我想按照here的要求做同样的事情,使用问题中的第一种方法。
遗憾的是,以下行中的
mods
变量未定义,我问自己如何调整:
g2 <- delete.edges(out, wc$removed.edges[seq(length = which.max(mods) - 1)])
但是,我猜函数
edge.betweenness.community
是旧的,我使用的新版本调整如下:
wc <- cluster_edge_betweenness(out, weights = (E(out)$value, directed = FALSE, bridges = TRUE, membership = TRUE, modularity = TRUE)
然而,我很难调整
delete.edge
功能 –
第一次调用删除了太多边,第二次调用删除了太多边:
out2 <- delete.edges(out, wc$removed.edges[seq(length = which.max(wc$modularity))])
out2 <- delete.edges(out, wc$removed.edges[which.max(wc$modularity)])
为了完整起见,我添加了引用问题中的数据:
from to value sourceID targetID
1 74 80 0.2829 255609 262854
2 74 61 0.2880 255609 179585
3 80 1085 0.2997 262854 3055482
4 1045 1046 0.1842 2970629 2971615
5 1046 1085 0.2963 2971615 3055482
6 1046 1154 0.2714 2971615 3087803
7 1085 1154 0.2577 3055482 3087803
8 1085 1187 0.2850 3055482 3101131
9 1085 1209 0.2850 3055482 3110186
10 1154 1243 0.2577 3087803 3130848
11 1154 1187 0.2305 3087803 3101131
12 1154 1209 0.2305 3087803 3110186
13 1154 1244 0.2577 3087803 3131379
14 1243 1187 0.1488 3130848 3101131
15 1243 1209 0.1488 3130848 3110186
16 1243 1244 0.1215 3130848 3131379
17 1243 1281 0.2997 3130848 3255811
我认为您可以使用
delete.edges
+ disjoint_union
,而不是使用 induced_subgraph
,如下所示
g <- graph_from_data_frame(df)
ceb <- cluster_edge_betweenness(g)
out <- do.call(
disjoint_union,
lapply(groups(ceb), \(x) induced_subgraph(g, x))
)
情节看起来像
par(mfrow = c(2, 1))
plot(ceb, g, main = "Edge betweenness")
plot(cluster_edge_betweenness(out), out, main = "Disjoint union")