What does the x: mean in this Code
Implementation of inits using foldr
inits :: [a] -> [[a]]
inits = foldr ( \ x y -> [] : (map (x:) y) ) [[]]
This is an effect of the infix operator sectioning [Haskell-wiki]:
(2^) (left section) is equivalent to (^) 2, or more verbosely \x -> 2 ^ x
So (x:) is short for (:) x, or \y -> x : y. The "cons" (:) :: a -> [a] -> [a] is a function that takes an element (type a) and a list (type [a]) and constructs a list with the element followed by the elements in the list.
(x:) :: [a] -> [a] is thus a function that takes a list and prepends that list with x.
We can make the fold function "point free" with:
foldr (((:) [] .) . map . (:)) [[]]
It's a function of a single argument that conses x to some list:
(x:) [] => [x]
(x:) [1, 2] => [x, 1, 2]
Here "conses" means "prepends a value to some list". cons is the "canonical" name of a function that does this. So, the : function is the cons function.
Related
I have a lambda function ((:) . ((:) x)) that I am passing to foldr like so: foldr ((:) . ((:) x)) [] xs where xs is a 2d list. I would like to refactor to make it clearer (so I can better understand it). I imagine it would be done like so:
foldr (\ element acc -> (element:acc) . (x:acc)) [] xs
But this gives me the error:
ex.hs:20:84: error:
• Couldn't match expected type ‘a0 -> b0’ with actual type ‘[[a]]’
• Possible cause: ‘(:)’ is applied to too many arguments
In the second argument of ‘(.)’, namely ‘(x : acc)’
In the expression: (element : acc) . (x : acc)
In the first argument of ‘foldr’, namely
‘(\ element acc -> (element : acc) . (x : acc))’
• Relevant bindings include
acc :: [[a]] (bound at ex.hs:20:60)
element :: [a] (bound at ex.hs:20:52)
xs :: [[a]] (bound at ex.hs:20:30)
x :: [a] (bound at ex.hs:20:28)
prefixes :: [a] -> [[a]] (bound at ex.hs:20:1)
|
20 | prefixes = foldr (\x xs -> [x] : (foldr (\ element acc -> (element:acc) . (x:acc)) [] xs)) []
|
Edit: My all relevant code surrounding this snippet is
prefixes :: Num a => [a] -> [[a]]
prefixes = foldr (\x acc -> [x] : (foldr ((:) . ((:) x)) [] acc)) []
and its invocation is:
prefixes [1, 2, 3]
How can I refactor the lambda ((:) . ((:) x)) to include both its arguments?
You can step-by-step convert it to a lambda.
(:) . ((:) x)
\y -> ((:) . (((:) x)) y -- conversion to lambda
\y -> (:) (((:) x) y) -- definition of (.)
\y -> (:) (x : y) -- rewrite second (:) using infix notation
\y z -> (:) (x : y) z -- add another parameter
\y z -> (x : y) : z -- rewrite first (:) using infix notation
I want to write a function that checks if two lists are "almost" equal. The first parameter d is used for precision - the difference between the elements must not exceed d.
For example, nearlyEqual 0.5 [2,5] [2.5, 5.1] equals True, but nearlyEqual 0.1 [2,5] [2.5, 5.1] equals False.
I wrote this but it is not working:
nearlyEqual :: Int -> [Int] -> [Int] -> Bool
nearlyEqual d xs ys = foldr(&&) True $ zipWith (\x y -> abs(x-y)<=d)
What am I missing? Any help would be greatly appreciated!
Not sure if it's a typo, but you're not passing xs and ys to your function.
nearlyEqual d xs ys = foldr(&&) True $ zipWith (\x y -> abs(x-y)<=d)
should be
nearlyEqual d xs ys = foldr(&&) True $ zipWith (\x y -> abs(x-y)<=d) xs ys
at least for it to typecheck.
