如何获得一个邻接数组来在mrqap
包中执行sna
测试?
我有一个加权多个网络(两个无向和一个有向),在带有属性的边列表中,如下所示:
source target terr type weight
1010 1007 1 3 1
1011 1303 1 2 1
1014 1048 1 4 2
1014 1138 1 4 3
我需要几个矩阵,阵列格式的节点数相同,类似这样(但是采用adyacency矩阵格式):
type 2
source target weight
1010 1007 0
1011 1303 1
1014 1048 0
1014 1138 0
type 3
source target weight
1010 1007 1
1011 1303 0
1014 1048 0
1014 1138 0
type 4
source target weight
1010 1007 0
1011 1303 0
1014 1048 2
1014 1138 3
我试过一个脚本:
el=read.csv("S_EDGES.csv", header = TRUE, sep = ",") # edgelist
Nodos=read.csv("S_NODES.csv", header = TRUE, sep = ",")
el$type[el$type==2] <- 1 # un solo vínculo de infraestructura
library(igraph)
G=graph.data.frame(el, Nodos, directed=F)
subv = (Nodos$id (Nodos$terr_name=="ART") # this fail and then also "neighverts" and "g3"
SG = decompose.graph(G,mode="weak") # because different territories are in fact different networks
neighverts = unique(unlist(sapply(SG,FUN=function(s){if(any(V(s)$name %in% subv)) V(s)$name else NULL})))
g3 = induced.subgraph(graph=G,vids=neighverts)
# or:
AM=get.adjacency(G, type=c("both"), attr=NULL, names=TRUE, sparse=FALSE) # doesn't distinguish the types of links in different matrices
答案 0 :(得分:0)
我知道这是一个老问题,但如果您仍想执行问题中要求的分解:
library(dplyr)
# your example rows
d <- read.table(header = TRUE,
text = "source target terr type weight
1010 1007 1 3 1
1011 1303 1 2 1
1014 1048 1 4 2
1014 1138 1 4 3") %>%
select(-terr)
# the transformation
lapply(unique(d$type), function(x) {
mutate(d, weight = ifelse(type == x, weight, 0)) %>%
select(-type)
}) %>%
setNames(unique(d$type))
代码返回您要求的内容:
$`3`
source target weight
1 1010 1007 1
2 1011 1303 0
3 1014 1048 0
4 1014 1138 0
$`2`
source target weight
1 1010 1007 0
2 1011 1303 1
3 1014 1048 0
4 1014 1138 0
$`4`
source target weight
1 1010 1007 0
2 1011 1303 0
3 1014 1048 2
4 1014 1138 3
从那时起,您应该能够根据需要转换列表中的每个元素(转换为图形,模拟边缘等)。