2482 - Difference Between Ones and Zeros in Row and Column (Medium)
Problem Link
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 beonesRowi
. - Let the number of ones in the
jth
column beonesColj
. - Let the number of zeros in the
ith
row bezerosRowi
. - Let the number of zeros in the
jth
column bezerosColj
. 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:
- is either or .
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.
- C++
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:
- C++
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 ?:
- C++
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 be the number of rows and be the number of columns then the
- Time complexity: as we need to compute the row and column sums and the fill the grid.
- Space complexity: for the row and column sums.