53.maximum-subarray

Statement

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Metadata

• Link: 最大子数组和
• Difficulty: Easy
• Tag: 数组 分治 动态规划

给你一个整数数组 nums ，请你找出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。

子数组 是数组中的一个连续部分。

 

示例 1：

输入：nums = [-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 。

示例 2：

输入：nums = [1]
输出：1

示例 3：

输入：nums = [5,4,-1,7,8]
输出：23

 

提示：

• 1 <= nums.length <= 105
• -104 <= nums[i] <= 104

 

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。

Metadata

• Link: Maximum Subarray
• Difficulty: Easy
• Tag: Array Divide and Conquer Dynamic Programming

Given an integer array nums, find the contiguous subarray (containing at least one number) which has the largest sum and return its sum.

A subarray is a contiguous part of an array.

 

Example 1:

Input: nums = [-2,1,-3,4,-1,2,1,-5,4]
Output: 6
Explanation: [4,-1,2,1] has the largest sum = 6.

Example 2:

Input: nums = [1]
Output: 1

Example 3:

Input: nums = [5,4,-1,7,8]
Output: 23

 

Constraints:

• 1 <= nums.length <= 105
• -104 <= nums[i] <= 104

 

Follow up: If you have figured out the O(n) solution, try coding another solution using the divide and conquer approach, which is more subtle.

Solution

Python 3

from typing import List


class Solution:
    def maxSubArray(self, nums: List[int]) -> int:
        res = -10000
        cur = 0
        for a in nums:
            cur += a
            res = max(res, cur)
            if cur < 0:
                cur = 0
        return res

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最后更新: October 11, 2023