from pyvis.network import Network
import json
import matplotlib.pyplot as plt
import networkx as nx

# 读取JSON知识图谱数据
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',
          encoding='utf-8') as f:
    data = json.load(f)

# 创建networkx图
G = nx.Graph()

# 添加节点
for node in data['nodes']:
    G.add_node(node['id'], name=node['id'][0:4])

for edge in data['links']:
    G.add_edge(edge['source'], edge['target'])

# 绘制知识图谱
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False
plt.figure(figsize=(16, 12), dpi=300)  # 增加DPI

# 使用更分散的布局算法
pos = nx.spring_layout(G, k=0.3, iterations=50)  # 增加k值和迭代次数

# 减少节点大小并增加透明度
nx.draw_networkx_nodes(G, pos, node_size=20, node_color="skyblue", alpha=0.7)
nx.draw_networkx_edges(G, pos, edge_color="gray", alpha=0.3, width=0.5)

# 优化标签显示
labels = {n: G.nodes[n]['name'] for n in G.nodes()}
nx.draw_networkx_labels(G, pos, labels=labels, font_size=8)

plt.title("华为反馈的知识图谱一", fontsize=20)
plt.axis("off")
plt.tight_layout()
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
plt.show()