Surrounded Regions
Given a 2D board containing
'X' and 'O', capture all regions surrounded by 'X'.
A region is captured by flipping all
'O's into 'X's in that surrounded region .
For example,
X X X X X O O X X X O X X O X X
After running your function, the board should be:
X X X X X X X X X X X X X O X X
Analysis:
Search is a good way to solve this problem!
First and easy thought might, scan all the element, if meets 'O', looking for a path to the boundary, if not exist, put it to 'X'. To look for the path, if all the four directions all have no way out, this element has no way out. The DFS can be used. See code(small case) below. Actually, it only cannot pass the last big test case (where 250x250 matrix is provided).
However, it will not pass the big test, because the complexity is too high. One common thought is to use BFS instead of DFS, which use more space, but less time.
So how BFS is conducted, we can think from out to inside. Because the boundary 'O' are definitely "live" (have a path out) element, so, we BFS from each 'O' in the boundary, mark all its four directions (where is also 'O') as "live". If you think here, you almost done, the standard BFS using a queue (here I use vector for simplicity) can solve the problem. Last step is to flip "O" to "X" because there is no way out, and flip "P"(live) to "O", because it has a path out. See code (big case) for details. All the test cases are passed.
Code (C++):
class Solution {
public:
void solve(vector<vector<char>> &board) {
int row = board.size(); //get row number
if (row==0){return;}
int col = board[0].size(); // get column number
vector<vector<bool> > bb(row, vector<bool>(col)); //result vector
queue<pair<int,int> > q; // queue for BFS
//search "O" from 1st row
for (int i=0;i<col;i++){
if (board[0][i]=='O'){
q.push(make_pair(0,i));
bb[0][i]=true;
}
}
//search "O" from 1st column
for (int i=0;i<row;i++){
if (board[i][0]=='O'){
q.push(make_pair(i,0));
bb[i][0]=true;
}
}
//search "O" from last row
for (int i=0;i<col;i++){
if (board[row-1][i]=='O'){
q.push(make_pair(row-1,i));
bb[row-1][i]=true;
}
}
//search "O" from last column
for (int i=0;i<row;i++){
if (board[i][col-1]=='O'){
q.push(make_pair(i,col-1));
bb[i][col-1]=true;
}
}
//BFS
int i,j; // current position
while (!q.empty()){
//get current live "O"
i = q.front().first;
j = q.front().second;
//pop up queue
q.pop();
//search four directions
if (i-1>0 && board[i-1][j]=='O' && bb[i-1][j]==false){bb[i-1][j]=true; q.push(make_pair(i-1,j));} //top
if (i+1<row-1 && board[i+1][j]=='O'&& bb[i+1][j]==false){bb[i+1][j]=true; q.push(make_pair(i+1,j));} // bottom
if (j-1>0 && board[i][j-1]=='O'&& bb[i][j-1]==false){bb[i][j-1]=true; q.push(make_pair(i,j-1));} // left
if (j+1<col-1 && board[i][j+1]=='O'&& bb[i][j+1]==false){bb[i][j+1]=true; q.push(make_pair(i,j+1));} // right
}
//Get result
for (int i=0;i<row;i++){
for (int j=0;j<col;j++){
if (board[i][j]=='O'&&bb[i][j]==false){
board[i][j]='X';
}
}
}
return;
}
};
Code(Python):
class Solution:
# @param board, a 2D array
# Capture all regions by modifying the input board in-place.
# Do not return any value.
def solve(self, board):
row = len(board)
if row==0:
return
col = len(board[0])
bb = [[False for j in xrange(0,col)] for i in xrange(0,row)]
que = []
for i in xrange(0,col):
if board[0][i]=='O':
bb[0][i]=True
que.append([0,i])
if board[row-1][i]=='O':
bb[row-1][i]=True
que.append([row-1,i])
for i in xrange(0,row):
if board[i][0]=='O':
bb[i][0]=True
que.append([i,0])
if board[i][col-1]=='O':
bb[i][col-1]=True
que.append([i,col-1])
while que:
i = que[0][0]
j = que[0][1]
que.pop(0)
if (i-1>0 and board[i-1][j]=='O' and bb[i-1][j]==False):
bb[i-1][j]=True
que.append([i-1,j])
if (i+1<row-1 and board[i+1][j]=='O' and bb[i+1][j]==False):
bb[i+1][j]=True
que.append([i+1,j])
if (j-1>0 and board[i][j-1]=='O' and bb[i][j-1]==False):
bb[i][j-1]=True
que.append([i,j-1])
if (j+1<col-1 and board[i][j+1]=='O' and bb[i][j+1]==False):
bb[i][j+1]=True
que.append([i,j+1])
for i in xrange(0,row):
for j in xrange(0,col):
if board[i][j]=='O' and bb[i][j]==False:
board[i][j] = 'X'
return
Good article, but I don't understand "use BFS instead of DFS, which use more space, but less time." I feel they are same, DFS use a stack, and BFS use queue.
ReplyDeleteDFS uses stack memory available for function call which is limited whereas BFS uses normal memory(we declare a vector or other stl).
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