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1727. Largest Submatrix With Rearrangements

Description

You are given a binary matrix matrix of size m x n, and you are allowed to rearrange the columns of the matrix in any order.

Return the area of the largest submatrix within matrix where every element of the submatrix is 1 after reordering the columns optimally.

 

Example 1:

Input: matrix = [[0,0,1],[1,1,1],[1,0,1]]
Output: 4
Explanation: You can rearrange the columns as shown above.
The largest submatrix of 1s, in bold, has an area of 4.

Example 2:

Input: matrix = [[1,0,1,0,1]]
Output: 3
Explanation: You can rearrange the columns as shown above.
The largest submatrix of 1s, in bold, has an area of 3.

Example 3:

Input: matrix = [[1,1,0],[1,0,1]]
Output: 2
Explanation: Notice that you must rearrange entire columns, and there is no way to make a submatrix of 1s larger than an area of 2.

 

Constraints:

  • m == matrix.length
  • n == matrix[i].length
  • 1 <= m * n <= 105
  • matrix[i][j] is either 0 or 1.

Solutions

Solution 1: Preprocessing + Sorting

Since the matrix is rearranged by columns according to the problem, we can first preprocess each column of the matrix.

For each element with a value of $1$, we update its value to the maximum consecutive number of $1$s above it, that is, $matrix[i][j] = matrix[i-1][j] + 1$.

Next, we can sort each row of the updated matrix. Then traverse each row, calculate the area of the largest sub-matrix full of $1$s with this row as the bottom edge. The specific calculation logic is as follows:

For a row of the matrix, we denote the value of the $k$-th largest element as $val_k$, where $k \geq 1$, then there are at least $k$ elements in this row that are not less than $val_k$, forming a sub-matrix full of $1$s with an area of $val_k \times k$. Traverse each element of this row from large to small, take the maximum value of $val_k \times k$, and update the answer.

The time complexity is $O(m \times n \times \log n)$. Here, $m$ and $n$ are the number of rows and columns of the matrix, respectively.

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class Solution:
    def largestSubmatrix(self, matrix: List[List[int]]) -> int:
        for i in range(1, len(matrix)):
            for j in range(len(matrix[0])):
                if matrix[i][j]:
                    matrix[i][j] = matrix[i - 1][j] + 1
        ans = 0
        for row in matrix:
            row.sort(reverse=True)
            for j, v in enumerate(row, 1):
                ans = max(ans, j * v)
        return ans
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class Solution {
    public int largestSubmatrix(int[][] matrix) {
        int m = matrix.length, n = matrix[0].length;
        for (int i = 1; i < m; ++i) {
            for (int j = 0; j < n; ++j) {
                if (matrix[i][j] == 1) {
                    matrix[i][j] = matrix[i - 1][j] + 1;
                }
            }
        }
        int ans = 0;
        for (var row : matrix) {
            Arrays.sort(row);
            for (int j = n - 1, k = 1; j >= 0 && row[j] > 0; --j, ++k) {
                int s = row[j] * k;
                ans = Math.max(ans, s);
            }
        }
        return ans;
    }
}
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class Solution {
public:
    int largestSubmatrix(vector<vector<int>>& matrix) {
        int m = matrix.size(), n = matrix[0].size();
        for (int i = 1; i < m; ++i) {
            for (int j = 0; j < n; ++j) {
                if (matrix[i][j]) {
                    matrix[i][j] = matrix[i - 1][j] + 1;
                }
            }
        }
        int ans = 0;
        for (auto& row : matrix) {
            sort(row.rbegin(), row.rend());
            for (int j = 0; j < n; ++j) {
                ans = max(ans, (j + 1) * row[j]);
            }
        }
        return ans;
    }
};
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func largestSubmatrix(matrix [][]int) int {
    m, n := len(matrix), len(matrix[0])
    for i := 1; i < m; i++ {
        for j := 0; j < n; j++ {
            if matrix[i][j] == 1 {
                matrix[i][j]