Given a 2D immutable array, Write an efficient program to support any given sub-rectangle sum query in this 2D matrix.
A simple solution is to add each entry inside the sub-rectangle. The runtime is O(n * m).
The problem of this solution is that for a given 2D matrix, we always start from scratch to compute the sum of a sub-rectangle.
Dynamic programming should be used to optimize the runtime.
State: T[i][j]: the sum of sub rectangle with top left corner (0, 0) and bottom right corner (i - 1, j - 1).
Function: T[i][j] = T[i - 1][j] + T[i][j - 1] + matrix[i - 1][j - 1] - T[i - 1][j - 1].
Initialization: T[0][j] = T[i][0] = 0;
Answer: given top left corner(x1, y1) and bottom right corner(x2, y2),
Sum of sub rectangle(x1, y1, x2, y2) is T[x2 + 1][y2 + 1] - T[x1][y2 + 1] - T[x2 + 1][y1] + T[x1][y1].
1 public class SumQuery {
2 private int[][] T;
3 public SumQuery(int[][] matrix) {
4 if(matrix == null || matrix.length == 0 || matrix[0].length == 0) {
5 T = null;
6 }
7 T = new int[matrix.length + 1][matrix[0].length + 1];
8 for(int i = 0; i < T.length; i++) {
9 T[i][0] = 0;
10 }
11 for(int j = 0; j < T[0].length; j++) {
12 T[0][j] = 0;
13 }
14 for(int i = 1; i < T.length; i++) {
15 for(int j = 1; j < T[0].length; j++) {
16 T[i][j] = T[i - 1][j] + T[i][j - 1] + matrix[i - 1][j - 1] - T[i - 1][j - 1];
17 }
18 }
19 }
20 public int querySubRectangleSum(int x1, int y1, int x2, int y2) {
21 x1++; y1++; x2++; y2++;
22 return T[x2][y2] - T[x1 - 1][y2] - T[x2][y1 - 1] + T[x1 - 1][y1 - 1];
23 }
24 }