enh: pivot_quantiles_longer adds quantile_level to epi_df other_keys

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: epipredict
 Title: Basic epidemiology forecasting methods
-Version: 0.1.15
+Version: 0.1.16
 Authors@R: c(
     person("Daniel J.", "McDonald", , "[email protected]", role = c("aut", "cre")),
     person("Ryan", "Tibshirani", , "[email protected]", role = "aut"),

NEWS.md

@@ -12,12 +12,12 @@ Pre-1.0.0 numbering scheme: 0.x will indicate releases, while 0.0.x will indicat
   `data(<dataset name>, package = "epidatasets")`, `epidatasets::<dataset name>`
   or, after loading the package, the name of the dataset alone (#382).
 - `step_adjust_latency()` no longer allows empty column selection.
-- Addresses upstream breaking changes from cmu-delphi/epiprocess#595 (`growth_rate()`). 
+- Addresses upstream breaking changes from cmu-delphi/epiprocess#595 (`growth_rate()`).
   `step_growth_rate()` has lost its `additional_gr_args_list` argument and now
   has an `na_rm` argument.
 - Moves `epiprocess` out of depends (#440). No internals have changed, but downstream
   users may need to add `library(epiprocess)` to existing code.
-- Removes dependence on the `distributional` package, replacing the quantiles 
+- Removes dependence on the `distributional` package, replacing the quantiles
   with `hardhat::quantile_pred()`. Some associated functions are deprecated with
   `lifecycle` messages.
 - Rename `check_enough_train_data()` to `check_enough_data()`, and generalize it
@@ -38,6 +38,8 @@ Pre-1.0.0 numbering scheme: 0.x will indicate releases, while 0.0.x will indicat
 - Replace `dist_quantiles()` with `hardhat::quantile_pred()`
 - Allow `quantile()` to threshold to an interval if desired (#434)
 - `arx_forecaster()` detects if there's enough data to predict
+- `pivot_quantiles_longer()` now appropriately adds `quantile_level` to the
+  `epi_df` other keys
 
 ## Bug fixes
 

R/pivot_quantiles.R

@@ -62,8 +62,12 @@ pivot_quantiles_longer <- function(.data, ...) {
   long_tib <- as_tibble(.data[[col]])
   .data <- select(.data, !all_of(col))
   names(long_tib)[1:2] <- c(glue::glue("{col}_value"), glue::glue("{col}_quantile_level"))
-  left_join(.data, long_tib, by = ".row") %>%
+  out <- left_join(.data, long_tib, by = ".row") %>%
     select(!.row)
+  if (inherits(.data, "epi_df")) {
+    attr(out, "metadata")$other_keys <- c(attr(.data, "metadata")$other_keys, glue::glue("{col}_quantile_level"))
+  }
+  out
 }
 
 #' Pivot a column containing `quantile_pred` wider

tests/testthat/test-pivot_quantiles.R

@@ -45,6 +45,11 @@ test_that("quantile pivotting longer behaves", {
   expect_length(pivot_quantiles_longer(tib, d1), 4L)
   expect_identical(nrow(pivot_quantiles_longer(tib, d1)), 6L)
   expect_identical(pivot_quantiles_longer(tib, d1)$d1_value, c(1:3, 2:4))
+
+  # add quantile_level to epi_df other_keys, if epi_df
+  tib <- tibble(geo_value = c("a", "b"), time_value = as.Date(c("2021-01-01", "2021-01-02")), d1 = d1, d2 = d2)
+  epi_df <- tib %>% as_epi_df() %>% pivot_quantiles_longer(d1)
+  expect_equal(key_colnames(epi_df), c("geo_value","d1_quantile_level", "time_value"))
 })
 
 test_that("nested_quantiles is deprecated, but works where possible", {