Leetcode 130. Surrounded Regions(python+cpp)

Leetcode 130. Surrounded Regions

  • 题目
  • 解析
  • 改进解法

题目

Leetcode 130. Surrounded Regions(python+cpp)_第1张图片

解析

这道题目的关键在于反向思路。如果要去判断某个O所在的位置是不是被包围,挺困难的,所以反向去找那些没有被包围的所有O的位置,而题目里明确说了,在四条boundary上的O是不被包围的。这应该是最straight forward的方法了,不过从提交结果来看速度还是比较慢。具体流程如下:

  • 从四条边界上找所有O的位置,这些O是最简单的可以确认是不被包围的点。那么进一步的就可以知道和这些O直接相连的点也肯定是不被包围的
  • 从这些点出发,用dfs或者bfs找到所有和这些点直接相连的点,可以通过修改这些位置的mark,也可以直接记录位置,我这边采用的直接记录位置
  • 遍历整个board,按照之前找到的位置做相应的修改
    python代码如下:
class Solution:
    def solve(self, board: List[List[str]]) -> None:
        """
        Do not return anything, modify board in-place instead.
        """
        def dfs(i,j):
            if i<0 or i>=m or j<0 or j>=n or board[i][j]!='O' or (i,j) in visited:
                return
            pos.append((i,j))
            visited.add((i,j))
            dfs(i+1,j)
            dfs(i-1,j)
            dfs(i,j+1)
            dfs(i,j-1)
            
        if not len(board) or not len(board[0]):
            return     
        visited = set()
        pos = []
        m = len(board)
        n = len(board[0])
        
        
        for i in range(m):
            dfs(i,0)
            dfs(i,n-1)
        for i in range(n):
            dfs(0,i)
            dfs(m-1,i)
        for i in range(m):
            for j in range(n):
                if board[i][j]=='O' and (i,j) not in pos:
                    board[i][j] = 'X'

C++版本如下:

class Solution {
     
public:
    void solve(vector<vector<char>>& board) {
     
        if (board.empty() || board[0].empty()) return;
        set<pair<int,int>> visited;
        set<pair<int,int>> pos;
        for (int i=0;i<board.size();++i){
     
            dfs(i,0,board,visited,pos);
            dfs(i,board[0].size()-1,board,visited,pos);
        }
        for (int i=0;i<board[0].size();++i){
     
            dfs(0,i,board,visited,pos);
            dfs(board.size()-1,i,board,visited,pos);
        }
        for (int i=0;i<board.size();++i){
     
            for (int j=0;j<board[0].size();++j){
     
                pair<int,int> curr(i,j);
                if (board[i][j]=='O' && !pos.count(curr)){
     
                    board[i][j] = 'X';
                }
            }
        }
    }
    void dfs(int i, int j, vector<vector<char>>& board,set<pair<int,int>>& visited,set<pair<int,int>>& pos){
     
        pair<int,int> curr_pos(i,j);
        if (i<0||i>=board.size()||j<0||j>=board[0].size()||board[i][j]!='O'||visited.count(curr_pos)) return;
        pos.insert(curr_pos);
        visited.insert(curr_pos);
        dfs(i+1,j,board,visited,pos);
        dfs(i-1,j,board,visited,pos);
        dfs(i,j+1,board,visited,pos);
        dfs(i,j-1,board,visited,pos);
        
    }
};

改进解法

上面速度比较慢的原因应该在于visited访问的时候需要log(n)的额外复杂度,其实这种问题不需要建立visited,直接通过修改board的状态就可以了,在从边界开始BFS或者DFS的时候,将能访问到的O全部修改为‘#’,最后只需将所有是’#'的位置恢复成O就可以了,我把BFS和DFS两种写法都写在一起了。只是替换不同的部分即可

class Solution:
    def solve(self, board: List[List[str]]) -> None:
        """
        Do not return anything, modify board in-place instead.
        """
        if not len(board):
            return
        m = len(board)
        n = len(board[0])
        
        #q = collections.deque()
        q = []
        for i in range(m):
            if board[i][0] == 'O':
                q.append((i,0))
            if board[i][n-1] == 'O':
                q.append((i,n-1))
                
        
        for j in range(n):
            if board[0][j] == 'O':
                q.append((0,j))
            if board[m-1][j] == 'O':
                q.append((m-1,j))
                
        
        # while q:
        #     curr = q.popleft()
        #     board[curr[0]][curr[1]] = '#'
        #     dirs = [[1,0],[-1,0],[0,1],[0,-1]]
        #     for d in dirs:
        #         x = curr[0]+d[0]
        #         y = curr[1]+d[1]
        #         if 0<=x
        #             if board[x][y] == 'X':
        #                 continue
        #             if board[x][y] == 'O':
        #                 q.append((x,y))
        def helper(i,j):
            if i<0 or i>=m or j<0 or j>=n or board[i][j]=='#' or board[i][j]=='X':
                return
            board[i][j] = '#'
            helper(i+1,j)
            helper(i-1,j)
            helper(i,j+1)
            helper(i,j-1)
            
        for (i,j) in q:
            helper(i,j)
        
        for i in range(m):
            for j in range(n):
                if board[i][j] == '#':
                    board[i][j] = 'O'
                else:
                    board[i][j] = 'X'

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