- add_to_heap(+OldHeap, +Key, +Datum, -NewHeap)
- inserts the new Key-Datum pair into the heap
- get_from_heap(+OldHeap, ?Key, ?Datum, -NewHeap)
- returns the Key-Datum pair in OldHeap with the smallest Key
- heap_size(+Heap, ?Size)
- reports the number of elements currently in the heap
- heap_to_list(+Heap, -List)
- returns the current set of Key-Datum pairs in the Heap as a List.
- list_to_heap(+List, -Heap)
- takes a list of Key-Datum pairs and forms them into a heap
- min_of_heap(+Heap, ?Key, ?Datum)
- returns the Key-Datum pair at the top of the heap
- min_of_heap(+Heap, ?Key1, ?Datum1, ?Key2, ?Datum2)
- returns the smallest and second smallest pairs in the heap
A heap is a labelled binary tree where the key of each node is less than or equal to the keys of its sons. The point of a heap is that we can keep on adding new elements to the heap and we can keep on taking out the minimum element. If there are N elements total, the total time is O(NlgN). If you know all the elements in advance, you are better off doing a merge-sort, but this file is for when you want to do say a best-first search, and have no idea when you start how many elements there will be, let alone what they are.
A heap is represented as a triple t(N, Free, Tree) where N is the number of elements in the tree, Free is a list of integers which specifies unused positions in the tree, and Tree is a tree made of
t terms for empty subtrees and t(Key,Datum,Lson,Rson) terms for the restThe nodes of the tree are notionally numbered like this:
				    1
		     2				    3
             4               6               5               7
         8      12      10     14       9       13      11     15
      ..  ..  ..  ..  ..  ..  ..  ..  ..  ..  ..  ..  ..  ..  ..  ..
    The idea is that if the maximum number of elements that have been in
    the heap so far is M, and the tree currently has K elements, the tree
    is some subtreee of the tree of this form having exactly M elements,
    and the Free list is a list of K-M integers saying which of the 
    positions in the M-element tree are currently unoccupied.  This free
    list is needed to ensure that the cost of passing N elements through
    the heap is O(NlgM) instead of O(NlgN).  For M say 100 and N say 10^4
    this means a factor of two.  The cost of the free list is slight.
    The storage cost of a heap in a copying Prolog (which Dec-10 Prolog is
    not) is 2K+3M words.