@@ -284,64 +284,68 @@ class Solution {
284284
285285### Python
286286
287- ``` Python
288- class Solution (object ):
289- # 可能的移动方向
290- DIRECTIONS = [(1 , 0 ), (- 1 , 0 ), (0 , 1 ), (0 , - 1 )]
291- 292- def exploreIsland (self row , col , grid , visited , island_id ):
293- """
294- 从给定的单元格开始,使用深度优先搜索探索岛屿。
295- """
296- if (row < 0 or row >= len (grid) or col < 0 or col >= len (grid[0 ]) or
297- visited[row][col] or grid[row][col] == 0 ):
298- return 0
299- 300- visited[row][col] = True
301- grid[row][col] = island_id
302- island_size = 1
303- for dr, dc in self .DIRECTIONS :
304- island_size += self .exploreIsland(row + dr, col + dc, grid, visited, island_id)
305- return island_size
306- 307- def largestIsland (self grid ):
308- """
309- 通过最多将一个0更改为1,找到可以形成的最大岛屿的大小。
310- """
311- rows, cols = len (grid), len (grid[0 ])
312- island_sizes = {}
313- island_id = 2 # 从2开始标记岛屿(因为0代表水,1代表未被发现的陆地)
314- is_all_land = True
315- visited = [[False ] * cols for _ in range (rows)]
316- 317- # 标记每个岛屿并存储其大小
318- for r in range (rows):
319- for c in range (cols):
287+ ``` python
288+ 289+ class Solution :
290+ def largestIsland (self grid : List[List[int ]]) -> int :
291+ visited = set () # 标记访问过的位置
292+ m, n = len (grid), len (grid[0 ])
293+ res = 0
294+ island_size = 0 # 用于保存当前岛屿的尺寸
295+ directions = [[0 , 1 ], [0 , - 1 ], [1 , 0 ], [- 1 , 0 ]] # 四个方向
296+ islands_size = defaultdict(int ) # 保存每个岛屿的尺寸
297+ 298+ def dfs (island_num , r , c ):
299+ visited.add((r, c))
300+ grid[r][c] = island_num # 访问过的位置标记为岛屿编号
301+ nonlocal island_size
302+ island_size += 1
303+ for i in range (4 ):
304+ nextR = r + directions[i][0 ]
305+ nextC = c + directions[i][1 ]
306+ if (nextR not in range (m) or # 行坐标越界
307+ nextC not in range (n) or # 列坐标越界
308+ (nextR, nextC) in visited): # 坐标已访问
309+ continue
310+ if grid[nextR][nextC] == 1 : # 遇到有效坐标,进入下一个层搜索
311+ dfs(island_num, nextR, nextC)
312+ 313+ island_num = 2 # 初始岛屿编号设为2, 因为grid里的数据有0和1, 所以从2开始编号
314+ all_land = True # 标记是否整个地图都是陆地
315+ for r in range (m):
316+ for c in range (n):
320317 if grid[r][c] == 0 :
321- is_all_land = False
322- elif not visited[r][c] and grid[r][c] == 1 :
323- island_size = self .exploreIsland(r, c, grid, visited, island_id)
324- island_sizes[island_id] = island_size
325- island_id += 1
326- 327- # 如果整个网格是陆地,则返回其大小
328- if is_all_land:
329- return rows * cols
330- 331- # 计算可以通过将一个0更改为1来形成的最大岛屿
332- max_island_size = 0
333- for r in range (rows):
334- for c in range (cols):
318+ all_land = False # 地图里不全是陆地
319+ if (r, c) not in visited and grid[r][c] == 1 :
320+ island_size = 0 # 遍历每个位置前重置岛屿尺寸为0
321+ dfs(island_num, r, c)
322+ islands_size[island_num] = island_size # 保存当前岛屿尺寸
323+ island_num += 1 # 下一个岛屿编号加一
324+ if all_land:
325+ return m * n # 如果全是陆地, 返回地图面积
326+ 327+ count = 0 # 某个位置0变成1后当前岛屿尺寸
328+ # 因为后续计算岛屿面积要往四个方向遍历,但某2个或3个方向的位置可能同属于一个岛,
329+ # 所以为避免重复累加,把已经访问过的岛屿编号加入到这个集合
330+ visited_island = set () # 保存访问过的岛屿
331+ for r in range (m):
332+ for c in range (n):
335333 if grid[r][c] == 0 :
336- adjacent_islands = set ()
337- for dr, dc in self .DIRECTIONS :
338- nr, nc = r + dr, c + dc
339- if 0 <= nr < rows and 0 <= nc < cols and grid[nr][nc] > 1 :
340- adjacent_islands.add(grid[nr][nc])
341- new_island_size = sum (island_sizes[island] for island in adjacent_islands) + 1
342- max_island_size = max (max_island_size, new_island_size)
343- 344- return max_island_size
334+ count = 1 # 把由0转换为1的位置计算到面积里
335+ visited_island.clear() # 遍历每个位置前清空集合
336+ for i in range (4 ):
337+ nearR = r + directions[i][0 ]
338+ nearC = c + directions[i][1 ]
339+ if nearR not in range (m) or nearC not in range (n): # 周围位置越界
340+ continue
341+ if grid[nearR][nearC] in visited_island: # 岛屿已访问
342+ continue
343+ count += islands_size[grid[nearR][nearC]] # 累加连在一起的岛屿面积
344+ visited_island.add(grid[nearR][nearC]) # 标记当前岛屿已访问
345+ res = max (res, count)
346+ return res
347+ 348+ 345349```
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347351<p align =" center " >
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