diff --git a/problems/kamacoder/0097.小明逛公园.md b/problems/kamacoder/0097.小明逛公园.md index 5465c356..e8d92cc2 100644 --- a/problems/kamacoder/0097.小明逛公园.md +++ b/problems/kamacoder/0097.小明逛公园.md @@ -339,7 +339,7 @@ int main() { } } -``` +``` ## 空间优化 @@ -426,6 +426,68 @@ floyd算法的时间复杂度相对较高,适合 稠密图且源点较多的 ### Python +基于三维数组的Floyd + +```python +if __name__ == '__main__': + max_int = 10005 # 设置最大路径,因为边最大距离为10^4 + + n, m = map(int, input().split()) + + grid = [[[max_int] * (n+1) for _ in range(n+1)] for _ in range(n+1)] # 初始化三维dp数组 + + for _ in range(m): + p1, p2, w = map(int, input().split()) + grid[p1][p2][0] = w + grid[p2][p1][0] = w + + # 开始floyd + for k in range(1, n+1): + for i in range(1, n+1): + for j in range(1, n+1): + grid[i][j][k] = min(grid[i][j][k-1], grid[i][k][k-1] + grid[k][j][k-1]) + + # 输出结果 + z = int(input()) + for _ in range(z): + start, end = map(int, input().split()) + if grid[start][end][n] == max_int: + print(-1) + else: + print(grid[start][end][n]) +``` + +基于二维数组的Floyd + +```python +if __name__ == '__main__': + max_int = 10005 # 设置最大路径,因为边最大距离为10^4 + + n, m = map(int, input().split()) + + grid = [[max_int]*(n+1) for _ in range(n+1)] # 初始化二维dp数组 + + for _ in range(m): + p1, p2, val = map(int, input().split()) + grid[p1][p2] = val + grid[p2][p1] = val + + # 开始floyd + for k in range(1, n+1): + for i in range(1, n+1): + for j in range(1, n+1): + grid[i][j] = min(grid[i][j], grid[i][k] + grid[k][j]) + + # 输出结果 + z = int(input()) + for _ in range(z): + start, end = map(int, input().split()) + if grid[start][end] == max_int: + print(-1) + else: + print(grid[start][end]) +``` + ### Go ### Rust diff --git a/problems/kamacoder/0099.岛屿的数量深搜.md b/problems/kamacoder/0099.岛屿的数量深搜.md index 46f7e779..b257ca9a 100644 --- a/problems/kamacoder/0099.岛屿的数量深搜.md +++ b/problems/kamacoder/0099.岛屿的数量深搜.md @@ -185,6 +185,100 @@ int main() { ### Python +版本一 + +```python +direction = [[0, 1], [1, 0], [0, -1], [-1, 0]] # 四个方向:上、右、下、左 + + +def dfs(grid, visited, x, y): + """ + 对一块陆地进行深度优先遍历并标记 + """ + for i, j in direction: + next_x = x + i + next_y = y + j + # 下标越界,跳过 + if next_x < 0 or next_x >= len(grid) or next_y < 0 or next_y >= len(grid[0]): + continue + # 未访问的陆地,标记并调用深度优先搜索 + if not visited[next_x][next_y] and grid[next_x][next_y] == 1: + visited[next_x][next_y] = True + dfs(grid, visited, next_x, next_y) + + +if __name__ == '__main__': + # 版本一 + n, m = map(int, input().split()) + + # 邻接矩阵 + grid = [] + for i in range(n): + grid.append(list(map(int, input().split()))) + + # 访问表 + visited = [[False] * m for _ in range(n)] + + res = 0 + for i in range(n): + for j in range(m): + # 判断:如果当前节点是陆地,res+1并标记访问该节点,使用深度搜索标记相邻陆地。 + if grid[i][j] == 1 and not visited[i][j]: + res += 1 + visited[i][j] = True + dfs(grid, visited, i, j) + + print(res) +``` + +版本二 + +```python +direction = [[0, 1], [1, 0], [0, -1], [-1, 0]] # 四个方向:上、右、下、左 + + +def dfs(grid, visited, x, y): + """ + 对一块陆地进行深度优先遍历并标记 + """ + # 与版本一的差别,在调用前增加判断终止条件 + if visited[x][y] or grid[x][y] == 0: + return + visited[x][y] = True + + for i, j in direction: + next_x = x + i + next_y = y + j + # 下标越界,跳过 + if next_x < 0 or next_x >= len(grid) or next_y < 0 or next_y >= len(grid[0]): + continue + # 由于判断条件放在了方法首部,此处直接调用dfs方法 + dfs(grid, visited, next_x, next_y) + + +if __name__ == '__main__': + # 版本二 + n, m = map(int, input().split()) + + # 邻接矩阵 + grid = [] + for i in range(n): + grid.append(list(map(int, input().split()))) + + # 访问表 + visited = [[False] * m for _ in range(n)] + + res = 0 + for i in range(n): + for j in range(m): + # 判断:如果当前节点是陆地,res+1并标记访问该节点,使用深度搜索标记相邻陆地。 + if grid[i][j] == 1 and not visited[i][j]: + res += 1 + dfs(grid, visited, i, j) + + print(res) +``` + ### Go ### Rust