三方图的水平布局

Question

我正在使用igraph 函数创建一个三方图，将一位讲师 (A) 与参加该讲师指导的 3 个俱乐部的学生列表（B 到 R）联系起来。学生有 2 个班级的交叉成员资格，并且可能具有相同的性别。最后，边的宽度代表教练和每个学生在给定周内平均投入每个俱乐部的时间。

创建图表很简单（我的代码在下面提供），但鉴于我的列表总共包含 17 名学生（B 到 R），最好以水平方式呈现图表将讲师 (A) 放在顶部，将 3 个俱乐部放在中间，将 17 名学生 (B 到 R) 放在底部。我怀疑这是因为我在图表中使用了layout_with_sugiyama()，但是任何人都可以提出替代方案来实现我想要的水平布局吗？

以下是我当前用于此图表的R 代码：

rm(list=ls())
library(foreign)
library(igraph)
library(dplyr)

### create tripartite node list and pairwise attributes
time <- data.frame(student = c("A", "A", "A", "B", "B", "B", "C", "C", "C", "D", "D", "D", "E", "E", "E", "F", "F", "F", "G", "G", "G", "H", "H", "H", "I", "I", "I", "J", "J", "J", "K", "K", "K", "L", "L", "L", "M", "M", "M", "N", "N", "N", "O", "O", "O", "P", "P", "P", "Q", "Q", "Q", "R", "R", "R"),
club = c("club 1", "club 2", "club 3", "club 1", "club 2", "club 3", "club 1", "club 2", "club 3", "club 1", "club 2", "club 3", "club 1", "club 2", "club 3", "club 1", "club 2", "club 3", "club 1", "club 2", "club 3", "club 1", "club 2", "club 3", "club 1", "club 2", "club 3", "club 1", "club 2", "club 3", "club 1", "club 2", "club 3", "club 1", "club 2", "club 3", "club 1", "club 2", "club 3", "club 1", "club 2", "club 3", "club 1", "club 2", "club 3", "club 1", "club 2", "club 3", "club 1", "club 2", "club 3", "club 1", "club 2", "club 3"), 
hours = c(10, 3, 6, 5, 2, 1, 3,	3, 2, 7, 5, 11,	1, 0, 3, 8, 2, 2, 2, 2,	0, 5, 7, 11, 1, 0, 1, 0, 1, 3, 8, 9, 2,	0, 0, 3, 4, 3, 6, 3, 1,	0, 3, 1, 7, 0, 0, 1, 0,	1, 5, 1, 3, 3))

### convert time dataframe into a graph object
df <- time[!time$hours == 0, ]
g <- graph_from_data_frame(df, directed = FALSE)
E(g)$width <- log(E(g)$hours)

### parse the data into three disjoint sets, use different node shapes to distinguish them

A <- "A"
club <- c("club 1", "club 2", "club 3")

V(g)$type <- 1
V(g)[name %in% club]$type <- 2
V(g)[name %in% "A"]$type <- 3
shape <- c("circle", "square", "circle")
size <- c(12, 15, 12)

### label class affiliation (except node A; G, K, L, Q do not belong to any classes)
Class1 <- c("B", "C", "E", "H", "J", "O")
Class2 <- c("D", "F", "M", "P", "I", "N", "R")

V(g)$color[V(g)$name] = "white"
V(g)$color[V(g)$name %in% Class1] = "red"
V(g)$color[V(g)$name %in% Class2] = "orange"
V(g)$color[V(g)$name == "A"] = "olivedrab1"

### highlight same sex nodes
s <- c("B", "D", "F", "G", "H", "K", "M", "P", "Q")
s_col = ifelse(V(g)$name %in% s,'black','grey80')

layout = layout_with_sugiyama(g, layers=V(g)$type)
V(g)$vertex_degree <-  igraph::degree(g)



plot(g,
     layout=cbind(V(g)$type, layout$layout[,1]), edge.curved=0,
     vertex.color = V(g)$color,
     vertex.label.color = "black",
     vertex.label.cex = 0.45,
     vertex.size = size[V(g)$type],
     vertex.shape = shape[V(g)$type],
     vertex.frame.color = s_col,
     edge.color= "grey30",
     asp = 1.3,
     edge.width = E(g)$width
)

上面的代码生成了这个图。

但我想要的输出应该是这样的

Answer 1

感谢您的澄清。这更像是评论而不是答案。如果我按照你自己和评论者here的建议运行代码：

plot(g,
     layout=cbind(V(g)$type, layout$layout[,1])[,2:1], edge.curved=0,
     vertex.color = V(g)$color,
     vertex.label.color = "black",
     vertex.label.cex = 0.45,
     vertex.size = size[V(g)$type],
     vertex.shape = shape[V(g)$type],
     vertex.frame.color = s_col,
     edge.color= "grey30",
     asp = 1.3,
     edge.width = E(g)$width
)

我得到以下输出：

这与你想要完成的有什么不同？

编辑：在 x 轴上找到更好看的顶点分布的一种方法是使用 cut 函数：

idx <- which(layout$layout[,2] == 2)  # find "club"-vertices
cuts <- layout$layout[idx, 1]         # find x-coords of vertices
cut(cuts, length(idx))                # cut into 3 intervals
layout$layout[idx,1] <- c(6,7.5,9)    # manually calculated even spans between x-coords

但是，我确信有更好的方法来做到这一点。