Cluster

May 9, 2014

Clustering is the process of collecting in groups all of the items from an input collection that share some common feature; for instance, the GROUP BY operator of SQL performs clustering. We will define cluster(proc, lt?, lst) as a function that takes an input list and returns a list of lists; proc computes a signature of each item in the input list, and each sub-list in the output list contains all those elements of the input list with identical signatures, with sub-lists in increasing order of signature according to lt?. The type of cluster is (α → β) × (β × β → boolean) × (list α) → (list (list α)).

Your task is to write the function cluster. When you are finished, you are welcome to read or run a suggested solution, or to post your own solution or discuss the exercise in the comments below.

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12 Responses to “Cluster”

  1. Jussi Piitulainen said

    Simple-minded grouping of consecutive items, the requested effect achieved by composing with sort:

    (include "sort-okeefe.scm")

    (define (group-by sign < items)
      (if (null? items)
          items
          (let group ((g (list (car items)))
                      (s (sign (car items)))
                      (items (cdr items)))
            (if (null? items)
                (list (reverse g))
                (let ((t (sign (car items))))
                  (if (or (< s t) (< t s))
                      (cons (reverse g)
                            (group (list (car items)) t (cdr items)))
                      (group (cons (car items) g) s (cdr items))))))))

    (define (cluster sign < items)
      (group-by sign < (sort items (lambda (i j) (< (sign i) (sign j))))))

    Test:

    (define test-data
      (list "oh" "one" "two" "three" "four" "five" "seven" "ate" "nine"))

    (write (cluster string-length < test-data)) (newline)

    Test result:

    (("oh") ("one" "two" "ate") ("four" "five" "nine") ("three" "seven"))

    (The predicate signature needs to have a pair of betas for input.)

  2. programmingpraxis said

    Added a beta. Thanks.

  3. matthew said

    Here’s a Haskell solution: tag the input list with the signature, sort, then run through the list gathering up the sublists. I tried to do something with foldl for this, but didn’t result in any nice simplifications.

    #!/usr/bin/runhaskell
    import Data.List
    
    h1 f (a,_)(b,_) = f a b
    cluster sig comp [] = []
    cluster sig comp s =
      let 
          ((a,n):s') = sortBy (flip (h1 comp)) (zip (map sig s) s)
          split [] _ s t = reverse s:t
          split ((a,n):s) a' s' t
                | a == a' = split s a' (n:s') t
                | otherwise = split s a [n] (reverse s':t)
      in
         split s' a [n] []
    
    s1 = [6,0,8,2,4,3,5,7,9,1];
    s2 = ["one","two","three","four","five","six"]
    
    main =
      print (cluster (`mod` 3) compare s1) >>
      print (cluster (`div` 3) compare s1) >>
      print (cluster (`mod` 3) compare []) >>
      print (cluster length compare s2)
    
  4. Globules said
    import Data.Function (on)
    import Data.List (groupBy, sortBy)
    import Data.Map (elems, fromListWith)
    import Data.Ord (comparing)
    
    --------------------------------------------------------------------------------
    
    cluster1 :: Eq β => (α -> β) -> (β -> β -> Bool) -> [α] -> [[α]]
    cluster1 proc' lt as =
      map (map snd) . groupBy ((==) `on` fst) . sortBy cmp $ zip bs as
      where bs = map proc' as
            cmp = ordFromLt lt `on` fst
    
    -- This is a bit dodgy...
    ordFromLt :: (a -> a -> Bool) -> a -> a -> Ordering
    ordFromLt lt a b = if lt a b then LT else GT
    
    --------------------------------------------------------------------------------
    
    -- Since the requirements imply that there exists an Ord instance for β (not
    -- just an Eq instance), we might as well take advantage of this.  This means
    -- the "lt" argument is no longer needed.
    
    cluster2 :: Ord β => (α -> β) -> [α] -> [[α]]
    cluster2 proc' as =
      map (map snd) . groupBy ((==) `on` fst) . sortBy (comparing fst) $ zip bs as
      where bs = map proc' as
    
    -------------------------------------------------------------------------------
    
    -- But, now that we have an Ord instance we can use a map instead.
    
    cluster3 :: Ord β => (α -> β) -> [α] -> [[α]]
    cluster3 proc' = elems . fromListWith (++) . map (\a -> (proc' a, [a]))
    
