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542. 01 Matrix

Description

Given an m x n binary matrix mat, return the distance of the nearest 0 for each cell.

The distance between two adjacent cells 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.length
  • n == mat[i].length
  • 1 <= m, n <= 104
  • 1 <= m * n <= 104
  • mat[i][j] is either 0 or 1.
  • There is at least one 0 in mat.

Solutions

Solution 1: BFS

We create a matrix $\textit{ans}$ of the same size as $\textit{mat}$ and initialize all elements to $-1$.

Then, we traverse $\textit{mat}$, adding the coordinates $(i, j)$ of all $0$ elements to the queue $\textit{q}$, and setting $\textit{ans}[i][j]$ to $0$.

Next, we use Breadth-First Search (BFS), removing an element $(i, j)$ from the queue and traversing its four directions. If the element in that direction $(x, y)$ satisfies $0 \leq x < m$, $0 \leq y < n$ and $\textit{ans}[x][y] = -1$, then we set $\textit{ans}[x][y]$ to $\textit{ans}[i][j] + 1$ and add $(x, y)$ to the queue $\textit{q}$.

Finally, we return $\textit{ans}$.

The time complexity is $O(m \times n)$, and the space complexity is $O(m \times n)$. Here, $m$ and $n$ are the number of rows and columns in the matrix $\textit{mat}$, respectively.

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class Solution:
    def updateMatrix(self, mat: List[List[int]]) -> List[List[int]]:
        m, n = len(mat), len(mat[0])
        ans = [[-1] * n for _ in range(m)]
        q = deque()
        for i, row in enumerate(mat):
            for j, x in enumerate(row):
                if x == 0:
                    ans[i][j] = 0
                    q.append((i, j))
        dirs = (-1, 0, 1, 0, -1)
        while q:
            i, j = q.popleft()
            for a, b in pairwise(dirs):
                x, y = i + a, j + b
                if 0 <= x < m and 0 <= y < n and ans[x][y] == -1:
                    ans[x][y] = ans[i][j] + 1
                    q.append((x, y))
        return ans

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class Solution {
    public int[][] updateMatrix(int[][] mat) {
        int m = mat.length, n = mat[0].length;
        int[][] ans = new int[m][n];
        for (int[] row : ans) {
            Arrays.fill(row, -1);
        }
        Deque<int[]> q = new ArrayDeque<>();
        for (int i = 0; i < m; ++i) {
            for (int j = 0; j < n; ++j) {
                if (mat[i][j] == 0) {
                    q.offer(new int[] {i, j});
                    ans[i][j] = 0;
                }
            }
        }
        int[] dirs = {-1, 0, 1, 0, -1};
        while (!q.isEmpty()) {
            int[] p = q.poll();
            int i = p[0], j = p[1];
            for (int k = 0; k < 4; ++k) {
                int x = i + dirs[k], y = j + dirs[k + 1];
                if (x >= 0 && x < m && y >= 0 && y < n && ans[x][y] == -1) {
                    ans[x][y] = ans[i][j] + 1;
                    q.offer(new int[] {x, y});
                }
            }
        }
        return ans;
    }
}

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class Solution {
public:
    vector<vector<int>> updateMatrix(vector<vector<int>>& mat) {
        int m = mat.size(), n = mat[0].size();
        vector<vector<int>> ans(m, vector<int>(n, -1));
        queue<pair<int, int>> q;
        for (int i = 0; i < m; ++i) {
            for (int j = 0; j < n; ++j) {
                if (mat[