[英]How to calculate adjacency matrices in R
I have this data. 我有这些数据。 I want to calculate Adjacency matrices in R.
我想在R中计算邻接矩阵。
How can I do this? 我怎样才能做到这一点? V1,V2,V3 are columns.V1 and V2 are NODES, and W3 are weight from V1 to V2.
V1,V2,V3为列.V1和V2为NODES,W3为V1至V2的权重。 Direction in this data is important.
此数据的方向很重要。 After calculating the Adjacency matrices, I want to calculate shortest path between these vertices with R language.
在计算邻接矩阵之后,我想用R语言计算这些顶点之间的最短路径。
How can I do this? 我怎样才能做到这一点?
V1 V2 V3
[1] 164885 431072 3
[2] 164885 164885 24
[3] 431072 431072 5
Here is a simpler solution that does not need reshape()
. 这是一个更简单的解决方案,不需要
reshape()
。 We just create an igraph graph directly from the data frame you have. 我们只是直接从您拥有的数据框创建一个igraph图。 If you really need the adjacency matrix, you can still get it via
get.adjacency()
: 如果你真的需要邻接矩阵,你仍然可以通过
get.adjacency()
得到它:
library(igraph)
## load data
df <- read.table(header=T, stringsAsFactors=F, text=
" V1 V2 V3
164885 431072 3
164885 164885 24
431072 431072 5")
## create graph
colnames(df) <- c("from", "to", "weight")
g <- graph.data.frame(df)
g
# IGRAPH DNW- 2 3 --
# + attr: name (v/c), weight (e/n)
## get shortest path lengths
shortest.paths(g, mode="out")
# 164885 431072
# 164885 0 3
# 431072 Inf 0
## get the actual shortest path
get.shortest.paths(g, from="164885", to="431072")
# [[1]]
# [1] 1 2
This should at the least get your started. 这应该至少让你开始。 The simplest way I could think of to get the
adjacency matrix
is to reshape
this and then build a graph using igraph
as follows: 我可以想到获得
adjacency matrix
的最简单方法是reshape
这个,然后使用igraph
构建图形,如下所示:
# load data
df <- read.table(header=T, stringsAsFactors=F, text=" V1 V2 V3
164885 431072 3
164885 164885 24
431072 431072 5")
> df
# V1 V2 V3
# 1 164885 431072 3
# 2 164885 164885 24
# 3 431072 431072 5
# using reshape2's dcast to reshape the matrix and set row.names accordingly
require(reshape2)
m <- as.matrix(dcast(df, V1 ~ V2, value.var = "V3", fill=0))[,2:3]
row.names(m) <- colnames(m)
> m
# 164885 431072
# 164885 24 3
# 431072 0 5
# load igraph and construct graph
require(igraph)
g <- graph.adjacency(m, mode="directed", weighted=TRUE, diag=TRUE)
> E(g)$weight # simple check
# [1] 24 3 5
# get adjacency
get.adjacency(g)
# 2 x 2 sparse Matrix of class "dgCMatrix"
# 164885 431072
# 164885 1 1
# 431072 . 1
# get shortest paths from a vertex to all other vertices
shortest.paths(g, mode="out") # check out mode = "all" and "in"
# 164885 431072
# 164885 0 3
# 431072 Inf 0
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