R/define.R

In statisfactions/simpr: Flexible 'Tidyverse'-Friendly Simulations

#' Define metaparameters to vary in simulation
#'
#' Takes the output of
#' \code{\link[=specify.formula]{specify}} (a
#' \code{simpr_spec} object) and defines the
#' metaparameters (i.e. simulation factors).
#'
#' This is the second step in the simulation
#' process, after specifying the simulated data
#' using \code{\link[=specify.formula]{specify}}.
#' The output of \code{\link{define}} is then
#' passed to
#' \code{\link[=generate.simpr_spec]{generate}} to
#' actually generate the simulation.
#'
#' Metaparameters are named arguments, passed to
#' \code{\dots}, that are used in the simulation.
#' A metaparameter is some kind of vector or list,
#' representing something that is to be
#' systematically varied as a part of the
#' simulation design. Any metaparameter should
#' also appear in the formulas of
#' \code{\link[=specify.formula]{specify}}, and
#' thus the simulation changes depending on the
#' value of the metaparameter.
#'
#' When creating the simulation, simulations for
#' all possible combinations of metaparameters are
#' generated, resulting in a fully crossed
#' simulation design.  If only a subset of the
#' fully crossed design is needed, use the
#' filtering options available in
#' \code{\link[=generate.simpr_spec]{generate}}.
#'
#' When one of \code{\dots} is a list, a new
#' column is generated in the output to
#' \code{\link[=generate.simpr_spec]{generate}} to
#' serve as the index of the list.  This new
#' column will be the name of the list argument,
#' with the \code{suffix} argument appended onto
#' the end.  So if \code{Y = list(a = 1:2, b =
#' letters[2:3])}, and \code{suffix = "_index"},
#' the default, a column named \code{Y_index}
#' would be added to the output of
#' \code{\link[=generate.simpr_spec]{generate}}
#' with values \code{"a"} and \code{"b"}.
#'
#' @param .x a \code{simpr_spec} object (the
#'   output of
#'   \code{\link[=specify.formula]{specify}})
#' @param ... metaparameters: named arguments
#'   containing vectors or lists of objects to be
#'   used in the simulation.
#' @param .list additional parameters passed to
#'   define() as a list.  Useful if you already
#'   have desired metaparameters already in list
#'   format or created by other functions.
#' @param .suffix name of suffix to append onto
#'   index column for list metaparameters,
#'   \code{"_index"} by default.  See
#'   \emph{Details}.
#' @return a \code{simpr_spec} object to pass onto
#'   \code{\link[=generate.simpr_spec]{generate}}
#'   for the simulation.
#'
#' @examples
#' # Simple example of setting a metaparameter
#' simple_meta = specify(a = ~ 1 + rnorm(n)) %>%
#'   define(n = c(5, 10)) %>%
#'   generate(1)
#'
#' simple_meta # $sim has a 5-row tibble and a 10-row tibble
#'
#' multi_meta = specify(a = ~ mu + rnorm(n)) %>%
#'   define(n = c(5, 10),
#'        mu = seq(-1, 1, length.out = 3)) %>%
#'   generate(1)
#'
#' multi_meta # generates simulations for all combos of n and mu
#'
#'
#' # define can handle lists which can contain multiple matrices, etc.
#' meta_list_out = specify(a = ~ MASS::mvrnorm(n, rep(0, 2), Sigma = S)) %>%
#'   define(n = c(10, 20, 30),
#'        S = list(independent = diag(2), correlated = diag(2) + 2)) %>%
#'   generate(1)
#'
#' meta_list_out # generates S_index column
#'
#' # define can also take arguments as a list using the .list argument
#' meta_list_out_2 = specify(a = ~ MASS::mvrnorm(n, rep(0, 2), Sigma = S)) %>%
#'   define(.list = list(n = c(10, 20, 30),
#'        S = list(independent = diag(2), correlated = diag(2) + 2))) %>%
#'   generate(1)
#'
#'
#' @export
define = function(.x = NULL, ..., .list = NULL, .suffix = "_index") {
  if(!(is.character(.suffix)) || length(.suffix) != 1 || nchar(.suffix) <= 0)
    stop(".suffix must be a string with at least 1 character")

  stopifnot(is.simpr_spec(.x))

  out = .x

  meta = c(list(...), .list)

  ## Create "index" element from names of list_elements
  list_elements = meta %>% purrr::map_lgl(is.list)

  ## Check list elements to see if dims work, assign index columns based on
  ## names of list
  if(any(list_elements)) {
    index_lookup = purrr::imap(meta[list_elements], function(x, n) {
      if(length(dim(x)) == 2) {
        stop("list arguments must be uni-dimensional")
      } else {
        if(is.null(names(x))) {
          index = 1:length(x)
        } else {
          index = names(x)
        }
      }

      lookup = tibble::tibble(index = index, value = x)
      names(lookup) = c(paste0(n, .suffix), n)

      list(index = index,
           lookup = lookup)
    })


    names(index_lookup) = paste0(names(index_lookup), .suffix)
    indices = purrr::map(index_lookup, "index")

    out$meta_info = list(indices = c(meta[!list_elements], purrr::map(index_lookup, "index")),
                  lookup =  purrr::map(index_lookup, "lookup"))

  } else {
    out$meta_info = list(indices = meta,
                  lookup = NULL)
  }

  out$conditions = expand.grid(out$meta_info$indices, stringsAsFactors = FALSE) %>%
    tibble::as_tibble()


  out
}