在R/igraph中可视化具有3层(三方)的图/网络 [英] Visualizing graph/network with 3 layeres (tripartite) in R/igraph

问题描述

我有一个分为3层的分层"网络，比方说父母(P)，孩子(C)，孙子(G).边缘总是朝着年轻一代的方向(专利->孩子，孩子->孙子或父母->孙子).同一代中的顶点之间没有边. 该图由3个边缘列表(P_C，C_G，P_C)表示.下面是一个简短的例子.

I have a "layered" network, with 3 layers, let's say parents(P), children(C), grandchildren(G). The edges are always directed and towards a younger generation (either patent->child, child->grandchild or parent->grandchild). No edges between vertices in the same generation. The graph is represented by 3 edge lists (P_C, C_G, P_C). A short example is given bellow.

1)这种图形/网络的恰当术语是什么?三方图?因此，我认为这是一个特殊的情况，因为缺少反向连接.

1) What is the proper term for this sort of graph/network? tripartite graph? As such, I suppose it is a particular case because of the lack of backward connections.

2)如何在R(igraph)中将其表示为图形对象?

2) How do I represent it as a graph object in R (igraph)?

3)我可以用描绘层"的方式绘制图形，使每个组(P，C，GC)的所有顶点都对齐在相同的x坐标上，从左侧的P开始，C在中间和GC的正确性?

3) Can I plot the graph in a way that depicts the "layers", with all the vertices for each group (P,C,GC) aligned at the same x coordinates, going from P on the left, C in the middle and GC on the rigth ?

4)我是否可以检查具有这种结构的图之间的图同构性，并考虑到数据的分层性质. (我知道对于常规图，它将是graph.isomorphic()函数).

4) Can I check for graph isomorphisms between graphs with this structure, thaking into account the layered nature of the data. (I know for regular graphs it would be the graph.isomorphic() function).

edge_P_C <- read.table(text="P C
A B
A C", header=T)

edge_C_G <- read.table(text="C G
B D
B E
C F", header=T)

edge_P_G <- read.table(text="P G
A G", header=T)

推荐答案

1.学期

我想您可以说这是一个三方图，但是我不确定该术语是否用于有向图.

1. Term

I think you could say it is a tripartite graph but I am not sure if the term is used for directed graphs.

要创建图形对象(使用igraph程序包)，只需rbind所有边并使用igraph.data.frame创建即可.绑定之前，列名称必须匹配.

To create a graph object (with igraph package) just rbind all the edges and create it with igraph.data.frame. Before binding the column names must match.

all_edges <- do.call(rbind,
  lapply( list(edge_C_G, edge_P_C, edge_P_G), function(x) setNames(x, c("1","2")) )
)

g1 <- graph.data.frame(d = all_edges, directed = TRUE)

3.情节

您需要在每个顶点上设置layer属性.据我了解，该层是由输入数据(三个表)隐式定义的:

3. Plot

You need to set the layer attribute on every vertex. As I understand, the layer is implicitly defined by input data (three tables):

v_layers_df <- unique( rbind(
  expand.grid( ID = edge_P_C$P, Layer = 1),
  expand.grid( ID = edge_P_G$P, Layer = 1),
  expand.grid( ID = edge_P_C$C, Layer = 2),
  expand.grid( ID = edge_C_G$C, Layer = 2),
  expand.grid( ID = edge_C_G$G, Layer = 3),
  expand.grid( ID = edge_P_G$G, Layer = 3)
))

v_layers <- setNames( v_layers_df$Layer, v_layers_df$ID)
V(g1)$layer <- v_layers[V(g1)$name]

在顶点上具有layer属性，您可以在自己的布局函数(修改后的Sugiyama)中使用它:

With the layer attribute on the vertices you can use it in your own layout function (modified Sugiyama):

layout.k_partite <- function(g) {
  l <- layout.sugiyama(g)$layout[,2:1]
  l[,1] <- V(g1)$layer
  l[,2] <- - l[,2] + 1 + max(l[,2])
  l
}

并以这种方式使用它:

plot(g1, layout = layout.k_partite(g1))

igraph软件包中的graph.isomorphic和其他功能应该可以正常工作.

The graph.isomorphic and other functions from igraph package should perform just fine.

这篇关于在R/igraph中可视化具有3层(三方)的图/网络的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！