the lists, that would look like this:
The first step in figuring out an algorithm is to carefully define the specifications of the problem. I want an algorithm to sum my custom list type. What exactly does that mean? Or, to be more specific, what exactly does that mean for the two different kinds of values (A and B) that my custom list type can have? Well, let's look at them one at a time. If a list is of type A, then that represents an empty list, so I need to decide what the sum of an empty list should be. The most sensible value for the sum of an empty list is 0, so the rule is "I the list is of type A, then the sum is 0". Now, if the list is of type B, then what does the sum of that list mean? Well, the sum of a list of type B would be its int value, plus the sum of the sublist.
So now we have a "sum" rule for each of the two types that list1 can have. If A, the sum is 0. If B, the sum is (value + sum of sublist). And that rule translates almost verbatim into F# code!
let rec sum (lst : list1) =
match lst with
| A -> 0
| B (value, sublist) -> value + sum sublist
A couple things I want to note about this code. First, one thing you may or may not have seen before (since you seem to be an F# beginner) is the rec keyword. This is required when you're writing a recursive function: due to internal details in how the F# parser is implemented, if a function is going to call itself, you have to declare that ahead of time when you declare the function's name and parameters. Second, this is not the best way to write a sum function, because it is not actually tail-recursive, which means that it might throw a StackOverflowException if you try to sum a really, really long list. At this point in your learning F# you maybe shouldn't worry about that just yet, but eventually you will learn a useful technique for turning a non-tail-recursive function into a tail-recursive one. It involves adding an extra parameter usually called an "accumulator" (and sometimes spelled acc for short), and a properly tail-recursive version of the above sum function would have looked like this:
let sum (lst : list1) =
let rec tailRecursiveSum (acc : int) (lst : list1) =
match lst with
| A -> acc
| B (value, sublist) -> tailRecursiveSum (acc + value) sublist
tailRecursiveSum 0 lst
If you're already at the point where you can understand this, great! If you're not at that point yet, bookmark this answer and come back to it once you've studied tail recursion, because this technique (turning a non-tail-recursive function into a tail-recursive one with the use of an inner function and an accumulator parameter) is a very valuable one that has all sorts of applications in F# programming.
Besides tail-recursion, generic programming may be a concept of importance for the functional learner. Why go to the trouble of creating a custom data type, if it only can hold integer values?
The sum of all elements of a list can be abstracted as the repeated application of the addition operator to all elements of the list and an accumulator primed with an initial state. This can be generalized as a functional fold:
type 'a list1 = A | B of 'a * 'a list1
let fold folder (state : 'State) list =
let rec loop s = function
| A -> s
| B(x : 'T, xs) -> loop (folder s x) xs
loop state list
// val fold :
// folder:('State -> 'T -> 'State) -> state:'State -> list:'T list1 -> 'State
B(1, B(2, B(3, B(4, A))))
|> fold (+) 0
// val it : int = 10
Making also the sum function generic needs a little black magic called statically resolved type parameters. The signature isn't pretty, it essentially tells you that it expects the (+) operator on a type to successfully compile.
let inline sum xs = fold (+) Unchecked.defaultof<_> xs
// val inline sum :
// xs: ^a list1 -> ^b
// when ( ^b or ^a) : (static member ( + ) : ^b * ^a -> ^b)
B(1, B(2, B(3, B(4, A))))
|> sum
// val it : int = 10
According to this previous answer
You could implement List.map like this:
let rec map project = function
| [] -> []
| head :: tail ->
project head :: map project tail ;;
but instead, it is implemented like this:
let rec map project = function
| [] -> []
| head :: tail ->
let result = project head in
result :: map project tail ;;
They say that it is done this way to make sure the projection function is called in the expected order in case it has side effects, e.g.
map print_int [1;2;3] ;;
should print 123, but the first implementation would print 321. However, when I test both of them myself in OCaml and F#, they produce exactly the same 123 result.
(Note that I am testing this in the OCaml and F# REPLs--Nick in the comments suggests this might be the cause of my inability to reproduce, but why?)
What am I misunderstanding? Can someone elaborate why they should produce different orders and how I can reproduce? This runs contrary to my previous understanding of OCaml code I've written in the past so this was surprising to me and I want to make sure not to repeat the mistake. When I read the two, I read it as exactly the same thing with an extraneous intermediary binding.
My only guess is that the order of expression evaluation using cons is right to left, but that seems very odd?
