先来看个用Python实现的二分查找算法实例
import sys
def search2(a,m):
low = 0
high = len(a) - 1
while(low <= high):
mid = (low + high)/2
midval = a[mid]
if midval < m:
low = mid + 1
elif midval > m:
high = mid - 1
else:
print mid
return mid
print -1
return -1
if __name__ == "__main__":
a = [int(i) for i in list(sys.argv[1])]
m = int(sys.argv[2])
search2(a,m)om/weixin.html#_labeldown
运行:
administrator@ubuntu:~/Python$ python test_search2.py 123456789 4
注:
1.'__':由于python的类成员都是公有、公开的被存取public,缺少像正统面向对象语言的私有private属性。
于是就用__来将就一下,模拟私有属性。这些__属性往往是内部使用,通常情况下不用改写。也不用读取。
加上2个下划线的目的,一是不和普通公有属性重名冲突,二是不让对象的使用者(非开发者)随意使用。
2.__name__ == "__main__"表示程序脚本是直接被执行的.
如果不等于表示脚本是被其他程序用import引入的.则其__name__属性被设为模块名
Python采用二分查找找出数字的下标
要考虑有重复数字的情况
class Solution(object):
def searchRange(self, nums, target):
"""
:type nums: List[int]
:type target: int
:rtype: List[int]
def binary_search(start,end,value):
while end>=start:
mid = (start+end)//2
print(mid)
if nums[mid]>target:
end = mid-1
elif nums[mid]<target: start="mid+1" else:="" if="" value="=-1:" mid-1="">=start and nums[mid+value] == target:
end = mid+value
else:
return mid
else:
if mid+1<=end and nums[mid+value] == target:
start = mid+value
return -1
a=binary_search(0,len(nums)-1,-1)
b=binary_search(0,len(nums)-1,1)
return [a,b]
a = Solution()
l = [2,2]
print(a.searchRange(l,2))
</target:>
二分算法的定义不在多说了
import sys
source = [1,2,3,4,5,6,7,8,9,10] #must be in order
des = int(sys.argv[1])
low = 0
high = len(source) - 1
targetIndex = -1
print "des=",des
while low <= high:
middle = (low + high)/2
if des == source[middle]:
targetIndex = middle
break
elif des < source[middle]:
high = middle -1
print "middle element[index=",middle,",value=",source[middle],"] is bigger than des, continue search from[",low,"to",high,"]"
else:
low = middle + 1
print "middle element[index=",middle,",value=",source[middle],"] is smaller than des, continue search from[",low,"to",high,"]"
print "search complete, target element's index in source list is ",targetIndex
最后在分享一个
'fileName--BinarySearch.py'
src = []
def BinarySearch(low, high, target, *src):
'二分查找'
while low <= high:
mid = (low + high) // 2
midVal = src[mid]
if target < midVal:
high = mid - 1
elif target > midVal:
low = mid + 1
else:
return mid
BinarySearch(low, high, target, *src)
print('Please input 10 number:')
for number in range(10):
src.append(int(input('Num %d:' % number)))
sortList = tuple(src)
key = int(input('Please input key:'))
location = BinarySearch(0, len(src) - 1, key, *sortList)
if location != None:
print('Find target at %d' % (location + 1))
else:
print('No target!')
实例补充
#!/usr/bin/python env
# -*- coding:utf-8 -*-
def half_search(array,target):
low = 0
high = len(array) - 1
while low < high:
mid = (low + high)/2
if array[mid] > target:
high = mid - 1
elif array[mid] < target:
low = mid + 1
elif array[mid] == target:
print 'I find it! It is in the position of:',mid
return mid
else:
print "please contact the coder!"
return -1
if __name__ == "__main__":
array = [1, 2, 2, 4, 4, 5]
运行结果如下:
I find it! It is in the position of: 4
4
-1
I find it! It is in the position of: 0
0
-1
以上就是Python如何实现的二分查找算法的详细内容,更多关于用Python实现的二分查找算法的资料请关注python博客其它相关文章!
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