Run the TLG-generating pipeline
run(
object,
adam_db,
auto_pre = TRUE,
verbose = FALSE,
unwrap = FALSE,
...,
user_args = list(...)
)# S4 method for 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(...)
)
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.
(chevron_tlg
) input.
(list
of data.frames
) object containing the ADaM
datasets
(flag
) whether to perform the default pre processing step.
(flag
) whether to print argument information.
(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.
(list
) arguments from ...
.
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.
run(mng01, syn_data, auto_pre = TRUE, dataset = "adlb")
Run the code above in your browser using DataLab