A clearer implementation would make use of all, which is of type Foldable t => (a -> Bool) -> t a -> Bool, and of the function composition operator (.):
nearlyEqual d xs ys = all ((<= d) . abs) $ zipWith (-) xs ys
where zipWith (-) xs ys is element-wise difference of the two lists, and all verifies that the predicate (<= d) . abs holds for all of the elements of that list; the predicate, given an argument, applies abs to it, and then (<= d) to the result.
I was given an assignment in my functional programming course that asks me to rewrite several functions, like map and filter to be tail recursive.
I'm not 100% sure how to go about this yet but I know that you can define functions by calling foldr and foldl. I know foldl is tail recursive, so if I can define say, filter with foldl, would it become tail recursive, too?
There are two ways to make a recursive function tail recursive:
Convert the function to accumulator passing style. This only works in some cases.
Convert the function to continuation passing style. This works in all cases.
Consider the definition of the map function:
map :: (a -> b) -> [a] -> [b]
map _ [] = []
map f (x:xs) = f x : map f xs
In accumulator passing style, we have an additional argument which accumulates the result:
mapA :: (a -> b) -> [a] -> [b] -> [b]
mapA _ [] = id
mapA f (x:xs) = mapA f xs . (f x :)
The original map function can be recovered as follows:
map :: (a -> b) -> [a] -> [b]
map f xs = reverse $ mapA f xs []
Note that we need to reverse the result. This is because mapA accumulates the result in reverse:
> mapA (+1) [1,2,3,4,5] []
> mapA (+1) [2,3,4,5] [2]
> mapA (+1) [3,4,5] [3,2]
> mapA (+1) [3,5] [4,3,2]
> mapA (+1) [5] [5,4,3,2]
> mapA (+1) [] [6,5,4,3,2]
> [6,5,4,3,2]
Now, consider continuation passing style:
mapK :: (a -> b) -> [a] -> ([b] -> r) -> r
mapK _ [] k = k []
mapK f (x:xs) k = mapK f xs (k . (f x :))
The original map function can be recovered as follows:
map :: (a -> b) -> [a] -> [b]
map f xs = mapK f xs id
Note that we do not need to reverse the result. This is because although mapK accumulates the continuations in reverse, yet when finally applied to the base case the continuations are unfolded to produce the result in the correct order:
> mapK (+1) [1,2,3,4,5] id
> mapK (+1) [2,3,4,5] (id . (2:))
> mapK (+1) [3,4,5] (id . (2:) . (3:))
> mapK (+1) [4,5] (id . (2:) . (3:) . (4:))
> mapK (+1) [5] (id . (2:) . (3:) . (4:) . (5:))
> mapK (+1) [] (id . (2:) . (3:) . (4:) . (5:) . (6:))
> (id . (2:) . (3:) . (4:) . (5:) . (6:)) []
> (id . (2:) . (3:) . (4:) . (5:)) [6]
> (id . (2:) . (3:) . (4:)) [5,6]
> (id . (2:) . (3:)) [4,5,6]
> (id . (2:)) [3,4,5,6]
> id [2,3,4,5,6]
> [2,3,4,5,6]
Note, that in both cases we're doing twice the required amount of work:
First, we accumulate an intermediate result in reverse order.
Next, we produce the final result in the correct order.
Some functions can be written efficiently in the accumulator passing style (e.g. the sum function):
sumA :: Num a => [a] -> a -> a
sumA [] = id
sumA (x:xs) = sumA xs . (+ x)
The original sum function can be recovered as follows:
sum :: Num a => [a] -> a
sum xs = sumA xs 0
Note that we don't need to do any post processing on the result.
However, list functions written in tail recursive style always need to be reversed. Hence, we do not write list functions in tail recursive style. Instead, we depend upon laziness to process only as much of the list as required.
