init: KG_ICH 项目初始化

- data/: 非遗地理编码数据（GIS shapefile + CSV）
- dofile/kg_project/: 知识图谱构建代码（纳入主仓库）
- dofile/visulization/: 可视化数据与路线图
- officefile/: 文献、草稿、bib 文档
- officefile/latex/: Overleaf 同步目录（独立管理，不纳入）
- output/: 输出目录
- logs/: 日志目录

dofile/kg_project/merge_kg_data.py

@@ -0,0 +1,155 @@
+# -*- coding: utf-8 -*-
+"""
+整合基础政务实体和深层语义实体
+方案3：合并项目节点，完全整合
+"""
+
+import pandas as pd
+import json
+from pathlib import Path
+
+def merge_kg_data():
+    """整合知识图谱数据"""
+
+    output_dir = Path(__file__).parent / 'output'
+
+    # 读取4个文件
+    print("=== 读取原始文件 ===")
+    nodes_basic = pd.read_csv(output_dir / 'nodes.csv', encoding='utf-8-sig')
+    nodes_deep = pd.read_csv(output_dir / 'nodes_desc.csv', encoding='utf-8-sig')
+    rels_basic = pd.read_csv(output_dir / 'rels.csv', encoding='utf-8-sig')
+    rels_deep = pd.read_csv(output_dir / 'rels_desc.csv', encoding='utf-8-sig')
+
+    print(f"基础节点: {len(nodes_basic)}")
+    print(f"深层节点: {len(nodes_deep)}")
+    print(f"基础关系: {len(rels_basic)}")
+    print(f"深层关系: {len(rels_deep)}")
+
+    # 1. 合并ICH项目节点
+    print("\n=== 合并ICH项目节点 ===")
+    basic_projects = nodes_basic[nodes_basic['type'] == 'ICH_Project'].copy()
+    deep_projects = nodes_deep[nodes_deep['type'] == 'ICH_Project'].copy()
+
+    print(f"基础项目节点: {len(basic_projects)}")
+    print(f"深层项目节点: {len(deep_projects)}")
+
+    # 合并项目节点的属性
+    merged_projects = []
+
+    for pid in basic_projects['id']:
+        basic_row = basic_projects[basic_projects['id'] == pid].iloc[0]
+
+        # 查找深层项目节点
+        deep_row = deep_projects[deep_projects['id'] == pid]
+
+        if len(deep_row) > 0:
+            # 合并属性
+            deep_row = deep_row.iloc[0]
+
+            # 解析属性JSON
+            basic_props = json.loads(basic_row['properties']) if basic_row['properties'] else {}
+            deep_props = json.loads(deep_row['properties']) if deep_row['properties'] else {}
+
+            # 合并属性（深层属性优先）
+            merged_props = {**basic_props, **deep_props}
+
+            merged_projects.append({
+                'id': pid,
+                'label': basic_row['label'],  # 保留基础标签
+                'type': 'ICH_Project',
+                'properties': json.dumps(merged_props, ensure_ascii=False)
+            })
+        else:
+            # 只在基础中存在
+            merged_projects.append({
+                'id': pid,
+                'label': basic_row['label'],
+                'type': 'ICH_Project',
+                'properties': basic_row['properties']
+            })
+
+    print(f"合并后项目节点: {len(merged_projects)}")
+
+    # 2. 合并其他节点（去除ICH_Project）
+    print("\n=== 合并其他节点 ===")
+    other_basic_nodes = nodes_basic[nodes_basic['type'] != 'ICH_Project']
+    other_deep_nodes = nodes_deep[nodes_deep['type'] != 'ICH_Project']
+
+    all_nodes = pd.concat([
+        pd.DataFrame(merged_projects),
+        other_basic_nodes,
+        other_deep_nodes
+    ], ignore_index=True)
+
+    print(f"合并后总节点数: {len(all_nodes)}")
+    print(f"  - ICH_Project: {len(merged_projects)}")
+    print(f"  - 其他节点: {len(all_nodes) - len(merged_projects)}")
+
+    # 3. 合并关系
+    print("\n=== 合并关系 ===")
+    all_rels = pd.concat([rels_basic, rels_deep], ignore_index=True)
+
+    # 去重关系
+    all_rels = all_rels.drop_duplicates(subset=['source', 'target', 'type'], keep='first')
+
+    print(f"合并后关系数: {len(all_rels)}")
+
+    # 4. 统计信息
+    print("\n=== 整合后统计 ===")
+    print(f"总节点数: {len(all_nodes)}")
+    print(f"总关系数: {len(all_rels)}")
+
+    print("\n节点类型分布:")
+    for ntype, count in all_nodes.groupby('type').size().items():
+        print(f"  {ntype}: {count}")
+
+    print(f"\n关系类型数量: {len(all_rels['type'].unique())}")
+
+    # 5. 保存整合后的文件
+    print("\n=== 保存整合文件 ===")
+    output_file_nodes = output_dir / 'kg_merged_nodes.csv'
+    output_file_rels = output_dir / 'kg_merged_rels.csv'
+
+    all_nodes.to_csv(output_file_nodes, index=False, encoding='utf-8-sig')
+    all_rels.to_csv(output_file_rels, index=False, encoding='utf-8-sig')
+
+    print(f"节点已保存: {output_file_nodes}")
+    print(f"关系已保存: {output_file_rels}")
+
+    # 6. 验证
+    print("\n=== 验证 ===")
+
+    # 检查项目节点完整性
+    project_count = len(all_nodes[all_nodes['type'] == 'ICH_Project'])
+    print(f"ICH项目节点数: {project_count} (应该是268)")
+
+    # 检查关系完整性
+    rel_sources = set(all_rels['source'].unique())
+    node_ids = set(all_nodes['id'].unique())
+
+    missing_sources = rel_sources - node_ids
+    if missing_sources:
+        print(f"警告: {len(missing_sources)} 个关系的源节点不在节点文件中")
+    else:
+        print("所有关系的源节点都存在于节点文件中")
+
+    # 统计每个项目的关系数
+    project_rels = all_rels[all_rels['source'].str.startswith('ICH-')].groupby('source').size()
+    print(f"\n有关系的项目数: {len(project_rels)}/268")
+
+    # 展示几个示例项目的统计
+    print("\n示例项目关系统计:")
+    sample_projects = ['ICH-1', 'ICH-118', 'ICH-229']
+    for pid in sample_projects:
+        basic_rel_count = len(rels_basic[rels_basic['source'] == pid])
+        deep_rel_count = len(rels_deep[rels_deep['source'] == pid])
+        total_rel_count = len(all_rels[all_rels['source'] == pid])
+        print(f"  {pid}: 基础{basic_rel_count} + 深层{deep_rel_count} = 总计{total_rel_count} 条关系")
+
+    print("\n完成！")
+
+    return all_nodes, all_rels
+
+
+if __name__ == '__main__':
+    merge_kg_data()