R/simulate_data.R

In jfjelstul/eumaps: Tools to make maps of the European Union

# Joshua C. Fjelstul, Ph.D.
# eumaps R package

#' Simulate map data
#'
#' @description This function simulates data for a map of the European Union
#'   (EU) made by `eumaps::make_map()`. The data is drawn from a uniform
#'   distribution. It creates a tibble. You can pass the column `member_state`
#'   to the `member_states` argument of `create_palette()` and the column
#'   `value` to the `values` argument of `create_palette()`.
#'
#' @return This function returns a `tibble` with 3 columns: `member_state_id`,
#'   `member_state`, and `value`.
#'
#' @param date String or date. Optional. If not `NULL`, data will only be
#'   simulated for countries that were member states on this date. If not
#'   `NULL`, today's date is used, and data will only be simulated for current
#'   member states. The default value is `NULL`.
#' @param min Numeric. Required, has a default value. The minimum value to use
#'   for the uniform distribution. The default value is `0`.
#' @param max Numeric. Required, has a default value. The maximum value to use
#'   for the uniform distribution. The default value is `1`.
#' @param missing String. Optional. A vector of member states names. The data
#'   for these member states will be coded as `NA`. This is option is useful for
#'   testing out color palettes. The default value is `NULL`.
#' @param seed Numeric. Optional. The seed to use for generating the data.
#'
#' @examples
#' # using the default values
#' data <- simulate_data()
#'
#' # using all options
#' data <- simulate_data(
#'   date = "2015-01-01",
#'   min = 0,
#'   max = 1,
#'   missing = c("France", "Germany")
#' )
#'
#' @export
simulate_data <- function(date = NULL, min = 0, max = 1, missing = NULL, seed = NULL) {
  if (is.null(date)) {
    date <- Sys.Date()
  }
  if (!is.null(seed)) {
    set.seed(seed)
  }
  data <- make_template(date)
  data$value <- runif(n = nrow(data), min = min, max = max)
  data$value[data$member_state %in% missing] <- NA
  data <- dplyr::select(data, member_state_id, member_state, value)
  return(data)
}