Nothing
# Tests for get_gender(..., nn = TRUE) delegation to get_gender_nn
skip_if_no_nn_model <- function() {
skip_if_not_installed("torch")
tryCatch(
{
.load_nn_model <- getFromNamespace(".load_nn_model", "genderBR")
.load_nn_model()
},
error = function(e) {
skip("NN model artifacts not available")
}
)
}
test_that("get_gender(nn = TRUE) delegates to the neural network model", {
skip_if_no_nn_model()
expect_equal(get_gender("maria", nn = TRUE), "Female")
expect_equal(get_gender("joao", nn = TRUE), "Male")
})
test_that("get_gender(nn = TRUE, prob = TRUE) returns probabilities", {
skip_if_no_nn_model()
p <- get_gender("maria", nn = TRUE, prob = TRUE)
expect_type(p, "double")
expect_gt(p, 0.5)
})
test_that("get_gender(nn = TRUE) ignores state, internal, and year", {
skip_if_no_nn_model()
# These extra arguments should be silently ignored
res <- get_gender("maria", nn = TRUE, state = "SP", internal = FALSE, year = 2010)
expect_equal(res, "Female")
})
test_that("get_gender(nn = TRUE) works with vectorised input", {
skip_if_no_nn_model()
res <- get_gender(c("maria", "joao"), nn = TRUE)
expect_length(res, 2)
expect_equal(res, c("Female", "Male"))
})
test_that("get_gender rejects non-logical nn", {
expect_error(get_gender("Ana", nn = "true"), "'nn' must be logical")
expect_error(get_gender("Ana", nn = 1), "'nn' must be logical")
})
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