Composing a chain of 2-argument functions - haskell

So I have a list of a functions of two arguments of the type [a -> a -> a]
I want to write a function which will take the list and compose them into a chain of functions which takes length+1 arguments composed on the left. For example if I have [f,g,h] all of types [a -> a -> a] I need to write a function which gives:
chain [f,g,h] = \a b c d -> f ( g ( h a b ) c ) d
Also if it helps, the functions are commutative in their arguments ( i.e. f x y = f y x for all x y ).
I can do this inside of a list comprehension given that I know the the number of functions in question, it would be almost exactly like the definition. It's the stretch from a fixed number of functions to a dynamic number that has me stumped.
This is what I have so far:
f xs = f' xs
where
f' [] = id
f' (x:xs) = \z -> x (f' xs) z
I think the logic is along the right path, it just doesn't type-check.
Thanks in advance!

The comment from n.m. is correct--this can't be done in any conventional way, because the result's type depends on the length of the input list. You need a much fancier type system to make that work. You could compromise in Haskell by using a list that encodes its length in the type, but that's painful and awkward.
Instead, since your arguments are all of the same type, you'd be much better served by creating a function that takes a list of values instead of multiple arguments. So the type you want is something like this: chain :: [a -> a -> a] -> [a] -> a
There are several ways to write such a function. Conceptually you want to start from the front of the argument list and the end of the function list, then apply the first function to the first argument to get something of type a -> a. From there, apply that function to the next argument, then apply the next function to the result, removing one element from each list and giving you a new function of type a -> a.
You'll need to handle the case where the list lengths don't match up correctly, as well. There's no way around that, other than the aforementioned type-encoded-lengths and the hassle associate with such.

I wonder, whether your "have a list of a functions" requirement is a real requirement or a workaround? I was faced with the same problem, but in my case set of functions was small and known at compile time. To be more precise, my task was to zip 4 lists with xor. And all I wanted is a compact notation to compose 3 binary functions. What I used is a small helper:
-- Binary Function Chain
bfc :: (c -> d) -> (a -> b -> c) -> a -> b -> d
bfc f g = \a b -> f (g a b)
For example:
ghci> ((+) `bfc` (*)) 5 3 2 -- (5 * 3) + 2
17
ghci> ((+) `bfc` (*) `bfc` (-)) 5 3 2 1 -- ((5 - 3) * 2) + 1
5
ghci> zipWith3 ((+) `bfc` (+)) [1,2] [3,4] [5,6]
[9,12]
ghci> getZipList $ (xor `bfc` xor `bfc` xor) <$> ZipList [1,2] <*> ZipList [3,4] <*> ZipList [5,6] <*> ZipList [7,8]
[0,8]
That doesn't answers the original question as it is, but hope still can be helpful since it covers pretty much what question subject line is about.

Related

parenthesis in Haskell functions

I just want to know how do we know which functions need brackets () and which ones do not? For example
replicate 100 (product (map (*3) (zipWith max [1,2,3,4,5] [4,5,6,7,8])))
works fine. But
replicate 100 (product (map (*3) (zipWith (max [1,2,3,4,5] [4,5,6,7,8]))))
does not work. It is because I put a set of brackets for zipWith. In this small example, zipWith and max do not have brackets, but replicate, product and map do. In general is there a way to know/figure out which functions need brackets and which ones dont.
Function application is left associative. So, when you write an expression like:
f g h x
it means:
((f g) h) x
And also the type of zipWith provides a clue:
zipWith :: (a -> b -> c) -> [a] -> [b] -> [c]
it says that zipWith has 3 parameters: a function and two lists.
When you write:
zipWith (max [1,2,3,4,5] [4,5,6,7,8])
The interpreter will understand that
max [1,2,3,4,5] [4,5,6,7,8]
will be the first parameter to zipWith, which is type incorrect. Note that zipWith expects a function of two arguments as its first argument and, as pointed out by #Cubic, max [1,2,3,4,5] [4,5,6,7,8] will return the maximum
between these two lists according the usual lexicographic order, which will be of type [a], for some type a which is instance of Ord and Num. Said that, the error become evident since you are trying to pass a value of type
(Num a, Ord a) => [a]
where a value of type
(a -> b -> c)
is expected.
Rodrigo gave the right answer. I'll just add that it is a misconception to think that some functions need parentheses, while others don't.
This is just like in school math:
3 * (4+5)
It is simply not the case that + expressions need parentheses and * expressions don't need them in general.
In Haskell, you can always get away without parentheses at all. Whenever you need to enclose an expression in parentheses, the alternative is to introduce a local name and bind it to that expression, then use the name instead of the expression.
In your example:
replicate 100 (product (map (*3) (zipWith max [1,2,3,4,5] [4,5,6,7,8])))
let list1 = product list2
list2 = map thrice list3
thrice x = x*3
list3 = zipWith max [1,2,3,4,5] [4,5,6,7,8]
in replicate 100 list1
In fact, I often write functions top down thus:
foo x y z = result
where
result = ...
...
However, as it was said before, expressions that consist of function applications can also often be written without parentheses by making use of (.) and ($) and in such cases, the top down approach from above may be overly verbose and the following would be much clearer (because there is no noise through newly introduced names):
replicate 100
. product
. map (*3)
$ zipWith max [1..5] [4..8]

