library(testthat)
library(recipes)
skip_if_not_installed("modeldata")
data(biomass, package = "modeldata")
# ------------------------------------------------------------------------------
biomass_tr <- biomass[biomass$dataset == "Training", ]
biomass_te <- biomass[biomass$dataset == "Testing", ]
rec <- recipe(HHV ~ carbon + hydrogen + oxygen + nitrogen + sulfur,
data = biomass_tr
)
# ------------------------------------------------------------------------------
test_that("correct basis functions", {
with_ns <- rec %>%
step_ns(carbon, hydrogen)
with_ns <- prep(with_ns, training = biomass_tr, verbose = FALSE)
with_ns_pred_tr <- bake(with_ns, new_data = biomass_tr)
with_ns_pred_te <- bake(with_ns, new_data = biomass_te)
carbon_ns_tr_exp <- splines::ns(biomass_tr$carbon, df = 2)
hydrogen_ns_tr_exp <- splines::ns(biomass_tr$hydrogen, df = 2)
carbon_ns_te_exp <- predict(carbon_ns_tr_exp, biomass_te$carbon)
hydrogen_ns_te_exp <- predict(hydrogen_ns_tr_exp, biomass_te$hydrogen)
expect_equal(
unname(attr(carbon_ns_tr_exp, "knots")),
attr(with_ns$steps[[1]]$objects$carbon, "knots")
)
expect_equal(
unname(attr(carbon_ns_tr_exp, "Boundary.knots")),
attr(with_ns$steps[[1]]$objects$carbon, "Boundary.knots")
)
expect_equal(
unname(attr(hydrogen_ns_tr_exp, "knots")),
attr(with_ns$steps[[1]]$objects$hydrogen, "knots")
)
expect_equal(
unname(attr(hydrogen_ns_tr_exp, "Boundary.knots")),
attr(with_ns$steps[[1]]$objects$hydrogen, "Boundary.knots")
)
carbon_ns_tr_res <- as.matrix(with_ns_pred_tr[, grep("carbon", names(with_ns_pred_tr))])
colnames(carbon_ns_tr_res) <- NULL
hydrogen_ns_tr_res <- as.matrix(with_ns_pred_tr[, grep("hydrogen", names(with_ns_pred_tr))])
colnames(hydrogen_ns_tr_res) <- NULL
carbon_ns_te_res <- as.matrix(with_ns_pred_te[, grep("carbon", names(with_ns_pred_te))])
colnames(carbon_ns_te_res) <- 1:ncol(carbon_ns_te_res)
hydrogen_ns_te_res <- as.matrix(with_ns_pred_te[, grep("hydrogen", names(with_ns_pred_te))])
colnames(hydrogen_ns_te_res) <- 1:ncol(hydrogen_ns_te_res)
## remove attributes
carbon_ns_tr_exp <- matrix(carbon_ns_tr_exp, ncol = 2)
carbon_ns_te_exp <- matrix(carbon_ns_te_exp, ncol = 2)
hydrogen_ns_tr_exp <- matrix(hydrogen_ns_tr_exp, ncol = 2)
hydrogen_ns_te_exp <- matrix(hydrogen_ns_te_exp, ncol = 2)
dimnames(carbon_ns_tr_res) <- NULL
dimnames(carbon_ns_te_res) <- NULL
dimnames(hydrogen_ns_tr_res) <- NULL
dimnames(hydrogen_ns_te_res) <- NULL
expect_equal(carbon_ns_tr_res, carbon_ns_tr_exp)
expect_equal(carbon_ns_te_res, carbon_ns_te_exp)
expect_equal(hydrogen_ns_tr_res, hydrogen_ns_tr_exp)
expect_equal(hydrogen_ns_te_res, hydrogen_ns_te_exp)
})
test_that("options(knots) works correctly (#1297)", {
exmaple_data <- tibble(x = seq(-2, 2, 0.01))
rec_res <- recipe(~., data = exmaple_data) %>%
step_ns(x, options = list(knots = seq(-1, 1, 0.125),
Boundary.knots = c(-1.5, 1.5))) %>%
prep() %>%
bake(new_data = NULL)
mm_res <- model.matrix(
~ splines::ns(
x,
knots = seq(-1, 1, 0.125),
Boundary.knots = c(-1.5, 1.5)
) - 1,
data = exmaple_data
)
attr(mm_res, "assign") <- NULL
mm_res <- setNames(as_tibble(mm_res), names(rec_res))
expect_identical(rec_res, mm_res)
})
