run styler

Author: dajmcdon

R/epi_workflow.R

@@ -253,7 +253,7 @@ predict.epi_workflow <- function(object, new_data, ...) {
   if (!workflows::is_trained_workflow(object)) {
     cli::cli_abort(c(
       "Can't predict on an untrained epi_workflow.",
-        i = "Do you need to call `fit()`?"
+      i = "Do you need to call `fit()`?"
     ))
   }
   components <- list()

R/layer_add_forecast_date.R

@@ -97,7 +97,7 @@ slather.layer_add_forecast_date <- function(object, components, workflow, new_da
   expected_time_type <- attr(
     workflows::extract_preprocessor(workflow)$template, "metadata"
   )$time_type
-  if (expected_time_type == "week") expected_time_type = "day"
+  if (expected_time_type == "week") expected_time_type <- "day"
   check <- validate_date(object$forecast_date, expected_time_type)
 
   if (!check$ok) {

R/layer_add_target_date.R

@@ -87,7 +87,7 @@ slather.layer_add_target_date <- function(object, components, workflow, new_data
   expected_time_type <- attr(
     workflows::extract_preprocessor(workflow)$template, "metadata"
   )$time_type
-  if (expected_time_type == "week") expected_time_type = "day"
+  if (expected_time_type == "week") expected_time_type <- "day"
 
   if (!is.null(object$target_date)) {
     check <- validate_date(object$target_date, expected_time_type)
@@ -101,10 +101,9 @@ slather.layer_add_target_date <- function(object, components, workflow, new_data
     target_date <- coerce_time_type(object$target_date, expected_time_type)
   } else if (
     detect_layer(the_frosting, "layer_add_forecast_date") &&
-    !is.null(possible_fd <- extract_argument(
-      the_frosting, "layer_add_forecast_date", "forecast_date"
-    ))) {
-
+      !is.null(possible_fd <- extract_argument(
+        the_frosting, "layer_add_forecast_date", "forecast_date"
+      ))) {
     check <- validate_date(possible_fd, expected_time_type)
     if (!check$ok) {
       cli::cli_abort(c(
@@ -117,13 +116,13 @@ slather.layer_add_target_date <- function(object, components, workflow, new_data
     ahead <- extract_argument(the_recipe, "step_epi_ahead", "ahead")
     target_date <- forecast_date + ahead
   } else {
-      max_time_value <- max(
-        workflows::extract_preprocessor(workflow)$max_time_value,
-        workflow$fit$meta$max_time_value,
-        max(new_data$time_value)
-      )
-      ahead <- extract_argument(the_recipe, "step_epi_ahead", "ahead")
-      target_date <- max_time_value + ahead
+    max_time_value <- max(
+      workflows::extract_preprocessor(workflow)$max_time_value,
+      workflow$fit$meta$max_time_value,
+      max(new_data$time_value)
+    )
+    ahead <- extract_argument(the_recipe, "step_epi_ahead", "ahead")
+    target_date <- max_time_value + ahead
   }
 
   components$predictions <- dplyr::bind_cols(components$predictions,

R/step_epi_shift.R

@@ -120,9 +120,8 @@ step_epi_ahead <-
     if (missing(ahead)) {
       cli::cli_abort(c(
         "The `ahead` argument must not be empty.",
-          i = "Did you perhaps pass an integer in `...` accidentally?"
-        )
-      )
+        i = "Did you perhaps pass an integer in `...` accidentally?"
+      ))
     }
     arg_is_nonneg_int(ahead)
     arg_is_chr_scalar(prefix, id)

R/time_types.R

@@ -3,35 +3,53 @@ guess_time_type <- function(time_value) {
   arg_is_scalar(time_value)
   if (is.character(time_value)) {
     if (nchar(time_value) <= "10") {
-      new_time_value <- tryCatch({
-        as.Date(time_value)
-      }, error = function(e) NULL)
+      new_time_value <- tryCatch(
+        {
+          as.Date(time_value)
+        },
+        error = function(e) NULL
+      )
     } else {
-      new_time_value <- tryCatch({
-        as.POSIXct(time_value)
-      }, error = function(e) NULL)
+      new_time_value <- tryCatch(
+        {
+          as.POSIXct(time_value)
+        },
+        error = function(e) NULL
+      )
     }
     if (!is.null(new_time_value)) time_value <- new_time_value
   }
-  if (inherits(time_value, "POSIXct")) return("day-time")
-  if (inherits(time_value, "Date")) return("day")
-  if (inherits(time_value, "yearweek")) return("yearweek")
-  if (inherits(time_value, "yearmonth")) return("yearmonth")
-  if (inherits(time_value, "yearquarter")) return("yearquarter")
+  if (inherits(time_value, "POSIXct")) {
+    return("day-time")
+  }
+  if (inherits(time_value, "Date")) {
+    return("day")
+  }
+  if (inherits(time_value, "yearweek")) {
+    return("yearweek")
+  }
+  if (inherits(time_value, "yearmonth")) {
+    return("yearmonth")
+  }
+  if (inherits(time_value, "yearquarter")) {
+    return("yearquarter")
+  }
   if (is.numeric(time_value) && all(time_value == as.integer(time_value)) &&
-      all(time_value >= 1582)) {
+    all(time_value >= 1582)) {
     return("year")
   }
   return("custom")
 }
 
 coerce_time_type <- function(x, target_type) {
   if (target_type == "year") {
-    if (is.numeric(x)) return(as.integer(x))
-    else return(as.POSIXlt(x)$year + 1900L)
+    if (is.numeric(x)) {
+      return(as.integer(x))
+    } else {
+      return(as.POSIXlt(x)$year + 1900L)
+    }
   }
-  switch(
-    target_type,
+  switch(target_type,
     "day-time" = as.POSIXct(x),
     "day" = as.Date(x),
     "week" = as.Date(x),

tests/testthat/test-layer_add_forecast_date.R

@@ -104,5 +104,4 @@ test_that("forecast date works for daily", {
     adjust_frosting(f, "layer_add_forecast_date", forecast_date = 2022L)
   )
   expect_error(predict(wf1, latest)) # wrong time type of forecast_date
-
 })

tests/testthat/test-layer_add_target_date.R

@@ -115,6 +115,4 @@ test_that("forecast date works for daily", {
     adjust_frosting(f, "layer_add_target_date", target_date = 2022L)
   )
   expect_error(predict(wf1, latest)) # wrong time type of forecast_date
-
 })
-