R中的网络和弦图很难过

Question

我有一些类似于data.frame d数据如下。

d <- structure(list(ID = c("KP1009", "GP3040", "KP1757", "GP2243", 
                           "KP682", "KP1789", "KP1933", "KP1662", "KP1718", "GP3339", "GP4007", 
                           "GP3398", "GP6720", "KP808", "KP1154", "KP748", "GP4263", "GP1132", 
                           "GP5881", "GP6291", "KP1004", "KP1998", "GP4123", "GP5930", "KP1070", 
                           "KP905", "KP579", "KP1100", "KP587", "GP913", "GP4864", "KP1513", 
                           "GP5979", "KP730", "KP1412", "KP615", "KP1315", "KP993", "GP1521", 
                           "KP1034", "KP651", "GP2876", "GP4715", "GP5056", "GP555", "GP408", 
                           "GP4217", "GP641"),
                    Type = c("B", "A", "B", "A", "B", "B", "B", 
                             "B", "B", "A", "A", "A", "A", "B", "B", "B", "A", "A", "A", "A", 
                             "B", "B", "A", "A", "B", "B", "B", "B", "B", "A", "A", "B", "A", 
                             "B", "B", "B", "B", "B", "A", "B", "B", "A", "A", "A", "A", "A", 
                             "A", "A"),
                    Set = c(15L, 1L, 10L, 21L, 5L, 9L, 12L, 15L, 16L, 
                            19L, 22L, 3L, 12L, 22L, 15L, 25L, 10L, 25L, 12L, 3L, 10L, 8L, 
                            8L, 20L, 20L, 19L, 25L, 15L, 6L, 21L, 9L, 5L, 24L, 9L, 20L, 5L, 
                            2L, 2L, 11L, 9L, 16L, 10L, 21L, 4L, 1L, 8L, 5L, 11L), Loc = c(3L, 
                                                                                          2L, 3L, 1L, 3L, 3L, 3L, 1L, 2L, 1L, 3L, 1L, 1L, 2L, 2L, 1L, 3L, 
                                                                                          2L, 2L, 2L, 3L, 2L, 3L, 2L, 1L, 3L, 3L, 3L, 2L, 3L, 1L, 3L, 3L, 
                                                                                          1L, 3L, 2L, 3L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 2L, 2L, 3L, 3L)),
               .Names = c("ID", "Type", "Set", "Loc"), class = "data.frame",
               row.names = c(NA, -48L))

我想使用类似于下面的和弦图来探索d$ID成员之间的关系。

它看起来有几种选择在R这样做。 （ R中的和弦图 ）。

在我的数据中，关系是根据d$Set （非定向）而分组是根据d$Loc 。 以下是我尝试将这些关系映射为和弦图。

尝试1：使用igraph

我根据程度尝试了如下节点大小的igraph 。

# Get vertex relationships
sets <- unique(d$Set[duplicated(d$Set)])
rel <-  vector("list", length(sets))
for (i in 1:length(sets)) {
  rel[[i]] <- as.data.frame(t(combn(subset(d, d$Set ==sets[i])$ID, 2)))
}
library(data.table)
rel <- rbindlist(rel)

# Get the graph
g <- graph.data.frame(rel, directed=F, vertices=d)
clr <- as.factor(V(g)$Loc)
levels(clr) <- c("salmon", "wheat", "lightskyblue")
V(g)$color <- as.character(clr)

# Plot
plot(g, layout = layout.circle, vertex.size=degree(g)*5, vertex.label=NA)

如何修改情节看起来像第一个数字？ 似乎没有选项来修改igraph layout.circle 。

尝试2：使用Circlize

看来平滑贝塞尔曲线和分组中是可能的R包circlize 。 但是在这里我无法对节点进行分组以及根据度数调整它们的大小，因为它们被绘制为扇区。

par(mar = c(1, 1, 1, 1), lwd = 0.1, cex = 0.7)
circos.initialize(factors = as.factor(d$ID), xlim = c(0, 10))
circos.trackPlotRegion(factors = as.factor(d$ID), ylim = c(0, 0.5), bg.col = V(g)$color,
                       bg.border = NA, track.height = 0.05)
for(i in 1:nrow(rel)) {
  circos.link(rel[i,1], 0, rel[i,2],0, h = 0.4)

