R/plot_wl.R

In climenv: Download, Extract and Visualise Climate and Elevation Data

#' plot_wl
#'
#'
#' @description Creates a graph using the climate and elevation data which has
#' been extracted for a given \code{location}. It accepts the data formatted
#' from the \code{ce_extract} function.
#' @template output_data_param
#' @template output_geo_id_param
#' @param \dots Arguments to control styling in
#' `ggclimat_walter_lieth()`.
#'
#' @returns
#' Returns a base R family of plot. This function uses the \pkg{climaemet}
#' package to create the Walter and Lieth (1960) climatic diagram.
#'
#' @author James L. Tsakalos and Martin R. Smith
#' @seealso Download climate data: [`ce_download()`]
#' @references{ Pizarro, M, Hernangómez, D. &
#' Fernández-Avilés G. (2023). climaemet: Climate AEMET Tools.
#' Comprehensive R Archive Network. \doi{10.5281/zenodo.5205573}
#'
#' Walter, H.B., & Lieth, H. (1960). Klimadiagramm-Weltatlas. VEB Gustav
#' Fischer Verlag, Jena.
#'
#' }
#' @encoding UTF-8
#' @examples
#' # Step 1. Import the Italian Biome polygon data
#' # Step 2. Run the download function
#' # Step 3. Run the extract function
#' #* See ce_download & ce_extract documentation
#'
#' # Steps 1, 2 & 3 can be skipped by loading the extracted data (it_data)
#' data("it_data", package = "climenv")
#'
#' # Step 4. Visualise the climatic envelope using a Walter-Lieth diagram
#'
#' plot_wl(data = it_data, geo_id = "NEM")
#'
#' @importFrom climaemet ggclimat_walter_lieth
#' @export
plot_wl <- function(data, geo_id, ...) {

  .validate_geo_id(geo_id, data)

  # Needed to print the climate date range on the plot
  c_source <- strsplit(data$Readme, " ")[[1]][5]

  # Walter-Lieth climate diagram

  climaemet::ggclimat_walter_lieth(
    dat = rbind(
      Prec. = data$prec_m[geo_id, 1:12],
      Max.t. = data$tmax_m[geo_id, 1:12],
      Min.t = data$tmin_m[geo_id, 1:12],
      Ab.m.t = data$abmt[geo_id, 1:12],
      make.row.names = TRUE
    ),
    alt = round(data$elev[geo_id, "mean"]),
    per = switch(
      c_source,
      "CHELSA" = "1981\u20132010",
      "WorldClim" = "1970\u20132000"
    ),
    est = geo_id,
    mlab = "en",
    shem = ifelse(data$lat[geo_id, ] > 0, FALSE, TRUE),
    ...

  )

}