You are starving and you want to eat food as quickly as possible. You want to find the shortest path to arrive at any food cell.
You are given an m x n character matrix, grid, of these different types of cells:
'*' is your location. There is exactly one '*' cell.
'#' is a food cell. There may be multiple food cells.
'O' is free space, and you can travel through these cells.
'X' is an obstacle, and you cannot travel through these cells.
You can travel to any adjacent cell north, east, south, or west of your current location if there is not an obstacle.
Return the length of the shortest path for you to reach any food cell. If there is no path for you to reach food, return -1.
Example 1:
Input: grid = [["X","X","X","X","X","X"],["X","*","O","O","O","X"],["X","O","O","#","O","X"],["X","X","X","X","X","X"]]
Output: 3
Explanation: It takes 3 steps to reach the food.
Example 2:
Input: grid = [["X","X","X","X","X"],["X","*","X","O","X"],["X","O","X","#","X"],["X","X","X","X","X"]]
Output: -1
Explanation: It is not possible to reach the food.
Example 3:
Input: grid = [["X","X","X","X","X","X","X","X"],["X","*","O","X","O","#","O","X"],["X","O","O","X","O","O","X","X"],["X","O","O","O","O","#","O","X"],["X","X","X","X","X","X","X","X"]]
Output: 6
Explanation: There can be multiple food cells. It only takes 6 steps to reach the bottom food.
Constraints:
m == grid.length
n == grid[i].length
1 <= m, n <= 200
grid[row][col] is '*', 'X', 'O', or '#'.
The grid contains exactly one'*'.
Solutions
Solution 1: BFS (Breadth-First Search)
According to the problem, we need to start from *, find the nearest #, and return the shortest path length.
First, we traverse the entire two-dimensional array to find the position of *, which will be the starting point for BFS, and put it into the queue.
Then, we start BFS, traversing the elements in the queue. Each time we traverse an element, we add the elements in the four directions (up, down, left, and right) of it into the queue, until we encounter #, and return the current layer number.
The time complexity is $O(m \times n)$, and the space complexity is $O(1)$. Here, $m$ and $n$ are the number of rows and columns of the two-dimensional array, respectively.