R/autoplot_spatial_initial_split.R

In tidysdm: Species Distribution Models with Tidymodels

#' Create a ggplot for a spatial initial rsplit.
#'
#' This method provides a good visualization method for a spatial
#' initial rsplit.
#'
#' @details
#' This plot method is a wrapper around the standard `spatial_rsplit` method,
#' but it re-labels the folds as *Testing* and *Training* following the
#' convention for a standard `initial_split` object
#'
#' @param object A `spatial_initial_rsplit` object.
#' Note that only resamples made from
#' `sf` objects  create `spatial_initial_rsplit` objects;
#' this function will not work for
#' resamples made with non-spatial tibbles or data.frames.
#' @param ... Options passed to [ggplot2::geom_sf()].
#' @param alpha Opacity, passed to [ggplot2::geom_sf()].
#' Values of alpha range from 0 to 1, with lower values corresponding to more
#' transparent colors.
#' @returns A ggplot object with each fold assigned a color, made using
#' [ggplot2::geom_sf()].
#'
#' @examples
#'
#' set.seed(123)
#' block_initial <- spatial_initial_split(boston_canopy,
#'   prop = 1 / 5, spatial_block_cv
#' )
#' autoplot(block_initial)
#' @importFrom ggplot2 autoplot
#' @export

autoplot.spatial_initial_split <- function(object, ..., alpha = 0.6) {
  p <- utils::getS3method(
    "autoplot",
    "spatial_rsplit"
  )(object, alpha = alpha, ...)
  p$data$.class. <- p$data$.class. %>%
    dplyr::case_match("Assessment" ~ "Testing", "Analysis" ~ "Training")
  p
}