Haskell: Chaining functions to find the middle value in a collection
I’ve been playing around with writing merge sort in Haskell and eventually ended up with the following function:
msort :: [Int] -> [Int]
msort unsorted =
let n = floor (fromIntegral(length unsorted) / 2)
in
if n == 0 then unsorted
else
let (left, right) = splitAt n unsorted
in merge (msort left) (msort right)
where
merge [] right = right
merge left [] = left
merge left@(x:xs) right@(y:ys) = if x < y then x : merge xs right else y : merge left ys
The 3rd line was annoying me as it has way too many brackets on it and I was fairly sure that it should be possible to just combine the functions like I learnt to do in F# a few years ago.
It’s pretty easy to do that for the first two functions 'length' and 'fromIntegral' which we can do like this:
middle = fromIntegral . length
The third line now reads like this:
let n = floor ((middle unsorted) / 2)
It’s a slight improvement but still not that great.
The problem with working out how to chain the division bit is that our value needs to be passed as the first argument to '/' so we can’t do the following…
middle = ((/) 2) . fromIntegral . length
…since that divides 2 by the length of our collection rather than the other way around!
> middle [1,2,3,4,5,6]
0.3333333333333333
Instead we want to create an anonymous function around the '/' function and then apply floor:
middle :: [Int] -> Int
middle = floor . (\y -> y / 2) . fromIntegral . length
And merge sort now looks like this:
msort :: [Int] -> [Int]
msort unsorted =
let n = middle unsorted
in
if n == 0 then unsorted
else
let (left, right) = splitAt n unsorted
in merge (msort left) (msort right)
where
merge [] right = right
merge left [] = left
merge left@(x:xs) right@(y:ys) = if x < y then x : merge xs right else y : merge left ys
Which I think is pretty neat!
About the author
I'm currently working on short form content at ClickHouse. I publish short 5 minute videos showing how to solve data problems on YouTube @LearnDataWithMark. I previously worked on graph analytics at Neo4j, where I also co-authored the O'Reilly Graph Algorithms Book with Amy Hodler.