2015-09-30 41 views
0

當我在用Python IGRAPH圖檢測的社區,我得到的結果是這樣的:設置團體指數與IGRAPH Python中的頂點屬性

print g.community_multilevel(return_levels=False) 

Clustering with 100 elements and 4 clusters 
[0] 16, 17, 18, 20, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 
    36, 37, 39, 40, 44 
[1] 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 19, 38, 92, 94, 96, 
    97, 98, 99 
[2] 42, 43, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 
    61, 62, 63, 64, 66, 67, 69 
[3] 21, 41, 65, 68, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 
    84, 85, 86, 87, 88, 89, 90, 91, 93, 95 

我加入相應的社區數量屬性到像這樣的每個頂點:

for v in g.vs(): 
    c = 0 
    for i in g.community_multilevel(return_levels=False): 
     if v.index in i: 
      print v.index,i,c 
      v["group"] = c 
     c += 1 

有沒有更好的方法來實現這個目標?

回答

1

你正在做的工作非常低效,因爲你爲外部循環的每一次迭代運行社區檢測算法,即使它的結果應該是相同的,無論你運行多少次。一個簡單得多的方法是:

cl = g.community_multilevel(return_levels=False) 
g.vs["group"] = cl.membership