sim_proc_many_pops: Simulate and process many populations
In philliplab/yasss: Yet Another Short Sequence Simulator

Simulate and process many populations

sim_proc_many_pops(
  arg_collection,
  n_sims = 1,
  output_dmat = FALSE,
  max_dmat_size = 10000,
  fitness_processing = "none",
  n_gen_with_perfect_fitness = 4,
  output_genealogy = "none",
  verbose = FALSE
)

`arg_collection`	The collection of argument sets to be used in the simulations
`n_sims`	The number of times sim_pop must be called for each arg_set. The total number of data sets produced will be `n_sims * length(arg_collection)` if no fitness processing is specified and `n_sims * length(arg_collection) * 2` if any fitness processing is specified.
`output_dmat`	If TRUE, the distance matrices will be included in the output. Uses lots of memory - default is FALSE.
`max_dmat_size`	If more sequences than this number is present in a last generation on which a distance matrix is about to be computed, then `max_dmat_size` sequences will be randomly sampled and the distance matrix will only be computed on those sequences. Default is 10000.
`fitness_processing`	The way that the fitness scores should be used to sample from the genealogy. Valid options include: none: This will produce one dataset per genealogy. fit_unfit_pair: This will use the threshold approach to remove all unfit individuals and their offspring. The remaining members of the last generation will be considered to be the fit member of the pair. An equal number of individuals will be sampled at random from the original genealogy to produce the unfit pair such that it is the same size as the fit pair. fit_unfit_unmatched_pair: Same as fit_unfit_pair except that the unfit member will not be down sampled to size match the fit member.
`n_gen_with_perfect_fitness`	The number of initial generations that must be assigned perfect fitness. If an early ancestor has low fitness and is thus removed, the likelihood that the end up with an empty genealogy is too large.
`output_genealogy`	Should the genealogy be output? Valid options include: 'none', 'last_gen_only', and 'full'.
`verbose`	If TRUE, progress is printed to STDOUT.

A list with the following elements:

dcollection: A dcollection as checked by check_dcollection
arg_collection: The input arg_collection as checked by check_arg_collection.
all_genealogies [OPTIONAL]: A data.frame that contains all the genealogies, or in the case that last_gen_only was specified, only the last generations of the genealogies and all the identifier columns.
all_dmats [OPTIONAL]: A list of lists containing the distance matrixes and their indentifiers.
n_sims: The input n_sims indicating the number of datasets you can expect.