fix: format

Author: dshemetov

R/layer_yeo_johnson.R

@@ -136,23 +136,29 @@ slather.layer_epi_YeoJohnson <- function(object, components, workflow, new_data,
     # Wish I could suggest `all_outcomes()` here, but currently it's the same as
     # not specifying any terms. I don't want to spend time with dealing with
     # this case until someone asks for it.
-    cli::cli_abort("Not specifying columns to layer Yeo-Johnson is not implemented.
+    cli::cli_abort(
+      "Not specifying columns to layer Yeo-Johnson is not implemented.
     If you had a single outcome, you can use `.pred` as a column name.
     If you had multiple outcomes, you'll need to specify them like
     `.pred_ahead_1_<outcome_col>`, `.pred_ahead_7_<outcome_col>`, etc.
-    ", call = rlang::caller_env())
+    ",
+      call = rlang::caller_env()
+    )
   } else {
     # In this case, we assume that the user has specified the columns they want
     # transformed here. We then need to determine the lambda columns for each of
     # these columns. That is, we need to convert a vector of column names like
     # c(".pred_ahead_1_case_rate", ".pred_ahead_7_case_rate") to
     # c("lambda_ahead_1_case_rate", "lambda_ahead_7_case_rate").
     original_outcome_cols <- stringr::str_match(col_names, ".pred_ahead_\\d+_(.*)")[, 2]
-    outcomes_wout_ahead <- stringr::str_match(names(components$mold$outcomes), "ahead_\\d+_(.*)")[,2]
+    outcomes_wout_ahead <- stringr::str_match(names(components$mold$outcomes), "ahead_\\d+_(.*)")[, 2]
     if (any(original_outcome_cols %nin% outcomes_wout_ahead)) {
-      cli_abort("All columns specified in `...` must be outcome columns.
+      cli_abort(
+        "All columns specified in `...` must be outcome columns.
       They must be of the form `.pred_ahead_1_<outcome_col>`, `.pred_ahead_7_<outcome_col>`, etc.
-      ", call = rlang::caller_env())
+      ",
+        call = rlang::caller_env()
+      )
     }
 
     for (i in seq_along(col_names)) {

R/step_yeo_johnson.R

@@ -189,7 +189,9 @@ bake.step_epi_YeoJohnson <- function(object, new_data, ...) {
   }
   # Check that the keys match.
   keys <- key_colnames(new_data, exclude = "time_value")
-  old_keys <- object$lambdas %>% select(-starts_with(".lambda_")) %>% colnames()
+  old_keys <- object$lambdas %>%
+    select(-starts_with(".lambda_")) %>%
+    colnames()
   if (!all(keys %in% old_keys)) {
     cli::cli_abort(
       "The keys of the new data do not match the keys of the training data.",
@@ -348,15 +350,15 @@ estimate_yj <- function(dat, limits = c(-5, 5), num_unique = 5, na_rm = TRUE, ca
   const <- sum(sign(dat) * log(abs(dat) + 1))
 
   suppressWarnings(
-  res <- optimize(
-    yj_obj,
-    interval = limits,
-    maximum = TRUE,
-    dat = dat,
-    ind_neg = ind_neg,
-    const = const,
-    tol = .0001
-  )
+    res <- optimize(
+      yj_obj,
+      interval = limits,
+      maximum = TRUE,
+      dat = dat,
+      ind_neg = ind_neg,
+      const = const,
+      tol = .0001
+    )
   )
   lam <- res$maximum
   if (abs(limits[1] - lam) <= eps | abs(limits[2] - lam) <= eps) {

tests/testthat/test-yeo-johnson.R

@@ -39,7 +39,9 @@ test_that("Yeo-Johnson steps and layers invert each other", {
   wf <- epi_workflow(r, linear_reg()) %>%
     fit(filtered_data) %>%
     add_frosting(f)
-  out1 <- filtered_data %>% as_tibble() %>% slice_max(time_value, by = geo_value)
+  out1 <- filtered_data %>%
+    as_tibble() %>%
+    slice_max(time_value, by = geo_value)
   out2 <- forecast(wf) %>% rename(cases = .pred)
   expect_equal(out1, out2)
 
@@ -68,7 +70,9 @@ test_that("Yeo-Johnson steps and layers invert each other", {
   wf <- epi_workflow(r, linear_reg()) %>%
     fit(filtered_data) %>%
     add_frosting(f)
-  out1 <- filtered_data %>% as_tibble() %>% slice_max(time_value, by = geo_value)
+  out1 <- filtered_data %>%
+    as_tibble() %>%
+    slice_max(time_value, by = geo_value)
   # debugonce(slather.layer_epi_YeoJohnson)
   out2 <- forecast(wf) %>% rename(case_rate = .pred_ahead_0_case_rate, death_rate = .pred_ahead_0_death_rate)
   expect_equal(out1, out2)
@@ -124,7 +128,14 @@ test_that("Yeo-Johnson steps and layers invert each other when other_keys are pr
   wf <- epi_workflow(r, linear_reg()) %>%
     fit(filtered_data) %>%
     add_frosting(f)
-  out1 <- filtered_data %>% as_tibble() %>% slice_max(time_value, by = geo_value) %>% select(geo_value, age_group, time_value, med_income_2y) %>% arrange(geo_value, age_group, time_value)
-  out2 <- forecast(wf) %>% rename(med_income_2y = .pred) %>% select(geo_value, age_group, time_value, med_income_2y) %>% arrange(geo_value, age_group, time_value)
+  out1 <- filtered_data %>%
+    as_tibble() %>%
+    slice_max(time_value, by = geo_value) %>%
+    select(geo_value, age_group, time_value, med_income_2y) %>%
+    arrange(geo_value, age_group, time_value)
+  out2 <- forecast(wf) %>%
+    rename(med_income_2y = .pred) %>%
+    select(geo_value, age_group, time_value, med_income_2y) %>%
+    arrange(geo_value, age_group, time_value)
   expect_equal(out1, out2)
 })