我正在使用 igraph R 包进行一些网络分析。
我必须操纵一个有向的加权邻接矩阵（从具有函数_as_adjacency_matrix（...）_的igraph对象中提取，以获得考虑到 两个节点的传入链接的数量和权重的不同矩阵互相分享。
假设有 4 个节点：节点A连接到节点C，节点B连接到A，节点C连接到节点A和B，节点D连接到A并且所有链接都被定向。
在此设置中，A和B共享来自C的向内链路，但没有其他节点共享任何传入链路。
因此，我想创建一个能够从原始邻接列表创建有向加权邻接列表的例程，其中每个条目 [i,j] 表示节点 i,j 彼此共享的传入边值的总和。
结果必须是一个对称的逻辑矩阵（只有真/假值），位于结果“公共链接”邻接矩阵的前面，而该邻接矩阵是有向的。
回到我做的例子，只有条目 [ A , B ] 和 [ B , A ] 应该有一个非零值，等于来自共享连接节点的向内边的值（[ A , B ] 应该包含 [ C -> A ] 值，而 [ B , A ] 应该包含 [ C -> B ] 值）。
任何关于它的建议将不胜感激
有趣但定义有点模糊的问题。我在理解您想要的输出时遇到了一些麻烦，但我想我明白了。我在下面的第一次尝试中留下了代码。您提供的示例数据我称之为g.
无论哪种方式，我认为您可以从这个代码示例中获得很多东西。我非常愿意以一种更聪明的方式来做到这一点而无需循环以提高速度，但这是我能想到的最具教学意义的代码，因为我不确定所需的输出。
如果我正确理解您的问题，您所要求的将在列表 ul 中输出，其中ul[[x]][[3]]包含图的 E()，其中边从节点 i ( ul[[x]][[1]]) 到 i 和 j 共享传入链接的每个节点图g。
library(igraph)
# Assume 4 nodes:
# - node A is connected to node C,
# - node B is connected to A,
# - node C is connected to node A and B,
# - node D connected to A
m <- matrix(ncol=4,c(0,0,1,0,
1,0,0,0,
1,1,0,0,
1,0,0,0), byrow=T)
colnames(m) <- rownames(m) <- c("A","B","C","D")
# Uncomment this stuff to use random network instead
# g <- erdos.renyi.game(n=12, 16, type="gnm", directed=TRUE, loops=FALSE)
# m <- as.matrix(as_adjacency_matrix(g))
# Check that the data is ok
graph_from_adjacency_matrix(m, mode="directed")
g <- graph_from_adjacency_matrix(m, mode="directed")
# Directed weighted adjacency list from the original one, where
# each entry [i,j] represents the sum of the value of incoming
# edge that node i,j share with each other.
# I first missunderstood your question and wrote this output
# This output will be an edgelist containing node-pairs i and j and
# the strength related to the number of other nodes whith which they
# share incoming links.
el <- matrix(ncol=3, nrow=0)
colnames(el) <- c("i","j","strength")
# I then reread your question and made this output containing a list
# wehre every node-pair which share incoming links from the same nodes
# contain the E()-object of igraph-edges from i to each of the nodes
# from which both i and j recieve incoming links in the graph g.
ul <- list()
# Use the empty graph like g to build edgelists
temp.g <- g %>% delete_edges(E(g)) # an empty graph
for(i in V(g)){
for(j in V(g)){
# Each node pair is i j for every node in g
if(i == j){next}
# Neighborhod() lists linked nodes, in this case at the distance
# of exactly 1 (mindist and order) for node x using the "in"-coming
# links:
in.to.i <- neighborhood(g, order=1, nodes=i, mode="in", mindist=1)
in.to.j <- neighborhood(g, order=1, nodes=j, mode="in", mindist=1)
# These are the nodes which all link to both i and j
shared.incoming <- intersect(in.to.i[[1]], in.to.j[[1]])
# Make a new graph (gg) with links from each node FROM which i and j both
# share incoming ties in g TO i.
# In the edgelist ul, each row can be read like:
# In graph g, "i" has "edges" incoming ties in common with "j"
gg <- temp.g %>% add_edges(unlist(lapply(shared.incoming, function(x) c(x,i)) ))
# E(gg) is what you want. Add it to the output-list
ul[[length(ul)+1]] <- list(i, j, as_edgelist(gg, names=T))
# how many nodes link to both i and j?
el <- rbind(el,c("i"=i, "j"=j, "edges"=length(shared.incoming) ) )
}
}
# The whole list of el contains all possible pairs
el
# Strip entries in the edgelist where a pair of nodes don't share any
# in-linking nodes at all
el <- el[el[,'strength'] != 0, ]
# Since nodes that share in-linking nodes are ALWAYS structually equivilent
# in that they both share in-links from the same other nodes, there is never
# any idea to have this edge-list directed.
# Make the edge-list one-directed by deleting duplicate pairs
el <- el[el[,'i'] < el[,'j'], ]
# In graph g, these node-pairs share the number of [strength] incoming links
# from the same other nodes.
(el)
# The whole list of ul contains all possible pairs
ul
# You only wanted the pairs which actually contained any shared incoming nodes
keep.from.ul <- unlist(lapply(ul, function(x) ifelse( nrow(x[[3]]) > 0, TRUE, FALSE) ))
ul <- ul[keep.from.ul]