def __init__(self):
self.queue = BinHeap()
def enqueue(self, item):
BinHeap.insert(self.queue, item)
from pythonds.trees.binheap import BinHeap bh = BinHeap() bh.insert(5) bh.insert(7) bh.insert(3) bh.insert(11) print(bh.delMin()) print(bh.delMin()) print(bh.delMin()) print(bh.delMin())
def dequeue(self):
return BinHeap.delMin(self.queue)
def postorder(tree):
if tree:
postorder(tree.get_left_child())
postorder(tree.get_right_child())
print(tree.get_root_val())
def midorder(tree):
if tree:
midorder(tree.get_left_child())
print(tree.get_root_val())
midorder(tree.get_right_child())
if __name__ == '__main__':
bh = BinHeap()
arr = [9, 5, 6, 2, 3]
bh.buildHelp(arr)
i = len(arr) - 1
while i >= 0:
arr_min = bh.delmin()
arr[i] = arr_min
print(arr)
'''
r = BinaryTree('a')
print(r.get_root_val())
print(r.get_left_child())
r.insert_left('b')
print(r.get_left_child())
print(r.get_left_child().get_root_val())
r.insert_right('c')
## Using PriorityQueue ##
#pq = PriorityQueue({1: "a", 2: "b", 3: "c"})
pq = PriorityQueue()
pq.put((2, 'code'))
pq.put((1, 'sleep'))
pq.put((3, 'eat'))
while not pq.empty():
print(pq.get())
## Using Binary Heap to implement Priority queue ##
p1 = [(2, "code"), (1, "eat"), (3, "sleep")]
heapq.heapify(p1)
p2 = []
heapq.heappush(p2, (1, "code"))
heapq.heappush(p2, (2, "eat"))
print("p1", p1)
while p1:
print(heapq.heappop(p1))
print("p2", p2)
while p2:
print(heapq.heappop(p2))
## Using pythonds module ##
p3 = BinHeap()
p3.insert(1)
p3.insert(2)
p3.insert(4)
print("p3", p3)
print(p3.delMin())
from pythonds.trees.binheap import BinHeap bh = BinHeap() bh.insert(5) bh.insert(55) bh.insert(10) bh.insert(2) bh.insert(8) print(bh.delMin()) print(bh.delMin()) print(bh.delMin()) print(bh.delMin()) print(bh.delMin())
"""
交换节点
"""
#首先判断i*2+1是否在超出列表长度
if i * 2 + 1 > self.currentSize:
return i * 2
else:
#若没有超出，则比较左右孩子的数据项的大小
if self.heapList[i * 2] < self.heapList[i * 2 + 1]:
return i * 2
else:
return i * 2 + 1
def delMin(self):
"""
删除最小的数据项
"""
#获取最小项，即根节点
reval = self.heapList[1]
self.heapList[1] = self.heapList[self.currentSize]
self.currentSize -= 1
# self.heapList.pop()
self.percDown(1)
return reval
if __name__ == '__main__':
alist = BinHeap()
alist.BuildHeap([5, 9, 11, 14, 18, 19, 21, 33, 17, 27])
print(alist.delMin())
# http://interactivepython.org/runestone/static/pythonds/Trees/BinaryHeapOperations.html
# BinaryHeap() creates a new, empty, binary heap.
# insert(k) adds a new item to the heap.
# findMin() returns the item with the minimum key value, leaving item in the heap.
# delMin() returns the item with the minimum key value, removing the item from the heap.
# isEmpty() returns true if the heap is empty, false otherwise.
# size() returns the number of items in the heap.
# buildHeap(list) builds a new heap from a list of keys.
print("\nBinary Heap Operations")
from pythonds.trees.binheap import BinHeap
# ----------------------------------
print("Sample 1")
bh = BinHeap()
bh.insert(5)
bh.insert(7)
bh.insert(3)
bh.insert(11)
print(bh.delMin())
print(bh.delMin())
print(bh.delMin())
print(bh.delMin())
# ----------------------------------
class BinHeap:
def __init__(self):
self.heapList = [0]
