53. Maximum Subarray 最大子序和
难度: Medium
刷题内容
原题连接
- https://leetcode.com/problems/maximum-subarray
- https://leetcode-cn.com/problems/maximum-subarray
内容描述
给定一个整数数组 nums ,找到一个具有最大和的连续子数组(子数组最少包含一个元素),返回其最大和。
示例:
输入: [-2,1,-3,4,-1,2,1,-5,4],
输出: 6
解释: 连续子数组 [4,-1,2,1] 的和最大,为 6。
进阶:
如果你已经实现复杂度为 O(n) 的解法,尝试使用更为精妙的分治法求解。
解题方案
思路 1
O(N^2)
从i开始,计算i到n,存比较大的sum,会超时
class Solution(object):
def maxSubArray(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
n = len(nums)
m = float('-inf')
for i in range(n):
s = 0
for j in range(i,n):
s = s + nums[j]
m = max(m,s)
return m
思路 2
- 动态规划(只关注:当然值 和 当前值+过去的状态,是变好还是变坏,一定是回看容易理解)
- ms(i) = max(ms[i-1]+ a[i],a[i])
- 到i处的最大值两个可能,一个是加上a[i], 另一个从a[i]起头,重新开始。可以AC
class Solution(object):
def maxSubArray(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
n = len(nums)
maxSum = [nums[0] for i in range(n)]
for i in range(1,n):
maxSum[i] = max(maxSum[i-1] + nums[i], nums[i])
return max(maxSum)
思路 3
Kadane’s Algorithm wikipedia可以查到,然后一般的是负的可以还回0,这里需要稍作修改,参考
http://algorithms.tutorialhorizon.com/kadanes-algorithm-maximum-subarray-problem/
start:
max_so_far = a[0]
max_ending_here = a[0]
loop i= 1 to n
(i) max_end_here = Max(arrA[i], max_end_here+a[i]);
(ii) max_so_far = Max(max_so_far,max_end_here);
return max_so_far
AC代码:
class Solution(object):
def maxSubArray(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
n = len(nums)
maxSum , maxEnd = nums[0], nums[0]
for i in range(1,n):
maxEnd = max(nums[i],maxEnd + nums[i])
maxSum = max(maxEnd,maxSum)
return maxSum
思路 4
参见clrs 第71页,用divide and conquer,有伪码
最大的subarray sum有三个可能,左半段或者右半段,或者跨越左右半段,
速度比较慢,AC代码,复杂度O(NlogN)
class Solution(object):
def maxSubArray(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
def find_max_crossing_subarray(nums, low, mid, high):
left_sum = float('-inf')
sum = 0
for i in xrange(mid,low-1,-1):
sum = sum + nums[i]
if sum > left_sum:
left_sum = sum
right_sum = float('-inf')
sum = 0
for j in range(mid+1,high+1):
sum = sum + nums[j]
if sum > right_sum:
right_sum = sum
return left_sum + right_sum
def find_max_subarray(nums,low,high):
if low == high:
return nums[low]
else:
mid = (low + high) / 2
left_sum = find_max_subarray(nums, low, mid)
right_sum = find_max_subarray(nums,mid+1,high)
cross_sum = find_max_crossing_subarray(nums,low,mid,high)
# print left_sum, right_sum, cross_sum
# print mid, low, high
return max(left_sum, right_sum, cross_sum)
return find_max_subarray(nums, 0, len(nums)-1)