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) })