library(testthat)
library(recipes)
skip_if_not_installed("modeldata")
data(biomass, package = "modeldata")
biomass <- as_tibble(biomass)
means <- vapply(biomass[, 3:7], mean, c(mean = 0))
rec <- recipe(HHV ~ carbon + hydrogen + oxygen + nitrogen + sulfur,
data = biomass
)
test_that("working correctly", {
standardized <- rec %>%
step_center(carbon, hydrogen, oxygen, nitrogen, sulfur, id = "center")
cent_tibble_un <-
tibble(
terms = c("carbon", "hydrogen", "oxygen", "nitrogen", "sulfur"),
value = rep(na_dbl, 5),
id = standardized$steps[[1]]$id
)
expect_equal(tidy(standardized, 1), cent_tibble_un)
standardized_trained <- prep(standardized, training = biomass)
cent_tibble_tr <-
tibble(
terms = c("carbon", "hydrogen", "oxygen", "nitrogen", "sulfur"),
value = unname(means),
id = standardized$steps[[1]]$id
)
expect_equal(tidy(standardized_trained, 1), cent_tibble_tr)
expect_equal(standardized_trained$steps[[1]]$means, means)
})
test_that("single predictor", {
standardized <- rec %>%
step_center(carbon)
standardized_trained <- prep(standardized, training = biomass)
results <- bake(standardized_trained, biomass)
exp_res <- biomass[, 3:8]
exp_res$carbon <- exp_res$carbon - mean(exp_res$carbon)
expect_equal(results, exp_res[, colnames(results)])
})
test_that("na_rm argument works for step_center", {
mtcars_na <- mtcars
mtcars_na[1, 1:4] <- NA
rec_no_na_rm <- recipe(~., data = mtcars_na) %>%
step_center(all_predictors(), na_rm = FALSE) %>%
prep()
rec_na_rm <- recipe(~., data = mtcars_na) %>%
step_center(all_predictors(), na_rm = TRUE) %>%
prep()
exp_no_na_rm <- vapply(mtcars_na, FUN = mean, FUN.VALUE = numeric(1))
exp_na_rm <- vapply(mtcars_na, FUN = mean, FUN.VALUE = numeric(1), na.rm = TRUE)
expect_equal(
tidy(rec_no_na_rm, 1)$value,
unname(exp_no_na_rm)
)
expect_equal(
tidy(rec_na_rm, 1)$value,
unname(exp_na_rm)
)
})
test_that("centering with case weights", {
mtcars_freq <- mtcars
mtcars_freq$cyl <- frequency_weights(mtcars_freq$cyl)
rec <-
recipe(mpg ~ ., mtcars_freq) %>%
step_center(all_numeric_predictors()) %>%
prep()
expect_equal(
tidy(rec, number = 1)[["value"]],
unname(averages(mtcars_freq[, -c(1, 2)], mtcars_freq$cyl))
)
expect_snapshot(rec)
mtcars_imp <- mtcars
mtcars_imp$wt <- importance_weights(mtcars_imp$wt)
rec <-
recipe(mpg ~ ., mtcars_imp) %>%
step_center(all_numeric_predictors()) %>%
prep()
expect_equal(
tidy(rec, number = 1)[["value"]],
unname(averages(mtcars_imp[, -c(1, 6)], NULL))
)
expect_snapshot(rec)
})
test_that("warns when NaN is returned due to Inf or -Inf",{
rec <- recipe(~., data = data.frame(x = c(2, 3, 4, Inf))) %>%
step_center(x)
expect_snapshot(prep(rec))
rec <- recipe(~., data = data.frame(x = c(2, 3, 4, -Inf))) %>%
step_center(x)
expect_snapshot(prep(rec))
})
# Infrastructure ---------------------------------------------------------------
test_that("bake method errors when needed non-standard role columns are missing", {
std <- rec %>%
step_center(carbon, hydrogen, oxygen, nitrogen, sulfur) %>%
update_role(carbon, hydrogen, oxygen, nitrogen, sulfur, new_role = "potato") %>%
update_role_requirements(role = "potato", bake = FALSE)
std_trained <- prep(std, training = biomass)
expect_snapshot(error = TRUE, bake(std_trained, new_data = biomass[, 1:2]))
})
test_that("empty printing", {
rec <- recipe(mpg ~ ., mtcars)
rec <- step_center(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_center(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_center(rec)
expect <- tibble(terms = character(), value = double(), id = character())
expect_identical(tidy(rec, number = 1), expect)
rec <- prep(rec, mtcars)
expect_identical(tidy(rec, number = 1), expect)
})
test_that("printing", {
rec <- rec %>%
step_center(carbon)
expect_snapshot(print(rec))
expect_snapshot(prep(rec))
})
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