----------------------------------------------------------------------------- -- | -- Module : Data.Set -- Copyright : (c) Daan Leijen 2002 -- License : BSD-style -- Maintainer : libraries@haskell.org -- Stability : provisional -- Portability : portable -- -- An efficient implementation of sets. -- -- Since many function names (but not the type name) clash with -- "Prelude" names, this module is usually imported @qualified@, e.g. -- -- > import Data.Set (Set) -- > import qualified Data.Set as Set -- -- The implementation of 'Set' is based on /size balanced/ binary trees (or -- trees of /bounded balance/) as described by: -- -- * Stephen Adams, \"/Efficient sets: a balancing act/\", -- Journal of Functional Programming 3(4):553-562, October 1993, -- <http://www.swiss.ai.mit.edu/~adams/BB/>. -- -- * J. Nievergelt and E.M. Reingold, -- \"/Binary search trees of bounded balance/\", -- SIAM journal of computing 2(1), March 1973. -- -- Note that the implementation is /left-biased/ -- the elements of a -- first argument are always preferred to the second, for example in -- 'union' or 'insert'. Of course, left-biasing can only be observed -- when equality is an equivalence relation instead of structural -- equality. ----------------------------------------------------------------------------- module Data.Set ( -- * Set type Set -- instance Eq,Ord,Show,Read,Data,Typeable -- * Operators , (\\) -- * Query , null , size , member , notMember , isSubsetOf , isProperSubsetOf -- * Construction , empty , singleton , insert , delete -- * Combine , union, unions , difference , intersection -- * Filter , filter , partition , split , splitMember -- * Map , map , mapMonotonic -- * Fold , fold -- * Min\/Max , findMin , findMax , deleteMin , deleteMax , deleteFindMin , deleteFindMax , maxView , minView -- * Conversion -- ** List , elems , toList , fromList -- ** Ordered list , toAscList , fromAscList , fromDistinctAscList -- * Debugging , showTree , showTreeWith , valid ) where import Prelude hiding (filter,foldr,null,map) import qualified Data.List as List import Data.Monoid (Monoid(..)) import Data.Typeable import Data.Foldable (Foldable(foldMap)) {- -- just for testing import QuickCheck import List (nub,sort) import qualified List -} #if __GLASGOW_HASKELL__ import Text.Read import Data.Generics.Basics import Data.Generics.Instances #endif {-------------------------------------------------------------------- Operators --------------------------------------------------------------------} infixl 9 \\ -- -- | /O(n+m)/. See 'difference'. (\\) :: Ord a => Set a -> Set a -> Set a m1 \\ m2 = difference m1 m2 {-------------------------------------------------------------------- Sets are size balanced trees --------------------------------------------------------------------} -- | A set of values @a@. data Set a = Tip | Bin {-# UNPACK #-} !Size a !(Set a) !(Set a) type Size = Int instance Ord a => Monoid (Set a) where mempty = empty mappend = union mconcat = unions instance Foldable Set where foldMap f Tip = mempty foldMap f (Bin _s k l r) = foldMap f l `mappend` f k `mappend` foldMap f r #if __GLASGOW_HASKELL__ {-------------------------------------------------------------------- A Data instance --------------------------------------------------------------------} -- This instance preserves data abstraction at the cost of inefficiency. -- We omit reflection services for the sake of data abstraction. instance (Data a, Ord a) => Data (Set a) where gfoldl f z set = z fromList `f` (toList set) toConstr _ = error "toConstr" gunfold _ _ = error "gunfold" dataTypeOf _ = mkNorepType "Data.Set.Set" dataCast1 f = gcast1 f #endif {-------------------------------------------------------------------- Query --------------------------------------------------------------------} -- | /O(1)/. Is this the empty set? null :: Set a -> Bool null t = case t of Tip -> True Bin sz x l r -> False -- | /O(1)/. The number of elements in the set. size :: Set a -> Int size t = case t of Tip -> 0 Bin sz x l r -> sz -- | /O(log n)/. Is the element in the set? member :: Ord a => a -> Set a -> Bool member x t = case t of Tip -> False Bin sz y l r -> case compare x y of LT -> member x l GT -> member x r EQ -> True -- | /O(log n)/. Is the element not in the set? notMember :: Ord a => a -> Set a -> Bool notMember x t = not $ member x t {-------------------------------------------------------------------- Construction --------------------------------------------------------------------} -- | /O(1)/. The empty set. empty :: Set a empty = Tip -- | /O(1)/. Create a singleton set. singleton :: a -> Set a singleton x = Bin 1 x Tip Tip {-------------------------------------------------------------------- Insertion, Deletion --------------------------------------------------------------------} -- | /O(log n)/. Insert an element in a set. -- If the set already contains an element equal to the given value, -- it is replaced with the new value. insert :: Ord a => a -> Set a -> Set a insert x t = case t of Tip -> singleton x Bin sz y l r -> case compare x y of LT -> balance y (insert x l) r GT -> balance y l (insert x r) EQ -> Bin sz x l r -- | /O(log n)/. Delete an element from a set. delete :: Ord a => a -> Set a -> Set a delete x t = case t of Tip -> Tip Bin sz y l r -> case compare x y of LT -> balance y (delete x l) r GT -> balance y l (delete x r) EQ -> glue l r {-------------------------------------------------------------------- Subset --------------------------------------------------------------------} -- | /O(n+m)/. Is this a proper subset? (ie. a subset but not equal). isProperSubsetOf :: Ord a => Set a -> Set a -> Bool isProperSubsetOf s1 s2 = (size s1 < size s2) && (isSubsetOf s1 s2) -- | /O(n+m)/. Is this a subset? -- @(s1 `isSubsetOf` s2)@ tells whether @s1@ is a subset of @s2@. isSubsetOf :: Ord a => Set a -> Set a -> Bool isSubsetOf t1 t2 = (size t1 <= size t2) && (isSubsetOfX t1 t2) isSubsetOfX Tip t = True isSubsetOfX t Tip = False isSubsetOfX (Bin _ x l r) t = found && isSubsetOfX l lt && isSubsetOfX r gt where (lt,found,gt) = splitMember x t {-------------------------------------------------------------------- Minimal, Maximal --------------------------------------------------------------------} -- | /O(log n)/. The minimal element of a set. findMin :: Set a -> a findMin (Bin _ x Tip r) = x findMin (Bin _ x l r) = findMin l findMin Tip = error "Set.findMin: empty set has no minimal element" -- | /O(log n)/. The maximal element of a set. findMax :: Set a -> a findMax (Bin _ x l Tip) = x findMax (Bin _ x l r) = findMax r findMax Tip = error "Set.findMax: empty set has no maximal element" -- | /O(log n)/. Delete the minimal element. deleteMin :: Set a -> Set a deleteMin (Bin _ x Tip r) = r deleteMin (Bin _ x l r) = balance x (deleteMin l) r deleteMin Tip = Tip -- | /O(log n)/. Delete the maximal element. deleteMax :: Set a -> Set a deleteMax (Bin _ x l Tip) = l deleteMax (Bin _ x l r) = balance x l (deleteMax r) deleteMax Tip = Tip {-------------------------------------------------------------------- Union. --------------------------------------------------------------------} -- | The union of a list of sets: (@'unions' == 'foldl' 'union' 'empty'@). unions :: Ord a => [Set a] -> Set a unions ts = foldlStrict union empty ts -- | /O(n+m)/. The union of two sets, preferring the first set when -- equal elements are encountered. -- The implementation uses the efficient /hedge-union/ algorithm. -- Hedge-union is more efficient on (bigset `union` smallset). union :: Ord a => Set a -> Set a -> Set a union Tip t2 = t2 union t1 Tip = t1 union t1 t2 = hedgeUnion (const LT) (const GT) t1 t2 hedgeUnion cmplo cmphi t1 Tip = t1 hedgeUnion cmplo cmphi Tip (Bin _ x l r) = join x (filterGt cmplo l) (filterLt cmphi r) hedgeUnion cmplo cmphi (Bin _ x l r) t2 = join x (hedgeUnion cmplo cmpx l (trim cmplo cmpx t2)) (hedgeUnion cmpx cmphi r (trim cmpx cmphi t2)) where cmpx y = compare x y {-------------------------------------------------------------------- Difference --------------------------------------------------------------------} -- | /O(n+m)/. Difference of two sets. -- The implementation uses an efficient /hedge/ algorithm comparable with /hedge-union/. difference :: Ord a => Set a -> Set a -> Set a difference Tip t2 = Tip difference t1 Tip = t1 difference t1 t2 = hedgeDiff (const LT) (const GT) t1 t2 hedgeDiff cmplo cmphi Tip t = Tip hedgeDiff cmplo cmphi (Bin _ x l r) Tip = join x (filterGt cmplo l) (filterLt cmphi r) hedgeDiff cmplo cmphi t (Bin _ x l r) = merge (hedgeDiff cmplo cmpx (trim cmplo cmpx t) l) (hedgeDiff