Appendix A — Appendix 1 - WordClim 2.1 data transformation for NetLogo

Code

library(beepr, quietly = TRUE)
library(checkmate, quietly = TRUE)
library(geobr, quietly = TRUE)
library(lubridate, quietly = TRUE)
library(raster, quietly = TRUE)
library(rutils, quietly = TRUE) # danielvartan/rutils (GitHub)
library(rstudioapi, quietly = TRUE)
library(stringr, quietly = TRUE)

A.1 Preset

Code

# dir <- rstudioapi::selectDirectory()
dir <- here::here("data-raw", "worldclim")
if (!checkmate::test_directory_exists(dir)) dir.create(dir)

A.2 Loading file

Code

file <- here::here("data-raw", "worldclim", "wc2.1_10m_tmin_03.tif")

Code

ras <- raster::raster(file)

A.3 Crop raster file

Code

br_shape <- geobr::read_country()

Code

croped_ras <- 
  raster::crop(ras, raster::extent(br_shape)) |>
  raster::mask(br_shape)

Code

raster::plot(croped_ras)

A.4 Transform raster in .asc

Code

files <- 
  here::here("data-raw", "worldclim") |>
  list.files(full.names = TRUE, pattern = "tif$", recursive = TRUE)

Code

convert_to_asc <- function(file) {
  checkmate::assert_character(file)

  years <- c(
    1872, 1900, 1911, 1920, 1933, 1940, 1950, 1960, 1970, 1980, 1991, 2000,
    2001, 2010, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020
  )
  
  for (i in file) {
    checkmate::assert_file(i, access = "r")
    
    year <- 
      i |>
      stringr::str_extract("19[0-9]{2}|20[0-9]{2}") |>
      as.numeric()
    
    if (is.na(year)){
      cli::cli_abort("Year not found in the file name.")
    }
    
    br_shape <- geobr::read_country(
      year = years[which.min(abs(years - year))],
      showProgress = FALSE
    )
    
    asc_file <- stringr::str_replace(i, "tif$", "asc")
    
    i |> 
      raster::raster() |> 
      raster::crop(raster::extent(br_shape)) |>
      raster::mask(br_shape) |>
      raster::aggregate(fact = 2) |>
      raster::writeRaster(
        filename = asc_file, 
        format = "ascii",
        overwrite = TRUE
      )
  }
  
  invisible(NULL)
}

Code

convert_to_asc(files)

beepr::beep(1)

A.5 Extracting data

Code

files <- 
  "C:/Users/Daniel/Documents/GitHub/gs-abm/data-raw/worldclim/" |>
  list.files(full.names = TRUE, pattern = "asc$", recursive = TRUE)

A.5.1 Months

Code

stringr::str_extract(files, "(?<=-)[0-9]{2}(?=.asc)") |> 
  rutils:::drop_na() |>
  unique()

A.5.2 Historical years

Code

stringr::str_extract(files, "[0-9]{4}(?=-[0-9]{2}.asc)") |> 
  rutils:::drop_na() |>
  unique()

A.5.3 Historical year-month

Code

stringr::str_extract(files, "[0-9]{4}-[0-9]{2}(?=.asc)") |> 
  rutils:::drop_na() |>
  unique() |>
  lubridate::ym()

A.5.4 Future years

Code

stringr::str_extract(files, "[0-9]{4}-[0-9]{4}(?=.asc)") |> 
  rutils:::drop_na() |>
  unique()

A.6 GCM

Code

stringr::str_extract(files, "(?<=_)[A-Z].+(?=_ssp[0-9]{3}_[0-9]{4}-[0-9]{4}.asc)") |> 
  rutils:::drop_na() |>
  unique()

A.6.1 SSP

Code

stringr::str_extract(files, "ssp[0-9]{3}(?=_[0-9]{4}-[0-9]{4}.asc)") |> 
  rutils:::drop_na() |>
  unique()