}

但是，这里没有修改节点的选项。 实际上它们只能作为扇区绘制？ 在这种情况下有没有办法根据程度将扇区修改为大小的圆形节点？

尝试3：使用edgebundleR （ https://github.com/garthtarr/edgebundleR ）

require(edgebundleR)
edgebundle(g,tension = 0.1,cutoff = 0.5, fontsize = 18,padding=40)

看来这里修改美学的选择有限。

Answer 1

我对edgebundleR做了一些更改。 这些现在是主要的回购。 以下代码可以让您接近所需的结果。 实例

# devtools::install_github("garthtarr/edgebundleR")

library(edgebundleR)
library(igraph)
library(data.table)

d <- structure(list(ID = c("KP1009", "GP3040", "KP1757", "GP2243", 
                           "KP682", "KP1789", "KP1933", "KP1662", "KP1718", "GP3339", "GP4007", 
                           "GP3398", "GP6720", "KP808", "KP1154", "KP748", "GP4263", "GP1132", 
                           "GP5881", "GP6291", "KP1004", "KP1998", "GP4123", "GP5930", "KP1070", 
                           "KP905", "KP579", "KP1100", "KP587", "GP913", "GP4864", "KP1513", 
                           "GP5979", "KP730", "KP1412", "KP615", "KP1315", "KP993", "GP1521", 
                           "KP1034", "KP651", "GP2876", "GP4715", "GP5056", "GP555", "GP408", 
                           "GP4217", "GP641"),
                    Type = c("B", "A", "B", "A", "B", "B", "B", 
                             "B", "B", "A", "A", "A", "A", "B", "B", "B", "A", "A", "A", "A", 
                             "B", "B", "A", "A", "B", "B", "B", "B", "B", "A", "A", "B", "A", 
                             "B", "B", "B", "B", "B", "A", "B", "B", "A", "A", "A", "A", "A", 
                             "A", "A"),
                    Set = c(15L, 1L, 10L, 21L, 5L, 9L, 12L, 15L, 16L, 
                            19L, 22L, 3L, 12L, 22L, 15L, 25L, 10L, 25L, 12L, 3L, 10L, 8L, 
                            8L, 20L, 20L, 19L, 25L, 15L, 6L, 21L, 9L, 5L, 24L, 9L, 20L, 5L, 
                            2L, 2L, 11L, 9L, 16L, 10L, 21L, 4L, 1L, 8L, 5L, 11L), Loc = c(3L, 
                                                                                          2L, 3L, 1L, 3L, 3L, 3L, 1L, 2L, 1L, 3L, 1L, 1L, 2L, 2L, 1L, 3L, 
                                                                                          2L, 2L, 2L, 3L, 2L, 3L, 2L, 1L, 3L, 3L, 3L, 2L, 3L, 1L, 3L, 3L, 
                                                                                          1L, 3L, 2L, 3L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 2L, 2L, 3L, 3L)),
               .Names = c("ID", "Type", "Set", "Loc"), class = "data.frame",
               row.names = c(NA, -48L))

# let's add Loc to our ID
d$key <- d$ID
d$ID <- paste0(d$Loc,".",d$ID)

# Get vertex relationships
sets <- unique(d$Set[duplicated(d$Set)])
rel <-  vector("list", length(sets))
for (i in 1:length(sets)) {
  rel[[i]] <- as.data.frame(t(combn(subset(d, d$Set ==sets[i])$ID, 2)))
}

rel <- rbindlist(rel)

