Run the TLG-generating pipeline

Usage

run(
  object,
  adam_db,
  auto_pre = TRUE,
  verbose = FALSE,
  unwrap = FALSE,
  ...,
  user_args = list(...)
)

# S4 method for class 'chevron_tlg'
run(
  object,
  adam_db,
  auto_pre = TRUE,
  verbose = get_arg("chevron.run.verbose", "R_CHEVRON_RUN_VERBOSE", FALSE),
  unwrap = get_arg("chevron.run.unwrap", "R_CHEVRON_RUN_UNWRAP", verbose),
  ...,
  user_args = list(...)
)

Arguments

object

(chevron_tlg) input.

adam_db

(list of data.frames) object containing the ADaM datasets

auto_pre

(flag) whether to perform the default pre processing step.

verbose

(flag) whether to print argument information.

unwrap

(flag) whether to print the preprocessing postprocessing and main function together with the associated layout function.

...

extra arguments to pass to the pre-processing, main and post-processing functions.

user_args

(list) arguments from ....

Value

an rtables (for chevron_t), rlistings (for chevron_l), grob (for chevron_g) or ElementaryTable (null report) depending on the class of chevron_tlg object passed as object argument.

Details

The functions stored in the preprocess, main and postprocess slots of the chevron_tlg objects are called respectively, preprocessing, main and postprocessing functions.

When executing the run method on a chevron_tlg object, if auto_pre is TRUE, the adam_bd list is first passed to the preprocessing function. The resulting list is then passed to the main function which produces a table, graph or listings or a list of these objects. This output is then passed to the postprocessing function which performed the final modifications before returning the output. Additional arguments specified in ... or user_args are passed to each of the three functions.

Examples

run(mng01, syn_data, auto_pre = TRUE, dataset = "adlb")
#> $`Alanine Aminotransferase Measurement`

#> 
#> $`C-Reactive Protein Measurement`

#> 
#> $`Immunoglobulin A Measurement`

#>