给你一个由 '1'(陆地)和 '0'(水)组成的的二维网格,请你计算网格中岛屿的数量。
岛屿总是被水包围,并且每座岛屿只能由水平方向和/或竖直方向上相邻的陆地连接形成。
此外,你可以假设该网格的四条边均被水包围。
示例 1:
输入:grid = [ ["1","1","1","1","0"], ["1","1","0","1","0"], ["1","1","0","0","0"], ["0","0","0","0","0"] ] 输出:1
示例 2:
输入:grid = [ ["1","1","0","0","0"], ["1","1","0","0","0"], ["0","0","1","0","0"], ["0","0","0","1","1"] ] 输出:3
示例代码:
class Solution:
def numIslands(self, grid: List[List[str]]) -> int:
row, col = len(grid), len(grid[0])
ret = 0
def dfs(x, y):
grid[x][y] = '0'
lst = [[1,0], [-1, 0], [0, 1], [0, -1]]
for i in lst:
nx, ny = x + i[0], y + i[1]
if 0 <= nx < row and 0 <= ny < col and grid[nx][ny] == '1':
dfs(nx, ny)
for i in range(row):
for j in range(col):
if grid[i][j] == '1':
dfs(i, j)
ret += 1
return ret
思路解析(深度优先搜索):
我们只需要对矩阵进行依次遍历,如果当前grid[x][y] == "1",则启动DFS模式。
找到与之相连的所有1,将其置为0。搜索结束后,我们找到了一个岛屿,岛屿数量+=1。
如此循环,最终返回岛屿数量即可。
本文解析如何使用深度优先搜索算法解决经典问题——给定由 '1' 和 '0' 构成的二维网格,计算其中岛屿的数量。通过DFS遍历并标记相连陆地,展示了计数过程和示例代码的应用。
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