It should be noted that continuation passing style is just a special case of accumulator passing style. Since foldl is both tail recursive and uses an accumulator, you can write mapA and mapK using foldl as follows:
mapA :: (a -> b) -> [a] -> [b] -> [b]
mapA f xs acc = foldl (\xs x -> f x : xs) acc xs
mapK :: ([b] -> r) -> (a -> b) -> [a] -> r
mapK k f xs = foldl (\k x xs -> k (f x : xs)) k xs []
For, mapK if you take the k to be id then you get map:
map :: (a -> b) -> [a] -> [b]
map f xs = foldl (\k x xs -> k (f x : xs)) id xs []
Similarly, for filter:
filter :: (a -> Bool) -> [a] -> [a]
filter p xs = foldl (\k x xs -> k (if p x then x : xs else xs)) id xs []
There you have it, tail recursive map and filter functions. However, don't forget that they are actually doing twice the work. In addition, they won't work for infinite lists because the result will not be generated until the end of the list is reached (which will never happen for infinite lists).
I'm suspecting the professor/lecturer is expecting solutions where tail recursion is used "directly", i.e. lexically, within the source code of the function, not indirectly, or "dynamically", where tail recursion only happens at runtime within the scope of some subroutine call.
Otherwise, you might as well supply e.g. Prelude.foldl as the implementation for a custom foldl of yours, since it, possibly, uses tail recursion under the hood, and thus does yours:
import Prelude as P
foldl = P.foldl
but obviously something like that wouldn't be accepted.
So i have
pair:: [a] -> [b] -> [(a,b)]
pair[] _ = []
pair(x:xs) (y:ys) = (x, y) : prod xs ys
But the result are only like the following:
>> pair [1,2] [3,4]
>> [(1,3),(2,4)]
How can I make this so it pairs like:
[(1,3),(1,4),(2,3),(2,4)]
You can use the list applicative (or monad) instance:
λ> liftA2 (,) [1,2] [3,4]
[(1,3),(1,4),(2,3),(2,4)]
Or, equivalently,
f = do
x <- [1,2]
y <- [3,4]
return (x,y)
You can also use a list comprehension:
[ (x,y) | x <- [1,3], y <- [2,4] ]
Although there is already a much more elegant answer, i think it is worthwhile to show how this would be achieved in a simple straightforward way. If you want to get all pairs, you obviously need to visit every element of one list for an element in the other.
pair :: [a] -> [b] -> [(a, b)]
pair [] _ = []
pair (x:xs) ys = pair' x ys ++ pair xs ys where
pair' :: a -> [b] -> [(a, b)]
pair' _ [] = []
pair' x (y:ys) = (x,y) : pair' x ys
But of course using the pair = liftA2 (,) or [1,3] >>= \x -> [2,4] >>= \y -> (x,y) in its do notation or list comprehension notation is much better. Also ++ isn't what you normally want to do. So maybe you can build the lists as pair' would do, keep them in a list and then concat them.
concat $ map (\x -> map (\y -> (x,y)) ys) xs
I'm doing a bit of self study on functional languages (currently using Haskell). I came across a Haskell based assignment which requires defining map and filter in terms of foldr. For the life of me I'm not fully understanding how to go about this.
For example when I define a map function like:
map' :: (a -> b) -> [a] -> [b]
map' f [] = []
map' f (x:xs) = foldr (\x xs -> (f x):xs) [] xs
I don't know why the first element of the list is always ignored. Meaning that:
map' (*2) [1,2,3,4]
results in [4,6,8] instead of [2,4,6,8]
Similarly, my filter' function:
filter' :: (a -> Bool) -> [a] -> [a]
filter' p [] = []
filter' p (x:xs) = foldr (\x xs -> if p x then x:xs else xs ) [] xs
when run as:
filter' even [2,3,4,5,6]
results in [4,6] instead of [2,4,6]
Why would this be the case? And how SHOULD I have defined these functions to get the expected results? I'm assuming something is wrong with my lambda expressions...
I wish I could just comment, but alas, I don't have enough karma.
The other answers are all good ones, but I think the biggest confusion seems to be stemming from your use of x and xs.
