SimExtract: Extract extra information from SimDesign objects

In SimDesign: Structure for Organizing Monte Carlo Simulation Designs

Extract extra information from SimDesign objects

Description

Extracts any error or warnings messages, the seeds associated with any error or warning messages, and any analysis results that were stored in the final simulation object.

Usage

SimExtract(object, what, fuzzy = TRUE, append = TRUE)

Arguments

object	object returned from runSimulation
what	character vector indicating what information to extract, written in agnostic casing (e.g., 'ERRORS' and 'errors' are equivalent). Possible inputs include 'errors' to return a tibble object containing counts of any error messages 'warnings' to return a data.frame object containing counts of any warning messages 'seeds' for the specified random number generation seeds 'Random.seeds' for the complete list of .Random.seed states across replications (only stored when runSimulation(..., control = list(store_Random.seeds=TRUE))) 'log_times' for the per replication generate/analyse execution times (recorded in seconds) 'error_seeds' and 'warning_seeds' to extract the associated .Random.seed values associated with the ERROR/WARNING messages 'prepare_seeds' to extract the .Random.seed states captured before prepare() was called for each condition 'prepare_error_seed' to extract the .Random.seed state when prepare() encountered an error (useful for debugging with load_seed_prepare) 'results' to extract the simulation results if the option store_results was passed to runSimulation , 'filename' and 'save_results_dirname' for extracting the saved file/directory name information (if used), 'functions' to extract the defined functions used in the experiment 'design' to extract the original design object Note that 'warning_seeds' are not stored automatically in simulations and require passing store_warning_seeds = TRUE to runSimulation.
fuzzy	logical; use fuzzy string matching to reduce effectively identical messages? For example, when attempting to invert a matrix the error message "System is computationally singular: reciprocal condition number = 1.92747e-17" and "System is computationally singular: reciprocal condition number = 2.15321e-16" are effectively the same, and likely should be reported in the same columns of the extracted output
append	logical; append the design conditions when extracting error/warning messages?

Author(s)

Phil Chalmers [e-mail]

References

Chalmers, R. P., & Adkins, M. C. (2020). Writing Effective and Reliable Monte Carlo Simulations with the SimDesign Package. The Quantitative Methods for Psychology, 16(4), 248-280. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.20982/tqmp.16.4.p248")}

Sigal, M. J., & Chalmers, R. P. (2016). Play it again: Teaching statistics with Monte Carlo simulation. Journal of Statistics Education, 24(3), 136-156. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/10691898.2016.1246953")}

See Also

SimErrors, SimWarnings

Examples

## Not run: 

Generate <- function(condition, fixed_objects) {
    int <- sample(1:10, 1)
    if(int > 5) warning('GENERATE WARNING: int greater than 5')
    if(int == 1) stop('GENERATE ERROR: integer is 1')
    rnorm(5)
}

Analyse <- function(condition, dat, fixed_objects) {
    int <- sample(1:10, 1)
    if(int > 5) warning('ANALYSE WARNING: int greater than 5')
    if(int == 1) stop('ANALYSE ERROR: int is 1')
    c(ret = 1)
}

Summarise <- function(condition, results, fixed_objects) {
    mean(results)
}

res <- runSimulation(replications = 100, seed=1234,
                     generate=Generate, analyse=Analyse, summarise=Summarise)
res

SimExtract(res, what = 'errors')     # see also SimErrors()
SimExtract(res, what = 'warnings')   # see also SimWarnings()
seeds <- SimExtract(res, what = 'error_seeds')
seeds[,1:3]

# replicate a specific error for debugging (type Q to exit debugger)
res <- runSimulation(replications = 100, load_seed=seeds[,1], debug='analyse-1',
                     generate=Generate, analyse=Analyse, summarise=Summarise)




## End(Not run)

SimDesign documentation built on July 28, 2026, 1:07 a.m.