给定一个二维矩阵 matrix
,以下类型的多个请求:
- 计算其子矩形范围内元素的总和,该子矩阵的左上角为
(row1, col1)
,右下角为(row2, col2)
。
实现 NumMatrix
类:
NumMatrix(int[][] matrix)
给定整数矩阵matrix
进行初始化int sumRegion(int row1, int col1, int row2, int col2)
返回左上角(row1, col1)
、右下角(row2, col2)
的子矩阵的元素总和。
示例 1:
输入: ["NumMatrix","sumRegion","sumRegion","sumRegion"] [[[[3,0,1,4,2],[5,6,3,2,1],[1,2,0,1,5],[4,1,0,1,7],[1,0,3,0,5]]],[2,1,4,3],[1,1,2,2],[1,2,2,4]] 输出: [null, 8, 11, 12] 解释: NumMatrix numMatrix = new NumMatrix([[3,0,1,4,2],[5,6,3,2,1],[1,2,0,1,5],[4,1,0,1,7],[1,0,3,0,5]]]); numMatrix.sumRegion(2, 1, 4, 3); // return 8 (红色矩形框的元素总和) numMatrix.sumRegion(1, 1, 2, 2); // return 11 (绿色矩形框的元素总和) numMatrix.sumRegion(1, 2, 2, 4); // return 12 (蓝色矩形框的元素总和)
提示:
m == matrix.length
n == matrix[i].length
1 <= m, n <= 200
-105 <= matrix[i][j] <= 105
0 <= row1 <= row2 < m
0 <= col1 <= col2 < n
- 最多调用
104
次sumRegion
方法
注意:本题与主站 304 题相同: https://leetcode.cn/problems/range-sum-query-2d-immutable/
动态规划-二维前缀和。
class NumMatrix:
def __init__(self, matrix: List[List[int]]):
m, n = len(matrix), len(matrix[0])
self.pre = [[0] * (n + 1) for _ in range(m + 1)]
for i in range(1, m + 1):
for j in range(1, n + 1):
self.pre[i][j] = (
self.pre[i - 1][j]
+ self.pre[i][j - 1]
- self.pre[i - 1][j - 1]
+ matrix[i - 1][j - 1]
)
def sumRegion(self, row1: int, col1: int, row2: int, col2: int) -> int:
return (
self.pre[row2 + 1][col2 + 1]
- self.pre[row2 + 1][col1]
- self.pre[row1][col2 + 1]
+ self.pre[row1][col1]
)
# Your NumMatrix object will be instantiated and called as such:
# obj = NumMatrix(matrix)
# param_1 = obj.sumRegion(row1,col1,row2,col2)
class NumMatrix {
private int[][] pre;
public NumMatrix(int[][] matrix) {
int m = matrix.length, n = matrix[0].length;
pre = new int[m + 1][n + 1];
for (int i = 1; i <= m; ++i) {
for (int j = 1; j <= n; ++j) {
pre[i][j]
= pre[i - 1][j] + pre[i][j - 1] - pre[i - 1][j - 1] + matrix[i - 1][j - 1];
}
}
}
public int sumRegion(int row1, int col1, int row2, int col2) {
return pre[row2 + 1][col2 + 1] - pre[row2 + 1][col1] - pre[row1][col2 + 1]
+ pre[row1][col1];
}
}
/**
* Your NumMatrix object will be instantiated and called as such:
* NumMatrix obj = new NumMatrix(matrix);
* int param_1 = obj.sumRegion(row1,col1,row2,col2);
*/
class NumMatrix {
public:
vector<vector<int>> pre;
NumMatrix(vector<vector<int>>& matrix) {
int m = matrix.size(), n = matrix[0].size();
pre.resize(m + 1, vector<int>(n + 1));
for (int i = 1; i <= m; ++i) {
for (int j = 1; j <= n; ++j) {
pre[i][j] = pre[i - 1][j] + pre[i][j - 1] - pre[i - 1][j - 1] + matrix[i - 1][j - 1];
}
}
}
int sumRegion(int row1, int col1, int row2, int col2) {
return pre[row2 + 1][col2 + 1] - pre[row2 + 1][col1] - pre[row1][col2 + 1] + pre[row1][col1];
}
};
/**
* Your NumMatrix object will be instantiated and called as such:
* NumMatrix* obj = new NumMatrix(matrix);
* int param_1 = obj->sumRegion(row1,col1,row2,col2);
*/
type NumMatrix struct {
pre [][]int
}
func Constructor(matrix [][]int) NumMatrix {
m, n := len(matrix), len(matrix[0])
pre := make([][]int, m+1)
for i := 0; i < m+1; i++ {
pre[i] = make([]int, n+1)
}
for i := 1; i < m+1; i++ {
for j := 1; j < n+1; j++ {
pre[i][j] = pre[i-1][j] + pre[i][j-1] + -pre[i-1][j-1] + matrix[i-1][j-1]
}
}
return NumMatrix{pre}
}
func (this *NumMatrix) SumRegion(row1 int, col1 int, row2 int, col2 int) int {
return this.pre[row2+1][col2+1] - this.pre[row2+1][col1] - this.pre[row1][col2+1] + this.pre[row1][col1]
}
/**
* Your NumMatrix object will be instantiated and called as such:
* obj := Constructor(matrix);
* param_1 := obj.SumRegion(row1,col1,row2,col2);
*/