堆排序的python實現

標籤：做了   第一個   結構   odi   獲得   等於   root   \n   inner   

#!/usr/bin/env python# -*- coding: utf-8 -*-import heapqimport copyimport datetimeimport randomdef get_max_heap(heap, size, root):  # 在堆中做結構調整使得父節點的值大於子節點    left = 2 * root + 1    right = left + 1    larger = root    if left < size and heap[larger] < heap[left]:  # 保證最大值不會被重新排序        larger = left    if right < size and heap[larger] < heap[right]:  # 保證最大值不會被重新排序        larger = right    if larger != root:  # 如果做了堆調整則larger的值等於左節點或者右節點的，這個時候做對調值操作        heap[larger], heap[root] = heap[root], heap[larger]        get_max_heap(heap, size, larger)def build_heap(heap):    # 構造一個堆，將堆中所有資料重新排序    for index in xrange(len(heap) / 2 - 1, -1, -1):  # 從第一個非葉子節點開始        get_max_heap(heap, len(heap), index)def sort(heap):    build_heap(heap)  # 獲得一個大頂堆    for index in xrange(len(heap) - 1, -1, -1):        heap[0], heap[index] = heap[index], heap[0]  # 將最大值調到最後        get_max_heap(heap, index, 0)  # size遞減，保證最大值不會被重新排序    return heapif __name__ == ‘__main__‘:    # a = eval(raw_input(‘請輸入一個待排序列表\n‘))    a = [random.randint(1, 2000) for i in range(1000)]    b = copy.deepcopy(a)    b_begin = datetime.datetime.now()    sort(b)    b_end = datetime.datetime.now()    print ‘my method use %s‘ % (b_end - b_begin).total_seconds()    c = copy.deepcopy(a)    c_begin = datetime.datetime.now()    heapq.heapify(c)    c_end = datetime.datetime.now()    print ‘inner method use %s‘ % (c_end - c_begin).total_seconds()——————————————————————————————my method use 0.011inner method use 0.001
#可以看到，我們實現的排序演算法在時間上不如內建的heapq.heapify()

 

堆排序的python實現