用组名及其方程式标记ggplot，可能用ggpmisc吗? [英] Label ggplot with group names and their equation, possibly with ggpmisc?

问题描述

我想标记我的绘图，可能使用ggpmisc的方程式方法来提供一个链接到颜色和方程式的信息标签(然后我可以完全删除图例).例如，在下面的图中，理想情况下，方程式LHS中的因子水平为4、6和8.

I would like to label my plot, possibly using the equation method from ggpmisc to give an informative label that links to the colour and equation (then I can remove the legend altogether). For example, in the plot below, I would ideally have the factor levels of 4, 6 and 8 in the equation LHS.

library(tidyverse)
library(ggpmisc)

df_mtcars <- mtcars %>% mutate(factor_cyl = as.factor(cyl))

p <- ggplot(df_mtcars, aes(x = wt, y = mpg, group = factor_cyl, colour= factor_cyl))+
  geom_smooth(method="lm")+
  geom_point()+
  stat_poly_eq(formula = my_formula,
               label.x = "centre",
               #eq.with.lhs = paste0(expression(y), "~`=`~"),
               eq.with.lhs = paste0("Group~factor~level~here", "~Cylinders:", "~italic(hat(y))~`=`~"),
               aes(label = paste(..eq.label.., sep = "~~~")), 
               parse = TRUE)
p

有一种解决方法，可以使用此处所述的技术修改图，但是肯定有更简单的方法吗?/p>

There is a workaround by modifying the plot afterwards using the technique described here, but surely there is something simpler?

p <- ggplot(df_mtcars, aes(x = wt, y = mpg, group = factor_cyl, colour= factor_cyl))+
  geom_smooth(method="lm")+
  geom_point()+
  stat_poly_eq(formula = my_formula,
               label.x = "centre",
               eq.with.lhs = paste0(expression(y), "~`=`~"),
               #eq.with.lhs = paste0("Group~factor~level~here", "~Cylinders:", "~italic(hat(y))~`=`~"),
               aes(label = paste(..eq.label.., sep = "~~~")), 
               parse = TRUE)
p

# Modification of equation LHS technique from:
# https://stackoverflow.com/questions/56376072/convert-gtable-into-ggplot-in-r-ggplot2
temp <- ggplot_build(p)
temp$data[[3]]$label <- temp$data[[3]]$label %>% 
  fct_relabel(~ str_replace(.x, "y", paste0(c("8","6","4"),"~cylinder:", "~~italic(hat(y))" )))
class(temp)

#convert back to ggplot object
#https://stackoverflow.com/questions/56376072/convert-gtable-into-ggplot-in-r-ggplot2
#install.packages("ggplotify")
library("ggplotify")
q <- as.ggplot(ggplot_gtable(temp))
class(q)
q

推荐答案

第一个示例将标签放在等式的右侧，并且部分是手动的.另一方面，编码非常简单.之所以可行，是因为group始终存在于data中，如图层功能(统计信息和几何图形)所示.

This first example puts the label to the right of the equation, and is partly manual. On the other hand it is very simple to code. Why this works is because group is always present in the data as seen by layer functions (statistics and geoms).

library(tidyverse)
library(ggpmisc)

df_mtcars <- mtcars %>% mutate(factor_cyl = as.factor(cyl))

my_formula <- y ~ x

p <- ggplot(df_mtcars, aes(x = wt, y = mpg, group = factor_cyl, colour = factor_cyl)) +
  geom_smooth(method="lm")+
  geom_point()+
  stat_poly_eq(formula = my_formula,
               label.x = "centre",
               eq.with.lhs = "italic(hat(y))~`=`~",
               aes(label = paste(stat(eq.label), "*\", \"*", 
                                 c("4", "6", "8")[stat(group)], 
                                 "~cylinders.",  sep = "")),
               label.x.npc = "right",
               parse = TRUE) +
  scale_colour_discrete(guide = FALSE)
p

实际上，只需一点点额外的杂耍就可以几乎解决这个问题.我们需要通过将 lhs 明确地粘贴到aes()中来添加它，以便我们还可以基于计算出的变量在其左侧添加文本.

In fact with a little bit of additional juggling one can achieve almost an answer to the question. We need to add the lhs by pasting it explicitly in aes() so that we can add also paste text to its left based on a computed variable.

library(tidyverse)
library(ggpmisc)

df_mtcars <- mtcars %>% mutate(factor_cyl = as.factor(cyl))

my_formula <- y ~ x

p <- ggplot(df_mtcars, aes(x = wt, y = mpg, group = factor_cyl, colour = factor_cyl)) +
  geom_smooth(method="lm")+
  geom_point()+
  stat_poly_eq(formula = my_formula,
               label.x = "centre",
               eq.with.lhs = "",
               aes(label = paste("bold(\"", c("4", "6", "8")[stat(group)], 
                                 " cylinders:  \")*",
                                 "italic(hat(y))~`=`~",
                                 stat(eq.label),
                                 sep = "")),
               label.x.npc = "right",
               parse = TRUE) +
  scale_colour_discrete(guide = FALSE)
p 

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