If you rewrote it as
map' :: (a -> b) -> [a] -> [b]
map' f [] = []
map' f (x:xs) = foldr (\y ys -> (f y):ys) [] xs
you would clearly see that x is not even mentioned on the right-hand side, so there's no way that it could be in the solution.
Cheers
For your first question, foldr already has a case for the empty list, so you need not and should not provide a case for it in your own map.
map' f = foldr (\x xs -> f x : xs) []
The same holds for filter'
filter' p = foldr (\x xs -> if p x then x : xs else xs) []
Nothing is wrong with your lambda expressions, but there is something wrong with your definitions of filter' and map'. In the cons case (x:xs) you eat the head (x) away and then pass the tail to foldr. The foldr function can never see the first element you already ate. :)
Alse note that:
filter' p = foldr (\x xs -> if p x then x : xs else xs) []
is equivalent (η-equivalent) to:
filter' p xs = foldr (\x xs -> if p x then x : xs else xs) [] xs
I would define map using foldr and function composition as follows:
map :: (a -> b) -> [a] -> [b]
map f = foldr ((:).f) []
And for the case of filter:
filter :: (a -> Bool) -> [a] -> [a]
filter p = foldr (\x xs -> if p x then x:xs else xs) []
Note that it is not necessary to pass the list itself when defining functions over lists using foldr or foldl.
The problem with your solution is that you drop the head of the list and then apply the map over the list and
this is why the head of the list is missing when the result is shown.
In your definitions, you are doing pattern matching for x:xs, which means, when your argument is [1,2,3,4], x is bound to 1 and xs is bound to the rest of the list: [2,3,4].
What you should not do is simply throw away x: part. Then your foldr will be working on whole list.
So your definitions should look as follows:
map' :: (a -> b) -> [a] -> [b]
map' f [] = []
map' f xs = foldr (\x xs -> (f x):xs) [] xs
and
filter' :: (a -> Bool) -> [a] -> [a]
filter' p [] = []
filter' p xs = foldr (\x xs -> if p x then x:xs else xs ) [] xs
I am new to Haskell (in fact I've found this page asking the same question) but this is my understanding of lists and foldr so far:
lists are elements that are linked to the next element with the cons (:) operator. they terminate with the empty list []. (think of it as a binary operator just like addition (+) 1+2+3+4 = 10, 1:2:3:4:[] = [1,2,3,4]
foldr function takes a function that takes two parameters. this will replace the cons operator, which will define how each item is linked to the next.
it also takes the terminal value for the operation, which can be tought as the initial value that will be assigned to the empty list. for cons it is empty list []. if you link an empty list to any list the result is the list itself. so for a sumfunction it is 0. for a multiply function it is 1, etc.
and it takes the list itself
So my solution is as follows:
filter' p = foldr (\x n -> if p x then x : n else n) []
the lambda expression is our link function, which will be used instead of the cons (:) operator. Empty list is our default value for an empty list. If predicate is satisfied we link to the next item using (:) as normal, else we simply don't link at all.
map' f = foldr (\x n -> f x : n) []
here we link f x to the next item instead of just x, which would simply duplicate the list.
Also, note that you don't need to use pattern matching, since we already tell foldr what to do in case of an empty list.
I know this question is really old but I just wanted to answer it anyway. I hope it is not against the rules.
