def test_randomized_quicksort(self):
for i in range(100):
A = [random.randint(1, 10000) for i in range(100)]
B = A[:]
randomized_quicksort(A, 0, len(A) - 1)
B.sort()
self.assertEqual(A, B)
def test_randomized_quicksort(self):
for i in range(0, 100):
A = [random.randint(1, 10000) for i in range(0, 100)]
B = A[:]
randomized_quicksort(A, 0, len(A) - 1)
B.sort()
self.assertEquals(A, B)
def note(self):
'''
Summary
====
Print chapter7.3 note
Example
====
>>> Chapter7_3().note()
'''
print('chapter7.3 note as follow')
print('7.3 快速排序的随机化版本')
print('在探讨快速排序的平均性态过程中，假定输入数据的所有排列都是等可能的')
print('但在工程中，这个假设就不会总是成立')
print('虽然第五章介绍过一些随机算法，但是如果采用一种不同的，称为随机取样的随机化技术的话，可以使分析更加简单')
print('在这种方法中，不是时钟采用A[r]作为主元，而是从子数组A[p..r]中随机选择一个元素')
print('然后将这个随机元素与A[r]交换作为主元')
print('因为主元元素是随机选择的，在期望的平均情况下，对输入数组的划分比较对称')
A = [8, 7, 6, 5, 4, 3, 2, 1]
print('数组[8, 7, 6, 5, 4, 3, 2, 1]的随机化快速排序：',
quicksort.randomized_quicksort(A))
print(
'练习7.3-1:大部分时候输入的待排序序列我们是不知道的，而对于快速排序来讲，一个平均的输入才能反映其算法性能，最坏情况出现的概率比较小'
)
print('练习7.3-2:最佳情况调用Θ(n)次，最坏情况调用Θ(n^2)次')
def median_of_two_arrays(X, x_start, x_end, Y, y_start, y_end, size):
print X[x_start:x_end + 1], '\t', Y[y_start:y_end + 1], '\t', size
if size == 1:
return min(X[x_start], Y[y_start])
xc = X[x_start + int(math.floor(size / 2)) - 1]
yc = Y[y_start + int(math.ceil(size / 2)) - 1]
print xc, yc
if xc == yc:
return xc
elif xc < yc:
return median_of_two_arrays(X, x_start + int(math.floor(size / 2)), x_end, Y, y_start, y_end, math.ceil(size / 2))
else:
return median_of_two_arrays(X, x_start, x_end, Y, y_start + int(math.ceil(size / 2)), y_end, math.floor(size / 2))
A = [random.randint(1, 100) for i in range(0, 15)]
print A
randomized_quicksort(A, 0, 14)
print A
B = [random.randint(1, 100) for i in range(0, 15)]
print B
randomized_quicksort(B, 0, 14)
print B
print median_of_two_arrays(A, 0, 14, B, 0, 14, 3.0)
#randomized_select(A, 0, 14, 7)
#print A
#for i in range(1, 16):
# randomized_select(A, 0, 14, i)
# print i, '\t', A
# print randomized_select(A, 0, 14, i)
def test_randomized_quicksort(self):
a = [3, 2, 4, 1, 5, 6]
qs.randomized_quicksort(a, 0, len(a) - 1)
b = [1, 2, 3, 4, 5, 6]
self.assertEqual(a, b)
xc = X[x_start + int(math.floor(size / 2)) - 1]
yc = Y[y_start + int(math.ceil(size / 2)) - 1]
print xc, yc
if xc == yc:
return xc
elif xc < yc:
return median_of_two_arrays(X, x_start + int(math.floor(size / 2)),
x_end, Y, y_start, y_end,
math.ceil(size / 2))
else:
return median_of_two_arrays(X, x_start, x_end, Y,
y_start + int(math.ceil(size / 2)), y_end,
math.floor(size / 2))
A = [random.randint(1, 100) for i in range(0, 15)]
print A
randomized_quicksort(A, 0, 14)
print A
B = [random.randint(1, 100) for i in range(0, 15)]
print B
randomized_quicksort(B, 0, 14)
print B
print median_of_two_arrays(A, 0, 14, B, 0, 14, 3.0)
#randomized_select(A, 0, 14, 7)
#print A
#for i in range(1, 16):
# randomized_select(A, 0, 14, i)
# print i, '\t', A
# print randomized_select(A, 0, 14, i)
