Given an array of integers and an integer k, you need to find the total number of continuous subarrays whose sum equals to k.
Example 1:
Input:nums = [1,1,1], k = 2 Output: 2
Note:
- The length of the array is in range [1, 20,000].
- The range of numbers in the array is [-1000, 1000] and the range of the integer k is [-1e7, 1e7].
这道题给了我们一个数组,让我们求和为k的连续子数组的个数,博主最开始看到这道题想着肯定要建立累加和数组啊,然后遍历累加和数组的每个数字,首先看其是否为k,是的话结果res自增1,然后再加个往前的循环,这样可以快速求出所有的子数组之和,看是否为k,参见代码如下:
解法一:
class Solution { public: int subarraySum(vector<int>& nums, int k) { int res = 0, n = nums.size(); vector<int> sums = nums; for (int i = 1; i < n; ++i) { sums[i] = sums[i - 1] + nums[i]; } for (int i = 0; i < n; ++i) { if (sums[i] == k) ++res; for (int j = i - 1; j >= 0; --j) { if (sums[i] - sums[j] == k) ++res; } } return res; } };
上面的求累加和的方法其实并没有提高程序的执行效率,跟下面这种暴力搜索的解法并没有什么不同,博主很惊奇OJ居然这么大度,让这种解法也能通过,参见代码如下:
解法二:
class Solution { public: int subarraySum(vector<int>& nums, int k) { int res = 0, n = nums.size(); for (int i = 0; i < n; ++i) { int sum = nums[i]; if (sum == k) ++res; for (int j = i + 1; j < n; ++j) { sum += nums[j]; if (sum == k) ++res; } } return res; } };
论坛上大家比较推崇的其实是这种解法,用一个哈希表来建立连续子数组之和跟其出现次数之间的映射,初始化要加入{0,1}这对映射,这是为啥呢,因为我们的解题思路是遍历数组中的数字,用sum来记录到当前位置的累加和,我们建立哈希表的目的是为了让我们可以快速的查找sum-k是否存在,即是否有连续子数组的和为sum-k,如果存在的话,那么和为k的子数组一定也存在,这样当sum刚好为k的时候,那么数组从起始到当前位置的这段子数组的和就是k,满足题意,如果哈希表中事先没有m[0]项的话,这个符合题意的结果就无法累加到结果res中,这就是初始化的用途。上面讲解的内容顺带着也把for循环中的内容解释了,这里就不多阐述了,有疑问的童鞋请在评论区留言哈,参见代码如下:
解法三:
class Solution { public: int subarraySum(vector<int>& nums, int k) { int res = 0, sum = 0, n = nums.size(); unordered_map<int, int> m{{0, 1}}; for (int i = 0; i < n; ++i) { sum += nums[i]; res += m[sum - k]; ++m[sum]; } return res; } };
类似题目:
参考资料:
https://leetcode.com/problems/subarray-sum-equals-k/
https://leetcode.com/problems/subarray-sum-equals-k/discuss/102153/Basic-Java-solution
https://leetcode.com/problems/subarray-sum-equals-k/discuss/134689/Three-Approaches-With-Explanation
https://leetcode.com/problems/subarray-sum-equals-k/discuss/102106/Java-Solution-PreSum-%2B-HashMap