LNR-server-02-cascading-failure-scenario-simulatio

import json import networkx as nx def identify_critical_facilities_considering_closeness(global_json_path): """ 读取 Global_Data.json 中的 present_network，计算每个节点的 closeness centrality 值，将其写入新的 JSON 文件 network_with_closeness.json， 并将文件路径保存回 Global_Data.json。 :param global_json_path: Global_Data.json 文件路径。 """ # 读取 Global_Data.json 文件以获取 present_network 的路径 with open(global_json_path, 'r') as f: file_paths = json.load(f) # 获取 present_network 文件的路径 network_path = file_paths.get('interdependent_infrastructure_networks') if not network_path: print("present_network path not found in Global_Data.json.") return # 读取 present_network.json 文件 with open(network_path, 'r') as f: present_network_data = json.load(f) # 创建有向图 G_present = nx.DiGraph() # 添加节点，并将 Coordinates 作为 pos 属性 for node in present_network_data['nodes']: G_present.add_node(node['Code'], layer=node['Infrastructure Type'], pos=(node['Coordinates'][0], node['Coordinates'][1])) # 添加边 for edge in present_network_data['edges']: G_present.add_edge(edge['Start'], edge['End']) # 计算每个节点的 closeness centrality 值 closeness_values = nx.closeness_centrality(G_present) # 将 closeness centrality 信息添加到节点数据中 for node in present_network_data['nodes']: node['closeness'] = closeness_values.get(node['Code'], 0) # 保存新的网络数据到 network_with_closeness.json 文件 output_json_path = 'facility_importance_using_closeness_centrality.json' with open(output_json_path, 'w') as f: json.dump(present_network_data, f, indent=4) print(f"Network with closeness centrality values saved to {output_json_path}") # 更新 Global_Data.json 文件，保存新的 network_with_closeness.json 文件路径 file_paths['facility_importance_using_closeness_centrality'] = output_json_path with open(global_json_path, 'w') as f: json.dump(file_paths, f, indent=4) print(f"Global_Data.json updated with network_with_closeness path.")