A different way to think about it - foldr exists because the following recursive pattern is used often:
-- Example 1: Sum up numbers
summa :: Num a => [a] -> a
summa [] = 0
summa (x:xs) = x + suma xs
Taking the product of numbers or even reversing a list looks structurally very similar to the previous recursive function:
-- Example 2: Reverse numbers
reverso :: [a] -> [a]
reverso [] = []
reverso (x:xs) = x `op` reverso xs
where
op = (\curr acc -> acc ++ [curr])
The structure in the above examples only differs in the initial value (0 for summa and [] for reverso) along with the operator between the first value and the recursive call (+ for summa and (\q qs -> qs ++ [q]) for reverso). So the function structure for the above examples can be generally seen as
-- Generic function structure
foo :: (a -> [a] -> [a]) -> [a] -> [a] -> [a]
foo op init_val [] = init_val
foo op init_val (x:xs) = x `op` foo op init_val xs
To see that this "generic" foo works, we could now rewrite reverso by using foo and passing it the operator, initial value, and the list itself:
-- Test: reverso using foo
foo (\curr acc -> acc ++ [curr]) [] [1,2,3,4]
Let's give foo a more generic type signature so that it works for other problems as well:
foo :: (a -> b -> b) -> b -> [a] -> b
Now, getting back to your question - we could write filter like so:
-- Example 3: filter
filtero :: (a -> Bool) -> [a] -> [a]
filtero p [] = []
filtero p (x:xs) = x `filterLogic` (filtero p xs)
where
filterLogic = (\curr acc -> if (p curr) then curr:acc else acc)
This again has a very similar structure to summa and reverso. Hence, we should be able to use foo to rewrite it. Let's say we want to filter the even numbers from the list [1,2,3,4]. Then again we pass foo the operator (in this case filterLogic), initial value, and the list itself. filterLogic in this example takes a p function, called a predicate, which we'll have to define for the call:
let p = even in foo (\curr acc -> if (p curr) then curr:acc else acc) [] [1,2,3,4]
foo in Haskell is called foldr. So, we've rewritten filter using foldr.
let p = even in foldr (\curr acc -> if (p curr) then curr:acc else acc) [] [1,2,3,4]
So, filter can be written with foldr as we've seen:
-- Solution 1: filter using foldr
filtero' :: (a -> Bool) -> [a] -> [a]
filtero' p xs = foldr (\curr acc -> if (p curr) then curr:acc else acc) [] xs
As for map, we could also write it as
-- Example 4: map
mapo :: (a -> b) -> [a] -> [b]
mapo f [] = []
mapo f (x:xs) = x `op` (mapo f xs)
where
op = (\curr acc -> (f curr) : acc)
which therefore can be rewritten using foldr. For example, to multiply every number in a list by two:
let f = (* 2) in foldr (\curr acc -> (f curr) : acc) [] [1,2,3,4]
So, map can be written with foldr as we've seen:
-- Solution 2: map using foldr
mapo' :: (a -> b) -> [a] -> [b]
mapo' f xs = foldr (\curr acc -> (f curr) : acc) [] xs
Your solution almost works .)
The problem is that you've got two differend bindings for x in both your functions (Inside the patternmatching and inside your lambda expression), therefore you loose track of the first Element.
map' :: (a -> b) -> [a] -> [b]
map' f [] = []
map' f (x:xs) = foldr (\x xs -> (f x):xs) [] (x:xs)
filter' :: (a -> Bool) -> [a] -> [a]
filter' p [] = []
filter' p (x:xs) = foldr (\x xs -> if p x then x:xs else xs ) [] (x:xs)
This should to the trick :). Also: you can write your functions pointfree style easily.
*Main> :{
*Main| map' :: (a -> b) -> [a] -> [b]
*Main| map' = \f -> \ys -> (foldr (\x -> \acc -> f x:acc) [] ys)
*Main| :}
*Main> map' (^2) [1..10]
[1,4,9,16,25,36,49,64,81,100]
*Main> :{
*Main| filter' :: (a -> Bool) -> [a] -> [a]
*Main| filter' = \p -> \ys -> (foldr (\x -> \acc -> if p x then x:acc else acc) [] ys)
*Main| :}
*Main> filter' (>10) [1..100]
In the above snippets acc refers to accumulator and x refers to the last element.
Everything is correct in your lambda expressions. The problem is you are missing the first element in the list. If you try,
map' f (x:xs) = foldr (\x xs -> f x:xs) [] (x:xs)
then you shouldn't miss the first element anymore. The same logic applies to filter.
filter' p (x:xs) = foldr(\ y xs -> if p y then y:xs else xs) [] (x:xs)