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53. Maximum Subarray
Description
Given an integer array nums, find the subarray with the largest sum, and return its sum.
Example 1:
Input: nums = [-2,1,-3,4,-1,2,1,-5,4] Output: 6 Explanation: The subarray [4,-1,2,1] has the largest sum 6.
Example 2:
Input: nums = [1] Output: 1 Explanation: The subarray [1] has the largest sum 1.
Example 3:
Input: nums = [5,4,-1,7,8] Output: 23 Explanation: The subarray [5,4,-1,7,8] has the largest sum 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.
Solutions
Solution 1: Dynamic Programming
We define $f[i]$ to represent the maximum sum of the continuous subarray ending with the element $nums[i]$. Initially, $f[0] = nums[0]$. The final answer we are looking for is $\max_{0 \leq i < n} f[i]$.
Consider $f[i]$, where $i \geq 1$, its state transition equation is:
\[f[i] = \max \{ f[i - 1] + nums[i], nums[i] \}\]Which is also:
\[f[i] = \max \{ f[i - 1], 0 \} + nums[i]\]Since $f[i]$ is only related to $f[i - 1]$, we can use a single variable $f$ to maintain the current value of $f[i]$, and then perform state transition. The answer is $\max_{0 \leq i < n} f$.
The time complexity is $O(n)$, where $n$ is the length of the array $nums$. We only need to traverse the array once to get the answer. The space complexity is $O(1)$, we only need constant space to store several variables.
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class Solution { public int maxSubArray(int[] nums) { int ans = nums[0]; for (int i = 1, f = nums[0]; i < nums.length; ++i) { f = Math.max(f, 0) + nums[i]; ans = Math.max(ans, f); } return ans; } } -
class Solution { public: int maxSubArray(vector<int>& nums) { int ans = nums[0], f = nums[0]; for (int i = 1; i < nums.size(); ++i) { f = max(f, 0) + nums[i]; ans = max(ans, f); } return ans; } }; -
class Solution: def maxSubArray(self, nums: List[int]) -> int: res = cur_sum = nums[0] for num in nums[1:]: cur_sum = num + max(cur_sum, 0) res = max(res, cur_sum) return res -
func maxSubArray(nums []int) int { ans, f := nums[0], nums[0] for _, x := range nums[1:] { f = max(f, 0) + x ans = max(ans, f) } return ans } -
function maxSubArray(nums: number[]): number { let [ans, f] = [nums[0], nums[0]]; for (let i = 1; i < nums.length; ++i) { f = Math.max(f, 0) + nums[i]; ans = Math.max(ans, f); } return ans; } -
/** * @param {number[]} nums * @return {number} */ var maxSubArray = function (nums) { let [ans, f] = [nums[0], nums[0]]; for (let i = 1; i < nums.length; ++i) { f = Math.max(f, 0) + nums[i]; ans = Math.max(ans, f); } return ans; }; -
public class Solution { public int MaxSubArray(int[] nums) { int ans = nums[0], f = nums[0]; for (int i = 1; i < nums.Length; ++i) { f = Math.Max(f, 0) + nums[i]; ans = Math.Max(ans, f); } return ans; } } -
impl Solution { pub fn max_sub_array(nums: Vec<i32>) -> i32 { let n = nums.len(); let mut ans = nums[0]; let mut f = nums[0]; for i in 1..n { f = f.max(0) + nums[i]; ans = ans.max(f); } ans } } -
class Solution { public int maxSubArray(int[] nums) { return maxSub(nums, 0, nums.length - 1); } private int maxSub(int[] nums, int left, int right) { if (left == right) { return nums[left]; } int mid = (left + right) >>> 1; int lsum = maxSub(nums, left, mid); int rsum = maxSub(nums, mid + 1, right); return Math.max(Math.max(lsum, rsum), crossMaxSub(nums, left, mid, right)); } private int crossMaxSub(int[] nums, int left, int mid, int right) { int lsum = 0, rsum = 0; int lmx = Integer.MIN_VALUE, rmx = Integer.MIN_VALUE; for (int i = mid; i >= left; --i) { lsum += nums[i]; lmx = Math.max(lmx, lsum); } for (int i = mid + 1; i <= right; ++i) { rsum += nums[i]; rmx = Math.max(rmx, rsum); } return lmx + rmx; } } -
class Solution: def maxSubArray(self, nums: List[int]) -> int: def crossMaxSub(nums, left, mid, right): lsum = rsum = 0 lmx = rmx = -inf for i in range(mid, left - 1, -1): lsum += nums[i] lmx = max(lmx, lsum) for i in range(mid + 1, right + 1): rsum += nums[i] rmx = max(rmx, rsum) return lmx + rmx def maxSub(nums, left, right): if left == right: return nums[left] mid = (left + right) >> 1 lsum = maxSub(nums, left, mid) rsum = maxSub(nums, mid + 1, right) csum = crossMaxSub(nums, left, mid, right) return max(lsum, rsum, csum) left, right = 0, len(nums) - 1 return maxSub(nums, left, right)