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`

#>