test_that("check_name() is used", {
dat <- mtcars
dat$mpg_ns_1 <- dat$mpg
rec <- recipe(~ ., data = dat) %>%
step_ns(mpg)
expect_snapshot(
error = TRUE,
prep(rec, training = dat)
)
})
test_that("tunable", {
rec <-
recipe(~., data = iris) %>%
step_ns(all_predictors())
rec_param <- tunable.step_ns(rec$steps[[1]])
expect_equal(rec_param$name, c("deg_free"))
expect_true(all(rec_param$source == "recipe"))
expect_true(is.list(rec_param$call_info))
expect_equal(nrow(rec_param), 1)
expect_equal(
names(rec_param),
c("name", "call_info", "source", "component", "component_id")
)
})
test_that("works when baked with 1 row", {
rec <- recipe(mpg ~ ., data = mtcars) %>%
step_ns(disp) %>%
prep()
expect_no_error(
res <- bake(rec, mtcars[1, ])
)
expect_identical(nrow(res), 1L)
})
# Infrastructure ---------------------------------------------------------------
test_that("bake method errors when needed non-standard role columns are missing", {
with_ns <- rec %>%
step_ns(carbon, hydrogen) %>%
update_role(carbon, hydrogen, new_role = "potato") %>%
update_role_requirements(role = "potato", bake = FALSE)
with_ns <- prep(with_ns, training = biomass_tr, verbose = FALSE)
expect_snapshot(error = TRUE, bake(with_ns, new_data = biomass_tr[, c(-3)]))
})
test_that("empty printing", {
rec <- recipe(mpg ~ ., mtcars)
rec <- step_ns(rec)
expect_snapshot(rec)
rec <- prep(rec, mtcars)
expect_snapshot(rec)
})
test_that("empty selection prep/bake is a no-op", {
rec1 <- recipe(mpg ~ ., mtcars)
rec2 <- step_ns(rec1)
rec1 <- prep(rec1, mtcars)
rec2 <- prep(rec2, mtcars)
baked1 <- bake(rec1, mtcars)
baked2 <- bake(rec2, mtcars)
expect_identical(baked1, baked2)
})
test_that("empty selection tidy method works", {
rec <- recipe(mpg ~ ., mtcars)
rec <- step_ns(rec)
expect <- tibble(terms = character(), id = character())
expect_identical(tidy(rec, number = 1), expect)
rec <- prep(rec, mtcars)
expect_identical(tidy(rec, number = 1), expect)
})
test_that("keep_original_cols works", {
new_names <- c("mpg_ns_1", "mpg_ns_2")
rec <- recipe(~ mpg, mtcars) %>%
step_ns(all_predictors(), keep_original_cols = FALSE)
rec <- prep(rec)
res <- bake(rec, new_data = NULL)
expect_equal(
colnames(res),
new_names
)
rec <- recipe(~ mpg, mtcars) %>%
step_ns(all_predictors(), keep_original_cols = TRUE)
rec <- prep(rec)
res <- bake(rec, new_data = NULL)
expect_equal(
colnames(res),
c("mpg", new_names)
)
})
test_that("keep_original_cols - can prep recipes with it missing", {
rec <- recipe(~ mpg, mtcars) %>%
step_ns(all_predictors())
rec$steps[[1]]$keep_original_cols <- NULL
expect_snapshot(
rec <- prep(rec)
)
expect_no_error(
bake(rec, new_data = mtcars)
)
})
test_that("printing", {
rec <- recipe(mpg ~ ., data = mtcars) %>%
step_ns(disp, wt)
expect_snapshot(print(rec))
expect_snapshot(prep(rec))
})
test_that("tunable is setup to work with extract_parameter_set_dials", {
skip_if_not_installed("dials")
rec <- recipe(~., data = mtcars) %>%
step_ns(
all_predictors(),
deg_free = hardhat::tune()
)
params <- extract_parameter_set_dials(rec)
expect_s3_class(params, "parameters")
expect_identical(nrow(params), 1L)
})
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