数据结构图的表示与遍历实验代码

好的，以下是一个简单的Python代码示例，实现了图的邻接矩阵表示方法、深度优先遍历算法和广度优先遍历算法：

class Graph:
    def __init__(self, nodes):
        self.nodes = nodes
        self.edges = [[0] * len(nodes) for i in range(len(nodes))]

    def add_edge(self, u, v):
        self.edges[u][v] = 1
        self.edges[v][u] = 1

    def remove_edge(self, u, v):
        self.edges[u][v] = 0
        self.edges[v][u] = 0

    def dfs(self, start_node):
        visited = [False] * len(self.nodes)
        stack = [start_node]
        while stack:
            node = stack.pop()
            if not visited[node]:
                print(node)
                visited[node] = True
                for i in range(len(self.nodes)):
                    if self.edges[node][i] and not visited[i]:
                        stack.append(i)

    def bfs(self, start_node):
        visited = [False] * len(self.nodes)
        queue = [start_node]
        while queue:
            node = queue.pop(0)
            if not visited[node]:
                print(node)
                visited[node] = True
                for i in range(len(self.nodes)):
                    if self.edges[node][i] and not visited[i]:
                        queue.append(i)

# 测试代码
nodes = [0, 1, 2, 3, 4]
graph = Graph(nodes)
graph.add_edge(0, 1)
graph.add_edge(0, 2)
graph.add_edge(1, 2)
graph.add_edge(2, 3)
graph.add_edge(3, 4)
graph.dfs(0)
graph.bfs(0)

以上代码实现了一个简单的图类 `Graph`，包括初始化函数、添加边函数、删除边函数、深度优先遍历函数和广度优先遍历函数。在测试代码中，我们创建了一个包含5个节点的图，并添加了5条边，然后对该图进行了深度优先遍历和广度优先遍历。