Nothing
test_that("normal usage works works", {
skip_if_not_installed("recipes")
skip_if_not_installed("parsnip")
skip_if_not_installed("workflows")
skip_if_not_installed("tidypredict")
skip_if_not_installed("kknn")
rec_spec <- recipes::recipe(mpg ~ ., data = mtcars) %>%
recipes::step_normalize(recipes::all_numeric_predictors())
lm_spec <- parsnip::nearest_neighbor(mode = "regression")
wf_spec <- workflows::workflow(rec_spec, lm_spec)
wf_fit <- parsnip::fit(wf_spec, mtcars)
expect_snapshot(
error = TRUE,
orbital(wf_fit)
)
})
test_that("prefix argument works", {
skip_if_not_installed("parsnip")
skip_if_not_installed("tidypredict")
lm_spec <- parsnip::linear_reg()
lm_fit <- parsnip::fit(lm_spec, mpg ~ ., mtcars)
orb_obj <- orbital(lm_fit, prefix = "pred")
expect_true("pred" %in% names(orb_obj))
expect_false(".pred" %in% names(orb_obj))
lr_spec <- parsnip::logistic_reg()
mtcars$vs <- factor(mtcars$vs)
lr_fit <- parsnip::fit(lr_spec, vs ~ disp, mtcars)
orb_obj <- orbital(lr_fit, prefix = "pred")
expect_true("pred_class" %in% names(orb_obj))
expect_false(".pred_class" %in% names(orb_obj))
})
test_that("errors on invalid modes", {
skip_if_not_installed("parsnip")
lm_spec <- parsnip::linear_reg()
lm_fit <- parsnip::fit(lm_spec, mpg ~ ., mtcars)
lm_fit$spec$mode <- "invalid mode"
expect_snapshot(
error = TRUE,
orbital(lm_fit)
)
})
test_that("type argument checking works", {
skip_if_not_installed("tidypredict")
lm_spec <- parsnip::linear_reg()
lm_fit <- parsnip::fit(lm_spec, mpg ~ ., mtcars)
expect_no_error(
orbital(lm_fit, type = "numeric")
)
expect_snapshot(
error = TRUE,
orbital(lm_fit, type = "invalid")
)
expect_snapshot(
error = TRUE,
orbital(lm_fit, type = "class")
)
expect_snapshot(
error = TRUE,
orbital(lm_fit, type = c("class", "numeric"))
)
lm_spec <- parsnip::logistic_reg()
mtcars$vs <- factor(mtcars$vs)
lm_fit <- parsnip::fit(lm_spec, vs ~ disp, mtcars)
expect_no_error(
orbital(lm_fit, type = "class")
)
expect_no_error(
orbital(lm_fit, type = c("class", "prob"))
)
expect_snapshot(
error = TRUE,
orbital(lm_fit, type = "invalid")
)
expect_snapshot(
error = TRUE,
orbital(lm_fit, type = "numeric")
)
expect_snapshot(
error = TRUE,
orbital(lm_fit, type = c("class", "numeric"))
)
})
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