Nothing
# ------------------------------------------------------------------------------
# Generated by 'pre-generate/generate-steps.R': do not edit by hand.
# ------------------------------------------------------------------------------
dist_train <- data.frame(
dist = I(list(eurodist))
)
dist_test <- data.frame(
dist = I(list(UScitiesD))
)
dist_rec <- recipe(~ ., data = dist_train) |>
step_phom_point_cloud(everything(), keep_original_cols = FALSE)
scale_seq <- seq(0, 5000, 100)
test_that("`step_vpd_tent_template_functions()` agrees with raw function", {
pl_rec <- dist_rec |>
step_vpd_tent_template_functions(
everything(),
hom_degree = 0,
keep_original_cols = FALSE
)
pl_prep <- prep(pl_rec, training = dist_train)
pl_pred <- bake(pl_prep, new_data = dist_test) |>
unlist() |> unname()
pl_exp <- dist_test$dist[[1L]] |>
ripserr::vietoris_rips() |> as.matrix() |>
TDAvec::computeTemplateFunction(
homDim = 0
) |>
as.vector()
expect_equal(pl_pred, pl_exp)
})
test_that("`tunable()` returns standard names", {
pl_rec <- dist_rec |>
step_vpd_tent_template_functions(everything(), keep_original_cols = FALSE)
tun <- tunable(pl_rec$steps[[2]])
expect_equal(
names(tun),
c("name", "call_info", "source", "component", "component_id")
)
expect_equal(
tun$name,
c("hom_degree", "tent_size", "num_bins", "tent_shift")
)
expect_equal(unique(tun$source), "recipe")
expect_true(is.list(tun$call_info))
})
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