The $profiles() method returns a list of data frames with profiling data if any profiling data was written to the profile CSV files. See save_profile_files() to control where the files are saved.

Support for profiling Stan programs is available with CmdStan >= 2.26 and requires adding profiling statements to the Stan program.

profiles()

Value

A list of data frames with profiling data if the profiling CSV files were created.

Examples


# \dontrun{
# first fit a model using MCMC
mcmc_program <- write_stan_file(
  'data {
    int<lower=0> N;
    array[N] int<lower=0,upper=1> y;
  }
  parameters {
    real<lower=0,upper=1> theta;
  }
  model {
    profile("likelihood") {
      y ~ bernoulli(theta);
    }
  }
  generated quantities {
    array[N] int y_rep;
    profile("gq") {
      y_rep = bernoulli_rng(rep_vector(theta, N));
    }
  }
'
)
mod_mcmc <- cmdstan_model(mcmc_program)

data <- list(N = 10, y = c(1,1,0,0,0,1,0,1,0,0))
fit <- mod_mcmc$sample(data = data, seed = 123, refresh = 0)
#> Running MCMC with 4 sequential chains...
#> 
#> Chain 1 finished in 0.0 seconds.
#> Chain 2 finished in 0.0 seconds.
#> Chain 3 finished in 0.0 seconds.
#> Chain 4 finished in 0.0 seconds.
#> 
#> All 4 chains finished successfully.
#> Mean chain execution time: 0.0 seconds.
#> Total execution time: 0.6 seconds.
#> 

fit$profiles()
#> [[1]]
#>         name      thread_id  total_time forward_time reverse_time chain_stack
#> 1 likelihood 0x7ff85af4eb00 0.001158940  0.000848855   0.00031008        6721
#> 2         gq 0x7ff85af4eb00 0.000444795  0.000444795   0.00000000           0
#>   no_chain_stack autodiff_calls no_autodiff_calls
#> 1           6721           6721                 1
#> 2              0              0              1000
#> 
#> [[2]]
#>         name      thread_id  total_time forward_time reverse_time chain_stack
#> 1 likelihood 0x7ff85af4eb00 0.001207200  0.000885927  0.000321272        6792
#> 2         gq 0x7ff85af4eb00 0.000453808  0.000453808  0.000000000           0
#>   no_chain_stack autodiff_calls no_autodiff_calls
#> 1           6792           6792                 1
#> 2              0              0              1000
#> 
#> [[3]]
#>         name      thread_id  total_time forward_time reverse_time chain_stack
#> 1 likelihood 0x7ff85af4eb00 0.001181750  0.000860407  0.000321346        6835
#> 2         gq 0x7ff85af4eb00 0.000418544  0.000418544  0.000000000           0
#>   no_chain_stack autodiff_calls no_autodiff_calls
#> 1           6835           6835                 1
#> 2              0              0              1000
#> 
#> [[4]]
#>         name      thread_id  total_time forward_time reverse_time chain_stack
#> 1 likelihood 0x7ff85af4eb00 0.001272150  0.000927098  0.000345053        6955
#> 2         gq 0x7ff85af4eb00 0.000416536  0.000416536  0.000000000           0
#>   no_chain_stack autodiff_calls no_autodiff_calls
#> 1           6955           6955                 1
#> 2              0              0              1000
#> 
# }