用于在sna包

时间:2016-04-01 20:18:00

标签: arrays r sna

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

1 个答案:

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)。