R/simulate_wrappers.R

In sxmorgan/ansimo: ANalysis and SIMulation of Omics data

#'@title Wrapper function for simulations attempting to use batchtools package
#'@description TBD
#'@param df.stats a nested data.frames of a single high-throughput data type
#'@param structure either 'single.factor' or 'n.factor' (currently only for n = 2)
#'@param type one of 'bootstrap', 'gaussian', or 'nbinom'
#'@param n the number of simulations to run OR NA if replication carried
#'     out elsewhere (e.g. within the batchtools framework)
#'@param s.var the stratification variable as a character string OR NULL for pooled analysis
#'@param parallel a character string specifying parallelization strategy,
#'     e.g. 'multicore' if forked processes are supported or 'multiprocess' for any system
#'@return a list of data frames, each with additional list-columns of simulated values
#'@importFrom dplyr mutate
#'@importFrom furrr future_map
#'@export
batchtools.simulate.dynamic <- function(df.stats, structure = 'single.factor',
                                        type = 'bootstrap',
                                        n = NA, s.var = NA,
                                        parallel = NA) {

  if (!is.na(parallel)) {
    # doFuture::registerDoFuture()
    future::plan(parallel)}

  switch(structure,
         'single.factor' = {
           df.stats %>%
             dplyr::mutate(data = furrr::future_map(data,
                                                    ~ ansimo::simulate.single.factor.data(.,
                                                                                          type = type,
                                                                                          s.var = s.var,
                                                                                          n = n)))},
         'n.factor' = {
           df.stats %>%
             dplyr::mutate(data = furrr::future_map(data,
                                                   ~ ansimo::simulate.n.factor.data(.,
                                                                                    type = type,
                                                                                    s.var = s.var,
                                                                                    n = n)))
         })

}

test.sim.foreach <- function(df.stats, s.var = NULL, parallel = NULL) {

  if (!is.null(parallel)) {
    doFuture::registerDoFuture()
    future::plan(parallel)}

  algs <- c('bootstrap','gaussian','nbinom')

  simulated <- foreach::foreach(i = algs, .combine = c) %dopar% {
    tmp <- tmp %>%
      dplyr::mutate(sim.data = furrr::future_map(data,
                                                 ~ ansimo::simulate.data(.,
                                                                         type = i,
                                                                         s.var = s.var,
                                                                         n = n)))
  }

  simulated <- simulated %>%
    dplyr::bind_rows() %>%
    dplyr::select(-data)
}