Issue #981: Convert as_forecast_ to s3 (#982)

NAMESPACE

@@ -5,10 +5,14 @@ S3method("[",forecast)
 S3method("[<-",forecast)
 S3method("[[<-",forecast)
 S3method(`[`,scores)
+S3method(as_forecast_binary,default)
+S3method(as_forecast_nominal,default)
+S3method(as_forecast_ordinal,default)
 S3method(as_forecast_point,default)
 S3method(as_forecast_point,forecast_quantile)
 S3method(as_forecast_quantile,default)
 S3method(as_forecast_quantile,forecast_sample)
+S3method(as_forecast_sample,default)
 S3method(assert_forecast,default)
 S3method(assert_forecast,forecast_binary)
 S3method(assert_forecast,forecast_nominal)

NEWS.md

@@ -5,6 +5,7 @@ Minor spelling / mathematical updates to Scoring rule vignette. (#969)
 ## Package updates
 
 - A bug was fixed where `crps_sample()` could fail in edge cases.
+- All `as_forecast_<type>()` functions now have S3 methods for converting from another forecast type to the respective forecast type.
 - Implemented a new forecast class, `forecast_ordinal` with appropriate metrics. Ordinal forecasts are a form of categorical forecasts. The main difference between ordinal and nominal forecasts is that the outcome is ordered, rather than unordered.
 - Refactored the way that columns get internally renamed in `as_forecast_<type>()` functions (#980)
 

R/class-forecast-binary.R

@@ -18,22 +18,31 @@
 #'
 #' See the [example_binary] data set for an example.
 #' @inheritSection forecast_types Forecast unit
+#' @param ... Unused
 #' @returns A `forecast` object of class `forecast_binary`
 #' @family functions to create forecast objects
-#' @importFrom cli cli_warn
-#' @keywords as_forecast
 #' @export
+#' @keywords as_forecast transform
 #' @examples
 #' as_forecast_binary(
 #'   example_binary,
 #'   predicted = "predicted",
 #'   forecast_unit = c("model", "target_type", "target_end_date",
 #'                     "horizon", "location")
 #' )
-as_forecast_binary <- function(data,
-                               forecast_unit = NULL,
-                               observed = NULL,
-                               predicted = NULL) {
+as_forecast_binary <- function(data, ...) {
+  UseMethod("as_forecast_binary")
+}
+
+#' @rdname as_forecast_binary
+#' @export
+#' @method as_forecast_binary default
+#' @importFrom cli cli_warn
+as_forecast_binary.default <- function(data,
+                                       forecast_unit = NULL,
+                                       observed = NULL,
+                                       predicted = NULL,
+                                       ...) {
   data <- as_forecast_generic(
     data,
     forecast_unit,
@@ -45,7 +54,6 @@ as_forecast_binary <- function(data,
   return(data)
 }
 
-
 #' @export
 #' @rdname assert_forecast
 #' @importFrom cli cli_abort

R/class-forecast-nominal.R

@@ -7,7 +7,8 @@
 #'
 #' # Required input
 #'
-#' The input needs to be a data.frame or similar with the following columns:
+#' The input needs to be a data.frame or similar for the default method
+#' with the following columns:
 #' - `observed`: Column with observed values of type `factor` with N levels,
 #'    where N is the number of possible outcomes.
 #'    The levels of the factor represent the possible outcomes that
@@ -26,12 +27,10 @@
 #'
 #' See the [example_nominal] data set for an example.
 #' @inheritSection forecast_types Forecast unit
-#' @param predicted_label (optional) Name of the column in `data` that denotes
-#'   the outcome to which a predicted probability corresponds to.
-#'   This column will be renamed to "predicted_label".
+#' @param ... Unused
 #' @returns A `forecast` object of class `forecast_nominal`
 #' @family functions to create forecast objects
-#' @keywords as_forecast
+#' @keywords as_forecast transform
 #' @export
 #' @examples
 #' as_forecast_nominal(
@@ -40,11 +39,23 @@
 #'   forecast_unit = c("model", "target_type", "target_end_date",
 #'                     "horizon", "location")
 #' )
-as_forecast_nominal <- function(data,
-                                forecast_unit = NULL,
-                                observed = NULL,
-                                predicted = NULL,
-                                predicted_label = NULL) {
+as_forecast_nominal <- function(data, ...) {
+  UseMethod("as_forecast_nominal")
+}
+
+#' @rdname as_forecast_nominal
+#' @param predicted_label (optional) Name of the column in `data` that denotes
+#'   the outcome to which a predicted probability corresponds to.
+#'   This column will be renamed to "predicted_label".
+#' @export
+#' @method as_forecast_nominal default
+#' @importFrom cli cli_warn
+as_forecast_nominal.default <- function(data,
+                                        forecast_unit = NULL,
+                                        observed = NULL,
+                                        predicted = NULL,
+                                        predicted_label = NULL,
+                                        ...) {
   data <- as_forecast_generic(
     data,
     forecast_unit,

