Hotfix growth rate

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: epipredict
 Title: Basic epidemiology forecasting methods
-Version: 0.1.9
+Version: 0.1.10
 Authors@R: c(
     person("Daniel J.", "McDonald", , "[email protected]", role = c("aut", "cre")),
     person("Ryan", "Tibshirani", , "[email protected]", role = "aut"),
@@ -25,7 +25,7 @@ URL: https://github.com/cmu-delphi/epipredict/,
 BugReports: https://github.com/cmu-delphi/epipredict/issues/
 Depends:
     epidatasets,
-    epiprocess (>= 0.9.0),
+    epiprocess (>= 0.10.4),
     parsnip (>= 1.0.0),
     R (>= 3.5.0)
 Imports:
@@ -73,7 +73,6 @@ Remotes:
     cmu-delphi/epidatasets,
     cmu-delphi/epidatr,
     cmu-delphi/epiprocess,
-    cmu-delphi/epidatasets,
     dajmcdon/smoothqr
 Config/Needs/website: cmu-delphi/delphidocs
 Config/testthat/edition: 3

NEWS.md

@@ -11,6 +11,9 @@ Pre-1.0.0 numbering scheme: 0.x will indicate releases, while 0.0.x will indicat
   `data(<dataset name>)`, but can be accessed with
   `data(<dataset name>, package = "epidatasets")`, `epidatasets::<dataset name>`
   or, after loading the package, the name of the dataset alone (#382).
+- 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.
 
 ## Improvements
 

R/arx_classifier.R

@@ -27,8 +27,9 @@
 #'
 #' @examples
 #' library(dplyr)
+#' tiny_geos <- c("as", "mp", "vi", "gu", "pr")
 #' jhu <- covid_case_death_rates %>%
-#'   filter(time_value >= as.Date("2021-11-01"))
+#'   filter(time_value >= as.Date("2021-11-01"), !(geo_value %in% tiny_geos))
 #'
 #' out <- arx_classifier(jhu, "death_rate", c("case_rate", "death_rate"))
 #'
@@ -58,7 +59,10 @@ arx_classifier <- function(
   if (args_list$adjust_latency == "none") {
     forecast_date_default <- max(epi_data$time_value)
     if (!is.null(args_list$forecast_date) && args_list$forecast_date != forecast_date_default) {
-      cli_warn("The specified forecast date {args_list$forecast_date} doesn't match the date from which the forecast is occurring {forecast_date}.")
+      cli_warn(
+        "The specified forecast date {args_list$forecast_date} doesn't match the
+        date from which the forecast is occurring {forecast_date}."
+      )
     }
   } else {
     forecast_date_default <- attributes(epi_data)$metadata$as_of
@@ -101,7 +105,7 @@ arx_classifier <- function(
 #'
 #' @return An unfit `epi_workflow`.
 #' @export
-#' @seealso [arx_classifier()]
+#' @seealso [arx_classifier()] [arx_class_args_list()]
 #' @examples
 #' library(dplyr)
 #' jhu <- covid_case_death_rates %>%
@@ -154,12 +158,13 @@ arx_class_epi_workflow <- function(
       role = "grp",
       horizon = args_list$horizon,
       method = args_list$method,
-      log_scale = args_list$log_scale,
-      additional_gr_args_list = args_list$additional_gr_args
+      log_scale = args_list$log_scale
     )
   for (l in seq_along(lags)) {
     pred_names <- predictors[l]
-    pred_names <- as.character(glue::glue_data(args_list, "gr_{horizon}_{method}_{pred_names}"))
+    pred_names <- as.character(glue::glue_data(
+      args_list, "gr_{horizon}_{method}_{pred_names}"
+    ))
     r <- step_epi_lag(r, !!pred_names, lag = lags[[l]])
   }
   # ------- outcome
@@ -185,8 +190,7 @@ arx_class_epi_workflow <- function(
           role = "pre-outcome",
           horizon = args_list$horizon,
           method = args_list$method,
-          log_scale = args_list$log_scale,
-          additional_gr_args_list = args_list$additional_gr_args
+          log_scale = args_list$log_scale
         )
     }
   }
@@ -270,9 +274,6 @@ arx_class_epi_workflow <- function(
 #' @param method Character. Options available for growth rate calculation.
 #' @param log_scale Scalar logical. Whether to compute growth rates on the
 #'   log scale.
-#' @param additional_gr_args List. Optional arguments controlling growth rate
-#'   calculation. See [epiprocess::growth_rate()] and the related Vignette for
-#'   more details.
 #' @param check_enough_data_n Integer. A lower limit for the number of rows per
 #'   epi_key that are required for training. If `NULL`, this check is ignored.
 #' @param check_enough_data_epi_keys Character vector. A character vector of
@@ -301,7 +302,6 @@ arx_class_args_list <- function(
     horizon = 7L,
     method = c("rel_change", "linear_reg"),
     log_scale = FALSE,
-    additional_gr_args = list(),
     check_enough_data_n = NULL,
     check_enough_data_epi_keys = NULL,
     ...) {
@@ -320,23 +320,14 @@ arx_class_args_list <- function(
   arg_is_lgl(log_scale)
   arg_is_pos(n_training)
   if (is.finite(n_training)) arg_is_pos_int(n_training)
-  if (!is.list(additional_gr_args)) {
-    cli_abort(c(
-      "`additional_gr_args` must be a {.cls list}.",
-      "!" = "This is a {.cls {class(additional_gr_args)}}.",
-      i = "See `?epiprocess::growth_rate` for available arguments."
-    ))
-  }
   arg_is_pos(check_enough_data_n, allow_null = TRUE)
   arg_is_chr(check_enough_data_epi_keys, allow_null = TRUE)
 
