igraph：如何为边和顶点分配颜色渐变？

Question

我正在尝试使用R为igraph上的边和顶点分配相同的颜色渐变。 渐变应在 V(data_graph)$Counts 部分从低计数到高计数着色。

一些可重现的数据：

library(igraph) 
data <- data.frame(Country = c("Africa", "Argentina", "Bolivia", "Chile", "France", "Guam", "Poland", "Greenland", "Switzerland", "UK", "US"), 
               Counts = c(2,2,8,1,5,3,3,15, 15,30,35), 
               Pillar = c(rep("SoS", 4), rep("CNES", 4), rep("STE", 3)))

data_center <- setNames(data.frame("c", 1, "Sos"), names(data))
data_vtx <- rbind(data_center, data)
data_rel <- data.frame(from = head(data_vtx$Country, 1), 
                    to = data_vtx$Country[2:12])

产生下图：

data_graph <- graph_from_data_frame(data_rel,  directed = FALSE, data_vtx)

plot(data_graph, 
 layout = layout.fruchterman.reingold(data_graph),
 vertex.size = round(V(data_graph)$Counts/1.5, 2), 
 vertex.label.color = "black",
 edge.curved = 0.3)

但是，接下来我想根据V(data_graph)$Counts对顶点和边应用相同的颜色渐变。 我需要的是类似于 ggplot2 的scale_color_gradient2命令的ggplot2 。

例子：

scale_color_gradient2(low = “blue”, mid = “yellow”, high = “red”, midpoint = mean(V(data_graph)$Counts))

我发现最接近的是以下帖子： How can I assign color range to edges in igraph plot in R based on edge attributes? 这篇文章对在igraph中制作颜色渐变提供了很多信息，但那里的每条边都有自己的颜色。 因为一些V(data_graph)$Counts是相同的，所以它们在颜色渐变中的颜色应该相同。

任何帮助将不胜感激！

Answer 1

您可以使用ColorRampPalette创建从蓝色到黄色再到红色的色带。 然后使用计数来选择顶点和边的颜色。 我使用了一种有点随意的方式来选择颜色，但您可以根据自己的喜好调整美学。

CRP = colorRampPalette(c("blue", "yellow", "red"))

plot(data_graph, 
 layout = layout.fruchterman.reingold(data_graph),
 vertex.size = round(V(data_graph)$Counts/1.5, 2), 
 vertex.label.color = "black",
 vertex.color = CRP(19)[round(V(data_graph)$Counts/2)+1],
 edge.color   = CRP(19)[round(V(data_graph)$Counts/2)+1],
 edge.curved = 0.3)

Answer 2

假设您的调色板是已知的。 如果看不到从颜色 1 到颜色 2 的 n 种颜色的渐变。 将 Palette 添加到data和data_center数据框中。 将顶点和边颜色添加到plot()语句。

library(igraph)

data <- data.frame(Country = c("Africa", "Argentina", "Bolivia", "Chile", "France", "Guam", "Poland", "Greenland", "Switzerland", "UK", "US"), 
               Counts = c(2,2,8,1,5,3,3,15, 15,30,35), 
               Pillar = c(rep("SoS", 4), rep("CNES", 4), rep("STE", 3)),
              Palette = rainbow(11)  # <<< 
         )

data_center <- setNames(data.frame("c", 1, "Sos", "black"), names(data)) # <<< center color  is black
data_vtx <- rbind(data_center, data)
data_rel <- data.frame(from = head(data_vtx$Country, 1), 
                         to = data_vtx$Country[2:12]
            )
                    
data_graph <- graph_from_data_frame(data_rel,  directed = FALSE, data_vtx)

set.seed(202212)
plot(data_graph, layout = layout_as_star(data_graph),
 vertex.size        = round(V(data_graph)$Counts/1.5, 2), 
 vertex.color       = data_vtx$Palette,
 vertex.label.color = "black",
 edge.width         = 3,
 edge.curved        = 0.3,
 edge.color         = data$Palette
)