【LeetCode】01 Matrix 解题报告

【LeetCode】01 Matrix 解题报告

标签（空格分隔）： LeetCode

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题目地址：https://leetcode.com/problems/01-matrix/#/description

题目描述：

Given a matrix consists of 0 and 1, find the distance of the nearest 0 for each cell.

The distance between two adjacent cells is 1.

Example：

Input:

0 0 0
0 1 0
0 0 0
Output:
0 0 0
0 1 0
0 0 0
Example 2:
Input:

0 0 0
0 1 0
1 1 1
Output:
0 0 0
0 1 0
1 2 1

Note:

1. The number of elements of the given matrix will not exceed 10,000.
2. There are at least one 0 in the given matrix.
3. The cells are adjacent in only four directions: up, down, left and right.

Ways

这个题的思想是BFS，广度优先遍历。也是让我学习了一下到底怎么写BFS。

首先，BFS要用到了队列，让值为0的节点全部进入队列，代表要进行遍历的点；把值为1的点设为最大值，表示距离很远，初始状态下不能到。然后对于队列中的每个点都有四个方向，要考虑这个点临近的四个方向的点距都离为当前点到0点的距离加1.有点类似DP，把某个点到0的距离设为周围点到0的最短值+1即可。注意，遍历时修改完另外点的值的时候，一定要把这个节点也加入到队列中。这个点到0的距离是最近距离+1，而不是单纯的1.

public class Solution {
    public List<List<Integer>> updateMatrix(List<List<Integer>> matrix) {
        if(matrix == null || matrix.size() == 0){
            return matrix;
        }
        int m = matrix.size();
        int n = matrix.get(0).size();
        Queue<int[]> queue = new LinkedList<>();
        for(int i = 0; i < m; i++){
            for(int j = 0; j < n; j++){
                if(matrix.get(i).get(j)==0){
                    queue.offer(new int[]{i, j});
                }else{
                    matrix.get(i).set(j, Integer.MAX_VALUE);
                }
            }
        }
        int[][] dirs = {{-1, 0}, {1, 0}, {0, -1}, {0, 1}};
        while(!queue.isEmpty()){
            int cell[]= queue.poll();
            for(int[] d: dirs){
                int r = cell[0] + d[0];
                int c = cell[1] + d[1];
                if (r < 0 || r >= m || c < 0 || c >= n ||
                        matrix.get(r).get(c) <= matrix.get(cell[0]).get(cell[1]) + 1)
                        continue;
                queue.offer(new int[]{r, c});
                matrix.get(r).set(c, matrix.get(cell[0]).get(cell[1]) + 1);
            }
        }
        return matrix;
    }
}

Date

2017 年 4 月 11 日