R/class-forecast-ordinal.R

@@ -7,7 +7,8 @@
 #'
 #' # Required input
 #'
-#' The input needs to be a data.frame or similar with the following columns:
+#' The input needs to be a data.frame or similar for the default method
+#' with the following columns:
 #' - `observed`: Column with observed values of type `factor` with N ordered
 #'   levels, where N is the number of possible outcomes.
 #'   The levels of the factor represent the possible outcomes that
@@ -26,25 +27,35 @@
 #'
 #' See the [example_ordinal] data set for an example.
 #' @inheritSection forecast_types Forecast unit
-#' @param predicted_label (optional) Name of the column in `data` that denotes
-#'   the outcome to which a predicted probability corresponds to.
-#'   This column will be renamed to "predicted_label".
-#' @returns A `forecast` object of class `forecast_ordinal`
+#' @param ... Unused
 #' @family functions to create forecast objects
-#' @keywords as_forecast
+#' @returns A `forecast` object of class `forecast_ordinal`
 #' @export
+#' @keywords as_forecast transform
 #' @examples
 #' as_forecast_ordinal(
 #'   na.omit(example_ordinal),
 #'   predicted = "predicted",
 #'   forecast_unit = c("model", "target_type", "target_end_date",
 #'                     "horizon", "location")
 #' )
-as_forecast_ordinal <- function(data,
-                                forecast_unit = NULL,
-                                observed = NULL,
-                                predicted = NULL,
-                                predicted_label = NULL) {
+as_forecast_ordinal <- function(data, ...) {
+  UseMethod("as_forecast_ordinal")
+}
+
+#' @rdname as_forecast_ordinal
+#' @param predicted_label (optional) Name of the column in `data` that denotes
+#'   the outcome to which a predicted probability corresponds to.
+#'   This column will be renamed to "predicted_label".
+#' @export
+#' @method as_forecast_ordinal default
+#' @importFrom cli cli_warn
+as_forecast_ordinal.default <- function(data,
+                                        forecast_unit = NULL,
+                                        observed = NULL,
+                                        predicted = NULL,
+                                        predicted_label = NULL,
+                                        ...) {
   data <- as_forecast_generic(
     data,
     forecast_unit,

R/class-forecast-point.R

@@ -3,7 +3,8 @@
 #' @details
 #' # Required input
 #'
-#' The input needs to be a data.frame or similar with the following columns:
+#' The input needs to be a data.frame or similar for the default method
+#' with the following columns:
 #' - `observed`: Column of type `numeric` with observed values.
 #' - `predicted`: Column of type `numeric` with predicted values.
 #'
@@ -24,6 +25,7 @@ as_forecast_point <- function(data, ...) {
 
 #' @rdname as_forecast_point
 #' @export
+#' @method as_forecast_point default
 #' @importFrom cli cli_warn
 as_forecast_point.default <- function(data,
                                       forecast_unit = NULL,

R/class-forecast-quantile.R

@@ -3,7 +3,8 @@
 #' @details
 #' # Required input
 #'
-#' The input needs to be a data.frame or similar with the following columns:
+#' The input needs to be a data.frame or similar for the default method
+#' with the following columns:
 #' - `observed`: Column of type `numeric` with observed values.
 #' - `predicted`: Column of type `numeric` with predicted values. Predicted
 #'    values represent quantiles of the predictive distribution.
@@ -39,6 +40,7 @@ as_forecast_quantile <- function(data, ...) {
 #'   the quantile level of the predicted values. This column will be renamed to
 #'   "quantile_level". Only applicable to quantile-based forecasts.
 #' @export
+#' @method as_forecast_quantile default
 #' @importFrom cli cli_warn
 as_forecast_quantile.default <- function(data,
                                          forecast_unit = NULL,

R/class-forecast-sample.R

@@ -3,7 +3,8 @@
 #' @details
 #' # Required input
 #'
-#' The input needs to be a data.frame or similar with the following columns:
+#' The input needs to be a data.frame or similar for the default method
+#' with the following columns:
 #' - `observed`: Column of type `numeric` with observed values.
 #' - `predicted`: Column of type `numeric` with predicted values. Predicted
 #'    values represent random samples from the predictive distribution.
@@ -17,18 +18,27 @@
 #' See the [example_sample_continuous] and [example_sample_discrete] data set
 #' for an example
 #' @inheritSection forecast_types Forecast unit
+#' @param ... Unused
+#' @family functions to create forecast objects
+#' @returns A `forecast` object of class `forecast_sample`
+#' @export
+#' @keywords as_forecast transform
+as_forecast_sample <- function(data, ...) {
+  UseMethod("as_forecast_sample")
+}
+
+
+#' @rdname as_forecast_sample
 #' @param sample_id (optional) Name of the column in `data` that contains the
 #'   sample id. This column will be renamed to "sample_id".
 #' @export
-#' @returns A `forecast` object of class `forecast_sample`
-#' @family functions to create forecast objects
 #' @importFrom cli cli_warn
-#' @keywords as_forecast
-as_forecast_sample <- function(data,
-                               forecast_unit = NULL,
-                               observed = NULL,
-                               predicted = NULL,
-                               sample_id = NULL) {
+as_forecast_sample.default <- function(data,
+                                       forecast_unit = NULL,
+                                       observed = NULL,
+                                       predicted = NULL,
+                                       sample_id = NULL,
+                                       ...) {
   data <- as_forecast_generic(
     data,
     forecast_unit,