README.md
In gglogger: Track 'ggplot2' Calls

gglogger

gglogger is an R package that logs the calls used to create ggplot2 objects.

This can be useful for debugging, reproducibility, and understanding the sequence of operations used to build a plot.

Have you ever created a plot in ggplot2 and then forgotten how you made it? Or wanted to reproduce a plot but couldn't remember the exact sequence of operations you used? gglogger can help!

You can install the gglogger package from source using devtools:

devtools::install_github("pwwang/gglogger")

# or
remotes::install_github("pwwang/gglogger")

To use the gglogger package, simply load it along with ggplot2 and create your plots as usual. The package will automatically log the calls used to create the plots.

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Evaluate the code in logs to reproduce the plot:

p$logs$evaluate()

You can also attach the variables in an environment for evaluation:

env <- new.env()
env$mpg <- mpg
env$mpg$hwy <- mpg$hwy / 2
p$logs$evaluate(env)

library(dplyr)
library(gglogger)

mtcars_radar <- mtcars %>%
  as_tibble(rownames = "group") %>%
  mutate_at(vars(-group), scales::rescale) %>%
  tail(4) %>%
  select(1:10)

ggradar <- register(ggradar::ggradar)

p <- ggradar(mtcars_radar, legend.position = "right")
print(p$logs)

# ggradar::ggradar(mtcars_radar, legend.position = "right")

# p is a ggradar plot created in the previous example

code <- p$logs$gen_code(setup = '
library(dplyr)
library(ggradar)

mtcars_radar <- mtcars %>%
  as_tibble(rownames = "group") %>%
  mutate_at(vars(-group), scales::rescale) %>%
  tail(4) %>%
  select(1:10)
')

cat(code)
## library(dplyr)
## library(ggradar)
##
## mtcars_radar <- mtcars %>%
##   as_tibble(rownames = "group") %>%
##   mutate_at(vars(-group), scales::rescale) %>%
##   tail(4) %>%
##   select(1:10)
##
##
## ggradar::ggradar(mtcars_radar, legend.position = "right")

# eval(parse(text = code)) # to reproduce the plot

gglogger cannot log the global settings used to create a plot, such as theme_set(). It can only log the calls used directly to create the plot itself. You may need to manually set these global settings when reproducing a plot, or prepare them using the setup argument in gen_code().

If your data is piped to ggplot function, you need to use |> instead of %>%, otherwise the data will be logged as ..