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42 lines
1.4 KiB
42 lines
1.4 KiB
from pyvis.network import Network
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import json
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import matplotlib.pyplot as plt
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import networkx as nx
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# 读取JSON知识图谱数据
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with open(r'D:\dsWork\dsProject\dsLightRag\Doc\史校长资料\技术一-知识图谱源文件\middle_school_math_graph.json',
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encoding='utf-8') as f:
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data = json.load(f)
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# 创建networkx图
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G = nx.Graph()
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# 添加节点
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for node in data['nodes']:
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G.add_node(node['id'], name=node['id'][0:4])
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for edge in data['links']:
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G.add_edge(edge['source'], edge['target'])
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# 绘制知识图谱
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plt.rcParams['font.sans-serif'] = ['SimHei']
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plt.rcParams['axes.unicode_minus'] = False
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plt.figure(figsize=(16, 12), dpi=300) # 增加DPI
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# 使用更分散的布局算法
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pos = nx.spring_layout(G, k=0.3, iterations=50) # 增加k值和迭代次数
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# 减少节点大小并增加透明度
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nx.draw_networkx_nodes(G, pos, node_size=20, node_color="skyblue", alpha=0.7)
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nx.draw_networkx_edges(G, pos, edge_color="gray", alpha=0.3, width=0.5)
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# 优化标签显示
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labels = {n: G.nodes[n]['name'] for n in G.nodes()}
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nx.draw_networkx_labels(G, pos, labels=labels, font_size=8)
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plt.title("华为反馈的知识图谱一", fontsize=20)
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plt.axis("off")
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plt.tight_layout()
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plt.savefig('华为反馈的知识图谱【技术一】.png', format='png', bbox_inches='tight', dpi=300) # 保存为PNG
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plt.show()
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