Custom ggplot2 log-scale transformation that preserves sign

log_sign_trans

library(ggplot2)
library(scales)

# transformation
log_sign_trans <- trans_new(
  name = "log_sign",
  transform = function(x) {sign(x) * log(abs(x))}, 
  inverse = function(x){sign(x)} * exp(abs(x))
)

# ugly, random sign
df <- data.frame(
  x = exp(rnorm(10000)) * sample(c(-1,1), 10000, TRUE)
)

# histogram on the raw scale masks outliers
p <- ggplot(df,aes(x)) + 
  geom_histogram()
plot(p)

# transformed version looks like this. the breaks aren't well
# placed, but can be fixed by specifying breaks argument when
# calling trans_new()
plot(p + scale_x_continuous(trans = log_sign_trans))