什么是图？

注意: 图表示为 $G(V, E)$，其中 $V$ 是顶点/节点构成的集合，$E$ 是边/链接构成的集合，因此 $u ∈ V$，$v ∈ V$，且 $(u,v) ∈ E$。

1import networkx as nx
2import matplotlib.pyplot as plt
3
4# 创建图的实例
5G = nx.Graph()
6
7# 添加节点
8G.add_node(1)
9G.add_node(2)
10G.add_node(3)
11G.add_node(4)
12
13# 添加边
14G.add_edge(1, 2)
15G.add_edge(1, 3)
16G.add_edge(1,4)
17
18# 可视化图
19plt.figure()
20nx.draw(G, with_labels=True, node_size=1000, font_size=30)

1import networkx as nx
2import matplotlib.pyplot as plt
3
4# 随机图
5G = nx.erdos_renyi_graph(100, 0.15)
6
7# 可视化图
8fig, ax = plt.subplots(figsize=(3, 2),dpi=300)
9fig.patch.set_linewidth(1)
10fig.patch.set_edgecolor('black')
11nx.draw(G, with_labels=True, node_size=25,width=0.2, font_size=3)

1import networkx as nx
2
3G = nx.erdos_renyi_graph(100, 0.15)
4number_of_nodes = nx.number_of_nodes(G)
5print("Total number of nodes: ",number_of_nodes)

1import networkx as nx
2
3G = nx.erdos_renyi_graph(100, 0.15)
4number_of_edges = nx.number_of_edges(G)
5print("Total number of edges: ",number_of_edges)

1import networkx as nx
2
3G = nx.erdos_renyi_graph(100, 0.15)
4degree = dict(nx.degree(G))
5print("Type of variable: ",type(degree))
6print("Degree of node 42: ",degree[42])