# Get the graph
g <- graph.data.frame(rel, directed=F, vertices=d)
clr <- as.factor(V(g)$Loc)
levels(clr) <- c("salmon", "wheat", "lightskyblue")
V(g)$color <- as.character(clr)
V(g)$size = degree(g)*5
# Plot
plot(g, layout = layout.circle, vertex.label=NA)


edgebundle( g )->eb

eb

Answer 2

我不想为另一个问题添加另一个答案，但我不知道如何处理评论中提出的其他问题。 评论询问我们如何为边缘着色。 通常，响应很容易，但在这种情况下，答案需要重写edgebundleR的大部分代码或者需要hack。 我会跟下面的黑客一起去。

library(edgebundleR)
library(igraph)
library(data.table)

d <- structure(list(ID = c("KP1009", "GP3040", "KP1757", "GP2243", 
                           "KP682", "KP1789", "KP1933", "KP1662", "KP1718", "GP3339", "GP4007", 
                           "GP3398", "GP6720", "KP808", "KP1154", "KP748", "GP4263", "GP1132", 
                           "GP5881", "GP6291", "KP1004", "KP1998", "GP4123", "GP5930", "KP1070", 
                           "KP905", "KP579", "KP1100", "KP587", "GP913", "GP4864", "KP1513", 
                           "GP5979", "KP730", "KP1412", "KP615", "KP1315", "KP993", "GP1521", 
                           "KP1034", "KP651", "GP2876", "GP4715", "GP5056", "GP555", "GP408", 
                           "GP4217", "GP641"),
                    Type = c("B", "A", "B", "A", "B", "B", "B", 
                             "B", "B", "A", "A", "A", "A", "B", "B", "B", "A", "A", "A", "A", 
                             "B", "B", "A", "A", "B", "B", "B", "B", "B", "A", "A", "B", "A", 
                             "B", "B", "B", "B", "B", "A", "B", "B", "A", "A", "A", "A", "A", 
                             "A", "A"),
                    Set = c(15L, 1L, 10L, 21L, 5L, 9L, 12L, 15L, 16L, 
                            19L, 22L, 3L, 12L, 22L, 15L, 25L, 10L, 25L, 12L, 3L, 10L, 8L, 
                            8L, 20L, 20L, 19L, 25L, 15L, 6L, 21L, 9L, 5L, 24L, 9L, 20L, 5L, 
                            2L, 2L, 11L, 9L, 16L, 10L, 21L, 4L, 1L, 8L, 5L, 11L), Loc = c(3L, 
                                                                                          2L, 3L, 1L, 3L, 3L, 3L, 1L, 2L, 1L, 3L, 1L, 1L, 2L, 2L, 1L, 3L, 
                                                                                          2L, 2L, 2L, 3L, 2L, 3L, 2L, 1L, 3L, 3L, 3L, 2L, 3L, 1L, 3L, 3L, 
                                                                                          1L, 3L, 2L, 3L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 2L, 2L, 3L, 3L)),
               .Names = c("ID", "Type", "Set", "Loc"), class = "data.frame",
               row.names = c(NA, -48L))

# let's add Loc to our ID
d$key <- d$ID
d$ID <- paste0(d$Loc,".",d$ID)

# Get vertex relationships
sets <- unique(d$Set[duplicated(d$Set)])
rel <-  vector("list", length(sets))
for (i in 1:length(sets)) {
  rel[[i]] <- as.data.frame(t(combn(subset(d, d$Set ==sets[i])$ID, 2)))
}

rel <- rbindlist(rel)

# Get the graph
g <- graph.data.frame(rel, directed=F, vertices=d)
clr <- as.factor(V(g)$Loc)
levels(clr) <- c("salmon", "wheat", "lightskyblue")
V(g)$color <- as.character(clr)

# Plot
plot(g, layout = layout.circle, vertex.size=degree(g)*5, vertex.label=NA)


edgebundle( g )->eb

eb

# temporary hack to accomplish edge coloring
# requires newest Github version of htmlwidgets
# devtools::install_github("ramnathv/htmlwidgets")

# add some imaginary colors
E(g)$color <- c("purple","green","black")[floor(runif(length(E(g)),1,4))]
# now append these edge attributes to our htmlwidget x
eb$x$edges <- jsonlite::toJSON(get.data.frame(g,what="edges"))

eb <- htmlwidgets::onRender(
  eb,
'
function(el,x){
  // loop through each of our edges supplied
  //  and change the color
  x.edges.map(function(edge){
    var source = edge.from.split(".")[1];
    var target = edge.to.split(".")[1];
    d3.select(el).select(".link.source-" + source + ".target-" + target)
      .style("stroke",edge.color);
  })
}
'
)
eb