Square Submatrix Sum Below Target - Google Top Interview Questions


Problem Statement :


You are given a two-dimensional list of non-negative integers matrix and a non-negative integer target. Return the area of the largest square sub-matrix whose sum is less than or equal to target. 

If there's no such matrix, return 0.

Constraints

1 ≤ n, m ≤ 250 where n and m are the number of rows and columns in matrix

Example 1

Input

matrix = [
    [3, 2, 1],

    [2, 0, 7],

    [1, 1, 9]

]

target = 10

Output

4

Explanation

This sub-matrix sums to 10:

[2, 1]

[0, 7]



Solution :



title-img




                        Solution in C++ :

int dp[255][255];
int solve(vector<vector<int>>& matrix, int target) {
    int r = matrix.size();
    int c = matrix[0].size();
    int ret = 0;
    for (int i = 1; i <= r; i++) {
        for (int j = 1; j <= c; j++) {
            dp[i][j] = matrix[i - 1][j - 1] + dp[i - 1][j] + dp[i][j - 1] - dp[i - 1][j - 1];
            while (ret + 1 <= min(i, j) && dp[i][j] - dp[i - ret - 1][j] - dp[i][j - ret - 1] +
                                                   dp[i - ret - 1][j - ret - 1] <=
                                               target)
                ret++;
        }
    }
    return ret * ret;
}
                    


                        Solution in Java :

import java.util.*;

class Solution {
    int[][] dp;
    int[][] matrix;
    public int area(int r1, int c1, int r2, int c2) {
        int m = matrix.length, n = matrix[0].length;
        if (r2 >= m || c2 >= n)
            return Integer.MAX_VALUE;
        return dp[r2 + 1][c2 + 1] + dp[r1][c1] - dp[r2 + 1][c1] - dp[r1][c2 + 1];
    }

    public boolean ok(int mid, int target) {
        int m = matrix.length, n = matrix[0].length;
        for (int i = 0; i < m; i++) {
            for (int j = 0; j < n; j++) {
                if (area(i, j, i + mid - 1, j + mid - 1) <= target)
                    return true;
            }
        }
        return false;
    }

    public int solve(int[][] mm, int target) {
        this.matrix = mm;
        int m = matrix.length;
        int n = matrix[0].length;
        dp = new int[m + 1][n + 1];
        for (int i = 0; i < m; i++) {
            for (int j = 0; j < n; j++) {
                dp[i + 1][j + 1] = matrix[i][j] + dp[i][j + 1] + dp[i + 1][j] - dp[i][j];
            }
        }
        int res = 0;
        int left = 1;
        int right = Math.min(m, n);
        while (left <= right) {
            int mid = left + (right - left) / 2;
            if (ok(mid, target)) {
                res = mid * mid;
                left = mid + 1;
            } else {
                right = mid - 1;
            }
        }
        return res;
    }
}
                    


                        Solution in Python : 
                            
class Solution:
    def solve(self, matrix, target):
        n, m = len(matrix), len(matrix[0])

        def prefix_sum_with_padding():
            prefix = [[0 for i in range(m + 1)] for j in range(n + 1)]
            for i in range(1, n + 1):
                for j in range(1, m + 1):
                    prefix[i][j] = matrix[i - 1][j - 1]
                    prefix[i][j] += prefix[i][j - 1]
                    prefix[i][j] += prefix[i - 1][j]
                    prefix[i][j] -= prefix[i - 1][j - 1]
            return prefix

        prefix = prefix_sum_with_padding()

        def found_less_equal(side):
            for i in range(side, n + 1):
                for j in range(side, m + 1):
                    cur_sum = (
                        prefix[i][j]
                        - prefix[i - side][j]
                        - prefix[i][j - side]
                        + prefix[i - side][j - side]
                    )
                    if cur_sum <= target:
                        return True
            return False

        def binary_search_for_side():
            l, r = 0, max(n, m)
            while l <= r:
                mid = (l + r) // 2
                if found_less_equal(mid):
                    l = mid + 1
                else:
                    r = mid - 1
            return r

        side = binary_search_for_side()

        return side * side
                    


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