[leetcode-523-Continuous Subarray Sum]
Given a list of non-negative numbers and a target integer k, write a function to check if the array has a continuous subarray of size at least 2 that sums up to the multiple of k, that is, sums up to n*k where n is also an integer.
Example 1:
Input: [23, 2, 4, 6, 7], k=6 Output: True Explanation: Because [2, 4] is a continuous subarray of size 2 and sums up to 6.
Example 2:
Input: [23, 2, 6, 4, 7], k=6 Output: True Explanation: Because [23, 2, 6, 4, 7] is an continuous subarray of size 5 and sums up to 42.
Note:
- The length of the array won't exceed 10,000.
- You may assume the sum of all the numbers is in the range of a signed 32-bit integer.
思路:
首先想到用动态规划,使用dp[i][j]记录nums中i到j的和,然后随时判断是否满足余数为0.
注意处理k==0时候的情况。
但是直接用二维数组记录的话,提示内存不足,耗费空间。
更新公式为 dp[i][j] = dp[i][j-1]+nums[j] ,可以看出dp[i][j]只与上一个dp[i][j-1]有关,
于是用两个变量替代即可。得到如下代码,时间复杂度为O(n2).
bool checkSubarraySum(vector<int>& nums, int k) { int len = nums.size(); // vector<vector<int>> dp(len, vector<int>(len, 0)); long long cur = 0, pre = 0; for (int i = 0; i < len;i++) { for (int j = i; j < len;j++) { if (j == i)cur = nums[i]; else { cur = pre + nums[j]; if (k != 0 && cur % k == 0)return true; else if (k == 0 && cur == 0) return true; } pre = cur; } } return false; }
后来参考网上大牛的代码,学习到了他们的解法。
比如他们用一个set去存储i之前元素和的余数,如果往后遍历到j元素和的余数之前出现过,说明i到j的和为k的整数倍。
这样时间复杂度为O(n).
class Solution { public: bool checkSubarraySum(vector<int>& nums, int k) { int n = nums.size(), sum = 0, pre = 0; unordered_set<int> modk; for (int i = 0; i < n; ++i) { sum += nums[i]; int mod = k == 0 ? sum : sum % k; if (modk.count(mod)) return true; modk.insert(pre); pre = mod; } return false; } };
参考:
https://discuss.leetcode.com/topic/80892/concise-c-solution-use-set-instead-of-map