使用Python生成20个带有AGraph()的标题

以下是使用Python生成20个带有AGraph()的标题，每个标题附带一个使用例子。

1. 图形可视化：使用AGraph()创建一个简单的无向图

import pygraphviz as pgv

G = pgv.AGraph()

G.add_edge('A', 'B')
G.add_edge('B', 'C')
G.add_edge('C', 'A')

G.draw('graph.png')

2. 属性设置：使用AGraph()设置节点和边的属性

import pygraphviz as pgv

G = pgv.AGraph(directed=True)

G.add_edge('A', 'B')
G.add_edge('B', 'C')
G.add_edge('C', 'A')

G.get_node('A').attr['color'] = 'red'
G.get_node('B').attr['color'] = 'blue'
G.get_node('C').attr['color'] = 'green'

G.draw('graph.png')

3. 添加标签：使用AGraph()为节点和边添加标签

import pygraphviz as pgv

G = pgv.AGraph()

G.add_edge('A', 'B', label='Edge 1')
G.add_edge('B', 'C', label='Edge 2')
G.add_edge('C', 'A', label='Edge 3')

G.add_node('D', label='Node 4')

G.draw('graph.png')

4. 修改布局：使用AGraph()修改图形的布局

import pygraphviz as pgv

G = pgv.AGraph(rankdir='LR')

G.add_edge('A', 'B')
G.add_edge('B', 'C')
G.add_edge('C', 'A')

G.draw('graph.png')

5. 删除节点和边：使用AGraph()删除图中的节点和边

import pygraphviz as pgv

G = pgv.AGraph()

G.add_edge('A', 'B')
G.add_edge('B', 'C')
G.add_edge('C', 'A')

G.delete_edge('B', 'C')

G.draw('graph.png')

6. 连接多个图：使用AGraph()连接多个图形

import pygraphviz as pgv

G1 = pgv.AGraph()
G2 = pgv.AGraph()

G1.add_edge('A', 'B')
G2.add_edge('C', 'D')

G = G1 + G2

G.draw('graph.png')

7. 批量添加节点和边：使用AGraph()批量添加节点和边

import pygraphviz as pgv

nodes = ['A', 'B', 'C', 'D']
edges = [('A', 'B'), ('B', 'C'), ('C', 'D'), ('D', 'A')]

G = pgv.AGraph()

G.add_nodes_from(nodes)
G.add_edges_from(edges)

G.draw('graph.png')

8. 图形布局自动调整：使用AGraph()自动调整图形布局

import pygraphviz as pgv

G = pgv.AGraph()

G.add_edge('A', 'B')
G.add_edge('A', 'C')
G.add_edge('A', 'D')

G.layout(prog='dot')

G.draw('graph.png')

9. 获取节点和边的数量：使用AGraph()获取图形中节点和边的数量

import pygraphviz as pgv

G = pgv.AGraph()

G.add_edge('A', 'B')
G.add_edge('B', 'C')
G.add_edge('C', 'D')

num_nodes = len(G.nodes())
num_edges = len(G.edges())

print(f'Number of nodes: {num_nodes}')
print(f'Number of edges: {num_edges}')

10. 节点度分布统计：使用AGraph()统计图形中节点的度分布

import pygraphviz as pgv
import matplotlib.pyplot as plt

G = pgv.AGraph()

G.add_edge('A', 'B')
G.add_edge('B', 'C')
G.add_edge('C', 'D')
G.add_edge('D', 'A')
G.add_edge('C', 'A')

degrees = [G.degree(node) for node in G.nodes()]

plt.hist(degrees)
plt.xlabel('Node Degree')
plt.ylabel('Frequency')
plt.show()

11. 设置节点形状：使用AGraph()设置节点的形状

import pygraphviz as pgv

G = pgv.AGraph()

G.add_edge('A', 'B')
G.add_edge('B', 'C')
G.add_edge('C', 'D')

G.get_node('A').attr['shape'] = 'box'
G.get_node('C').attr['shape'] = 'circle'

G.draw('graph.png')

12. 遍历邻接节点：使用AGraph()遍历节点的邻接节点

import pygraphviz as pgv

G = pgv.AGraph()

G.add_edge('A', 'B')
G.add_edge('B', 'C')
G.add_edge('C', 'D')

neighbors = list(G.neighbors('B'))

print(f'Neighbors of B: {neighbors}')

13. 寻找最短路径：使用AGraph()查找最短路径

import pygraphviz as pgv

G = pgv.AGraph()

G.add_edge('A', 'B', weight=3)
G.add_edge('A', 'C', weight=2)
G.add_edge('B', 'C', weight=1)
G.add_edge('C', 'D', weight=4)

path = G.shortest_path('A', 'D', weight='weight')

print(f'Shortest path from A to D: {path}')

14. 节点聚类分析：使用AGraph()进行节点聚类分析

import pygraphviz as pgv
import networkx as nx

G = pgv.AGraph()

G.add_edge('A', 'B')
G.add_edge('B', 'C')
G.add_edge('C', 'D')
G.add_edge('D', 'E')
G.add_edge('E', 'F')
G.add_edge('F', 'A')

G_nx = nx.nx_agraph.from_agraph(G)
clusters = nx.algorithms.community.greedy_modularity_communities(G_nx)

print(f'Clusters: {clusters}')

15. 图形可视化样式定制：使用AGraph()自定义图形可视化样式

import pygraphviz as pgv

G = pgv.AGraph()

G.add_edge('A', 'B')
G.add_edge('B', 'C')
G.add_edge('C', 'D')

G.node_attr['shape'] = 'box'
G.edge_attr['color'] = 'red'

G.draw('graph.png')

16. 图形布局类型选择：使用AGraph()选择不同的图形布局类型

import pygraphviz as pgv

G = pgv.AGraph()

G.add_edge('A', 'B')
G.add_edge('A', 'C')
G.add_edge('A', 'D')

G.layout(prog='neato')  # 使用neato布局

G.draw('graph.png')

17. 图形截图和保存：使用AGraph()截图并保存图形

import pygraphviz as pgv

G = pgv.AGraph()

G.add_edge('A', 'B')
G.add_edge('B', 'C')
G.add_edge('C', 'D')

# 截图一部分图形
G.drawable_areas([(100, 100, 300, 300)])

G.draw('graph.png')

18. 使用节点属性进行筛选：使用AGraph()使用节点属性进行筛选

import pygraphviz as pgv

G = pgv.AGraph()

G.add_edge('A', 'B', weight=3)
G.add_edge('A', 'C', weight=2)
G.add_edge('B', 'C', weight=1)
G.add_edge('C', 'D', weight=4)

filtered_edges = [edge for edge in G.edges() if G.get_edge(*edge).attr['weight'] > 2]

print(f'Filtered edges: {filtered_edges}')

19. 图形格式转换：使用AGraph()将图形转换为不同的格式

import pygraphviz as pgv

G = pgv.AGraph()

G.add_edge('A', 'B')
G.add_edge('B', 'C')
G.add_edge('C', 'D')

G.write('graph.dot')  # 将图形写入.dot文件
G.draw('graph.png')  # 将图形保存为PNG文件
G.draw('graph.pdf')  # 将图形保存为PDF文件

20. 导入和导出图形数据：使用AGraph()导入