for edge in G.edges(): print(edge) 5. 图的可视化 NetworkX提供了一些基本的绘图功能,利用matplotlib可以实现图的可视化。 import matplotlib.pyplot as plt nx.draw(G, with_labels=True) plt.show() 6、详细示例:构建和分析一个简单的社交网络 import networkx as nx import matplotlib.pyplot as plt # ...
G.add_edge('B','D', weight=4) G.add_edge('C','D', weight=1) pos = nx.spring_layout(G) nx.draw(G, pos, with_labels=True) # 获取边的权重 labels = nx.get_edge_attributes(G,'weight') # 绘制带有权重的边 nx.draw_networkx_edge_labels(G, pos, edge_labels=labels) plt.show(...
nx.draw_networkx_edge_labels(G,pos,font_size=12,edge_labels=w) plt.show() 2.有向图 根据以下邻接矩阵创建有向图 # 创建有向图G=nx.DiGraph()List=[(1,2),(1,3),(2,3),(3,2),(3,5),(4,2),(4,6),(5,2),(5,4),(5,6),(6,5)]# 添加顶点和弧G.add_nodes_from(range(1,...
draw_networkx_nodes(G,pos,[nodelist]) 绘制网络G的节点图 draw_networkx_edges(G,pos[edgelist]) 绘制网络G的边图 draw_networkx_edge_labels(G, pos[, ...])绘制网络G的边图,边有label ---有layout 布局画图函数的分界线--- draw_circular(G, **kwargs)Draw the graph G with a circular layout....
您可以使用 draw_networkx_edge_labels(edge_labels) 在边缘之间绘制标签。如果未给出 edge_labels ,则使用边的属性。 edge_labels 应该是由边二元组文本标签键入的字典。仅绘制字典中键的标签。要遍历图形的边缘,您可以使用 G.edges。G.edges returns a list of (node1, node2) , where node1 and node2 ...
draw_networkx_edges(G,pos[edgelist]) 绘制网络G的边图 draw_networkx_edge_labels(G, pos[, ...]) 绘制网络G的边图,边有label ---有layout 布局画图函数的分界线--- draw_circular(G, **kwargs)Draw the graph G with a circular layout. ...
nx.draw(G2,pos,with_labels=True,alpha=0.5) labels=nx.get_edge_attributes(G2,'weight') nx.draw_networkx_edge_labels(G2,pos,edge_labels=labels) plt.show() 3.3 程序运行结果 顶点v1到顶点v11的最短加权路径:[1,2,5,6,3,7,10,9,11] ...
nx.draw_networkx_edge_labels(gAnt,pos,edge_labels=labels, font_color='c') # 显示权值 nx.draw_networkx_nodes(gAnt,pos,nodelist=[0,17],node_color='yellow') # 设置顶点颜色 nx.draw_networkx_nodes(gAnt,pos,nodelist=[7,12],node_color='lime') # 设置顶点颜色 ...
绘制图形,并根据颜色标签进行边的着色:pos = nx.spring_layout(G) # 定义节点的布局 nx.draw_networkx_nodes(G, pos) # 绘制节点 nx.draw_networkx_labels(G, pos) # 绘制节点标签 nx.draw_networkx_edges(G, pos, edge_color=[edge_colors[u][v] for u, v in G.edges()]) # 绘制...
'edge_color':'gray', 'with_labels':True, 'node_shape':'s',# 设置节点的形状 } nx.draw(G, **options) plt.show() # networkx可视化网络:高阶案例,绘制Gephi自带的一个网络 # Gephi可视化如下: fromIPython.displayimportImage Image(filename ='./17.png', width=600, height=450) ...