    -------------------------------------------------------------------------------
    
    main :: IO ()
    main = do
      let s1 = [6,0,8,2,4,3,5,7,9,1] :: [Int]
          s2 = ["one","two","three","four","five","six"] :: [String]
    
      print $ cluster1 (`mod` 3) (<) s1
      print $ cluster1 (`div` 3) (<) s1
      print $ cluster1 (`mod` 3) (<) ([] :: [Int])
      print $ cluster1 length (<) s2
    
      print $ cluster2 (`mod` 3) s1
      print $ cluster2 (`div` 3) s1
      print $ cluster2 (`mod` 3) ([] :: [Int])
      print $ cluster2 length s2
    
      print $ cluster3 (`mod` 3) s1
      print $ cluster3 (`div` 3) s1
      print $ cluster3 (`mod` 3) ([] :: [Int])
      print $ cluster3 length s2
    
  5. matthew said

    Nice solution. I’m still finding my way around the standard library so lots of new stuff there for me. I was wondering about converting from the Bool function from an Ord function, but I thought being Haskell, we’d probably get one of them anyway.

    Had another think about fold and came up with the following (I’m not sure what the pros and cons of using foldr or foldl are – here foldr works nicely to keep everything in the right order):

    import Data.List
    import Data.Function
    import Control.Arrow
    
    f (a,n) [] = [(a,[n])]
    f (a,n) ((a',s):t) 
      | a == a' = (a',n:s):t
      | otherwise = (a,[n]):(a',s):t
    
    cluster sig comp = 
      map (sig &&& id) >>> sortBy (comp `on` fst) >>> foldr f [] >>> map snd
    
    s1 = [6,0,8,2,4,3,5,7,9,1];
    s2 = ["one","two","three","four","five","six"]
    
    main =
      print (cluster (`mod` 3) compare s1) >>
      print (cluster (`div` 3) compare s1) >>
      print (cluster (`mod` 3) compare []) >>
      print (cluster length compare s2)
    
  6. chmllr said

    Clojure:

    (defn cluster [proc lt? lst]
      (vals (group-by proc (sort-by proc lt? lst))))
    
  7. matthew said

    @chmllr:

    NIce, but will group-by preserve the correct ordering by signatures? If not, then you can move the sort to the end.

  8. @matthew, I don’t know why exactly, but I observed in Clojure, that the sets are always iterated as LIFO queues (maybe the maps are based on Java’s LinkedHashMaps). Now, since sort-by is implemented with the reduce function starting with an empty set, I always get the correct order. However, you’re right: this is a weak assumption to rely on.

    I thought again and I came up with even a shorter solution, without any implicit assumptions:

    (defn cluster [proc lt? lst]
    (partition-by proc (sort-by proc lt? lst)))

  9. matthew said

    @christian: Very nice (of course, we call proc twice for each element, but that’s just one of those tradeoffs).

    Here’s something similar in Haskell, p is partition-by:

    g sig k u (a:s) =
      if k == k' then g sig k (a:u) s
      else reverse u:g sig k' [a] s
      where k' = sig a
    g sig k u [] = [reverse u]
    
    p sig [] = []
    p sig (a:s) = g sig (sig a) [a] s
    
    cluster sig comp = sortBy (comp `on` sig) >>> (p sig)
    
  10. chmllr said

    @matthew: just for curiosity: I didn’t touch Haskell for years, but would this pattern matching based idea work, to implement partition-by? (I think it’s the same what you do above, but without if-the-else and with TCO)

    partition-by sig lst = h [] [] (map (\ x -> [(sig x) x]) lst)
    where
    h tmp acc [] = map reverse acc
    h tmp acc [[s:x]:[s:y]:xs] = h [x:tmp] acc [[s:y]:xs]
    h tmp acc [[s:x]:[q:y]:xs] = h [] [[x:tmp]:acc] [[q:y]:xs]

  11. chmllr said

    PS: oops, one case was missing :-)

    partition-by sig lst = h [] [] (map (\ x -> [(sig x) x]) lst)
        where
            h tmp acc [] = map reverse acc
            h tmp acc [[s:x]:[s:y]:xs] = h [x:tmp] acc [[s:y]:xs]
            h tmp acc [[s:x]:[q:y]:xs] = h [] [[x:tmp]:acc] [[q:y]:xs]
            h tmp acc [[s:x]:[]] = h [] [[x:tmp]:acc] []
    
  12. matthew said

    @chmllr
    That would be nice, but Haskell doesn’t seem to like having the same variable twice in a pattern match:

    cluster4.hs:23:21:
        Conflicting definitions for `s'
        Bound at: cluster4.hs:23:21
                  cluster4.hs:23:27
        In an equation for `h'
    

    We could use a guard expression here (I would have done this but I wanted to bind the result of sig first, maybe there’s some other way of doing this).

    Writing list generating functions as “f a b c = x : f a’ b’ c'” without TCO I suppose seems more natural in Haskell since it will work with lazy lists (which partition-by could do).

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