E - Evaluate Matrix Sum

Description

Given a matrix, the elements of which are all integer number from 0 to 50, you are required to evaluate the square sum of its specified sub-matrix.

Input

The first line of the input contains a single integer T (1 <= T <= 5), the number of test cases.

For each test case, the first line contains two integers m and n (1
<= m, n <= 500), which are the row and column sizes of the matrix,
respectively. The next m lines with n numbers each gives the elements
of the matrix.

The next line contains a single integer N (1
<= N <= 100,000), the number of queries. The next N lines give one
query on each line, with four integers r1, c1, r2, c2 (1 <= r1 <=
r2 <= m, 1 <= c1 <= c2 <= n), which are the indices of the
upper-left corner and lower-right corner of the sub-matrix in question.

Output

For each test case, first print the number of the test case, then N
lines with one number on each line, the required square sum. Refer to
the sample output for details.

Sample Input

2
2 3
1 2 3
4 5 6
2
1 1 2 2
1 3 2 3
3 3
4 2 3
2 5 1
7 9 2
1
1 1 3 3

Sample Output

Case 1:
46
45
Case 2:
193
题意：给一个n*m矩阵  下表（1,1)~~~(n,m)给两个点做对角线   求中间矩阵的值朴素算法也可以过   但是这个在不断输入的同时也将值存在数组中   查询更快

 #include <iostream>
 #include <string.h>
 #include <stdio.h>

 using namespace std;
 int map[505][505];

 int main()
 {
     int t;
     int n,m;
     int k;
     int tt,x1,x2,y1,y2;
     int num;
     scanf("%d",&t);
     for(num=1;num<=t;num++)
     {
         scanf("%d%d",&n,&m);
         memset(map,0,sizeof(map));
         for(int i=1;i<=n;i++)
         {
             for(int j=1;j<=m;j++)
             {
                 scanf("%d",&k);
                 map[i][j]=k*k+map[i-1][j]+map[i][j-1]-map[i-1][j-1];
             }
         }
         printf("Case %d:\n",num);
         scanf("%d",&tt);
         while(tt--)
         {
             scanf("%d%d%d%d",&x1,&y1,&x2,&y2);
             int ans=map[x1-1][y1-1]+map[x2][y2]-map[x1-1][y2]-map[x2][y1-1];
             printf("%d\n",ans);

         }
     }
     return 0;
 }

E - Evaluate Matrix Sum