4. Median of Two Sorted Arrays leetcode python New season for 2016
2015-12-30 11:26
597 查看
There are two sorted arrays nums1 and nums2 of
size m and n respectively. Find the median of the two sorted arrays. The overall run time complexity should be O(log (m+n)).
the main idea is if nums1_mid < nums2_mid nums1 = nums1_right_part nums2 = nums2_left_part
we need constant space and O(log(m+n)) time
class Solution(object):
def findMedianSortedArrays(self, nums1, nums2):
"""
:type nums1: List[int]
:type nums2: List[int]
:rtype: float
"""
nums1_length = len(nums1)
nums2_length = len(nums2)
left = (nums1_length + nums2_length + 1) / 2
right = (nums1_length + nums2_length + 2) / 2
return (self.getKth(nums1, 0, nums2, 0, left) + self.getKth(nums1, 0, nums2, 0, right)) / 2.0
#if nums1 mid < nums2 mid keep nums1 right + nums2 left
def getKth(self, nums1, nums1_start, nums2, nums2_start, k):
if nums1_start > len(nums1) - 1:
return nums2[nums2_start + k - 1]
if nums2_start > len(nums2) - 1:
return nums1[nums1_start + k - 1]
if k == 1:
return min(nums1[nums1_start], nums2[nums2_start])
nums1_mid, nums2_mid = 1 << 31, 1 << 31
if nums1_start + k / 2 - 1 < len(nums1):
nums1_mid = nums1[nums1_start + k / 2 - 1]
if nums2_start + k / 2 - 1 < len(nums2):
nums2_mid = nums2[nums2_start + k / 2 - 1]
if nums1_mid < nums2_mid:
return self.getKth(nums1, nums1_start + k / 2, nums2, nums2_start, k - k / 2)
else:
return self.getKth(nums1, nums1_start, nums2, nums2_start + k / 2, k - k / 2)
size m and n respectively. Find the median of the two sorted arrays. The overall run time complexity should be O(log (m+n)).
the main idea is if nums1_mid < nums2_mid nums1 = nums1_right_part nums2 = nums2_left_part
we need constant space and O(log(m+n)) time
class Solution(object):
def findMedianSortedArrays(self, nums1, nums2):
"""
:type nums1: List[int]
:type nums2: List[int]
:rtype: float
"""
nums1_length = len(nums1)
nums2_length = len(nums2)
left = (nums1_length + nums2_length + 1) / 2
right = (nums1_length + nums2_length + 2) / 2
return (self.getKth(nums1, 0, nums2, 0, left) + self.getKth(nums1, 0, nums2, 0, right)) / 2.0
#if nums1 mid < nums2 mid keep nums1 right + nums2 left
def getKth(self, nums1, nums1_start, nums2, nums2_start, k):
if nums1_start > len(nums1) - 1:
return nums2[nums2_start + k - 1]
if nums2_start > len(nums2) - 1:
return nums1[nums1_start + k - 1]
if k == 1:
return min(nums1[nums1_start], nums2[nums2_start])
nums1_mid, nums2_mid = 1 << 31, 1 << 31
if nums1_start + k / 2 - 1 < len(nums1):
nums1_mid = nums1[nums1_start + k / 2 - 1]
if nums2_start + k / 2 - 1 < len(nums2):
nums2_mid = nums2[nums2_start + k / 2 - 1]
if nums1_mid < nums2_mid:
return self.getKth(nums1, nums1_start + k / 2, nums2, nums2_start, k - k / 2)
else:
return self.getKth(nums1, nums1_start, nums2, nums2_start + k / 2, k - k / 2)
相关文章推荐
- 【python】多个文件共用日志系统的重复打印问题
- C#中通过Process运行Python脚本
- leetcode之Binary Tree Paths
- Python 1.5 循环
- leetcode之Sum Root to Leaf Numbers
- 修改ubuntu的默认python版本
- supervisor运行python程序时的环境配置
- python之commands模块
- leetcode之Path Sum
- Python-Windows下安装BeautifulSoup和requests第三方模块
- Python 1.4 条件判断
- BeautifulSoup使用
- 笨方法学Python(6-10)
- python UserBasedCF
- python Item_CF
- python3使用了更多内存优化的技巧,比如,python3的zip就是生成可迭代的对象
- Python Network Programming(7)---泊松分布与发包
- Python 字符串编码中中文字符注意事项
- Python标准库08 多线程与同步 (threading包)
- Python For MySQL 使用连接器连接 ( 一)