update default args to assert_forecast_type()

R/forecast.R

@@ -118,7 +118,7 @@ as_forecast.default <- function(data,
   }
 
   # assert forecast type is as expected
-  assert_forecast_type(data, forecast_type)
+  assert_forecast_type(data, desired = forecast_type)
   forecast_type <- get_forecast_type(data)
 
   # produce warning if old format is suspected
@@ -205,7 +205,7 @@ validate_forecast.default <- function(data, forecast_type = NULL, ...) {
 #' @keywords check-forecasts
 validate_forecast.forecast_binary <- function(data, forecast_type = NULL, ...) {
   data <- validate_general(data)
-  assert_forecast_type(data, forecast_type)
+  assert_forecast_type(data, actual = "binary", desired = forecast_type)
 
   columns_correct <- test_columns_not_present(
     data, c("sample_id", "quantile_level")
@@ -239,7 +239,7 @@ validate_forecast.forecast_binary <- function(data, forecast_type = NULL, ...) {
 #' @keywords check-forecasts
 validate_forecast.forecast_point <- function(data, forecast_type = NULL, ...) {
   data <- validate_general(data)
-  assert_forecast_type(data, forecast_type)
+  assert_forecast_type(data, actual = "point", desired = forecast_type)
   #nolint start: keyword_quote_linter object_usage_linter
   input_check <- check_input_point(data$observed, data$predicted)
   if (!is.logical(input_check)) {
@@ -261,7 +261,7 @@ validate_forecast.forecast_point <- function(data, forecast_type = NULL, ...) {
 validate_forecast.forecast_quantile <- function(data,
                                                 forecast_type = NULL, ...) {
   data <- validate_general(data)
-  assert_forecast_type(data, forecast_type)
+  assert_forecast_type(data, actual = "quantile", desired = forecast_type)
   assert_numeric(data$quantile_level, lower = 0, upper = 1)
   return(data[])
 }
@@ -271,9 +271,8 @@ validate_forecast.forecast_quantile <- function(data,
 #' @rdname validate_forecast
 #' @keywords check-forecasts
 validate_forecast.forecast_sample <- function(data, forecast_type = NULL, ...) {
-
   data <- validate_general(data)
-  assert_forecast_type(data, forecast_type)
+  assert_forecast_type(data, actual = "sample", desired = forecast_type)
   return(data[])
 }
 

R/get_-functions.R

@@ -100,20 +100,22 @@ test_forecast_type_is_quantile <- function(data) {
 
 #' Assert that forecast type is as expected
 #' @param data A forecast object as produced by [as_forecast()].
-#' @inheritParams as_forecast
+#' @param actual The actual forecast type of the data
+#' @param desired The desired forecast type of the data
 #' @inherit document_assert_functions return
 #' @importFrom cli cli_abort
 #' @importFrom checkmate assert_character
-assert_forecast_type <- function(data, forecast_type = NULL) {
-  assert_character(forecast_type, null.ok = TRUE)
-  desired <- forecast_type
-  forecast_type <- get_forecast_type(data)
-  if (!is.null(desired) && desired != forecast_type) {
+#' @keywords internal_input_check
+assert_forecast_type <- function(data,
+                                 actual = get_forecast_type(data),
+                                 desired = NULL) {
+  assert_character(desired, null.ok = TRUE)
+  if (!is.null(desired) && desired != actual) {
     #nolint start: object_usage_linter keyword_quote_linter
     cli_abort(
       c(
         "!" = "Forecast type determined by scoringutils based on input:
-        {.val {forecast_type}}.",
+        {.val {actual}}.",
         "i" = "Desired forecast type: {.val {desired}}."
       )
     )