


Consider ARR = [[1 , 2 , 3] , [3 , 4 , 1] , [2 , 1 , 2]] and Queries = [[0 , 0 , 1 , 2]], the submatrix with the left top index (0 , 0) and right bottom index (1 , 2) is
[[1 , 2 , 3] ,
[3 , 4 , 1]].
The sum of the submatrix is 14. Hence, the answer is 14 in this case.
The first line of the input contains an integer, 'T,’ denoting the number of test cases.
The first line of each test case contains three space-separated integers, 'N', M’, and ‘K’, denoting the number of rows and the number of columns in the array 'ARR', and the number of rows in the array 'Queries' respectively.
The Next 'N' lines of each test case contain 'M' space-separated integers denoting the elements of the array 'ARR'.
The Next 'K' lines of each test case contain four space-separated integers denoting the elements of the array ‘Queries’.
For each test case, print ‘K’ space-separated integers - the sum of the submatrix for each query.
Print the output of each test case in a separate line.
1 <= N <= 10 ^ 3
1 <= M <= 10 ^ 3
1 <= K <= 10 ^ 3
1 <= ARR[i][j] <= 10 ^ 6
0 <= Queries[i][0] , Queries[i][2] < N
0 <= Queries[i][1] , Queries[i][3] < M
Where 'T' denotes the number of test cases, 'N' and 'M' denotes the number of rows and the number of columns in the array ‘ARR’ respectively, ’K’ denotes the number of rows in the array ‘Queries’, 'ARR[i][j]' denotes the ’j-th’ element of 'i-th' row of the array 'ARR' and 'Queries[i]' contains four integers denoting the left top and right bottom indices of the submatrix.
Time Limit: 1sec
A simple method is to traverse through the submatrix, and we will find the sum of the submatrix for each query.
Our approach will be to create an array answer to store the sum of the submatrix for each query. We will iterate queryNumber from 0 to K - 1, and we will maintain a variable sum to store the sum of the submatrix of the current query.
In the end, we will return the array answer.
The basic idea is to create a matrix auxiliary with N rows and M columns in which auxiliary[r][c] will store the sum of the submatrix from (0 , 0) to (r , c). Using this idea, we can find the sum of the submatrix for each query in O(1) Space Complexity.
We can find the sum of the submatrix from (r1 , c1) to (r2 , c2) in the following way given below.
sum = auxiliary[r2][c2] - auxiliary[r2][c1 - 1] - auxiliary[r1 - 1][c2] + auxiliary[r1- 1][c1 - 1]
The element auxiliary[r2][c2] stores the sum of the submatrix from (0 , 0) to (r2 , c2), auxiliary[r1 - 1][c2] stores the sum of the submatrix from (0 , 0) to (r1 - 1 , c2), auxiliary[r2][c1 - 1] stores the sum of the submatrix from (0 , 0) to (r2 , c1 - 1), and auxiliary[r1 - 1][c1 - 1] stores the sum of the submatrix from (0 , 0) to (r1 - 1 , c1 - 1).
Our approach will be to create an array answer to store the sum of the submatrix for each query.
In the end, we will return the array answer.