01 Matrix
01 Matrix
Given an m x n binary matrix mat, return a matrix where each cell contains the distance to the nearest 0.
The distance between two adjacent cells (sharing an edge) is 1.
Example 1:
Input: mat = [[0,0,0],[0,1,0],[0,0,0]]
Output: [[0,0,0],[0,1,0],[0,0,0]]
Example 2:
Input: mat = [[0,0,0],[0,1,0],[1,1,1]]
Output: [[0,0,0],[0,1,0],[1,2,1]]
Constraints:
m == mat.lengthn == mat[i].length1 <= m, n <= 1041 <= m * n <= 104mat[i][j]is either0or1.- There is at least one
0inmat.
Similar LeetCode problem: 01 Matrix
AI interview prep
Core dilemma
Efficiently computing shortest paths from multiple sources (all '0' cells) to all other cells in a grid, while managing memory and computational complexity for potentially large grids.
2 tradeoffs and 2 stress tests locked
Interview prep
Unlock the interviewer X-Ray rubric, tradeoff matrix, stress tests, clarifying questions, and key concepts.
01 Matrix
01 Matrix
Given an m x n binary matrix mat, return a matrix where each cell contains the distance to the nearest 0.
The distance between two adjacent cells (sharing an edge) is 1.
Example 1:
Input: mat = [[0,0,0],[0,1,0],[0,0,0]]
Output: [[0,0,0],[0,1,0],[0,0,0]]
Example 2:
Input: mat = [[0,0,0],[0,1,0],[1,1,1]]
Output: [[0,0,0],[0,1,0],[1,2,1]]
Constraints:
m == mat.lengthn == mat[i].length1 <= m, n <= 1041 <= m * n <= 104mat[i][j]is either0or1.- There is at least one
0inmat.
Similar LeetCode problem: 01 Matrix