
和为 K 的子数组
题目解析
算法讲解

编写代码
class Solution {
public int subarraySum(int[] nums, int k) {
Map<Integer, Integer> hash = new HashMap<>();
hash.put(0, 1);
int sum = 0, count = 0;
for (int i = 0; i < nums.length; i++) {
sum += nums[i];
count += hash.getOrDefault(sum - k, 0);
hash.put(sum, hash.getOrDefault(sum, 0) + 1);
}
return count;
}
}
和可被 K 整除的子数组
题目解析
算法讲解

编写代码
class Solution {
public int subarraysDivByK(int[] nums, int k) {
Map<Integer, Integer> hash = new HashMap<>();
hash.put(0, 1);
int sum = 0, count = 0;
for (int x: nums) {
sum += x;
int mod = (sum % k + k) % k;
count += hash.getOrDefault(mod, 0);
hash.put(mod, hash.getOrDefault(mod, 0) + 1);
}
return count;
}
}
连续数组
题目解析
算法讲解

编写代码
class Solution {
public int findMaxLength(int[] nums) {
Map<Integer, Integer> hash = new HashMap<>();
hash.put(0, -1);
int sum = 0, len = 0;
for (int i = 0; i < nums.length; i++) {
sum += nums[i] == 0 ? -1 : 1;
if (hash.containsKey(sum)) len = Math.max(len, i - hash.get(sum));
else hash.put(sum, i);
}
return len;
}
}
矩阵区域和
题目解析
算法讲解
编写代码
class Solution {
public int[][] matrixBlockSum(int[][] mat, int k) {
int m = mat.length + 1, n = mat[0].length + 1;
int[][] dp = new int[m][n];
for (int i = 1; i < m; i++) {
for (int j = 1; j < n; j++) {
dp[i][j] = dp[i - 1][j] + dp[i][j-1] + mat[i - 1][j - 1] - dp[i-1][j-1];
}
}
int[][] answer = new int[m - 1][n - 1];
for (int i = 0; i < m - 1; i++) {
for (int j = 0; j < n - 1; j++) {
int x1 = Math.max(i - k, 0), x2 = Math.min(i + k, m - 2);
int y1 = Math.max(j - k, 0), y2 = Math.min(j + k, n - 2);
answer[i][j] = dp[x2 + 1][y2 + 1] - dp[x1][y2 + 1] - dp[x2 + 1][y1] + dp[x1][y1];
}
}
return answer;
}
}
