图的两种遍历方法及对应的生成树。自己编写源程序，把图的深度优先遍历、广度优先遍历改为输出深度优先生成树、广度优先生成树。

以下是深度优先生成树的代码实现：

from collections import defaultdict

class Graph:
    def __init__(self):
        self.graph = defaultdict(list)

    def add_edge(self, u, v):
        self.graph[u].append(v)
        self.graph[v].append(u)

    def DFS(self, v, visited, parent, dfs_tree):
        visited[v] = True

        for i in self.graph[v]:
            if not visited[i]:
                parent[i] = v
                dfs_tree[v].append(i)
                self.DFS(i, visited, parent, dfs_tree)

    def DFS_Tree(self, start):
        visited = defaultdict(bool)
        parent = defaultdict(int)
        dfs_tree = defaultdict(list)

        self.DFS(start, visited, parent, dfs_tree)

        return dfs_tree

以下是广度优先生成树的代码实现：

from collections import defaultdict, deque

class Graph:
    def __init__(self):
        self.graph = defaultdict(list)

    def add_edge(self, u, v):
        self.graph[u].append(v)
        self.graph[v].append(u)

    def BFS(self, start, visited, parent, bfs_tree):
        queue = deque()
        queue.append(start)
        visited[start] = True

        while queue:
            v = queue.popleft()

            for i in self.graph[v]:
                if not visited[i]:
                    visited[i] = True
                    parent[i] = v
                    bfs_tree[v].append(i)
                    queue.append(i)

    def BFS_Tree(self, start):
        visited = defaultdict(bool)
        parent = defaultdict(int)
        bfs_tree = defaultdict(list)

        self.BFS(start, visited, parent, bfs_tree)

        return bfs_tree

以上两个类中，DFS和BFS方法用于进行深度优先遍历和广度优先遍历，而DFS_Tree和BFS_Tree方法则是对应的深度优先生成树和广度优先生成树。其中，dfs_tree和bfs_tree分别为存储生成树的字典。