python算法实践7 归并排序
def MergeSort(mylist, low, mid, high):
i = low
j = mid + 1
tmp = []
while i <= mid and j <= high:
if mylist[i] <= mylist[j]:
tmp.append(mylist[i])
i = i + 1
else:
tmp.append(mylist[j])
j = j + 1
while i <= mid:
tmp.append(mylist[i])
i = i + 1
while j <= high:
tmp.append(mylist[j])
j = j + 1
for k in range(low, high):
mylist[k] = tmp[k]
mylist0 = [1, 3, 5, 7, 9, 11, 6, 8, 66, 88, 100]
MergeSort(mylist0, 0, 5, len(mylist0) - 1)
print(mylist0)
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程对数据取出处理。但是如果缓冲区的太小而生产者和消费者两个异步线程的速度不同时，容易出现一个线程等待另一个情况。为了尽可能的缩短共享资源并以相同
速度工作的各线� ......
#shell排序
def ShellPass(mylist, d):
size = len(mylist)
i = d
while i < size:
if mylist[i] < mylist[i - d]:
tmp = mylist[i]
j = i - d
mylist[j + d] = mylist[j]
j = j - d
while j >= 0 and mylist[j] > ......
#快速排序
def Partition(mylist, low, high):
tmp = mylist[low]
while low < high:
while low < high and mylist[high] >= tmp:
high = high - 1
if low < high:
mylist[low] = mylist[high]
low = low + 1
while low < hi ......
#堆排序
def Heapify(mylist, start, end):
left = 0
right = 0
maxv = 0
left = start * 2
right = start * 2 + 1
while left <= end:
maxv = left
if right <= end:
if mylist[left] < mylist[right]:
maxv = right
......
