R：识别图中的点（可能用 dplyr？）

Question

我发现以前的 Whosebug post 处理了我遇到的类似问题，但答案并不完全相同：

我在 R 中创建了一些数据，然后制作了图表。做出图后，我对图进行了聚类。现在，假设我有一个人的列表，我想找出他们属于哪个集群。

我知道手动检查数据并找出这一点很容易，但我认为如果你有一个大数据集，这将很难做到。

我写了下面的代码。一切正常，直到最后两行我试图找出“John”、“Peter”和“Tim”属于哪些集群：

#load libraries
        library(igraph) 
    library(dplyr)
    

#create data
        Data_I_Have <- data.frame(
               
                "Node_A" = c("John", "John", "John", "Peter", "Peter", "Peter", "Tim", "Kevin", "Adam", "Adam", "Xavier"),
                "Node_B" = c("Claude", "Peter", "Tim", "Tim", "Claude", "Henry", "Kevin", "Claude", "Tim", "Henry", "Claude")
                
            )

#create graph
               
                graph <- graph.data.frame( Data_I_Have, directed=F)
                graph <- simplify(graph)
    
#perform clustering
        cluster = cluster_louvain(graph)

#plot graph
            plot(graph, cluster)

#make list of people
people <- c("John", "Peter", "Tim")

#find out which cluster each of these people belong in (here is the error)
location <- names("people")[!(names("people") %in% cluster)]

#transform the previous data frame into a table
location_table <- table(location)

有人可以告诉我我做错了什么吗？

谢谢

Answer 1

顶点的成员资格在 $membership 中，顶点的名称在 $names 中：

cluster$membership[match(people,cluster$names)]
#[1] 2 3 1

或者，如果您愿意，可以使用访问器函数 igraph::membership:

membership(cluster)[people]
# John Peter   Tim 
#    2     3     1

有关详细信息，请参阅 help(communities)。

示例数据：

cluster <- structure(list(membership = c(2, 3, 1, 1, 1, 2, 2, 3), memberships = structure(c(2, 
3, 1, 1, 1, 2, 2, 3), .Dim = c(1L, 8L)), modularity = 0.115702479338843, 
    names = c("John", "Peter", "Tim", "Kevin", "Adam", "Xavier", 
    "Claude", "Henry"), vcount = 8L, algorithm = "multi level"), class = "communities")

R：识别图中的点（可能用 dplyr？）

R: identifying points in a graph (possible with dplyr?)

r

data-visualization

graph

nodes

dplyr