我应该为四元搜索算法编写代码。我得到的唯一描述是它是对二进制搜索算法的修改,但不是将数组拆分为两个,而是将数组拆分为四个。
我对这样的搜索究竟是如何工作有点困惑。我搜索了一些伪代码,甚至只是一个YouTube视频,解释/可视化搜索的工作原理,但我还没有找到任何东西。
是否有人对此搜索算法的工作方式有伪代码或快速而肮脏的解释?
谢谢!
答案 0 :(得分:2)
array (size=5)
'car1' => boolean true
'car2' => boolean false
'car3' => boolean false
'car4' => boolean true
'car5' => boolean true
答案 1 :(得分:2)
def Ping(url):
r = requests.get(url) #http://192.168.1.10
if r.status_code == 200:
return True
return False
答案 2 :(得分:0)
此算法是Divide and Conquer
算法 ie 的示例,主要问题分为smaller
,independent
和similar
子问题。这些类型的问题通常通过递归来解决。
如果$ \ Theta(\ log_2 n)$,则四元搜索的时间复杂度与二元搜索的复杂度相同(存在较小的差异,渐近无关紧要)。
这是一个Python实现:
''' quaternary search STUDY
0 1 2 3 4 5 ... n-4 n-3 n-2 n-1
L B1 B2 B3 R
- size of array to be split in 4 in each recursion ==> S_4 = R - L + 1
- size of each split ==> N_4 = S_4 >> 2
- last split will eventually be larger than N_4 due to the remainder of the division by 4
- length of FIRST subarray = N_4
- length of SECOND subarray = N_4
- length of THIRD subarray = N_4
- length of FOURTH subarray = N_4 + S_4 mod 4
- position of breakpoint 1 => B1 = L + N_4
- position of breakpoint 2 => B2 = L + 2*N_4
- position of breakpoint 3 => B2 = L + 3*N_4
'''
def qsearch(A, L, R, key): # i.e. qsearch(A,0,len(A)-1,key)
'''
Quaternary search (divide & conquer)
INPUTS:
A = sorted array
L = index of leftmost element
R = index of rightmost element
key = value to be found
OUTPUT:
zero-indexed position of <key> or <-1> if <key> is not in tha input array
'''
if L <= R:
N_4 = (R-L+1) >> 2
#print(N_4, L, R)
if A[L+N_4] == key:
return L+N_4
elif key < A[L+N_4]:
return qsearch(A, L, L+N_4-1, key)
elif A[L+2*N_4] == key:
return L+2*N_4
elif key < A[L+2*N_4]:
return qsearch(A, L+N_4+1, L+2*N_4-1, key)
elif A[L+3*N_4] == key:
return L+3*N_4
elif key < A[L+3*N_4]:
return qsearch(A, L+2*N_4+1, L+3*N_4-1, key)
else:
return qsearch(A, L+3*N_4+1, R, key)
else:
return -1