cmpx cmphi (trim cmpx cmphi t) r) where cmpx y = compare x y {-------------------------------------------------------------------- Intersection --------------------------------------------------------------------} -- | /O(n+m)/. The intersection of two sets. -- Elements of the result come from the first set, so for example -- -- > import qualified Data.Set as S -- > data AB = A | B deriving Show -- > instance Ord AB where compare _ _ = EQ -- > instance Eq AB where _ == _ = True -- > main = print (S.singleton A `S.intersection` S.singleton B, -- > S.singleton B `S.intersection` S.singleton A) -- -- prints @(fromList [A],fromList [B])@. intersection :: Ord a => Set a -> Set a -> Set a intersection Tip t = Tip intersection t Tip = Tip intersection t1@(Bin s1 x1 l1 r1) t2@(Bin s2 x2 l2 r2) = if s1 >= s2 then let (lt,found,gt) = splitLookup x2 t1 tl = intersection lt l2 tr = intersection gt r2 in case found of Just x -> join x tl tr Nothing -> merge tl tr else let (lt,found,gt) = splitMember x1 t2 tl = intersection l1 lt tr = intersection r1 gt in if found then join x1 tl tr else merge tl tr {-------------------------------------------------------------------- Filter and partition --------------------------------------------------------------------} -- | /O(n)/. Filter all elements that satisfy the predicate. filter :: Ord a => (a -> Bool) -> Set a -> Set a filter p Tip = Tip filter p (Bin _ x l r) | p x = join x (filter p l) (filter p r) | otherwise = merge (filter p l) (filter p r) -- | /O(n)/. Partition the set into two sets, one with all elements that satisfy -- the predicate and one with all elements that don't satisfy the predicate. -- See also 'split'. partition :: Ord a => (a -> Bool) -> Set a -> (Set a,Set a) partition p Tip = (Tip,Tip) partition p (Bin _ x l r) | p x = (join x l1 r1,merge l2 r2) | otherwise = (merge l1 r1,join x l2 r2) where (l1,l2) = partition p l (r1,r2) = partition p r {---------------------------------------------------------------------- Map ----------------------------------------------------------------------} -- | /O(n*log n)/. -- @'map' f s@ is the set obtained by applying @f@ to each element of @s@. -- -- It's worth noting that the size of the result may be smaller if, -- for some @(x,y)@, @x \/= y && f x == f y@ map :: (Ord a, Ord b) => (a->b) -> Set a -> Set b map f = fromList . List.map f . toList -- | /O(n)/. The -- -- @'mapMonotonic' f s == 'map' f s@, but works only when @f@ is monotonic. -- /The precondition is not checked./ -- Semi-formally, we have: -- -- > and [x < y ==> f x < f y | x <- ls, y <- ls] -- > ==> mapMonotonic f s == map f s -- > where ls = toList s mapMonotonic :: (a->b) -> Set a -> Set b mapMonotonic f Tip = Tip mapMonotonic f (Bin sz x l r) = Bin sz (f x) (mapMonotonic f l) (mapMonotonic f r) {-------------------------------------------------------------------- Fold --------------------------------------------------------------------} -- | /O(n)/. Fold over the elements of a set in an unspecified order. fold :: (a -> b -> b) -> b -> Set a -> b fold f z s = foldr f z s -- | /O(n)/. Post-order fold. foldr :: (a -> b -> b) -> b -> Set a -> b foldr f z Tip = z foldr f z (Bin _ x l r) = foldr f (f x (foldr f z r)) l {-------------------------------------------------------------------- List variations --------------------------------------------------------------------} -- | /O(n)/. The elements of a set. elems :: Set a -> [a] elems s = toList s {-------------------------------------------------------------------- Lists --------------------------------------------------------------------} -- | /O(n)/. Convert the set to a list of elements. toList :: Set a -> [a] toList s = toAscList s -- | /O(n)/. Convert the set to an ascending list of elements. toAscList :: Set a -> [a] toAscList t = foldr (:) [] t -- | /O(n*log n)/. Create a set from a list of elements. fromList :: Ord a => [a] -> Set a fromList xs = foldlStrict ins empty xs where ins t x = insert x t {-------------------------------------------------------------------- Building trees from ascending/descending lists can be done in linear time. Note that if [xs] is ascending that: fromAscList xs == fromList xs --------------------------------------------------------------------} -- | /O(n)/. Build a set from an