comparer (version 0.2.0)

ffexp: Full factorial experiment

Description

A class for easily creating and evaluating full factorial experiments.

Usage

e1 <- ffexp$new(eval_func=, )

e1$run_all()

e1$plot_run_times()

e1$save_self()

Arguments

eval_func The function called to evaluate each design point.

... Factors and their levels to be evaluated at.

save_output Should the output be saved?

parallel If TRUE, function evaluations are done in parallel.

parallel_cores Number of cores to be used in parallel. If "detect", parallel::detectCores() is used to determine number. "detect-1" may be used so that the computer isn't running at full capacity, which can slow down other tasks.

Methods

$new() Initialize an experiment. The preprocessing is done, but no function evaluations are run.

$run_all() Run all factor combinations.

$run_one() Run a single factor combination.

$add_result_of_one() Used to add result of evaluation to data set, don't manually call.

$plot_run_times() Plot the run times. Especially useful when they have been run in parallel.

$save_self() Save ffexp R6 object.

$recover_parallel_temp_save() If you ran the experiment using parallel with parallel_temp_save=TRUE and it crashes partway through, call this to recover the runs that were completed. Runs that were stopped mid-execution are not recoverable.

Examples

# NOT RUN {
# Two factors, both with two levels.
#   The evaluation function simply prints out the combination
cc <- ffexp$new(a=1:2,b=c("A","B"),
                eval_func=function(...) {c(...)})
# View the factor settings it will run (each row).
cc$rungrid
# Evaluate all four settings
cc$run_all()


cc <- ffexp$new(a=1:3,b=2, cd=data.frame(c=3:4,d=5:6),
                eval_func=function(...) {list(...)})
# }

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