R/maxentTh.R

In SDMtune: Species Distribution Model Selection

#' MaxEnt Thresholds
#'
#' Returns the value of the thresholds generated by the MaxEnt software.
#'
#' @param model \linkS4class{SDMmodel} object trained using the "Maxent" method.
#'
#' @return data.frame with the thresholds.
#' @export
#'
#' @author Sergio Vignali
#'
#' @seealso \link{maxentVarImp}.
#'
#' @examples
#' \donttest{# Acquire environmental variables
#' files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
#'                     pattern = "grd",
#'                     full.names = TRUE)
#'
#' predictors <- terra::rast(files)
#'
#' # Prepare presence and background locations
#' p_coords <- virtualSp$presence
#' bg_coords <- virtualSp$background
#'
#' # Create SWD object
#' data <- prepareSWD(species = "Virtual species",
#'                    p = p_coords,
#'                    a = bg_coords,
#'                    env = predictors,
#'                    categorical = "biome")
#'
#' # Train a Maxent model
#' model <- train(method = "Maxent",
#'                data = data,
#'                fc = "l")
#'
#' maxentTh(model)}
maxentTh <- function(model) {

  if (!inherits(model@model, "Maxent"))
    cli::cli_abort(c(
      "!" = "Function available only for {.cls Maxent} models",
      "x" = "You have supplied a {.cls {class(model@model)}} instead."))

  thresholds <- grep(".threshold", rownames(model@model@results), value = TRUE)
  thresholds <- grep("cumulative.threshold", thresholds, value = TRUE,
                     invert = TRUE)
  labels <- gsub(".threshold", "", thresholds)
  df <- data.frame(threshold = model@model@results[thresholds, ])
  rownames(df) <- labels

  df
}