总结数据结构中的排序算法(python)
# 时间复杂度:o(nlogn)
#快速排序
def quick_sort(alist, start, end):
if start >= end:
return
mid_value = alist[start]
low = start
hight = end
while low < hight:
while low<high and alist[high] >= mid_value:
high -= 1
alist[low] = alist[high]
while low < high and alist[low] <= mid_value:
low += 1
alist[high] = alist[low]
alist[low] = mid_value
quick_sort(alist, start, low-1)
quick_sort(alist, low+1, end)
if __name__ == '__main__':
li = [54, 26, 93, 17, 77, 31, 44, 55, 20, 13]
quick_sort(li, 0, len(li)-1)
print(li)
#归并排序
def merge_sort(alist):
n = len(alist)
if n <= 1:
return alist
mid = n//2
left = merge_sort(alist[:mid])
right = merge_sort(alist[mid:])
left_point,right_point = 0,0
result = []
while left_point < len(left) and right_point < len(right):
if left[left_point] <= right[right_point]:
result.append(left[left_point])
left_point += 1
else:
result.append(right[right_point])
right_point += 1
result += left[right_point:]
result += right[left_point:]
return result
# 堆排序
# 向下调整函数的实现, 此处建立大根堆,可实现数组升序排列
def sift(alist, low, high):
# 假设只有根节点需要调整,两棵子树都是堆
i = low
j = i *2 +1 #j指向i的左子树
tmp = alist[i]
while j <=high:
if j+1<= high and alist[j] < alist[j+1] #右子树比较大,则指向右子树
j = j+1
if alist[j] > tmp: # 若子树的值比较大,则根节点换成子树,然后向下看一层
alist[i] = alist[j]
i = j
j = i *2 +1
else:
alist[i] = tmp # 子树的值小于根节点,则根节点就放在这一层
break
else:
alist[i] = tmp # j越界跳出循环,则把根节点放在叶子节点
def heap_sort(alist):
# 1、建堆
# 先找到最后一个不是叶子节点的根节点,为(n-2)//2 (若叶子节点为i,则他的父节点为(i-1)//2 )
# 再向上循环根节点,从小到大
n = len(alist)
for i in range((n-2)//2, -1, -1):
sift(alist,i,n-1)
# 2、挨个出数,按升序排列
for i in range(n-1, -1, -1):
alist[0], alist[i] = alist[i], alist[0]
sift(alist, 0, i-1)
if __name__ == '__main__':
li = [54, 26, 93, 17, 77, 31, 44, 55, 20, 13]
heap_sort(li)
print(li)