ascending list in linear time. -- /The precondition (input list is ascending) is not checked./ fromAscList :: Eq a => [a] -> Set a fromAscList xs = fromDistinctAscList (combineEq xs) where -- [combineEq xs] combines equal elements with [const] in an ordered list [xs] combineEq xs = case xs of [] -> [] [x] -> [x] (x:xx) -> combineEq' x xx combineEq' z [] = [z] combineEq' z (x:xs) | z==x = combineEq' z xs | otherwise = z:combineEq' x xs -- | /O(n)/. Build a set from an ascending list of distinct elements in linear time. -- /The precondition (input list is strictly ascending) is not checked./ fromDistinctAscList :: [a] -> Set a fromDistinctAscList xs = build const (length xs) xs where -- 1) use continutations so that we use heap space instead of stack space. -- 2) special case for n==5 to build bushier trees. build c 0 xs = c Tip xs build c 5 xs = case xs of (x1:x2:x3:x4:x5:xx) -> c (bin x4 (bin x2 (singleton x1) (singleton x3)) (singleton x5)) xx build c n xs = seq nr $ build (buildR nr c) nl xs where nl = n `div` 2 nr = n - nl - 1 buildR n c l (x:ys) = build (buildB l x c) n ys buildB l x c r zs = c (bin x l r) zs {-------------------------------------------------------------------- Eq converts the set to a list. In a lazy setting, this actually seems one of the faster methods to compare two trees and it is certainly the simplest :-) --------------------------------------------------------------------} instance Eq a => Eq (Set a) where t1 == t2 = (size t1 == size t2) && (toAscList t1 == toAscList t2) {-------------------------------------------------------------------- Ord --------------------------------------------------------------------} instance Ord a => Ord (Set a) where compare s1 s2 = compare (toAscList s1) (toAscList s2) {-------------------------------------------------------------------- Show --------------------------------------------------------------------} instance Show a => Show (Set a) where showsPrec p xs = showParen (p > 10) $ showString "fromList " . shows (toList xs) showSet :: (Show a) => [a] -> ShowS showSet [] = showString "{}" showSet (x:xs) = showChar '{' . shows x . showTail xs where showTail [] = showChar '}' showTail (x:xs) = showChar ',' . shows x . showTail xs {-------------------------------------------------------------------- Read --------------------------------------------------------------------} instance (Read a, Ord a) => Read (Set a) where #ifdef __GLASGOW_HASKELL__ readPrec = parens $ prec 10 $ do Ident "fromList" <- lexP xs <- readPrec return (fromList xs) readListPrec = readListPrecDefault #else readsPrec p = readParen (p > 10) $ \ r -> do ("fromList",s) <- lex r (xs,t) <- reads s return (fromList xs,t) #endif {-------------------------------------------------------------------- Typeable/Data --------------------------------------------------------------------} #include "Typeable.h" INSTANCE_TYPEABLE1(Set,setTc,"Set") {-------------------------------------------------------------------- Utility functions that return sub-ranges of the original tree. Some functions take a comparison function as argument to allow comparisons against infinite values. A function [cmplo x] should be read as [compare lo x]. [trim cmplo cmphi t] A tree that is either empty or where [cmplo x == LT] and [cmphi x == GT] for the value [x] of the root. [filterGt cmp t] A tree where for all values [k]. [cmp k == LT] [filterLt cmp t] A tree where for all values [k]. [cmp k == GT] [split k t] Returns two trees [l] and [r] where all values in [l] are <[k] and all keys in [r] are >[k]. [splitMember k t] Just like [split] but also returns whether [k] was found in the tree. --------------------------------------------------------------------} {-------------------------------------------------------------------- [trim lo hi t] trims away all subtrees that surely contain no values between the range [lo] to [hi]. The returned tree is either empty or the key of the root is between @lo@ and @hi@. --------------------------------------------------------------------} trim :: (a -> Ordering) -> (a -> Ordering) -> Set a -> Set a trim cmplo cmphi Tip = Tip trim cmplo cmphi t@(Bin sx x l r) = case cmplo x of LT -> case cmphi x of GT -> t le -> trim cmplo cmphi l ge -> trim cmplo cmphi r trimMemberLo :: Ord a => a -> (a -> Ordering) -> Set