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For my recently published paper, I produced not-so-standard figures that show the two step decomposition used in the analysis. Have a look:
Figure 3 from my paper (PDF)
Actually, ggplot2 is a very powerful and flexible tool that allows to draw figures with quite a complex layout. Today I want to show the code that aligns six square plots (actually, maps) just as in the figure above. And it’s all about the handy function ggplot2::annotation_custom(). Since I used the layout more than once, I wrapped the code that produced it into a function that takes a list of 6 square plots as an input and yields the arranged figure with arrows as an output. Here is the commented code of the function.
align_six_plots <- function(list.plots,
family = "",
labels=LETTERS[1:6],
labels.size=8){
require(tidyverse)
require(gridExtra)
gg <- ggplot()+
coord_equal(xlim = c(0, 21), ylim = c(0, 30), expand = c(0,0))+
annotation_custom(ggplotGrob(list.plots[[1]]),
xmin = 0.5, xmax = 8.5, ymin = 21, ymax = 29)+
annotation_custom(ggplotGrob(list.plots[[2]]),
xmin = 12.5, xmax = 20.5, ymin = 19.5, ymax = 27.5)+
annotation_custom(ggplotGrob(list.plots[[3]]),
xmin = 12.5,xmax = 20.5,ymin = 10.5,ymax = 18.5)+
annotation_custom(ggplotGrob(list.plots[[4]]),
xmin = 0.5, xmax = 8.5, ymin = 9,ymax = 17)+
annotation_custom(ggplotGrob(list.plots[[5]]),
xmin = 0.5, xmax = 8.5, ymin = 0, ymax = 8)+
annotation_custom(ggplotGrob(list.plots[[6]]),
xmin = 12.5,xmax = 20.5, ymin = 0, ymax = 8)+
labs(x = NULL, y = NULL)+
theme_void()
# DF with the coordinates of the 5 arrows
df.arrows <- data.frame(id=1:5,
x=c(8.5,8.5,12.5,12.5,12.5),
y=c(21,21,10.5,10.5,10.5),
xend=c(12.5,12.5,8.5,8.5,12.5),
yend=c(20.5,17.5,10,7,7))
# add arrows
gg <- gg +
geom_curve(data = df.arrows %>% filter(id==1),
aes(x=x,y=y,xend=xend,yend=yend),
curvature = 0.1,
arrow = arrow(type="closed",length = unit(0.25,"cm"))) +
geom_curve(data = df.arrows %>% filter(id==2),
aes(x=x,y=y,xend=xend,yend=yend),
curvature = -0.1,
arrow = arrow(type="closed",length = unit(0.25,"cm"))) +
geom_curve(data = df.arrows %>% filter(id==3),
aes(x=x,y=y,xend=xend,yend=yend),
curvature = -0.15,
arrow = arrow(type="closed",length = unit(0.25,"cm"))) +
geom_curve(data = df.arrows %>% filter(id==4),
aes(x=x,y=y,xend=xend,yend=yend),
curvature = 0,
arrow = arrow(type="closed",length = unit(0.25,"cm"))) +
geom_curve(data = df.arrows %>% filter(id==5),
aes(x=x,y=y,xend=xend,yend=yend),
curvature = 0.3,
arrow = arrow(type="closed",length = unit(0.25,"cm")))
# add labes
gg <- gg + annotate('text',label = labels,
x=c(.5,12.5,12.5,.5,.5,12.5)+.5,
y=c(29,27.5,18.5,17,8,8)+.1,
size=labels.size,hjust=0, vjust=0, family = family)
return(gg)
}
Let’s check, if the function works. For that I create just a blank plot, clone it six times, store the six plots in a list, and finally feed it to the function.
library(tidyverse)
library(ggthemes)
# create a simple blank square plot
p <- ggplot()+
expand_limits(x = c(0,1), y = c(0,1))+
theme_map()+
theme(panel.border = element_rect(color = "black", size = 0.5, fill = NA),
aspect.ratio = 1)
# clone this plot six times and store as a list of six
plots <- mget(rep("p", 6))
# use the function on the list
six <- align_six_plots(plots)
# save the output
ggsave("six_square_plots_aligned.png", six, width=12, height=18)
Just what we wanted to get.
To reproduce all the actual results and figures from my paper, have a look at this github repo.
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