在多面网格ggplot2中插入一个额外的图

Question

I would like to display a set of parameters in the ggplot2 faceted plot format. Three of the parameters come from the same dataset and can be easily faceted. I'd now like to add a fourth plot into the grid, the dataset of which is a completely different length/value to the others (but still relevant to view together).

This is the best I have (terrible). Is there a way to exactly align the coordinates and theme? Thank you

library(ggplot2)

data(mtcars)
data(iris)

a_plot <- ggplot(mtcars, aes(mpg, disp))+
  geom_line()+
  facet_wrap(~cyl,nrow=2,scales='free')+
  theme_bw()

b_plot<- ggplot(iris, aes(Sepal.Length,Petal.Length))+
  geom_line()+
  ggtitle('imposter')+
  theme_bw()

vp <- viewport(width = 0.52, height = 0.5, x = 0.75, y = 0.25)

png("test.png")
print(a_plot)
print(b_plot, vp = vp)
dev.off()][1]][1]

Answer 1

One suggestion would be to handle this in the data and let the plot faceting work naturally. (I'm using dplyr here to combine the datasets, but it's only for convenience. Any mechanism that provides a single set of columns to plot on should work.)

library(dplyr)
library(ggplot2)

bind_rows(
  transmute(mtcars, x=mpg         , y=disp        , z=as.character(cyl)),
  transmute(iris,   x=Sepal.Length, y=Petal.Length, z="imposter")
) %>%
  ggplot(aes(x, y)) +
  geom_line() +
  facet_wrap(~ z, nrow = 2, scales = "free") +
  theme_bw()

Answer 2

Use the parameter plot.margin and panel.spacing in the them to customize the size of the background you are plotting. And then modify the viewport to width so it matches your other 3 plots. You will probably have to try some times but it is achievable.

library(ggplot2)
library(grid)

a_plot <- ggplot(mtcars, aes(mpg, disp))+
  geom_line()+
  facet_wrap(~cyl,nrow=2,scales='free')+
  theme_bw()+
  theme(plot.margin = unit(c(0,0.3,0,0), "cm"),
        panel.spacing= unit(1, "cm"))


b_plot<- ggplot(mtcars, aes(mpg,disp))+
  geom_line()+
  ggtitle('imposter')+
  theme_bw()

vp <- viewport(width = 0.49, height = 0.5, x = 0.75, y = 0.25)
print(a_plot)
print(b_plot, vp = vp)