The min heap uses heapq as well as custom written _siftup and _siftdown methods to allow the heap positions to be tracked by an additional dict keyed by element to position. The smallest element can be popped in O(1) time, new elements can be pushed in O(log n) time, and any element can be removed or updated in O(log n) time. The queue cannot contain duplicate elements and an attempt to push an element already in the queue will have no effect.
MappedQueue complements the heapq package from the python standard library. While MappedQueue is designed for maximum compatibility with heapq, it adds element removal, lookup, and priority update.
The MappedQueue class implements a min-heap with removal and update-priority.
A MappedQueue
can be created empty or optionally given an array of initial elements. Calling :None:None:`push()` will add an element and calling :None:None:`pop()` will remove and return the smallest element.
>>> q = MappedQueue([916, 50, 4609, 493, 237])
... q.push(1310) True
>>> [q.pop() for i in range(len(q.heap))] [50, 237, 493, 916, 1310, 4609]
Elements can also be updated or removed from anywhere in the queue.
>>> q = MappedQueue([916, 50, 4609, 493, 237])See :
... q.remove(493)
... q.update(237, 1117)
... [q.pop() for i in range(len(q.heap))] [50, 916, 1117, 4609]
The following pages refer to to this document either explicitly or contain code examples using this.
networkx.utils.mapped_queue.MappedQueue
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