Partial application of functions and currying, how to make a better code instead of a lot of maps?

I am a beginner at Haskell and I am trying to grasp it.
I am having the following problem:
I have a function that gets 5 parameters, lets say
f x y w z a = x - y - w - z - a
And I would like to apply it while only changing the variable x from 1 to 10 whereas y, w, z and a will always be the same. The implementation I achieved was the following but I think there must be a better way.
Let's say I would like to use:
x from 1 to 10
y = 1
w = 2
z = 3
a = 4
Accordingly to this I managed to apply the function as following:
map ($ 4) $ map ($ 3) $ map ($ 2) $ map ($ 1) (map f [1..10])
I think there must be a better way to apply a lot of missing parameters to partially applied functions without having to use too many maps.
All the suggestions so far are good. Here's another, which might seem a bit weird at first, but turns out to be quite handy in lots of other situations.
Some type-forming operators, like [], which is the operator which maps a type of elements, e.g. Int to the type of lists of those elements, [Int], have the property of being Applicative. For lists, that means there is some way, denoted by the operator, <*>, pronounced "apply", to turn lists of functions and lists of arguments into lists of results.
(<*>) :: [s -> t] -> [s] -> [t] -- one instance of the general type of <*>
rather than your ordinary application, given by a blank space, or a $
($) :: (s -> t) -> s -> t
The upshot is that we can do ordinary functional programming with lists of things instead of things: we sometimes call it "programming in the list idiom". The only other ingredient is that, to cope with the situation when some of our components are individual things, we need an extra gadget
pure :: x -> [x] -- again, one instance of the general scheme
which wraps a thing up as a list, to be compatible with <*>. That is pure moves an ordinary value into the applicative idiom.
For lists, pure just makes a singleton list and <*> produces the result of every pairwise application of one of the functions to one of the arguments. In particular
pure f <*> [1..10] :: [Int -> Int -> Int -> Int -> Int]
is a list of functions (just like map f [1..10]) which can be used with <*> again. The rest of your arguments for f are not listy, so you need to pure them.
pure f <*> [1..10] <*> pure 1 <*> pure 2 <*> pure 3 <*> pure 4
For lists, this gives
[f] <*> [1..10] <*> [1] <*> [2] <*> [3] <*> [4]
i.e. the list of ways to make an application from the f, one of the [1..10], the 1, the 2, the 3 and the 4.
The opening pure f <*> s is so common, it's abbreviated f <$> s, so
f <$> [1..10] <*> [1] <*> [2] <*> [3] <*> [4]
is what would typically be written. If you can filter out the <$>, pure and <*> noise, it kind of looks like the application you had in mind. The extra punctuation is only necessary because Haskell can't tell the difference between a listy computation of a bunch of functions or arguments and a non-listy computation of what's intended as a single value but happens to be a list. At least, however, the components are in the order you started with, so you see more easily what's going on.
Esoterica. (1) in my (not very) private dialect of Haskell, the above would be
(|f [1..10] (|1|) (|2|) (|3|) (|4|)|)
where each idiom bracket, (|f a1 a2 ... an|) represents the application of a pure function to zero or more arguments which live in the idiom. It's just a way to write
pure f <*> a1 <*> a2 ... <*> an
Idris has idiom brackets, but Haskell hasn't added them. Yet.
(2) In languages with algebraic effects, the idiom of nondeterministic computation is not the same thing (to the typechecker) as the data type of lists, although you can easily convert between the two. The program becomes
f (range 1 10) 2 3 4
where range nondeterministically chooses a value between the given lower and upper bounds. So, nondetermism is treated as a local side-effect, not a data structure, enabling operations for failure and choice. You can wrap nondeterministic computations in a handler which give meanings to those operations, and one such handler might generate the list of all solutions. That's to say, the extra notation to explain what's going on is pushed to the boundary, rather than peppered through the entire interior, like those <*> and pure.
Managing the boundaries of things rather than their interiors is one of the few good ideas our species has managed to have. But at least we can have it over and over again. It's why we farm instead of hunting. It's why we prefer static type checking to dynamic tag checking. And so on...
Others have shown ways you can do it, but I think it's useful to show how to transform your version into something a little nicer. You wrote
map ($ 4) $ map ($ 3) $ map ($ 2) $ map ($ 1) (map f [1..10])
map obeys two fundamental laws:
map id = id. That is, if you map the identity function over any list, you'll get back the same list.
For any f and g, map f . map g = map (f . g). That is, mapping over a list with one function and then another one is the same as mapping over it with the composition of those two functions.
The second map law is the one we want to apply here.
map ($ 4) $ map ($ 3) $ map ($ 2) $ map ($ 1) (map f [1..10])
=
map ($ 4) . map ($ 3) . map ($ 2) . map ($ 1) . map f $ [1..10]
=
map (($ 4) . ($ 3) . ($ 2) . ($ 1) . f) [1..10]
What does ($ a) . ($ b) do? \x -> ($ a) $ ($ b) x = \x -> ($ a) $ x b = \x -> x b a. What about ($ a) . ($ b) . ($ c)? That's (\x -> x b a) . ($ c) = \y -> (\x -> x b a) $ ($ c) y = \y -> y c b a. The pattern now should be clear: ($ a) . ($ b) ... ($ y) = \z -> z y x ... c b a. So ultimately, we get
map ((\z -> z 1 2 3 4) . f) [1..10]
=
map (\w -> (\z -> z 1 2 3 4) (f w)) [1..10]
=
map (\w -> f w 1 2 3 4) [1..10]
=
map (\x -> ($ 4) $ ($ 3) $ ($ 2) $ ($ 1) $ f x) [1..10]
In addition to what the other answers say, it might be a good idea to reorder the parameters of your function, especially x is usually the parameter that you vary over like that:
f y w z a x = x - y - w - z - a
If you make it so that the x parameter comes last, you can just write
map (f 1 2 3 4) [1..10]
This won't work in all circumstances of course, but it is good to see what parameters are more likely to vary over a series of calls and put them towards the end of the argument list and parameters that tend to stay the same towards the start. When you do this, currying and partial application will usually help you out more than they would otherwise.
Assuming you don't mind variables you simply define a new function that takes x and calls f. If you don't have a function definition there (you can generally use let or where) you can use a lambda instead.
f' x = f x 1 2 3 4
Or with a lambda
\x -> f x 1 2 3 4
Currying won't do you any good here, because the argument you want to vary (enumerate) isn't the last one. Instead, try something like this.
map (\x -> f x 1 2 3 4) [1..10]
The general solution in this situation is a lambda:
\x -> f x 1 2 3 4
however, if you're seeing yourself doing this very often, with the same argument, it would make sense to move that argument to be the last argument instead:
\x -> f 1 2 3 4 x
in which case currying applies perfectly well and you can just replace the above expression with
f 1 2 3 4
so in turn you could write:
map (f 1 2 3 4) [1..10]

