Run NONMEM jobs

Source: R/run_nm.R

[Stable]

Run nm objects. Uses system_nm() to submit the cmd() value of object.

run_nm(
  m,
  threads = Inf,
  ignore.stdout = FALSE,
  quiet = getOption("quiet_run"),
  intern = getOption("intern"),
  force = FALSE,
  cache_ignore_cmd = FALSE,
  cache_ignore_ctl = FALSE,
  cache_ignore_data = FALSE
)

Arguments

m

An nm object.

threads

Numeric. Number of jobs to run concurrently (default = Inf). Will block the console until all jobs are submitted.

ignore.stdout

Logical (default=TRUE). Parameter passed to system_nm().

quiet

Logical (default=FALSE). Should system_nm() output be piped to screen?

intern

Logical. intern argument to be passed to system_nm().

force

Logical (default = FALSE). Force run even results unchanged.

cache_ignore_cmd

Logical (default = FALSE). Should check cmd field with cache?

cache_ignore_ctl

Logical (default = FALSE). Should check control file contents with cache?

cache_ignore_data

Logical (default = FALSE). Should check dataset with cache?

Value

m with job_info fields populated.

Details

In grid environment it is recommended to run nm_tran() via the RStudio 'Addin' prior to executing this code.

By default, when highlighting code and evaluating it via an RStudio app, run_nm() will not execute and will just return the nm object.

For vector nm objects of length more than 1, all runs will be launched at the same time with a gap of getOption("job_time_spacing") seconds (default = 0). This could overwhelm resources if not in a grid environment.

run_nm is a variant of run_nm_single() containing a threads argument that will submit run_nm()'s in batches and wait for them to complete. If you need all the runs to complete ensure you use a wait_finish() statement afterwards as R console will only be blocked for until the last batch has been submitted which will be before all runs have completed.

The job_time_spacing argument

See also

nm_tran()

Examples

## requires NONMEM to be installed
if (FALSE) {
m1 <- new_nm(
  run_id = "m1",
  based_on = "staging/Models/ADVAN2.mod",
  data_path = "DerivedData/data.csv"
) %>%
  cmd("execute {ctl_name} -dir={run_dir}") %>%
  fill_input() %>%
  run_nm()
}