This is being done purely as research to better understand how OCaml executes code, I don't really need to create my own List.map for production code.
The point is that the order of function application in OCaml is unspecified, not that it will be in some specific undesired order.
When evaluating this expression:
project head :: map project tail
OCaml is allowed to evaluate project head first or it can evaluate map project tail first. Which one it chooses to do is unspecified. (In theory it would probably be admissible for the order to be different for different calls.) Since you want a specified order, you need to use the form with let.
The fact that the order is unspecified is documented in Section 6.7 of the OCaml manual. See the section Function application:
The order in which the expressions expr, argument1, …, argumentn are evaluated is not specified.
(The claim that the evaluation order is unspecified isn't something you can test. No number of cases of a particular order prove that that order is always going to be chosen.)
So when you have an implementation of map like this:
let rec map f = function
| [] -> []
| a::l -> f a :: map f l
none of the function applications (f a) within the map calls are guaranteed to be evaluated sequentially in the order you'd expect. So when you try this:
map print_int [1;2;3]
you get the output
321- : unit list = [(); (); ()]
since by the time those function applications weren't executed in a specific order.
Now when you implement the map like this:
let rec map f = function
| [] -> []
| a::l -> let r = f a in r :: map f l
you're forcing the function applications to be executed in the order you're expecting because you explicitly make a call to evaluate let r = f a.
So now when you try:
map print_int [1;2;3]
you will get
123- : unit list = [(); (); ()]
because you've explicitly made an effort to evaluate the function applications in order.
I very frequently want to apply the same argument twice to a binary function f, is there a name for this convert function/combinator?
// convert: f: ('a -> 'a -> 'b) -> 'a -> 'b
let convert f x = f x x
Example usage might be partially applying convert with the multiplication operator * to fix the multiplicand and multiplier:
let fixedMultiplication = convert (*)
fixedMultiplication 2 // returns 4
That combinator is usually called a warbler; the name comes from Raymond Smullyan's book To Mock a Mockingbird, which has a bunch of logic puzzles around combinator functions, presented in the form of birds that can imitate each other's songs. See this usage in Suave, and this page which lists a whole bunch of combinator functions (the "standard" ones and some less-well-known ones as well), and the names that Smullyan gave them in his book.
Not really an answer to what it's called in F#, but in APL or J, it's called the "reflexive" (or perhaps "reflex") operator. In APL it is spelt ⍨ and used monadically – i.e. applied to one function (on its left). In J it's called ~, and used in the same way.
For example: f⍨ x is equivalent to x f x (in APL, functions that take two arguments are always used in a binary infix fashion).
So the "fixedMultiplication" (or square) function is ×⍨ in APL, or *~ in J.
This is the monadic join operator for functions. join has type
Monad m => m (m a) => m a
and functions form a monad where the input type is fixed (i.e. ((->) a), so join has type:
(a -> (a -> b)) -> (a -> b)
I am trying to write a F# function that finds the biggest value. I am new to F# and am confused as to how to implement this with the correct type and recursion.
Any help would be greatly appreciated along with an explanation of how it works, I really need to understand how it works so I can attempt to create other F# functions. Thanks!
When creating recursive functions, start thinking about the corner cases. Your helper function takes a list and a "maximum so far". Corner cases: What if your list is empty? What if you only have a 1 element list, or focus on the first element? That directly translates into a match statement:
let rec helper (l, m) =
match l, m with
| [], m -> m
| (l1 :: rest), m ->
let max1 = if l1 > m then l1 else m
helper(rest, max1)
I'll leave the wrapper findMax open, but clearly you can solve that using the same thinking: What if you get an empty list? (scream!) What if you get a list with elements (the first element is your maximum so far, feed the rest of the list into your helper)
And of course you could put it all into one function. I've chosen this rather roundabout helper because your template code was shaped in that way.
The first thing to do is to start thinking recursively and/or mathematically. In most general vague terms, it should look like "The result of my function is..." - then try to actually put into words what the result should be.
Applying to your particular problem, I would phrase it like this:
when given a list of one element, the result of findMax is that element.
when given a list of more than one element, the result of findMax is the maximum of the lists's head and the maximum element of its tail.
This thinking can be translated into F# almost word for word:
let rec findMax list =
match list with
| [x] -> x
| head::tail -> max head (findMax tail)
where:
let max a b = if a > b then a else b
Note, however, that this function is incomplete: it doesn't specify what the result should be when given an empty list. I will leave this as an exercise for the reader.