implement heap which stores distance for later use with Dijkstra's algorithm
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153
fcore/heap.sml
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153
fcore/heap.sml
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(* implementation based on Chris Okasaki's paper describing SkewBinomialQueues
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* from the following PDF, based on figure 6 and figure 7.
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* https://www.brics.dk/RS/96/37/BRICS-RS-96-37.pdf
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*
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* Differences:
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* - No exception is raised as we return a default value
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* in the case of findMin when queue is empty
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* and we return the empty queue when queue is empty
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* in the case of deleteMin.
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* - Use foldDeleteMin function to eliminate
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* runtime cost of closure/defunctionalisation
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* *)
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signature ORDERED =
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sig
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type t
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type id
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val default: id
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val getID: t -> id
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val leq: t * t -> bool
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end
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signature PRIORITY_QUEUE =
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sig
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structure Elem: ORDERED
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type t
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val empty: t
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val isEmpty: t -> bool
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val insert: Elem.t * t -> t
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val findMin: t -> Elem.id
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val deleteMin: t -> t
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end
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functor MakeSkewHeap(E: ORDERED): PRIORITY_QUEUE =
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struct
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structure Elem = E
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type rank = int
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datatype tree = NODE of Elem.t * rank * tree list
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type t = tree list
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fun root (NODE (x, _, _)) = x
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fun rank (NODE (_, r, _)) = r
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fun link (t1, t2) =
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case (t1, t2) of
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(NODE (x1, r1, c1), NODE (x2, r2, c2)) =>
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if Elem.leq (x1, x2) then NODE (x1, r1 + 1, t2 :: c1)
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else NODE (x2, r2 + 1, t1 :: c2)
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fun skewLink (t0, t1, t2) =
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case (t0, t1, t2) of
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(NODE (x0, r0, _), NODE (x1, r1, c1), NODE (x2, r2, c2)) =>
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if Elem.leq (x1, x0) andalso Elem.leq (x1, x2) then
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NODE (x1, r1 + 1, t0 :: t2 :: c1)
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else if Elem.leq (x2, x0) andalso Elem.leq (x2, x1) then
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NODE (x2, r2 + 1, t0 :: t1 :: c2)
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else
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NODE (x0, r1 + 1, [t1, t2])
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fun ins (t, t' :: ts) =
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if rank t < rank t' then t :: t' :: ts else ins (link (t, t'), ts)
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| ins (t, []) = [t]
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val empty = []
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fun isEmpty [] = true
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| isEmpty _ = false
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fun insert (x, ts as t1 :: t2 :: rest) =
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if rank t1 = rank t2 then skewLink (NODE (x, 0, []), t1, t2) :: rest
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else NODE (x, 0, []) :: ts
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| insert (x, ts) =
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NODE (x, 0, []) :: ts
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fun helpFindMin (t, ts) =
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case ts of
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[x] => root x
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| x :: tl =>
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let val x = helpFindMin (x, tl)
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in if Elem.leq (root t, x) then root t else x
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end
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| [] => root t
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fun findMin [t] =
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Elem.getID (root t)
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| findMin (t :: ts) =
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let val x = helpFindMin (t, ts)
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in if Elem.leq (root t, x) then Elem.getID (root t) else Elem.getID x
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end
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| findMin [] = Elem.default
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fun getMin (prevT, t) =
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case t of
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[t] => (t, [])
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| t :: ts =>
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let val (t', ts') = getMin (t, ts)
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in if Elem.leq (root t, root t') then (t, ts) else (t', t :: ts')
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end
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| [] => (prevT, [])
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fun split (ts, xs, []) = (ts, xs)
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| split (ts, xs, t :: c) =
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if rank t = 0 then split (ts, root t :: xs, c)
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else split (t :: ts, xs, c)
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fun unify [] = []
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| unify (t :: ts) = ins (t, ts)
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fun meldUniq ([], ts) = ts
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| meldUniq (ts, []) = ts
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| meldUniq (t1 :: ts1, t2 :: ts2) =
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if rank t1 < rank t2 then t1 :: meldUniq (ts1, t2 :: ts2)
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else if rank t2 < rank t1 then t2 :: meldUniq (t1 :: ts1, ts2)
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else ins (link (t1, t2), meldUniq (ts1, ts2))
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fun meld (ts, ts') =
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meldUniq (unify ts, unify ts')
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fun foldDeleteMin (lst, state) =
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case lst of
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[] => state
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| hd :: tl =>
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let val state = insert (hd, state)
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in foldDeleteMin (tl, state)
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end
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fun deleteMin [] = raise Empty
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| deleteMin (ts as hd :: tl) =
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let
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val (NODE (x, r, c), ts) = getMin (hd, tl)
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val (ts', xs') = split ([], [], c)
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in
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foldDeleteMin (xs', meld (ts, ts'))
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end
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end
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structure DistHeap =
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MakeSkewHeap
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(struct
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type t = {distance: int, id: int}
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type id = int
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(* default = defaultID returned when queue is empty *)
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val default = ~1
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fun getID {id, distance = _} = id
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fun leq ({distance = d1, ...}: t, {distance = d2, ...}: t) = d1 <= d2
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end)
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