Haskell apply single value to a list of functions

For an assignment I am working on a list of functions [Int -> Int] (eg. [(+3), (*4), (+1)] ) and I would like to apply a single Int to each of them, in turn creating a list of results [Int]
I already searched a lot, but I am unable to find a way to do such an operation. Using map does not work as I would expect. The related error is this:
ERROR - Cannot infer instance
*** Instance : Num ((Label -> Label) -> a)
As requested the code:
data Tree = Node (Label -> Label) Label [Tree]
type Label = Int
testTree = Node (+1) 3 [ Node (+1) 5 [], Node (+1) 4 [Node (+1) 1 [], Node (+2) 7 []]]
listify :: Tree -> [(Label -> Label)]
listify t = [(getNodeFunction t)] ++ concat(map (listify) (getSubTrees t))
*Main> map (\f -> f 7) (listify testTree)
this actually works. Had a piece of faulty code in the file still, sorry for the fuss.
You can use the $ operator, which stands for function application.
> map ($ 3) [(+3), (*4), (+1)]
[6,12,4]
This basically expands to [(+3) $ 3, (*4) $ 3, (+1) $ 3], which is just function application.
Basically this is an applicative job. You may do like
λ> [(+3), (*4), (+1)] <*> pure 3 -- or [3]
[6,12,4]
You also can use list comprehension for this. This line is enough for your example:
[ f 3 | f <- [(+3), (*4), (+1)] ]
This applies every function in the list on the right hand side to the value (3 in this case) on the left hand side.
For a more general version, this could be helpful:
applyFuns :: [(a->b)] -> a -> [b]
applyFuns fs x = [ f x | f <- fs ]
applyFuns [(+3), (*4), (+1)] 3
The Function applyFuns takes a list of functions from Type a->b as the first and a value of type b as the second. The result is a list of type b that contains the result of every function in the first list applied to the second argument.
If flist is the list of functions and x is the argument, you need map (\f -> f x) flist.
For example
Prelude> map (\f -> f 10) [(4 +), (3 *)]
[14,30]
I know this question is a bit old, but I feel like there oughta be an answer mentioning sequence:
> sequence [(+3), (*4), (+1)] 3
[6,12,4]
(These days, sequenceA is considered the modern replacement for sequence; it has the same behavior whenever both typecheck, but typechecks in slightly more situations. No difference here, though, so I like the slightly less-noisy name for this.)

How does currying work?