a -> (Bool, Set a) trimMemberLo lo cmphi Tip = (False,Tip) trimMemberLo lo cmphi t@(Bin sx x l r) = case compare lo x of LT -> case cmphi x of GT -> (member lo t, t) le -> trimMemberLo lo cmphi l GT -> trimMemberLo lo cmphi r EQ -> (True,trim (compare lo) cmphi r) {-------------------------------------------------------------------- [filterGt x t] filter all values >[x] from tree [t] [filterLt x t] filter all values <[x] from tree [t] --------------------------------------------------------------------} filterGt :: (a -> Ordering) -> Set a -> Set a filterGt cmp Tip = Tip filterGt cmp (Bin sx x l r) = case cmp x of LT -> join x (filterGt cmp l) r GT -> filterGt cmp r EQ -> r filterLt :: (a -> Ordering) -> Set a -> Set a filterLt cmp Tip = Tip filterLt cmp (Bin sx x l r) = case cmp x of LT -> filterLt cmp l GT -> join x l (filterLt cmp r) EQ -> l {-------------------------------------------------------------------- Split --------------------------------------------------------------------} -- | /O(log n)/. The expression (@'split' x set@) is a pair @(set1,set2)@ -- where all elements in @set1@ are lower than @x@ and all elements in -- @set2@ larger than @x@. @x@ is not found in neither @set1@ nor @set2@. split :: Ord a => a -> Set a -> (Set a,Set a) split x Tip = (Tip,Tip) split x (Bin sy y l r) = case compare x y of LT -> let (lt,gt) = split x l in (lt,join y gt r) GT -> let (lt,gt) = split x r in (join y l lt,gt) EQ -> (l,r) -- | /O(log n)/. Performs a 'split' but also returns whether the pivot -- element was found in the original set. splitMember :: Ord a => a -> Set a -> (Set a,Bool,Set a) splitMember x t = let (l,m,r) = splitLookup x t in (l,maybe False (const True) m,r) -- | /O(log n)/. Performs a 'split' but also returns the pivot -- element that was found in the original set. splitLookup :: Ord a => a -> Set a -> (Set a,Maybe a,Set a) splitLookup x Tip = (Tip,Nothing,Tip) splitLookup x (Bin sy y l r) = case compare x y of LT -> let (lt,found,gt) = splitLookup x l in (lt,found,join y gt r) GT -> let (lt,found,gt) = splitLookup x r in (join y l lt,found,gt) EQ -> (l,Just y,r) {-------------------------------------------------------------------- Utility functions that maintain the balance properties of the tree. All constructors assume that all values in [l] < [x] and all values in [r] > [x], and that [l] and [r] are valid trees. In order of sophistication: [Bin sz x l r] The type constructor. [bin x l r] Maintains the correct size, assumes that both [l] and [r] are balanced with respect to each other. [balance x l r] Restores the balance and size. Assumes that the original tree was balanced and that [l] or [r] has changed by at most one element. [join x l r] Restores balance and size. Furthermore, we can construct a new tree from two trees. Both operations assume that all values in [l] < all values in [r] and that [l] and [r] are valid: [glue l r] Glues [l] and [r] together. Assumes that [l] and [r] are already balanced with respect to each other. [merge l r] Merges two trees and restores balance. Note: in contrast to Adam's paper, we use (<=) comparisons instead of (<) comparisons in [join], [merge] and [balance]. Quickcheck (on [difference]) showed that this was necessary in order to maintain the invariants. It is quite unsatisfactory that I haven't been able to find out why this is actually the case! Fortunately, it doesn't hurt to be a bit more conservative. --------------------------------------------------------------------} {-------------------------------------------------------------------- Join --------------------------------------------------------------------} join :: a -> Set a -> Set a -> Set a join x Tip r = insertMin x r join x l Tip = insertMax x l join x l@(Bin sizeL y ly ry) r@(Bin sizeR z lz rz) | delta*sizeL <= sizeR = balance z (join x l lz) rz | delta*sizeR <= sizeL = balance y ly (join x ry r) | otherwise = bin x l r -- insertMin and insertMax don't perform potentially expensive comparisons. insertMax,insertMin :: a -> Set a -> Set a insertMax x t = case t of Tip -> singleton x Bin sz y l r -> balance y l (insertMax x r) insertMin x t = case t of Tip -> singleton x Bin sz y l r -> balance y (insertMin x l) r {-------------------------------------------------------------------- [merge