如何扩展元素列表并绘制它们

Question

我在网络中检测到一些社区，我想使该过程尽可能自动化，尤其是在检测到大量社区时。我使用的代码是

from networkx.algorithms.community.modularity_max 
import greedy_modularity_communities

c = list(greedy_modularity_communities(G))

检测到 3 个社区。要查看集群并绘制它们，我通常运行以下内容：

community_0 = sorted(c[0])
community_1 = sorted(c[1])
community_2 = sorted(c[2])

并绘制每组节点：

nx.draw_networkx_nodes(G,circ_pos, nodelist=community_0, node_color='g', alpha=0.5)
nx.draw_networkx_nodes(G,circ_pos, nodelist=community_1, node_color='r', alpha=0.5)
nx.draw_networkx_nodes(G,circ_pos, nodelist=community_2, node_color='b', alpha=0.5)

其中 G 是 G = nx.karate_club_graph()。我的问题是如何扩展 community_x 的列表，即可以使用 greedy_modularity_communities 检测到的 x 个社区，并绘制它们，在节点列表中迭代添加参数。

Answer 1

使用python eval() 函数并搜索元编程概念。

我为您提供了一些示例代码：

for i in range(1,3):
    eval('community_'+str(i)+' = sorted(c['+str(i)+']))'

Answer 2

我会这样做：

from networkx.algorithms.community.modularity_max 
import greedy_modularity_communities

# list of detected communities 
c = list(greedy_modularity_communities(G))
sortedCommunities = []

# iterate through list of discovered communities. Sort each community and add them to new list.

for community in c:
    sortedCommunities.append(sorted(community))

# draw community
# here we are using a different color at each iteration but cycling back to the first color.

colors = ['g', 'r', 'b']
temp_counter = 0
for community in sortedCommunities:
    
    chosenColor = colors[temp_counter%3]
    temp_counter += 1
    nx.draw_networkx_nodes(G,circ_pos, nodelist=community , node_color=chosenColor , alpha=0.5)

如何扩展元素列表并绘制它们

How to extend a list of elements and draw them

python

networkx

pandas