I'm very new to Haskell and FP in general. I've read many of the writings that describe what currying is, but I haven't found an explanation to how it actually works.
Here is a function: (+) :: a -> (a -> a)
If I do (+) 4 7, the function takes 4 and returns a function that takes 7 and returns 11. But what happens to 4 ? What does that first function do with 4? What does (a -> a) do with 7?
Things get more confusing when I think about a more complicated function:
max' :: Int -> (Int -> Int)
max' m n | m > n = m
| otherwise = n
what does (Int -> Int) compare its parameter to? It only takes one parameter, but it needs two to do m > n.
Understanding higher-order functions
Haskell, as a functional language, supports higher-order functions (HOFs). In mathematics HOFs are called functionals, but you don't need any mathematics to understand them. In usual imperative programming, like in Java, functions can accept values, like integers and strings, do something with them, and return back a value of some other type.
But what if functions themselves were no different from values, and you could accept a function as an argument or return it from another function? f a b c = a + b - c is a boring function, it sums a and b and then substracts c. But the function could be more interesting, if we could generalize it, what if we'd want sometimes to sum a and b, but sometimes multiply? Or divide by c instead of subtracting?
Remember, (+) is just a function of 2 numbers that returns a number, there's nothing special about it, so any function of 2 numbers that returns a number could be in place of it. Writing g a b c = a * b - c, h a b c = a + b / c and so on just doesn't cut it for us, we need a general solution, we are programmers after all! Here how it is done in Haskell:
let f g h a b c = a `g` b `h` c in f (*) (/) 2 3 4 -- returns 1.5
And you can return functions too. Below we create a function that accepts a function and an argument and returns another function, which accepts a parameter and returns a result.
let g f n = (\m -> m `f` n); f = g (+) 2 in f 10 -- returns 12
A (\m -> m `f` n) construct is an anonymous function of 1 argument m that applies f to that m and n. Basically, when we call g (+) 2 we create a function of one argument, that just adds 2 to whatever it receives. So let f = g (+) 2 in f 10 equals 12 and let f = g (*) 5 in f 5 equals 25.
(See also my explanation of HOFs using Scheme as an example.)
Understanding currying
Currying is a technique that transforms a function of several arguments to a function of 1 argument that returns a function of 1 argument that returns a function of 1 argument... until it returns a value. It's easier than it sounds, for example we have a function of 2 arguments, like (+).
Now imagine that you could give only 1 argument to it, and it would return a function? You could use this function later to add this 1st argument, now encased in this new function, to something else. E.g.:
f n = (\m -> n - m)
g = f 10
g 8 -- would return 2
g 4 -- would return 6
Guess what, Haskell curries all functions by default. Technically speaking, there are no functions of multiple arguments in Haskell, only functions of one argument, some of which may return new functions of one argument.
It's evident from the types. Write :t (++) in interpreter, where (++) is a function that concatenates 2 strings together, it will return (++) :: [a] -> [a] -> [a]. The type is not [a],[a] -> [a], but [a] -> [a] -> [a], meaning that (++) accepts one list and returns a function of type [a] -> [a]. This new function can accept yet another list, and it will finally return a new list of type [a].
That's why function application syntax in Haskell has no parentheses and commas, compare Haskell's f a b c with Python's or Java's f(a, b, c). It's not some weird aesthetic decision, in Haskell function application goes from left to right, so f a b c is actually (((f a) b) c), which makes complete sense, once you know that f is curried by default.
In types, however, the association is from right to left, so [a] -> [a] -> [a] is equivalent to [a] -> ([a] -> [a]). They are the same thing in Haskell, Haskell treats them exactly the same. Which makes sense, because when you apply only one argument, you get back a function of type [a] -> [a].
