Merge pull request #2325 from gggxxxx/XiongGu-branch

添加0827.最大人工岛Python3版本

problems/0827.最大人工岛.md

@@ -284,64 +284,68 @@ class Solution {
 
 ### Python
 
-```Python
-class Solution(object):
-    # 可能的移动方向
-    DIRECTIONS = [(1, 0), (-1, 0), (0, 1), (0, -1)]
+```python
 
-    def exploreIsland(self, row, col, grid, visited, island_id):
-        """
-        从给定的单元格开始，使用深度优先搜索探索岛屿。
-        """
-        if (row < 0 or row >= len(grid) or col < 0 or col >= len(grid[0]) or 
-            visited[row][col] or grid[row][col] == 0):
-            return 0
+class Solution:
+    def largestIsland(self, grid: List[List[int]]) -> int:
+        visited = set()    #标记访问过的位置
+        m, n = len(grid), len(grid[0])
+        res = 0
+        island_size = 0     #用于保存当前岛屿的尺寸
+        directions = [[0, 1], [0, -1], [1, 0], [-1, 0]] #四个方向
+        islands_size = defaultdict(int)  #保存每个岛屿的尺寸
 
-        visited[row][col] = True
-        grid[row][col] = island_id
-        island_size = 1
-        for dr, dc in self.DIRECTIONS:
-            island_size += self.exploreIsland(row + dr, col + dc, grid, visited, island_id)
-        return island_size
+        def dfs(island_num, r, c):
+            visited.add((r, c))
+            grid[r][c] = island_num     #访问过的位置标记为岛屿编号
+            nonlocal island_size
+            island_size += 1
+            for i in range(4):
+                nextR = r + directions[i][0]
+                nextC = c + directions[i][1]
+                if (nextR not in range(m) or     #行坐标越界
+                    nextC not in range(n) or     #列坐标越界
+                    (nextR, nextC) in visited):  #坐标已访问
+                    continue
+                if grid[nextR][nextC] == 1:      #遇到有效坐标，进入下一个层搜索
+                    dfs(island_num, nextR, nextC)
 
-    def largestIsland(self, grid):
-        """
-        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。
-        """
-        rows, cols = len(grid), len(grid[0])
-        island_sizes = {}
-        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）
-        is_all_land = True
-        visited = [[False] * cols for _ in range(rows)]
-        
-        # 标记每个岛屿并存储其大小
-        for r in range(rows):
-            for c in range(cols):
+        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
+        all_land = True            #标记是否整个地图都是陆地
+        for r in range(m):
+            for c in range(n):
                 if grid[r][c] == 0:
-                    is_all_land = False
-                elif not visited[r][c] and grid[r][c] == 1:
-                    island_size = self.exploreIsland(r, c, grid, visited, island_id)
-                    island_sizes[island_id] = island_size
-                    island_id += 1
+                    all_land = False    #地图里不全是陆地
+                if (r, c) not in visited and grid[r][c] == 1:
+                    island_size = 0     #遍历每个位置前重置岛屿尺寸为0
+                    dfs(island_num, r, c)
+                    islands_size[island_num] = island_size #保存当前岛屿尺寸
+                    island_num += 1     #下一个岛屿编号加一
+        if all_land:
+            return m * n     #如果全是陆地， 返回地图面积
 
-        # 如果整个网格是陆地，则返回其大小
-        if is_all_land:
-            return rows * cols
-        
-        # 计算可以通过将一个0更改为1来形成的最大岛屿
-        max_island_size = 0
-        for r in range(rows):
-            for c in range(cols):
+        count = 0            #某个位置0变成1后当前岛屿尺寸
+        #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，
+        #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
+        visited_island = set() #保存访问过的岛屿
+        for r in range(m):
+            for c in range(n):
                 if grid[r][c] == 0:
-                    adjacent_islands = set()
-                    for dr, dc in self.DIRECTIONS:
-                        nr, nc = r + dr, c + dc
-                        if 0 <= nr < rows and 0 <= nc < cols and grid[nr][nc] > 1:
-                            adjacent_islands.add(grid[nr][nc])
-                    new_island_size = sum(island_sizes[island] for island in adjacent_islands) + 1
-                    max_island_size = max(max_island_size, new_island_size)
+                    count = 1        #把由0转换为1的位置计算到面积里
+                    visited_island.clear()   #遍历每个位置前清空集合
+                    for i in range(4):
+                        nearR = r + directions[i][0]
+                        nearC = c + directions[i][1]
+                        if nearR not in range(m) or nearC not in range(n): #周围位置越界
+                            continue
+                        if grid[nearR][nearC] in visited_island:  #岛屿已访问
+                            continue
+                        count += islands_size[grid[nearR][nearC]] #累加连在一起的岛屿面积
+                        visited_island.add(grid[nearR][nearC])    #标记当前岛屿已访问
+                    res = max(res, count) 
+        return res
+
 
-        return max_island_size
 ```
 
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