library(testthat)
library(recipes)
library(tibble)
n <- 20
set.seed(1)
ex_dat <- data.frame(
x1 = exp(rnorm(n, mean = .1)),
x2 = 1 / abs(rnorm(n)),
x3 = rep(1:2, each = n / 2),
x4 = rexp(n),
x5 = rep(0:1, each = n / 2)
)
test_that("simple inverse trans", {
rec <- recipe(~ x1 + x2 + x3 + x4, data = ex_dat) %>%
step_inverse(x1, x2, x3, x4)
rec_trained <- prep(rec, training = ex_dat, verbose = FALSE)
rec_trans <- bake(rec_trained, new_data = ex_dat)
exp_res <- as_tibble(lapply(ex_dat[, -5], function(x) 1 / x))
expect_equal(rec_trans, exp_res)
})
test_that("alt offset", {
rec <- recipe(~., data = ex_dat) %>%
step_inverse(x1, x2, x3, x4, x5, offset = 0.1)
rec_trained <- prep(rec, training = ex_dat, verbose = FALSE)
rec_trans <- bake(rec_trained, new_data = ex_dat)
exp_res <- as_tibble(lapply(ex_dat, function(x) 1 / (x + 0.1)))
expect_equal(rec_trans, exp_res)
})
test_that("printing", {
rec <- recipe(~., data = ex_dat) %>%
step_inverse(x1, x2, x3, x4)
expect_snapshot(print(rec))
expect_snapshot(prep(rec))
})
test_that("empty selection prep/bake is a no-op", {
rec1 <- recipe(mpg ~ ., mtcars)
rec2 <- step_inverse(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_inverse(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("empty printing", {
skip_if(packageVersion("rlang") < "1.0.0")
rec <- recipe(mpg ~ ., mtcars)
rec <- step_inverse(rec)
expect_snapshot(rec)
rec <- prep(rec, mtcars)
expect_snapshot(rec)
})
test_that("bake method errors when needed non-standard role columns are missing", {
rec <- recipe(~ x1 + x2 + x3 + x4, data = ex_dat) %>%
step_inverse(x1, x2, x3, x4) %>%
update_role(x1, x2, x3, x4, new_role = "potato") %>%
update_role_requirements(role = "potato", bake = FALSE)
rec_trained <- prep(rec, training = ex_dat, verbose = FALSE)
expect_error(bake(rec_trained, new_data = ex_dat[, 1:3]),
class = "new_data_missing_column")
})
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