On the other hand, check the type of map: (a -> b) -> [a] -> [b], it receives a function as its first argument, and that's why it has parentheses.
To really hammer down the concept of currying, try to find the types of the following expressions in the interpreter:
(+)
(+) 2
(+) 2 3
map
map (\x -> head x)
map (\x -> head x) ["conscience", "do", "cost"]
map head
map head ["conscience", "do", "cost"]
Partial application and sections
Now that you understand HOFs and currying, Haskell gives you some syntax to make code shorter. When you call a function with 1 or multiple arguments to get back a function that still accepts arguments, it's called partial application.
You understand already that instead of creating anonymous functions you can just partially apply a function, so instead of writing (\x -> replicate 3 x) you can just write (replicate 3). But what if you want to have a divide (/) operator instead of replicate? For infix functions Haskell allows you to partially apply it using either of arguments.
This is called sections: (2/) is equivalent to (\x -> 2 / x) and (/2) is equivalent to (\x -> x / 2). With backticks you can take a section of any binary function: (2`elem`) is equivalent to (\xs -> 2 `elem` xs).
But remember, any function is curried by default in Haskell and therefore always accepts one argument, so sections can be actually used with any function: let (+^) be some weird function that sums 4 arguments, then let (+^) a b c d = a + b + c in (2+^) 3 4 5 returns 14.
Compositions
Other handy tools to write concise and flexible code are composition and application operator. Composition operator (.) chains functions together. Application operator ($) just applies function on the left side to the argument on the right side, so f $ x is equivalent to f x. However ($) has the lowest precedence of all operators, so we can use it to get rid of parentheses: f (g x y) is equivalent to f $ g x y.
It is also helpful when we need to apply multiple functions to the same argument: map ($2) [(2+), (10-), (20/)] would yield [4,8,10]. (f . g . h) (x + y + z), f (g (h (x + y + z))), f $ g $ h $ x + y + z and f . g . h $ x + y + z are equivalent, but (.) and ($) are different things, so read Haskell: difference between . (dot) and $ (dollar sign) and parts from Learn You a Haskell to understand the difference.
You can think of it like that the function stores the argument and returns a new function that just demands the other argument(s). The new function already knows the first argument, as it is stored together with the function. This is handled internally by the compiler. If you want to know how this works exactly, you may be interested in this page although it may be a bit complicated if you are new to Haskell.
If a function call is fully saturated (so all arguments are passed at the same time), most compilers use an ordinary calling scheme, like in C.
Does this help?
max' = \m -> \n -> if (m > n)
then m
else n
Written as lambdas. max' is a value of a lambda that itself returns a lambda given some m, which returns the value.
Hence max' 4 is
max' 4 = \n -> if (4 > n)
then 4
else n
Something that may help is to think about how you could implement curry as a higher order function if Haskell didn't have built in support for it. Here is a Haskell implementation that works for a function on two arguments.
curry :: (a -> b -> c) -> a -> (b -> c)
curry f a = \b -> f a b
Now you can pass curry a function on two arguments and the first argument and it will return a function on one argument (this is an example of a closure.)
In ghci:
Prelude> let curry f a = \b -> f a b
Prelude> let g = curry (+) 5
Prelude> g 10
15
Prelude> g 15
20
Prelude>
Fortunately we don't have to do this in Haskell (you do in Lisp if you want currying) because support is built into the language.
If you come from C-like languages, their syntax might help you to understand it. For example in PHP the add function could be implemented as such:
function add($a) {
return function($b) use($a) {
return $a + $b;
};
}
Haskell is based on Lambda calculus. Internally what happens is that everything gets converted into a function. So your compiler evaluates (+) as follows
(+) :: Num a => a -> a -> a
(+) x y = \x -> (\y -> x + y)
That is, (+) :: a -> a -> a is essentially the same as (+) :: a -> (a -> a). Hope this helps.

