我在 Brad Miller 和 David Ranum 所著的“用算法和数据结构解决问题”中偶然发现了快速排序算法 ( http://interactivepython.org/runestone/static/pythonds/SortSearch/sorting.html#the-quick-sort )。
此处提供的快速排序算法将列表中的第一个值作为主值。练习是修改程序以选择枢轴值作为三的中位数。这是原始脚本:
def quickSort(alist):
quickSortHelper(alist,0,len(alist)-1)
def quickSortHelper(alist,first,last):
if first<last:
splitpoint = partition(alist,first,last)
quickSortHelper(alist,first,splitpoint-1)
quickSortHelper(alist,splitpoint+1,last)
def partition(alist,first,last):
pivotvalue = alist[first]
leftmark = first+1
rightmark = last
done = False
while not done:
while leftmark <= rightmark and \
alist[leftmark] <= pivotvalue:
leftmark = leftmark + 1
while alist[rightmark] >= pivotvalue and \
rightmark >= leftmark:
rightmark = rightmark -1
if rightmark < leftmark:
done = True
else:
temp = alist[leftmark]
alist[leftmark] = alist[rightmark]
alist[rightmark] = temp
temp = alist[first]
alist[first] = alist[rightmark]
alist[rightmark] = temp
return rightmark
我对其进行了一些修改,首先添加了 median()
函数:
def median(data):
sd = sorted(data)
N = len(data) - 1
a = sd[N // 2]
b = sd[(N + 1) // 2]
return (a+b) // 2
然后,在partition()
函数中,将pivotvalue
修改为:
pivotvalue = median([alist[0]] + [alist[len(alist)-1]] + [alist[len(alist)//2]])
并将 leftmark
更改为以索引 0
开头,而不是 1
:
leftmark = first
而不是:
leftmark = first+1
然后更改了最终done == True
时执行的步骤,以正确交换rightmark
和pivot
值:
temp = pivotvalue
alist[alist.index(pivotvalue)] = alist[rightmark]
alist[rightmark] = temp
但是当调用时:
alist = [77,26,93,17,54,31,44,55,20]
quickSort(alist)
print(alist)
我得到:
Traceback (most recent call last):
File "/home/reloader/Templates/Exercises/quick_sort.py", line 52, in <module>
quickSort(alist)
File "/home/reloader/Templates/Exercises/quick_sort.py", line 9, in quickSort
quickSortHelper(alist,0,len(alist)-1)
File "/home/reloader/Templates/Exercises/quick_sort.py", line 17, in quickSortHelper
quickSortHelper(alist,splitpoint+1,last)
File "/home/reloader/Templates/Exercises/quick_sort.py", line 17, in quickSortHelper
quickSortHelper(alist,splitpoint+1,last)
File "/home/reloader/Templates/Exercises/quick_sort.py", line 17, in quickSortHelper
quickSortHelper(alist,splitpoint+1,last)
File "/home/reloader/Templates/Exercises/quick_sort.py", line 17, in quickSortHelper
quickSortHelper(alist,splitpoint+1,last)
File "/home/reloader/Templates/Exercises/quick_sort.py", line 17, in quickSortHelper
quickSortHelper(alist,splitpoint+1,last)
File "/home/reloader/Templates/Exercises/quick_sort.py", line 17, in quickSortHelper
.......
RuntimeError: maximum recursion depth exceeded in comparison
由于我发现这个算法有点复杂(并且执行的步骤有点太多),我真的不知道要更改什么才能使其正常工作,而且我所做的破坏了我的修改。我只是将枢轴值设置为列表中间的值。其他我目前看不到的东西是否也应该修改?
谢谢。
编辑:
如果我将 leftmark
的初始值保留为 firstmark + 1
(即列表的索引 1),我不会收到无限递归错误,但列表也未正确排序:
[55, 26, 31, 44, 17, 77, 54, 20, 93]
最佳答案
您必须从正在分区的子数组中选择中位数:
替换这个:
pivotvalue = alist[first]
与
pivotindex = median(alist, first, last, (first + last) // 2)
alist[first], alist[pivotindex] = alist[pivotindex], alist[first]
pivotvalue = alist[first]
中值查找器不必如此复杂。
def median(a, i, j, k):
if a[i] < a[j]:
return i if a[k] < a[i] else k if a[k] < a[j] else j
else:
return j if a[k] < a[j] else k if a[k] < a[i] else i
关于python - 实现中位数为三的快速排序,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/24533359/