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[LeetCode] [DP] 53. Maximum SubarrayAlgorithm/LeetCode 2021. 10. 5. 08:56
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
class Solution: def maxSubArray(self, nums: List[int]) -> int: max = -10000 result_max = -10000 if len(nums)==1: return nums[0] for k in range(len(nums)): for i in range(len(nums) - k): window = nums[i:i + k +1] sumw = sum(window) if sumw > max: max = sumw if max > result_max: result_max = max return result_max # Brutal Force 로 첫 번째 시도. 역시나 Time Limit Exceed
# Credit to @Google class Solution: # @param A, a list of integers # @return an integer # 6:57 def maxSubArray(self, A): if not A: return 0 curSum = maxSum = A[0] for num in A[1:]: curSum = max(num, curSum + num) # 누적합의 negative 가 커서, 다음 수가 starting 이 되는게 나은지 판단. # fx = g(fx) 형태의 recursive maxSum = max(maxSum, curSum) return maxSum
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