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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其它相关文章!
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