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2482 - Difference Between Ones and Zeros in Row and Column (Medium)

https://leetcode.com/problems/difference-between-ones-and-zeros-in-row-and-column/

Problem Statement

You are given a 0-indexed m x n binary matrix grid.

A 0-indexed m x n difference matrix diff is created with the following procedure:

  • Let the number of ones in the ith row be onesRowi.
  • Let the number of ones in the jth column be onesColj.
  • Let the number of zeros in the ith row be zerosRowi.
  • Let the number of zeros in the jth column be zerosColj.
  • diff[i][j] = onesRowi + onesColj - zerosRowi - zerosColj

Return the difference matrixdiff.

Example 1:

Input: grid = [[0,1,1],[1,0,1],[0,0,1]]
Output: [[0,0,4],[0,0,4],[-2,-2,2]]
Explanation:
- diff[0][0] = onesRow0 + onesCol0 - zerosRow0 - zerosCol0 = 2 + 1 - 1 - 2 = 0
- diff[0][1] = onesRow0 + onesCol1 - zerosRow0 - zerosCol1 = 2 + 1 - 1 - 2 = 0
- diff[0][2] = onesRow0 + onesCol2 - zerosRow0 - zerosCol2 = 2 + 3 - 1 - 0 = 4
- diff[1][0] = onesRow1 + onesCol0 - zerosRow1 - zerosCol0 = 2 + 1 - 1 - 2 = 0
- diff[1][1] = onesRow1 + onesCol1 - zerosRow1 - zerosCol1 = 2 + 1 - 1 - 2 = 0
- diff[1][2] = onesRow1 + onesCol2 - zerosRow1 - zerosCol2 = 2 + 3 - 1 - 0 = 4
- diff[2][0] = onesRow2 + onesCol0 - zerosRow2 - zerosCol0 = 1 + 1 - 2 - 2 = -2
- diff[2][1] = onesRow2 + onesCol1 - zerosRow2 - zerosCol1 = 1 + 1 - 2 - 2 = -2
- diff[2][2] = onesRow2 + onesCol2 - zerosRow2 - zerosCol2 = 1 + 3 - 2 - 0 = 2

Example 2:

Input: grid = [[1,1,1],[1,1,1]]
Output: [[5,5,5],[5,5,5]]
Explanation:
- diff[0][0] = onesRow0 + onesCol0 - zerosRow0 - zerosCol0 = 3 + 2 - 0 - 0 = 5
- diff[0][1] = onesRow0 + onesCol1 - zerosRow0 - zerosCol1 = 3 + 2 - 0 - 0 = 5
- diff[0][2] = onesRow0 + onesCol2 - zerosRow0 - zerosCol2 = 3 + 2 - 0 - 0 = 5
- diff[1][0] = onesRow1 + onesCol0 - zerosRow1 - zerosCol0 = 3 + 2 - 0 - 0 = 5
- diff[1][1] = onesRow1 + onesCol1 - zerosRow1 - zerosCol1 = 3 + 2 - 0 - 0 = 5
- diff[1][2] = onesRow1 + onesCol2 - zerosRow1 - zerosCol2 = 3 + 2 - 0 - 0 = 5

Constraints:

  • m==grid.lengthm == grid.length
  • n==grid[i].lengthn == grid[i].length
  • 1<=m,n<=1051 <= m, n <= 10 ^ 5
  • 1<=mn<=1051 <= m * n <= 10 ^ 5
  • grid[i][j]grid[i][j] is either 00 or 11.

Approach 1: Row and Column Sum

We compute the sum of each row and column, which is equal to the number of ones and from that we can reason about the number of zeros. Note that we are rewriting the input.

Written by @heder
class Solution {
public:
static vector<vector<int>> onesMinusZeros(vector<vector<int>>& grid) noexcept {
const int rows = size(grid);
const int cols = size(grid[0]);

vector<int> rs(rows);
vector<int> cs(cols);
for (int r = 0; r < rows; ++r)
for (int c = 0; c < cols; ++c) {
rs[r] += grid[r][c];
cs[c] += grid[r][c];
}

for (int r = 0; r < rows; ++r)
for (int c = 0; c < cols; ++c)
grid[r][c] = rs[r] + cs[c] - (rows - rs[r]) - (cols - cs[c]);

return grid;
}
};

For the second pass over the grid we can factor out some invariants and make it:

Written by @heder
for (int r = 0; r < rows; ++r) {
const int k = 2 * rs[r] - rows - cols;
for (int c = 0; c < cols; ++c)
grid[r][c] = k + 2 * cs[c];
}

This generated different code (https://godbolt.org/z/G7xoWGqj9) and is faster than the version above.

Bonus Variant: using the Elvis operator ?:

Written by @heder
class Solution {
public:
static vector<vector<int>> onesMinusZeros(vector<vector<int>>& grid) noexcept {
const int rows = size(grid);
const int cols = size(grid[0]);

vector<int> rs(rows);
vector<int> cs(cols);
for (int r = 0; r < rows; ++r)
for (int c = 0; c < cols; ++c) {
rs[r] += grid[r][c] ?: -1;
cs[c] += grid[r][c] ?: -1;
}

for (int r = 0; r < rows; ++r)
for (int c = 0; c < cols; ++c)
grid[r][c] = rs[r] + cs[c];

return grid;
}
};

Unfortunatly this variant seems quite a bit slower, but if you turn your head to the left you might see the King of Rock'n'Roll. :)

Complexity Analysis

Let nn be the number of rows and mm be the number of columns then the

  • Time complexity: O(nm)O(n * m) as we need to compute the row and column sums and the fill the grid.
  • Space complexity: O(n+m)O(n + m) for the row and column sums.