igraph：总结每个节点的邻居特征答案

【问题标题】：igraph: summarize each node's neighbours characteristicsigraph：总结每个节点的邻居特征
【发布时间】：2020-12-07 16:47:06
【问题描述】：

使用 igraph 对象我想捕获每个节点的邻居的一些特征，例如其邻居的平均度数。

我想出了这段代码，它不优雅而且很慢。对于大型复杂的网络，我应该如何重新考虑它？

library(igraph)

# Toy example
set.seed(123)
g <- erdos.renyi.game(10,0.2)

# Loop to calculate average degree of each node's neighbourhood
s <- character(0)
for(i in 1:gorder(g)){
  n <- ego_size(g, nodes = i, order = 1, mindist = 1)
  node_of_interest <- unique(unlist(ego(g, nodes = i, order = 1, mindist = 1)))
  m <- mean(degree(g, v = node_of_interest, loops = TRUE, normalized = FALSE)-1)
  
  s <- rbind(s,data.frame(node = i, neighbours = n, mean = m))

}

【问题讨论】：

标签： r for-loop igraph neighbours

【解决方案1】：

在循环中使用rbind 扩展数据结构在R 中会变得非常慢，因为在每一步它都需要为新对象分配空间，然后复制它（参见第24.6 节here）。此外，如果一个节点是多个节点的邻居，您可能会多次计算该节点的度数。

一个可能更好的选择可能是：

# add vertex id (not really necessary)
V(g)$name <- V(g) 

# add degree to the graph
V(g)$degree <- degree(g, loops = TRUE, normalized = FALSE)

# get a list of neighbours, for each node
g_ngh <- neighborhood(g, mindist = 1) 

# write a function that gets the means                       
get.mean <- function(x){
  mean(V(g)$degree[x]-1)
}

# apply the function, add result to the graph
V(g)$av_degr_nei <- sapply(g_ngh, get.mean)


# get data into dataframe, if necessary
d_vert_attr <- as_data_frame(g, what = "vertices")

d_vert_attr
   name degree av_degr_nei
1     1      0         NaN
2     2      1   2.0000000
3     3      2   1.0000000
4     4      1   1.0000000
5     5      2   1.0000000
6     6      1   1.0000000
7     7      3   0.6666667
8     8      1   0.0000000
9     9      1   0.0000000
10   10      0         NaN

【讨论】：