The composition of functions in a list of functions!

I need to define a function 'Compose' which takes a list 'L' which is a list of functions. When I specify a parameter that will suit all the functions in the list, the last function evaluates itself using this param. The result is then passed to the second last function and so on until we get to the first item (function) in the list and we get the final result.
E.g.
Compose ( ( fn N -> N + 1 ) ^ ( fn N -> 2 * N ) ^ # ) 3 .
give the answer 7.
I have to write this in a functional programming language called SAL (simple applicative language) devised by a lecturer in my college (hence funny syntax above ( ^ seperates list items and # marks end of list)).
If any solutions could be written in pseudo-code bearing in mind I can't use loops, variables etc. that would be much appreciated. Apparently the solution is a one-line answer. I imagine it involves recursion (99% of our task functions do!).
Also I don't understand Haskell (guess I'll have to learn!) so psuedo code or even plain English would be great. –
Thanks a bunch.
If the solution is a one-line answer, it could be something involving a fold:
compose :: [a -> a] -> a -> a
compose fs v = foldl (flip (.)) id fs $ v
http://haskell.org/haskellwiki/Compose
You can also implement it as a right fold, which works the way you want:
compose = foldr (.) id
*Main> let compose = foldr (.) id
*Main> compose [\x -> x+1, \x -> 2 * x, id] 3
7
in haskell:
compose :: a -> [a -> a] -> a
compose a (x:xs) = x (compose a xs)
compose a [] = a
Dan kind of gives it away, but here's a hint on how to do it yourself. You can recurse over numbers:
0! = 1
n! = (n-1)! * n
You can also recurse over structure. A list, for example, has a recursive structure, broken down into two cases: an empty list, and an item followed by the rest of the list. In no particular language:
List := Item x List
| Nil
Item marks the head of the list, x is the value stored in the head, and List is the tail. In this grammar, your list would be written:
Item ( fn N -> N + 1 ) Item ( fn N -> 2 * N ) Nil
The rule for a list in the syntax your professor invented could be written recursively as:
List := x ^ List
| #
A function on a list must recurse over this structure, which means it handles each of the two cases:
sum l:List = Nil -> 0
| Item x xs:List = x + sum xs
The recursion, specifically, is the term sum l:List = x + sum xs. Writing this function using the professor's syntax left as an exercise.
In your problem, your metafunction takes a list of functions and must return a function. Consider each case, the empty list and an item (the head) followed by a list (the tail). In the latter case, you can recursively use your function to get a function from the tail, then combine that somehow with the head to return a function. That's the gist, at any rate.
The same using monoids, point-free
import Data.Monoid
compose :: [a -> a] -> a -> a
compose = appEndo . mconcat . map Endo
Or somewhat more generally:
import Data.Monoid
compose :: (Functor t, Foldable t) => t (a -> a) -> a -> a
compose = appEndo . foldl1 (<>) . fmap Endo
Here's what I used:
compose :: [a -> a] -> a -> a
compose list startingvalue = foldl (\x f -> f x) startingvalue list

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