Nothing
# Loading data for testing resampling
BTsubset_meta <- base::readRDS(testthat::test_path("testdata", "data-meta.rds"))
BTsubset_data <- base::readRDS(testthat::test_path(
"testdata",
"data-query.rds"
))
test_df <- gridding(BTsubset_meta, BTsubset_data)
test_that("resampling returns an object of same class as meta", {
expect_no_error(resdf <- resampling(test_df, measure = "BIOMASS"))
expect_s3_class(resdf, "data.frame")
expect_no_error(
restbl <- resampling(test_df |> dplyr::as_tibble(), measure = "BIOMASS")
)
expect_s3_class(
restbl,
c("tbl_df", "tbl", "data.frame")
)
expect_no_error(
resdt <- resampling(
test_df |> data.table::as.data.table(),
measure = "BIOMASS"
)
)
expect_s3_class(
resdt,
c("data.table", "data.frame")
)
})
test_that("gridded object passed to resampling is not changed by reference", {
expect_no_error({
gdf <- gridding(BTsubset_meta, BTsubset_data)
resampling(gdf, measure = "BIOMASS")
})
expect_s3_class(gdf, "data.frame", exact = TRUE)
expect_no_error({
gtbl <- gridding(
BTsubset_meta |> dplyr::as_tibble(),
BTsubset_data |> dplyr::as_tibble()
)
resampling(gtbl, measure = "BIOMASS")
})
expect_s3_class(
gtbl,
c("tbl_df", "tbl", "data.frame"),
exact = TRUE
)
expect_no_error({
gdt <- gridding(
BTsubset_meta |> data.table::as.data.table(),
BTsubset_data |> data.table::as.data.table()
)
resampling(gdt, measure = "BIOMASS")
})
expect_s3_class(
gdt,
c("data.table", "data.frame"),
exact = TRUE
)
})
test_that("resampling correctly excludes 1 year long studies", {
test_df_1y <- rbind(
test_df,
test_df |>
dplyr::filter(SAMPLE_DESC == "1984_12_Control_0_Medium") |>
dplyr::mutate(
SAMPLE_DESC = "TEST",
STUDY_ID = 9999L,
YEAR = 2005L,
BIOMASS = 1L,
ABUNDANCE = 1L
)
)
expect_warning(
resampling(test_df_1y, "BIOMASS"),
regexp = "Some 1-year-long studies were removed."
)
expect_equal(
object = {
set.seed(42)
resampling(test_df_1y, "BIOMASS", verbose = FALSE)
},
expected = {
set.seed(42)
resampling(test_df, "BIOMASS", verbose = FALSE)
}
)
})
test_that("resampling correctly manages data.table, tibble and data.frame objects and respect class", {
skip_on_ci()
skip_on_cran()
set.seed(42)
data.table::setDT(test_df)
test_object <- resampling(test_df, measure = "BIOMASS") # BIOMASS would be faster
expect_s3_class(object = test_object, class = c("data.table", "data.frame"))
# if test_df is a tibble, test_object has to be a tibble
})
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