test_that("Cressman Objective Analysis Method works correctly", {
  if (Sys.getenv("NOT_CRAN") != "true") {  # Desactiva este test en CRAN
    data("BD_Obs", package = "InterpolateR")
    data("BD_Coord", package = "InterpolateR")

    # Load the study area where the interpolation will be performed.
    shapefile <- terra::vect(system.file("extdata/study_area.shp", package = "InterpolateR"))

    # Performing interpolation using the Cressman method
    Interpolated_Cressman <- Cressman(BD_Obs, BD_Coord, shapefile, grid_resolution = 5,
                                      search_radius = c(20, 10), training = 1,
                                      stat_validation = "M001", Rain_threshold = NULL,
                                      save_model = FALSE)

    # Results
    Radius_20 = Interpolated_Cressman$Ensamble[[1]] # Interpolated data with a 20 km radius
    Radius_10 = Interpolated_Cressman$Ensamble[[2]] # Interpolated data with a 10 km radius

    # Validation statistics
    Validation_results_20 = Interpolated_Cressman$Validation[[1]] # Validation results with a 20 km radius
    Validation_results_10 = Interpolated_Cressman$Validation[[2]] # Validation results with a 10 km radius

    # Check that the result is a raster object
    expect_true(inherits(Radius_20, "SpatRaster"))
    expect_true(inherits(Radius_10, "SpatRaster"))
    expect_equal(terra::nlyr(Radius_20), length(unique(BD_Obs$Date)))
    expect_equal(terra::nlyr(Radius_10), length(unique(BD_Obs$Date)))
  } else {
    # Si estás en CRAN, omite esta prueba.
    message("Skipping test on CRAN.")
  }
})