用于迭代快速排序的Python程序
# Python program for implementation of Quicksort
# This function is same in both iterative and recursive
def partition(arr,l,h):
i = ( l - 1 )
x = arr[h]
for j in range(l , h):
if arr[j] <= x:
# increment index of smaller element
i = i+1
arr[i],arr[j] = arr[j],arr[i]
arr[i+1],arr[h] = arr[h],arr[i+1]
return (i+1)
# Function to do Quick sort
# arr[] --> Array to be sorted,
# l --> Starting index,
# h --> Ending index
def quickSortIterative(arr,l,h):
# Create an auxiliary stack
size = h - l + 1
stack = [0] * (size)
# initialize top of stack
top = -1
# push initial values of l and h to stack
top = top + 1
stack[top] = l
top = top + 1
stack[top] = h
# Keep popping from stack while is not empty
while top >= 0:
# Pop h and l
h = stack[top]
top = top - 1
l = stack[top]
top = top - 1
# Set pivot element at its correct position in
# sorted array
p = partition( arr, l, h )
# If there are elements on left side of pivot,
# then push left side to stack
if p-1 > l:
top = top + 1
stack[top] = l
top = top + 1
stack[top] = p - 1
# If there are elements on right side of pivot,
# then push right side to stack
if p+1 < h:
top = top + 1
stack[top] = p + 1
top = top + 1
stack[top] = h
# Driver code to test above
arr = [4, 3, 5, 2, 1, 3, 2, 3]
n = len(arr)
quickSortIterative(arr, 0, n-1)
print ("Sorted array is:")
for i in range(n):
print ("%d" %arr[i]),
# This code is contributed by Mohit Kumra
输出:
Sorted array is:
1 2 2 3 3 3 4 5
上述递归快速排序的优化也可以应用于迭代版本。
1)递归和迭代的分区过程相同。选择最佳枢轴的相同技术也可以应用于迭代版本。
2)为了减少堆栈大小,首先压入较小一半的索引。
3) 当大小减小到实验计算的阈值以下时,使用插入排序。
有关详细信息,请参阅有关迭代快速排序的完整文章!