边缘密度分布图 | ggExtra包/aplot拼图/ggpubr包等的实现方法

概述：aplot 拼图效果好

根据网友探索[1]，总结如下：

ggExtra 包的拼图间隙有点大，图例在主图和边缘图之间，除非去掉图例，否则没法看。
aplot包的默认拼图间隙很小，比较美观，图例在外面。
gridExtra包默认拼图之间的间隙比较大。
另外仔细比较aplot包和gridExtra包的拼图结果，可以发现aplot包是把子图的panel区域对齐，而gridExtra包是把子图的plot区域对齐。
结论：aplot包的对齐效果显然是我们需要的。

1. ggExtra 画边缘密度图

# 1. get data
set.seed(2024)
dat=diamonds[sample(1:nrow(diamonds), 1000),]
library(ggplot2)
# 2. base plot
# with legend
p1=ggplot(dat, aes(carat, price, color=clarity))+
  geom_point()+
  theme_classic()+
  theme(
    panel.border = element_rect(size = 1, colour = "black", fill="#00112200")
  ); p1
# no legend
p2=ggplot(dat, aes(carat, price, color=clarity))+
  geom_point(show.legend = F)+
  theme_classic()+
  theme(
    panel.border = element_rect(size = 1, colour = "black", fill="#00112200")
  ); p2

# 3.margin density
library(ggExtra)
ggExtra::ggMarginal(p1+ggtitle("p1-A"), type = "density")
ggMarginal(p1+ggtitle("p1-B"), colour = "red")

# no legend
ggMarginal(p2+ggtitle("p2-A"), groupColour = TRUE)
ggMarginal(p2+ggtitle("p2-B"),type = "density",groupColour = TRUE,groupFill = TRUE)
ggMarginal(p2+ggtitle("p2-C"),  
           xparams=list( fill = c("deeppink")),
           yparams=list( fill = c("navy")),
           color=NA)

在这里插入图片描述

2. ggplot2绘图+aplot拼图

library(RColorBrewer)
len=length( unique(dat$clarity) ); len #8

# upper density
top_panel <- ggplot()+
  geom_density(data = dat,
               mapping=aes(carat, fill=clarity, color=clarity),
               alpha=0.5)+
  scale_fill_manual(values = brewer.pal(len,'Set2'))+ #设置填充颜色
  scale_color_manual(values = brewer.pal(len,'Set2'))+ # 设置线的颜色
  theme_void()+ # 设置主题
  theme(legend.position="none") # 去除图例
top_panel

# 右侧密度分布图
right_panel <- ggplot()+
  geom_density(data=dat,
               aes(price, fill=clarity,color=clarity),
               alpha=0.5)+
  scale_fill_manual(values = brewer.pal(len,'Set2'))+ #设置填充颜色
  scale_color_manual(values = brewer.pal(len,'Set2'))+ # 设置线的颜色
  theme_void()+ # 设置主题
  coord_flip()+ # 翻转坐标轴
  theme(legend.position="none")# 去除图例
right_panel

# aplot 包拼图
library(aplot)

# no legend
p2 %>% insert_right(right_panel, width=.4) %>% insert_top(top_panel, height=0.2)  

# with legend
p1 %>% insert_right(right_panel, width=.4) %>% insert_top(top_panel, height=0.2)  

#ggsave('plot2.pdf',width = 6,height = 5)

在这里插入图片描述

3. ggpubr 包绘制边缘密度分布图

# fig1
library(ggpubr)
gp1<-ggscatterhist(
  iris, x = "Sepal.Length", y = "Sepal.Width",
  color = "Species", size = 3, alpha = 0.6)
gp1
# 不支持theme()
# gp1+theme(panel.background = element_rect(fill="#00112200", color="black"))


# fig2
set.seed(2024)
dat=diamonds[sample(1:nrow(diamonds), 1000),]

ggscatterhist(
  dat, x = "carat", y = "price",
  color = "clarity", size = 2, alpha = 0.6)

# fig3
ggscatterhist(
  dat, x = "carat", y = "price",
  color = "clarity", size = 3, alpha = 0.6,
  #palette = c("#00AFBB", "#E7B800", "#FC4E07"),
  margin.params = list(fill = "clarity", color = "black", size = 0.2)
)


# Fig4：指定主图黑边框（略）
ggscatterhist(
  dat, x = "carat", y = "price",
  color = "clarity", size = 3, alpha = 0.6,
  #palette = c("#00AFBB", "#E7B800", "#FC4E07"),
  margin.params = list(fill = "clarity", color = "black", size = 0.2),
  ggtheme = theme_classic() + #指定周围边框
    theme(panel.background = element_rect(fill="#00112200", color="black"))
)

在这里插入图片描述