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Return the command that ran CmdStan

Source: R/fit.R
fit-method-command.Rd

The $command() method returns the command line CmdStanR ran for each CmdStan run. A few things to know before running one again:

  • The paths are the ones R used. Input files CmdStanR wrote for the run (data passed as a list, inits, an inverse metric, the CSV files $laplace() and $generate_quantities() read) are in a temporary directory, even when output_dir is set, and don't outlive the R session.

  • The output paths are this fit's CSV files, so running the line again overwrites them unless you change the paths after output.

  • threads_per_chain (or threads) reaches CmdStan as the STAN_NUM_THREADS environment variable, not an argument, so set it first.

  • $sample_mpi() runs the line through the MPI launcher, which the line doesn't include.

  • On Windows CmdStanR puts the TBB library on PATH for the run, so the terminal needs it there too.

  • On WSL the command runs inside the Linux distribution, where the paths are already spelled for it.

Usage

command()

Value

A character vector with one command per CmdStan run.

Examples

# \dontrun{
fit <- cmdstanr_example("logistic", method = "sample")
fit$command()
#> [1] "'/tmp/RtmpwHIm89/logistic' 'id=1' 'random' 'seed=1199584326' 'data' 'file=/home/runner/work/_temp/Library/cmdstanr/logistic.data.json' 'output' 'file=/tmp/RtmpwHIm89/logistic-202610151525-01-6cf609.csv' 'profile_file=/tmp/RtmpwHIm89/logistic-profile-202610151525-01-0a0e76.csv' 'save_cmdstan_config=0' 'method=sample' 'save_warmup=0' 'algorithm=hmc' 'engine=nuts' 'adapt' 'engaged=1' 'save_metric=0'"
#> [2] "'/tmp/RtmpwHIm89/logistic' 'id=2' 'random' 'seed=1199584326' 'data' 'file=/home/runner/work/_temp/Library/cmdstanr/logistic.data.json' 'output' 'file=/tmp/RtmpwHIm89/logistic-202610151525-02-6cf609.csv' 'profile_file=/tmp/RtmpwHIm89/logistic-profile-202610151525-02-0a0e76.csv' 'save_cmdstan_config=0' 'method=sample' 'save_warmup=0' 'algorithm=hmc' 'engine=nuts' 'adapt' 'engaged=1' 'save_metric=0'"
#> [3] "'/tmp/RtmpwHIm89/logistic' 'id=3' 'random' 'seed=1199584326' 'data' 'file=/home/runner/work/_temp/Library/cmdstanr/logistic.data.json' 'output' 'file=/tmp/RtmpwHIm89/logistic-202610151525-03-6cf609.csv' 'profile_file=/tmp/RtmpwHIm89/logistic-profile-202610151525-03-0a0e76.csv' 'save_cmdstan_config=0' 'method=sample' 'save_warmup=0' 'algorithm=hmc' 'engine=nuts' 'adapt' 'engaged=1' 'save_metric=0'"
#> [4] "'/tmp/RtmpwHIm89/logistic' 'id=4' 'random' 'seed=1199584326' 'data' 'file=/home/runner/work/_temp/Library/cmdstanr/logistic.data.json' 'output' 'file=/tmp/RtmpwHIm89/logistic-202610151525-04-6cf609.csv' 'profile_file=/tmp/RtmpwHIm89/logistic-profile-202610151525-04-0a0e76.csv' 'save_cmdstan_config=0' 'method=sample' 'save_warmup=0' 'algorithm=hmc' 'engine=nuts' 'adapt' 'engaged=1' 'save_metric=0'"

# one line per chain
cat(fit$command(), sep = "\n")
#> '/tmp/RtmpwHIm89/logistic' 'id=1' 'random' 'seed=1199584326' 'data' 'file=/home/runner/work/_temp/Library/cmdstanr/logistic.data.json' 'output' 'file=/tmp/RtmpwHIm89/logistic-202610151525-01-6cf609.csv' 'profile_file=/tmp/RtmpwHIm89/logistic-profile-202610151525-01-0a0e76.csv' 'save_cmdstan_config=0' 'method=sample' 'save_warmup=0' 'algorithm=hmc' 'engine=nuts' 'adapt' 'engaged=1' 'save_metric=0'
#> '/tmp/RtmpwHIm89/logistic' 'id=2' 'random' 'seed=1199584326' 'data' 'file=/home/runner/work/_temp/Library/cmdstanr/logistic.data.json' 'output' 'file=/tmp/RtmpwHIm89/logistic-202610151525-02-6cf609.csv' 'profile_file=/tmp/RtmpwHIm89/logistic-profile-202610151525-02-0a0e76.csv' 'save_cmdstan_config=0' 'method=sample' 'save_warmup=0' 'algorithm=hmc' 'engine=nuts' 'adapt' 'engaged=1' 'save_metric=0'
#> '/tmp/RtmpwHIm89/logistic' 'id=3' 'random' 'seed=1199584326' 'data' 'file=/home/runner/work/_temp/Library/cmdstanr/logistic.data.json' 'output' 'file=/tmp/RtmpwHIm89/logistic-202610151525-03-6cf609.csv' 'profile_file=/tmp/RtmpwHIm89/logistic-profile-202610151525-03-0a0e76.csv' 'save_cmdstan_config=0' 'method=sample' 'save_warmup=0' 'algorithm=hmc' 'engine=nuts' 'adapt' 'engaged=1' 'save_metric=0'
#> '/tmp/RtmpwHIm89/logistic' 'id=4' 'random' 'seed=1199584326' 'data' 'file=/home/runner/work/_temp/Library/cmdstanr/logistic.data.json' 'output' 'file=/tmp/RtmpwHIm89/logistic-202610151525-04-6cf609.csv' 'profile_file=/tmp/RtmpwHIm89/logistic-profile-202610151525-04-0a0e76.csv' 'save_cmdstan_config=0' 'method=sample' 'save_warmup=0' 'algorithm=hmc' 'engine=nuts' 'adapt' 'engaged=1' 'save_metric=0'
# }