# # # Nim's Runtime Library # (c) Copyright 2016 Yuriy Glukhov # # See the file "copying.txt", included in this # distribution, for details about the copyright. ##[ The `heapqueue` module implements a `heap data structure`_ that can be used as a `priority queue`_. Heaps are arrays for which `a[k] <= a[2*k+1]` and `a[k] <= a[2*k+2]` for all `k`, counting elements from 0. The interesting property of a heap is that `a[0]` is always its smallest element. Basic usage ----------- .. code-block:: Nim import heapqueue var heap = initHeapQueue[int]() heap.push(8) heap.push(2) heap.push(5) # The first element is the lowest element assert heap[0] == 2 # Remove and return the lowest element assert heap.pop() == 2 # The lowest element remaining is 5 assert heap[0] == 5 Usage with custom object ------------------------ To use a `HeapQueue` with a custom object, the `<` operator must be implemented. .. code-block:: Nim import heapqueue type Job = object priority: int proc `<`(a, b: Job): bool = a.priority < b.priority var jobs = initHeapQueue[Job]() jobs.push(Job(priority: 1)) jobs.push(Job(priority: 2)) assert jobs[0].priority == 1 ]## type HeapQueue*[T] = object ## A heap queue, commonly known as a priority queue. data: seq[T] proc initHeapQueue*[T](): HeapQueue[T] = ## Create a new empty heap. discard proc len*[T](heap: HeapQueue[T]): int {.inline.} = ## Return the number of elements of `heap`. heap.data.len proc `[]`*[T](heap: HeapQueue[T], i: Natural): T {.inline.} = ## Access the i-th element of `heap`. heap.data[i] proc heapCmp[T](x, y: T): bool {.inline.} = return (x < y) proc siftdown[T](heap: var HeapQueue[T], startpos, p: int) = ## 'heap' is a heap at all indices >= startpos, except possibly for pos. pos ## is the index of a leaf with a possibly out-of-order value. Restore the ## heap invariant. var pos = p var newitem = heap[pos] # Follow the path to the root, moving parents down until finding a place # newitem fits. while pos > startpos: let parentpos = (pos - 1) shr 1 let parent = heap[parentpos] if heapCmp(newitem, parent): heap.data[pos] = parent pos = parentpos else: break heap.data[pos] = newitem proc siftup[T](heap: var HeapQueue[T], p: int) = let endpos = len(heap) var pos = p let startpos = pos let newitem = heap[pos] # Bubble up the smaller child until hitting a leaf. var childpos = 2*pos + 1 # leftmost child position while childpos < endpos: # Set childpos to index of smaller child. let rightpos = childpos + 1 if rightpos < endpos and not heapCmp(heap[childpos], heap[rightpos]): childpos = rightpos # Move the smaller child up. heap.data[pos] = heap[childpos] pos = childpos childpos = 2*pos + 1 # The leaf at pos is empty now. Put newitem there, and bubble it up # to its final resting place (by sifting its parents down). heap.data[pos] = newitem siftdown(heap, startpos, pos) proc push*[T](heap: var HeapQueue[T], item: T) = ## Push `item` onto heap, maintaining the heap invariant. heap.data.add(item) siftdown(heap, 0, len(heap)-1) proc pop*[T](heap: var HeapQueue[T]): T = ## Pop and return the smallest item from `heap`, ## maintaining the heap invariant. let lastelt = heap.data.pop() if heap.len > 0: result = heap[0] heap.data[0] = lastelt siftup(heap, 0) else: result = lastelt proc del*[T](heap: var HeapQueue[T], index: Natural) = ## Removes the element at `index` from `heap`, maintaining the heap invariant. swap(heap.data[^1], heap.data[index]) let newLen = heap.len - 1 heap.data.setLen(newLen) if index < newLen: heap.siftup(index) proc replace*[T](heap: var HeapQueue[T], item: T): T = ## Pop and return the current smallest value, and add the new item. ## This is more efficient than pop() followed by push(), and can be ## more appropriate when using a fixed-size heap. Note that the value ## returned may be larger than item! That constrains reasonable uses of ## this routine unless written as part of a conditional replacement: ## ## .. code-block:: nim ## if item > heap[0]: ## item = replace(heap, item) result = heap[0] heap.data[0] = item siftup(heap, 0) proc pushpop*[T](heap: var HeapQueue[T], item: T): T = ## Fast version of a push followed by a pop. if heap.len > 0 and heapCmp(heap[0], item): swap(item, heap[0]) siftup(heap, 0) return item proc clear*[T](heap: var HeapQueue[T]) = ## Remove all elements from `heap`, making it empty. runnableExamples: var heap = initHeapQueue[int]() heap.push(1) heap.clear() assert heap.len == 0 heap.data.setLen(0) proc `$`*[T](heap: HeapQueue[T]): string = ## Turn a heap into its string representation. runnableExamples: var heap = initHeapQueue[int]() heap.push(1) heap.push(2) assert $heap == "[1, 2]" result = "[" for x in heap.data: if result.len > 1: result.add(", ") result.addQuoted(x) result.add("]") proc newHeapQueue*[T](): HeapQueue[T] {.deprecated.} = ## **Deprecated since v0.20.0:** use ``initHeapQueue`` instead. initHeapQueue[T]() proc newHeapQueue*[T](heap: var HeapQueue[T]) {.deprecated.} = ## **Deprecated since v0.20.0:** use ``clear`` instead. heap.clear() when isMainModule: proc toSortedSeq[T](h: HeapQueue[T]): seq[T] = var tmp = h result = @[] while tmp.len > 0: result.add(pop(tmp)) block: # Simple sanity test var heap = initHeapQueue[int]() let data = [1, 3, 5, 7, 9, 2, 4, 6, 8, 0] for item in data: push(heap, item) doAssert(heap[0] == 0) doAssert(heap.toSortedSeq == @[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) block: # Test del var heap = initHeapQueue[int]() let data = [1, 3, 5, 7, 9, 2, 4, 6, 8, 0] for item in data: push(heap, item) heap.del(0) doAssert(heap[0] == 1) heap.del(heap.data.find(7)) doAssert(heap.toSortedSeq == @[1, 2, 3, 4, 5, 6, 8, 9]) heap.del(heap.data.find(5)) doAssert(heap.toSortedSeq == @[1, 2, 3, 4, 6, 8, 9]) heap.del(heap.data.find(6)) doAssert(heap.toSortedSeq == @[1, 2, 3, 4, 8, 9]) heap.del(heap.data.find(2)) doAssert(heap.toSortedSeq == @[1, 3, 4, 8, 9]) block: # Test del last var heap = initHeapQueue[int]() let data = [1, 2, 3] for item in data: push(heap, item) heap.del(2) doAssert(heap.toSortedSeq == @[1, 2]) heap.del(1) doAssert(heap.toSortedSeq == @[1]) heap.del(0) doAssert(heap.toSortedSeq == @[])