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# 导入pipmaster模块用于检查并安装依赖包
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import pipmaster as pm
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# 检查并安装pyvis库（用于可视化网络图）
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if not pm.is_installed("pyvis"):
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pm.install("pyvis")
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# 检查并安装networkx库（用于处理图结构数据）
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if not pm.is_installed("networkx"):
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pm.install("networkx")
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# 导入必要的库
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import networkx as nx # 用于创建和操作复杂的网络结构
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from pyvis.network import Network # 用于交互式网络可视化
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import random # 用于生成随机颜色
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# 从GraphML文件读取知识图谱数据
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# 文件路径: ./dickens/graph_chunk_entity_relation.graphml
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G = nx.read_graphml("Topic/Chinese/graph_chunk_entity_relation.graphml")
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# 创建pyvis网络可视化对象
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# 参数说明:
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# height="100vh" - 设置可视化高度为100%视口高度
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# notebook=True - 设置为在notebook环境中使用
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net = Network(height="100vh", notebook=True)
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# 将networkx图转换为pyvis网络图
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net.from_nx(G)
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# 为每个节点设置随机颜色和提示信息
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for node in net.nodes:
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# 生成随机十六进制颜色代码
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node["color"] = "#{:06x}".format(random.randint(0, 0xFFFFFF))
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# 如果节点有description属性，设置为鼠标悬停提示
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if "description" in node:
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node["title"] = node["description"]
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# 为每条边设置提示信息
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for edge in net.edges:
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# 如果边有description属性，设置为鼠标悬停提示
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if "description" in edge:
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edge["title"] = edge["description"]
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# 生成并显示HTML格式的可视化结果
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# 输出文件: knowledge_graph.html
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net.show("./Html/knowledge_graph.html")
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