Run a simulator over prior draws

Draws n parameter vectors from the prior and calls the simulator once per draw. Under a future plan the draws are spread across workers. See nsbi_simulator, nsbi_parallel and nsbi_progress.

Usage

simulate_for_sbi(
  simulator,
  prior,
  n,
  sim_args = list(),
  seed = NULL,
  verbose = FALSE
)

Arguments

simulator

A function called once per parameter set, returning one simulated observation: a numeric vector, a scalar, or a one-row matrix or data frame. See nsbi_simulator. Note the order: the simulator is the first argument here and the second in npe(prior, simulator, ...).

prior

An nsbi_prior (see prior_uniform(), prior_normal()).

n

Number of simulations.

sim_args

Named list of extra arguments passed to every simulator call: observed data, a time grid, a fixed population size, solver settings. See nsbi_simulator.

seed

Optional integer seed for reproducibility.

verbose

Print training progress.

Value

A list with theta (n x dim) and x (n x d) matrices and n_dropped, the number of simulations discarded for non-finite output.

Details

Simulations whose output is not finite are dropped together with their parameters, with a warning.

The simulator comes first here and second in npe(), nle() and npe_sequential(). That is the reverse of the fitting functions and it is easy to get backwards, so a call with the two swapped is detected and named rather than left to fail inside sample_prior().

Examples

prior <- prior_uniform(c(a = -1, b = -1), c(a = 1, b = 1))
sims <- simulate_for_sbi(function(a, b) c(a^2, b^2), prior, n = 100)
str(sims)
#> List of 3
#>  $ theta    : num [1:100, 1:2] 0.382 0.656 0.148 -0.736 -0.426 ...
#>   ..- attr(*, "dimnames")=List of 2
#>   .. ..$ : NULL
#>   .. ..$ : chr [1:2] "a" "b"
#>  $ x        : num [1:100, 1:2] 0.1462 0.4301 0.0218 0.5416 0.1819 ...
#>  $ n_dropped: int 0