avigdorz / adaptive-structural-fingerprint Goto Github PK

    for i, is_neighbor in enumerate(ri_index):
        for j, js_neighbor in enumerate(ri_index):
            intersection = list(set(is_neighbor).intersection(set(js_neighbor)))
            union = list(set(is_neighbor).union(set(js_neighbor)))
            union_rest = list(set(union).difference(set(intersection)))
    
            intersection_ri_all_i, intersection_ri_all_j = [], []
            union_ri_all_i, union_ri_all_j = [], []
            adj_delta[i][j] = 0
            if len(intersection) == 0:
                adj_delta[i][j] = 0.0001
                break
            **elif len(union_rest) == 0: # correct : intersection == union case simliarytiy maximum
                adj_delta[i][j] = 1.0
                break**
            else:
                for inter_neighbor in intersection:
                    intersection_ri_all_i.append(ri_all[i][is_neighbor.tolist().index(inter_neighbor)])
                    intersection_ri_all_j.append(ri_all[j][js_neighbor.tolist().index(inter_neighbor)])
    
                for rest_neighbor in union_rest:
                    if rest_neighbor in is_neighbor:
                        union_ri_all_i.append(ri_all[i][is_neighbor.tolist().index(rest_neighbor)])
                        union_ri_all_j.append(0)
                    else:
                        union_ri_all_j.append(ri_all[j][js_neighbor.tolist().index(rest_neighbor)])
                        union_ri_all_i.append(0)
    
                k_max = max(intersection_ri_all_j, intersection_ri_all_i)
                k_min = min(intersection_ri_all_j, intersection_ri_all_i)
                **final_max = k_max + union_ri_all_j + union_ri_all_i # correct** 
    
                union_num = np.sum(np.array(final_max), axis=0)
                inter_num = np.sum(np.array(k_min), axis=0)
    
                adj_delta[i][j] = inter_num/union_num

# calculate n-hop neighbors
    G = nx.DiGraph()
    # inf = pickle.load(open('adj_citeseer.pkl', 'rb'))
    inf = pickle.load(open("data/citeseer/ind.citeseer.graph", "rb"), encoding="latin1")
    for i in range(len(inf)):
        for j in range(len(inf[i])):
            G.add_edge(i, inf[i][j], weight=1)
    for i in range(3312):
          for j in range(3312):
              try:
                  rs = nx.astar_path_length \
                          (
                          G,
                          i,
                          j,
                      )
              except nx.NetworkXNoPath:
                 rs = 0
              if rs == 0:
                  length = 0
              else:
                  # print(rs)
                  length = len(rs)
              adj_delta[i][j] = length