How to get a reversed, log10 scale in ggplot2?

You can apply the logarithm directly inside the ggplot function, in the aes() specification:

require(ggplot2)
df <- data.frame(x=1:10, y=runif(10))
p <- ggplot(data=df, aes(x = log10(x), y=y)) + geom_point() 

and then reverse the x axis

p + scale_x_reverse()

in this way your data is not altered, but you can scale the graph


ggforce package has trans_reverser() function for this task.

library(ggplot2)
library(ggforce)

p <- ggplot() +
  geom_line(aes(x = 1:100, y = 1:100))

p +
  scale_x_continuous(trans = trans_reverser('log10')) +
  annotation_logticks(sides = 'tb') +
  theme_bw()

Edit: starting from v1.2.0 of the scales package, this will also work

library(scales)

p +
  scale_x_continuous(
    trans  = compose_trans("log10", "reverse"),
    breaks = c(100, 10, 1)
  ) +
  annotation_logticks(sides = 'tb') +
  theme_bw()

p +
  scale_x_continuous(
    trans  = compose_trans("log10", "reverse"),
    labels = label_log()
  ) +
  annotation_logticks(sides = 'tb') +
  theme_bw()

Created on 2020-11-14 by the reprex package (v0.3.0)


The link that @joran gave in his comment gives the right idea (build your own transform), but is outdated with regard to the new scales package that ggplot2 uses now. Looking at log_trans and reverse_trans in the scales package for guidance and inspiration, a reverselog_trans function can be made:

library("scales")
reverselog_trans <- function(base = exp(1)) {
    trans <- function(x) -log(x, base)
    inv <- function(x) base^(-x)
    trans_new(paste0("reverselog-", format(base)), trans, inv, 
              log_breaks(base = base), 
              domain = c(1e-100, Inf))
}

This can be used simply as:

p + scale_x_continuous(trans=reverselog_trans(10))

which gives the plot:

enter image description here

Using a slightly different data set to show that the axis is definitely reversed:

DF <- data.frame(x=1:10,  y=1:10)
ggplot(DF, aes(x=x,y=y)) + 
  geom_point() +
  scale_x_continuous(trans=reverselog_trans(10))

enter image description here

Tags:

R

Ggplot2