This packages up the R utility code that
- I use frequently enough to have trial-by-fired many approaches
- I use frequently enough to warrant packaging
I do a lot of simulation, with the results ending up in a data.table, then summarized by quantile. quantile.data.table provides a native-data.table-like interface to use the base::quantile on groups within a data.table. E.g.
require(data.table)
dtcars <- mtcars |> as.data.table()
dtcars |> quantile(.(mpg), keyby=.(cyl, gear), probs = 0.5)
dtcars |> quantile(.(mpg, wt), keyby=.(cyl, gear), probs = c(med=0.5))
I mostly run code from a command prompt, but debug interactively. This version wraps the base::commandArgs() to provide a when-used-interactively return value that is sensible. E.g.
.args <- commandArgs(args = c(
file.path("input", "data.csv"),
file.path("output", "plot.png")
))
# when interactively coding, returns args
# when running, returns e.g. whatever input csv / output png target
remotes::install_github("pearsonca/cabputils")
Sure, why not. I am unlikely to consider your convenience functions, but bug fixes, performance improvements, unit tests, &c to whatever is in here will be considered.