CODEWITHSUNDEEP
algorithmhaskellfunctional-programming
lambdacalculator
lambdacalculator

Reputation: 363

Efficient functional algorithm for computing closure under an operator

I'm interested in efficient functional algorithms (preferably in Haskell, and even more preferably already implemented as part of a library!) for computing the closure of a container under a unary operator.

A basic and inefficient example of what I have in mind, for lists, is:

closure :: Ord a => (a -> a) -> [a] -> [a]
closure f xs = first_dup (iterate (\xs -> nub $ sort $ xs ++ map f xs) xs) where
    first_dup (xs:ys:rest) = if xs == ys then xs else first_dup (ys:rest)

A more efficient implementation keeps tracks of the new elements generated at each stage (the "fringe") and doesn't apply the function to elements to which it has already been applied:

closure' :: Ord a => (a -> a) -> [a] -> [a]
closure' f xs = stable (iterate close (xs, [])) where
    -- return list when it stabilizes, i.e., when fringe is empty
    stable ((fringe,xs):iterates) = if null fringe then xs else stable iterates

    -- one iteration of closure on (fringe, rest);  key invariants:
    -- (1) fringe and rest are disjoint; (2) (map f rest) subset (fringe ++ rest)
    close (fringe, xs) = (fringe', xs') where
        xs' = sort (fringe ++ xs)
        fringe' = filter (`notElem` xs') (map f fringe)

As an example, if xs is a nonempty sublist of [0..19], then closure' (\x->(x+3)`mod`20) xs is [0..19], and the iteration stabilizes in 20 steps for [0], 13 steps for [0,1], and 4 steps for [0,4,8,12,16].

Even more efficiency could be gotten using a tree-based ordered-set implementation. Has this been done already? What about the related but harder question of closure under binary (or higher-arity) operators?

Upvotes: 9

Views: 419

Answers (1)

J. Abrahamson
J. Abrahamson

Reputation: 74344

How about something like this which uses the Hash Array Mapped Trie data structures in unordered-containers. For unordered-containers member and insert are O(min(n,W)) where W is the length of the hash.

module Closed where

import Data.HashSet (HashSet)
import Data.Hashable
import qualified Data.HashSet as Set

data Closed a = Closed { seen :: HashSet a, iter :: a -> a } 

insert :: (Hashable a, Eq a) => a -> Closed a -> Closed a
insert a c@(Closed set iter)
  | Set.member a set = c
  | otherwise        = insert (iter a) $ Closed (Set.insert a set) iter

empty :: (a -> a) -> Closed a
empty = Closed Set.empty

close :: (Hashable a, Eq a) => (a -> a) -> [a] -> Closed a
close iter = foldr insert (empty iter)

Here's a variation on the above that generates the solution set more lazily, in a breadth-first manner.

data Closed' a = Unchanging | Closed' (a -> a) (HashSet a) (Closed' a)

close' :: (Hashable a, Eq a) => (a -> a) -> [a] -> Closed' a
close' iter = build Set.empty where
  inserter :: (Hashable a, Eq a) => a -> (HashSet a, [a]) -> (HashSet a, [a])
  inserter a (set, fresh) | Set.member a set = (set, fresh)
                          | otherwise        = (Set.insert a set, a:fresh)
  build curr [] = Unchanging
  build curr as =
    Closed' iter curr $ step (foldr inserter (curr, []) as)
  step (set, added) = build set (map iter added)

-- Only computes enough iterations of the closure to 
-- determine whether a particular element has been generated yet
-- 
-- Returns both a boolean and a new 'Closed'' value which will 
-- will be more precisely defined and thus be faster to query
member :: (Hashable a, Eq a) => a -> Closed' a -> (Bool, Closed' a)
member _ Unchanging = False
member a c@(Closed' _ set next) | Set.member a set = (True, c)
                                | otherwise        = member a next

improve :: Closed' a -> Maybe ([a], Closed' a)
improve Unchanging = Nothing
improve (Closed' _ set next) = Just (Set.toList set, next)

seen' :: Closed' a -> HashSet a
seen' Unchanging = Set.empty
seen' (Closed' _ set Unchanging) = set
seen' (Closed' _ set next)       = seen' next

And to check

>>> member 6 $ close (+1) [0]
...

>>> fst . member 6 $ close' (+1) [0]
True

Upvotes: 7

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