Nothing
library(testthat)
library(recipes)
set.seed(5522)
sim_dat <- data.frame(x1 = (20:100) / 10)
n <- nrow(sim_dat)
sim_dat$y1 <- sin(sim_dat$x1) + rnorm(n, sd = 0.1)
sim_dat$y2 <- cos(sim_dat$x1) + rnorm(n, sd = 0.1)
sim_dat$x2 <- runif(n)
sim_dat$x3 <- rnorm(n)
sim_dat$fac <- sample(letters[1:3], size = n, replace = TRUE)
rec <- recipe(~., data = sim_dat)
test_that("error checks", {
expect_snapshot(error = TRUE,
rec %>% step_window(y1, size = 6)
)
expect_snapshot(error = TRUE,
rec %>% step_window(y1, size = NA)
)
# Wait for call pass through
expect_error(
rec %>% step_window(y1, size = NULL)
)
expect_snapshot(error = TRUE,
rec %>% step_window(y1, statistic = "average")
)
expect_snapshot(error = TRUE,
rec %>% step_window(y1, size = 1)
)
expect_snapshot(error = TRUE,
rec %>% step_window(y1, size = 2)
)
expect_snapshot(error = TRUE,
rec %>% step_window(y1, size = -1)
)
expect_snapshot(
rec %>% step_window(y1, size = pi)
)
expect_snapshot(error = TRUE,
prep(rec %>% step_window(fac), training = sim_dat)
)
expect_snapshot(error = TRUE,
prep(rec %>% step_window(y1, size = 1000L), training = sim_dat)
)
bad_names <- rec %>%
step_window(starts_with("y"), names = "only_one_name")
expect_snapshot(error = TRUE,
prep(bad_names, training = sim_dat)
)
})
test_that("basic moving average", {
skip_if_not_installed("RcppRoll")
simple_ma <- rec %>%
step_window(starts_with("y"))
simple_ma <- prep(simple_ma, training = sim_dat)
simple_ma_res <- bake(simple_ma, new_data = sim_dat)
expect_equal(names(sim_dat), names(simple_ma_res))
for (i in 2:(n - 1)) {
expect_equal(simple_ma_res$y1[i], mean(sim_dat$y1[(i - 1):(i + 1)]))
expect_equal(simple_ma_res$y2[i], mean(sim_dat$y2[(i - 1):(i + 1)]))
}
expect_equal(simple_ma_res$y1[1], mean(sim_dat$y1[1:3]))
expect_equal(simple_ma_res$y2[1], mean(sim_dat$y2[1:3]))
expect_equal(simple_ma_res$y1[n], mean(sim_dat$y1[(n - 2):n]))
expect_equal(simple_ma_res$y2[n], mean(sim_dat$y2[(n - 2):n]))
})
test_that("creating new variables", {
skip_if_not_installed("RcppRoll")
new_names <- rec %>%
step_window(starts_with("y"), names = paste0("new", 1:2), role = "predictor")
new_names <- prep(new_names, training = sim_dat)
new_names_res <- bake(new_names, new_data = sim_dat)
simple_ma <- rec %>%
step_window(starts_with("y"))
simple_ma <- prep(simple_ma, training = sim_dat)
simple_ma_res <- bake(simple_ma, new_data = sim_dat)
expect_equal(new_names_res$new1, simple_ma_res$y1)
expect_equal(new_names_res$new2, simple_ma_res$y2)
})
test_that("na_rm argument works for step_window", {
skip_if_not_installed("RcppRoll")
sim_dat_na <- sim_dat
sim_dat_na[7, 2:3] <- NA
simple_ma_no_rm_na <- recipe(~., data = sim_dat_na) %>%
step_window(starts_with("y"), na_rm = FALSE) %>%
prep() %>%
bake(new_data = NULL)
simple_ma_rm_na <- recipe(~., data = sim_dat_na) %>%
step_window(starts_with("y"), na_rm = TRUE) %>%
prep() %>%
bake(new_data = NULL)
expect_false(any(is.na(simple_ma_rm_na$y1)))
expect_false(any(is.na(simple_ma_rm_na$y2)))
exp_rm_na <- simple_ma_rm_na
exp_rm_na[6:8, 2:3] <- NA
expect_equal(
simple_ma_no_rm_na,
exp_rm_na
)
})
test_that("tunable", {
rec <-
recipe(~., data = iris) %>%
step_window(all_predictors(), outcome = "Species")
rec_param <- tunable.step_window(rec$steps[[1]])
expect_equal(rec_param$name, c("statistic", "size"))
expect_true(all(rec_param$source == "recipe"))
expect_true(is.list(rec_param$call_info))
expect_equal(nrow(rec_param), 2)
expect_equal(
names(rec_param),
c("name", "call_info", "source", "component", "component_id")
)
})
test_that("check_name() is used", {
skip_if_not_installed("RcppRoll")
dat <- mtcars
dat$new_value <- dat$mpg
rec <- recipe(~ ., data = dat) %>%
step_window(mpg, names = "new_value")
expect_snapshot(
error = TRUE,
prep(rec, training = dat)
)
})
# Infrastructure ---------------------------------------------------------------
test_that("bake method errors when needed non-standard role columns are missing", {
skip_if_not_installed("RcppRoll")
rec <- rec %>%
step_window(x1) %>%
update_role(x1, new_role = "potato") %>%
update_role_requirements(role = "potato", bake = FALSE)
rec_trained <- prep(rec, training = sim_dat)
expect_error(bake(rec_trained, new_data = sim_dat[, -1]),
class = "new_data_missing_column")
})
test_that("empty printing", {
rec <- recipe(mpg ~ ., mtcars)
rec <- step_window(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_window(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_window(rec)
expect <- tibble(
terms = character(),
statistic = character(),
size = integer(),
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", {
skip_if_not_installed("RcppRoll")
new_names <- c("new_y1")
rec <- recipe(~ y1, data = sim_dat) %>%
step_window(y1, names = "new_y1", keep_original_cols = FALSE)
rec <- prep(rec)
res <- bake(rec, new_data = NULL)
expect_equal(
colnames(res),
new_names
)
rec <- recipe(~ y1, data = sim_dat) %>%
step_window(y1, names = "new_y1", keep_original_cols = TRUE)
rec <- prep(rec)
res <- bake(rec, new_data = NULL)
expect_equal(
colnames(res),
c("y1", new_names)
)
})
test_that("keep_original_cols - can prep recipes with it missing", {
skip_if_not_installed("RcppRoll")
rec <- recipe(~ y1, data = sim_dat) %>%
step_window(y1, names = "new_y1")
rec$steps[[1]]$keep_original_cols <- NULL
expect_snapshot(
rec <- prep(rec)
)
expect_error(
bake(rec, new_data = sim_dat),
NA
)
})
test_that("printing", {
rec <- recipe(mpg ~ ., mtcars)
rec <- step_window(rec)
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_window(
all_predictors(),
statistic = hardhat::tune(), size = hardhat::tune()
)
params <- extract_parameter_set_dials(rec)
expect_s3_class(params, "parameters")
expect_identical(nrow(params), 2L)
})
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