   if (!is.null(forecast_date) && !is.null(target_date)) {
     if (forecast_date + ahead != target_date) {
       cli_warn(
-        paste0(
-          "`forecast_date`  {.val {forecast_date}} +",
-          " `ahead` {.val {ahead}} must equal `target_date` {.val {target_date}}."
-        ),
+        "`forecast_date` {.val {forecast_date}} +
+        `ahead` {.val {ahead}} must equal `target_date` {.val {target_date}}.",
         class = "epipredict__arx_args__inconsistent_target_ahead_forecaste_date"
       )
     }
@@ -362,7 +353,6 @@ arx_class_args_list <- function(
       horizon,
       method,
       log_scale,
-      additional_gr_args,
       check_enough_data_n,
       check_enough_data_epi_keys
     ),

R/step_growth_rate.R

@@ -22,22 +22,25 @@
 #'   being removed from the data. Alternatively, you could specify arbitrary
 #'   large values, or perhaps zero. Setting this argument to `NULL` will result
 #'   in no replacement.
-#' @param additional_gr_args_list A list of additional arguments used by
-#'   [epiprocess::growth_rate()]. All `...` arguments may be passed here along
-#'   with `dup_rm` and `na_rm`.
+#' @inheritParams epiprocess::growth_rate
 #' @template step-return
 #'
 #'
 #' @family row operation steps
 #' @importFrom epiprocess growth_rate
 #' @export
 #' @examples
-#' r <- epi_recipe(covid_case_death_rates) %>%
+#' library(dplyr)
+#' tiny_geos <- c("as", "mp", "vi", "gu", "pr")
+#' rates <- covid_case_death_rates %>%
+#'   filter(time_value >= as.Date("2021-11-01"), !(geo_value %in% tiny_geos))
+#'
+#' r <- epi_recipe(rates) %>%
 #'   step_growth_rate(case_rate, death_rate)
 #' r
 #'
 #' r %>%
-#'   prep(covid_case_death_rates) %>%
+#'   prep(rates) %>%
 #'   bake(new_data = NULL)
 step_growth_rate <-
   function(recipe,
@@ -46,11 +49,11 @@ step_growth_rate <-
            horizon = 7,
            method = c("rel_change", "linear_reg"),
            log_scale = FALSE,
+           na_rm = TRUE,
            replace_Inf = NA,
            prefix = "gr_",
            skip = FALSE,
-           id = rand_id("growth_rate"),
-           additional_gr_args_list = list()) {
+           id = rand_id("growth_rate")) {
     if (!is_epi_recipe(recipe)) {
       cli_abort("This recipe step can only operate on an {.cls epi_recipe}.")
     }
@@ -63,15 +66,7 @@ step_growth_rate <-
     }
     arg_is_chr(role)
     arg_is_chr_scalar(prefix, id)
-    arg_is_lgl_scalar(log_scale, skip)
-
-
-    if (!is.list(additional_gr_args_list)) {
-      cli_abort(c(
-        "`additional_gr_args_list` must be a {.cls list}.",
-        i = "See `?epiprocess::growth_rate` for available options."
-      ))
-    }
+    arg_is_lgl_scalar(log_scale, skip, na_rm)
 
     recipes::add_step(
       recipe,
@@ -82,13 +77,13 @@ step_growth_rate <-
         horizon = horizon,
         method = method,
         log_scale = log_scale,
+        na_rm = na_rm,
         replace_Inf = replace_Inf,
         prefix = prefix,
         keys = key_colnames(recipe),
         columns = NULL,
         skip = skip,
-        id = id,
-        additional_gr_args_list = additional_gr_args_list
+        id = id
       )
     )
   }
@@ -101,13 +96,13 @@ step_growth_rate_new <-
            horizon,
            method,
            log_scale,
+           na_rm,
            replace_Inf,
            prefix,
            keys,
            columns,
            skip,
-           id,
-           additional_gr_args_list) {
+           id) {
     recipes::step(
       subclass = "growth_rate",
       terms = terms,
@@ -116,13 +111,13 @@ step_growth_rate_new <-
       horizon = horizon,
       method = method,
       log_scale = log_scale,
+      na_rm = na_rm,
       replace_Inf = replace_Inf,
       prefix = prefix,
       keys = keys,
       columns = columns,
       skip = skip,
-      id = id,
-      additional_gr_args_list = additional_gr_args_list
+      id = id
     )
   }
 
@@ -137,13 +132,13 @@ prep.step_growth_rate <- function(x, training, info = NULL, ...) {
     horizon = x$horizon,
     method = x$method,
     log_scale = x$log_scale,
+    na_rm = x$na_rm,
     replace_Inf = x$replace_Inf,
     prefix = x$prefix,
     keys = x$keys,
     columns = recipes::recipes_eval_select(x$terms, training, info),
     skip = x$skip,
-    id = x$id,
-    additional_gr_args_list = x$additional_gr_args_list
+    id = x$id
   )
 }
 
@@ -177,10 +172,12 @@ bake.step_growth_rate <- function(object, new_data, ...) {
       across(
         all_of(object$columns),
         ~ epiprocess::growth_rate(
-          time_value, .x,
+          .x,
+          x = time_value,
           method = object$method,
-          h = object$horizon, log_scale = object$log_scale,
-          !!!object$additional_gr_args_list
+          h = object$horizon,
+          log_scale = object$log_scale,
+          na_rm = object$na_rm
         ),
         .names = "{object$prefix}{object$horizon}_{object$method}_{.col}"
       )