Given an n x n binary matrix grid, return the length of the shortest clear path in the matrix. If there is no clear path, return -1.
A clear path in a binary matrix is a path from the top-left cell (i.e., (0, 0)) to the bottom-right cell (i.e., (n - 1, n - 1)) such that:
All the visited cells of the path are 0.
All the adjacent cells of the path are 8-directionally connected (i.e., they are different and they share an edge or a corner).
The length of a clear path is the number of visited cells of this path.
Examples
Input: grid = [[0,1],[1,0]] Output: 2
Input: grid = [[0,0,0],[1,1,0],[1,1,0]] Output: 4
Input: grid = [[1,0,0],[1,1,0],[1,1,0]] Output: -1
Constraints
Java Solution (Breadth First Search)
class Solution {
private static final int[][] directions = new int[][]{{-1, -1}, {-1, 0}, {-1, 1}, {0, -1}, {0, 1}, {1, -1}, {1, 0}, {1, 1}};
public int shortestPathBinaryMatrix(int[][] grid) {
if(grid[0][0] != 0 || grid[grid.length-1][grid[0].length-1] != 0) return -1;
Queue<int[]> queue = new ArrayDeque<>();
grid[0][0] = 1;
queue.add(new int[] {0,0});
while(!queue.isEmpty()) {
int[] cell = queue.poll();
int row = cell[0];
int column = cell[1];
int distance = grid[row][column];
if(row == grid.length-1 && column == grid[0].length-1) return distance;
for(int[] neighbor : getNeighbors(grid, row, column)) {
int neighborRow = neighbor[0];
int neighborColumn = neighbor[1];
queue.add(new int[]{neighborRow, neighborColumn});
grid[neighborRow][neighborColumn] = distance + 1;
}
}
return -1;
}
private List<int[]> getNeighbors(int[][] grid, int row, int column) {
List<int[]> neighbors = new ArrayList<>();
for(int i = 0; i < directions.length; i++) {
int newRow = row + directions[i][0];
int newColumn = column + directions[i][1];
if(newRow < 0 || newRow >= grid.length || newColumn < 0 || newColumn >= grid[0].length || grid[newRow][newColumn] != 0) continue;
neighbors.add(new int[]{newRow, newColumn});
}
return neighbors;
}
}