自我网络中自我顶点的 igraph r 约束

如何解决自我网络中自我顶点的 igraph r 约束

我喜欢计算自我网络中顶点的约束（例如，距离 1）。 我想使用应用函数自动执行此操作。

到目前为止，我可以计算自我网络所有顶点的约束。然而，我没有设法选择 ego 的约束，因为 ego 网络中 ego 顶点的位置是不同的（顶点是有序的，并且根据属于 ego 网络的顶点，ego 的位置会有所不同）。

这是一个小样本网络，希望能阐明任务。

谢谢！

library(igraph)



g <- graph.formula( Andre----Beverly:Diane:Fernando:Carol,Beverly--Andre:Diane:Garth:Ed,Carol----Andre:Diane:Fernando,Diane----Andre:Carol:Fernando:Garth:Ed:Beverly,Ed-------Beverly:Diane:Garth,Fernando-Carol:Andre:Diane:Garth:Heather,Garth----Ed:Beverly:Diane:Fernando:Heather,Heather--Fernando:Garth:Ike,Ike------Heather:Jane,Jane--Ike )
g <- simplify(g)
coords <- c(5,5,119,256,120,340,478,622,116,330,231,451,231)
coords <- matrix(coords,nc=2)
V(g)$label <- V(g)$name
g$layout <- coords
plot(g)


ego_1_graph <- make_ego_graph(
 g,order = 1,nodes = V(g),mode = c("all"),mindist = 0
)

# ideally,I would want to calculate Ego's constraint in their ego network and store this value in a data frame with one line for each vertice.


dat <- data.frame(
 Node_ID = names(V(g)),ego_1_cons = lapply(ego_1_graph,constraint) %>% unlist()
 )

# constraint saves the constraint for each vertex in each ego network

# I need to access the individual ego networks (10 = one for each vertex)
# I need to pick the constraint only for the ego vertex

# Problem: vertices are ordered 1-10. 
# Ego networks are constructed from all vertices with connections to the ego vertex or from connections among such vertices.
# Therefore,the ego vertex is not always the first vertex in the ego network. 
#,E.g.:

# Vertex name: Heather (eighth vertex in the complete network)
cons8 <- round(constraint(ego_1_graph[[8]]),4)
cons8 # Heather's constraint is at position 3 of the list because of her connections to Fernando (fourth vertex in the complete network) and Garth (sixth vertex in the complete network)
cons8[[3]]


# How can I select the constraint value for the ego vertex? 
# How Could I automate this for all ego networks in an apply function?```

解决方法

尝试sapply，如下所示

dat <- transform(
  data.frame(
    Node_ID = names(V(g))
  ),ego_1_cons = sapply(
    seq_along(Node_ID),function(k) constraint(ego_1_graph[[k]])[Node_ID[k]]
  )
)

给出

> dat
          Node_ID ego_1_cons
Andre       Andre  0.7044271
Beverly   Beverly  0.7044271
Diane       Diane  0.4984568
Fernando Fernando  0.5541667
Carol       Carol  0.9259259
Garth       Garth  0.5541667
Ed             Ed  0.9259259
Heather   Heather  0.6111111
Ike           Ike  0.5000000
Jane         Jane  1.0000000