l r]: merges two trees. --------------------------------------------------------------------} merge :: Set a -> Set a -> Set a merge Tip r = r merge l Tip = l merge l@(Bin sizeL x lx rx) r@(Bin sizeR y ly ry) | delta*sizeL <= sizeR = balance y (merge l ly) ry | delta*sizeR <= sizeL = balance x lx (merge rx r) | otherwise = glue l r {-------------------------------------------------------------------- [glue l r]: glues two trees together. Assumes that [l] and [r] are already balanced with respect to each other. --------------------------------------------------------------------} glue :: Set a -> Set a -> Set a glue Tip r = r glue l Tip = l glue l r | size l > size r = let (m,l') = deleteFindMax l in balance m l' r | otherwise = let (m,r') = deleteFindMin r in balance m l r' -- | /O(log n)/. Delete and find the minimal element. -- -- > deleteFindMin set = (findMin set, deleteMin set) deleteFindMin :: Set a -> (a,Set a) deleteFindMin t = case t of Bin _ x Tip r -> (x,r) Bin _ x l r -> let (xm,l') = deleteFindMin l in (xm,balance x l' r) Tip -> (error "Set.deleteFindMin: can not return the minimal element of an empty set", Tip) -- | /O(log n)/. Delete and find the maximal element. -- -- > deleteFindMax set = (findMax set, deleteMax set) deleteFindMax :: Set a -> (a,Set a) deleteFindMax t = case t of Bin _ x l Tip -> (x,l) Bin _ x l r -> let (xm,r') = deleteFindMax r in (xm,balance x l r') Tip -> (error "Set.deleteFindMax: can not return the maximal element of an empty set", Tip) -- | /O(log n)/. Retrieves the minimal key of the set, and the set stripped from that element -- @fail@s (in the monad) when passed an empty set. minView :: Monad m => Set a -> m (a, Set a) minView Tip = fail "Set.minView: empty set" minView x = return (deleteFindMin x) -- | /O(log n)/. Retrieves the maximal key of the set, and the set stripped from that element -- @fail@s (in the monad) when passed an empty set. maxView :: Monad m => Set a -> m (a, Set a) maxView Tip = fail "Set.maxView: empty set" maxView x = return (deleteFindMax x) {-------------------------------------------------------------------- [balance x l r] balances two trees with value x. The sizes of the trees should balance after decreasing the size of one of them. (a rotation). [delta] is the maximal relative difference between the sizes of two trees, it corresponds with the [w] in Adams' paper, or equivalently, [1/delta] corresponds with the $\alpha$ in Nievergelt's paper. Adams shows that [delta] should be larger than 3.745 in order to garantee that the rotations can always restore balance. [ratio] is the ratio between an outer and inner sibling of the heavier subtree in an unbalanced setting. It determines whether a double or single rotation should be performed to restore balance. It is correspondes with the inverse of $\alpha$ in Adam's article. Note that: - [delta] should be larger than 4.646 with a [ratio] of 2. - [delta] should be larger than 3.745 with a [ratio] of 1.534. - A lower [delta] leads to a more 'perfectly' balanced tree. - A higher [delta] performs less rebalancing. - Balancing is automatic for random data and a balancing scheme is only necessary to avoid pathological worst cases. Almost any choice will do in practice - Allthough it seems that a rather large [delta] may perform better than smaller one, measurements have shown that the smallest [delta] of 4 is actually the fastest on a wide range of operations. It especially improves performance on worst-case scenarios like a sequence of ordered insertions. Note: in contrast to Adams' paper, we use a ratio of (at least) 2 to decide whether a single or double rotation is needed. Allthough he actually proves that this ratio is needed to maintain the invariants, his implementation uses a (invalid) ratio of 1. He is aware of the problem though since he has put a comment in his original source code that he doesn't care about generating a slightly inbalanced tree since it doesn't seem to matter in practice. However (since we use quickcheck :-) we will stick to strictly balanced trees. --------------------------------------------------------------------} delta,ratio :: Int delta = 4 ratio = 2 balance :: a -> Set a -> Set a -> Set a balance x l r | sizeL + sizeR <= 1 = Bin sizeX x l r | sizeR >= delta*sizeL = rotateL x l r | sizeL >= delta*sizeR = rotateR x l r | otherwise = Bin sizeX x l r where sizeL = size l sizeR = size r sizeX = sizeL + sizeR + 1 -- rotate rotateL x l r@(Bin _ _ ly ry) | size ly < ratio*size ry = singleL x l r | otherwise = doubleL x l r rotateR x l@(Bin _ _ ly ry) r | size ry < ratio*size ly = singleR x l r | otherwise = doubleR x l r -- basic rotations singleL x1 t1 (Bin _ x2 t2 t3) = bin x2 (bin x1 t1 t2) t3 singleR x1 (Bin _ x2 t1 t2) t3 = bin x2 t1 (bin x1 t2 t3) doubleL x1 t1 (Bin _ x2 (Bin _ x3 t2 t3) t4) = bin x3 (bin x1 t1 t2) (bin x2 t3 t4) doubleR x1 (Bin _ x2 t1 (Bin _ x3 t2 t3)) t4 = bin x3 (bin x2 t1 t2) (bin x1 t3 t4) {-------------------------------------------------------------------- The bin constructor maintains the size of the tree --------------------------------------------------------------------} bin :: a -> Set a -> Set a -> Set a bin x l r = Bin (size l + size r + 1) x l r {-------------------------------------------------------------------- Utilities --------------------------------------------------------------------} foldlStrict f z xs = case xs of [] -> z (x:xx) -> let z' = f z x in seq z' (foldlStrict f z' xx) {-------------------------------------------------------------------- Debugging --------------------------------------------------------------------} -- | /O(n)/. Show the tree that implements the set. The tree is shown -- in a compressed, hanging format. showTree :: Show a => Set a -> String showTree s = showTreeWith True False s {- | /O(n)/. The expression (@showTreeWith hang wide map@) shows the tree that implements the set. If @hang@ is @True@, a /hanging/ tree is shown otherwise a rotated tree is shown. If @wide@ is 'True', an extra wide version is shown. > Set> putStrLn $ showTreeWith True False $ fromDistinctAscList [1..5] > 4 > +--2 > | +--1 > | +--3 > +--5 > > Set> putStrLn $ showTreeWith True True $ fromDistinctAscList [1..5] > 4 > | > +--2 > | | > | +--1 > | | > | +--3 > | > +--5 > > Set> putStrLn $ showTreeWith False True $ fromDistinctAscList [1..5] > +--5 > | > 4 > | > | +--3 > | | > +--2 > | > +--1 -} showTreeWith :: Show a => Bool -> Bool -> Set a -> String showTreeWith hang wide t | hang = (showsTreeHang wide [] t) "" | otherwise = (showsTree wide [] [] t) "" showsTree :: Show a => Bool -> [String] -> [String] -> Set a -> ShowS showsTree wide lbars rbars t = case t of Tip -> showsBars lbars . showString "|\n" Bin sz x Tip Tip -> showsBars lbars . shows x . showString "\n" Bin sz x l r -> showsTree wide (withBar rbars) (withEmpty rbars) r . showWide wide rbars . showsBars lbars . shows x . showString "\n" . showWide wide lbars . showsTree wide (withEmpty lbars) (withBar lbars) l showsTreeHang :: Show a => Bool -> [String] -> Set a -> ShowS showsTreeHang wide bars t = case t of Tip -> showsBars bars . showString "|\n" Bin sz x Tip Tip -> showsBars bars . shows x . showString "\n" Bin sz x l r -> showsBars bars . shows x . showString "\n" . showWide wide bars . showsTreeHang wide (withBar bars) l . showWide wide bars . showsTreeHang wide (withEmpty bars) r showWide wide bars | wide = showString (concat (reverse bars)) . showString "|\n" | otherwise = id showsBars :: [String] -> ShowS showsBars bars = case bars of [] -> id _ -> showString (concat (reverse (tail bars))) . showString node node = "+--" withBar bars = "| ":bars withEmpty bars = " ":bars {-------------------------------------------------------------------- Assertions --------------------------------------------------------------------} -- | /O(n)/. Test if the internal set structure is valid. valid :: Ord a => Set a -> Bool valid t = balanced t && ordered t && validsize t ordered t = bounded (const True) (const True) t where bounded lo hi t = case t of Tip -> True Bin sz x l r -> (lo x) && (hi x) && bounded lo (<x) l && bounded (>x) hi r balanced :: Set a -> Bool balanced t = case t of Tip -> True Bin sz x l r -> (size l + size r <= 1 || (size l <= delta*size r && size r <= delta*size l)) && balanced l && balanced r validsize t = (realsize t == Just (size t)) where realsize t = case t of Tip -> Just 0 Bin sz x l r -> case (realsize l,realsize r) of (Just n,Just m) | n+m+1 == sz -> Just sz other -> Nothing {- {-------------------------------------------------------------------- Testing --------------------------------------------------------------------} testTree :: [Int] -> Set Int testTree xs = fromList xs test1 = testTree [1..20] test2 = testTree [30,29..10] test3 = testTree [1,4,6,89,2323,53,43,234,5,79,12,9,24,9,8,423,8,42,4,8,9,3] {-------------------------------------------------------------------- QuickCheck --------------------------------------------------------------------} qcheck prop = check config prop where config = Config { configMaxTest = 500 , configMaxFail = 5000 , configSize = \n -> (div n 2 + 3) , configEvery = \n args -> let s = show n in s ++ [ '\b' | _ <- s ] } {-------------------------------------------------------------------- Arbitrary, reasonably balanced trees --------------------------------------------------------------------} instance (Enum a) => Arbitrary (Set a) where arbitrary = sized (arbtree 0 maxkey) where maxkey = 10000 arbtree :: (Enum a) => Int -> Int -> Int -> Gen (Set a) arbtree lo hi n | n <= 0 = return Tip | lo >= hi = return Tip | otherwise = do{ i <- choose (lo,hi) ; m <- choose (1,30) ; let (ml,mr) | m==(1::Int)= (1,2) | m==2 = (2,1) | m==3 = (1,1) | otherwise = (2,2) ; l <- arbtree lo (i-1) (n `div` ml) ; r <- arbtree (i+1) hi (n `div` mr) ; return (bin (toEnum i) l r) } {-------------------------------------------------------------------- Valid tree's --------------------------------------------------------------------} forValid :: (Enum a,Show a,Testable b) => (Set a -> b) -> Property forValid f = forAll arbitrary $ \t -> -- classify (balanced t) "balanced" $ classify (size t == 0) "empty" $ classify (size t > 0 && size t <= 10) "small" $ classify (size t > 10 && size t <= 64) "medium" $ classify (size t > 64) "large" $ balanced t ==> f t forValidIntTree :: Testable a => (Set Int -> a) -> Property forValidIntTree f = forValid f forValidUnitTree :: Testable a => (Set Int -> a) -> Property forValidUnitTree f = forValid f prop_Valid = forValidUnitTree $ \t -> valid t {-------------------------------------------------------------------- Single, Insert, Delete --------------------------------------------------------------------} prop_Single :: Int -> Bool prop_Single x = (insert x empty == singleton x) prop_InsertValid :: Int -> Property prop_InsertValid k = forValidUnitTree $ \t -> valid (insert k t) prop_InsertDelete :: Int -> Set Int -> Property prop_InsertDelete k t = not (member k t) ==> delete k (insert k t) == t prop_DeleteValid :: Int -> Property prop_DeleteValid k = forValidUnitTree $ \t -> valid (delete k (insert k t)) {-------------------------------------------------------------------- Balance --------------------------------------------------------------------} prop_Join :: Int -> Property prop_Join x = forValidUnitTree $ \t -> let (l,r) = split x t in valid (join x l r) prop_Merge :: Int -> Property prop_Merge x = forValidUnitTree $ \t -> let (l,r) = split x t in valid (merge l r) {-------------------------------------------------------------------- Union --------------------------------------------------------------------} prop_UnionValid :: Property prop_UnionValid = forValidUnitTree $ \t1 -> forValidUnitTree $ \t2 -> valid (union t1 t2) prop_UnionInsert :: Int -> Set Int -> Bool prop_UnionInsert x t = union t (singleton x) == insert x t prop_UnionAssoc :: Set Int -> Set Int -> Set Int -> Bool prop_UnionAssoc t1 t2 t3 = union t1 (union t2 t3) == union (union t1 t2) t3 prop_UnionComm :: Set Int -> Set Int -> Bool prop_UnionComm t1 t2 = (union t1 t2 == union t2 t1) prop_DiffValid = forValidUnitTree $ \t1 -> forValidUnitTree $ \t2 -> valid (difference t1 t2) prop_Diff :: [Int] -> [Int] -> Bool prop_Diff xs ys = toAscList (difference (fromList xs) (fromList ys)) == List.sort ((List.\\) (nub xs) (nub ys)) prop_IntValid = forValidUnitTree $ \t1 -> forValidUnitTree $ \t2 -> valid (intersection t1 t2) prop_Int :: [Int] -> [Int] -> Bool prop_Int xs ys = toAscList (intersection (fromList xs) (fromList ys)) == List.sort (nub ((List.intersect) (xs) (ys))) {-------------------------------------------------------------------- Lists --------------------------------------------------------------------} prop_Ordered = forAll (choose (5,100)) $ \n -> let xs = [0..n::Int] in fromAscList xs == fromList xs prop_List :: [Int] -> Bool prop_List xs = (sort (nub xs) == toList (fromList xs)) -}