Update functionality of as_forceast()

R/validate.R

@@ -18,16 +18,84 @@
 #' @keywords check-forecasts
 #' @examples
 #' as_forecast(example_binary)
-#' as_forecast(example_quantile)
-as_forecast <- function(data, ...) {
+#' as_forecast(
+#'   example_quantile,
+#'   forecast_unit = c("model", "target_type", "target_end_date",
+#'                     "horizon", "location")
+#' )
+as_forecast <- function(data,
+                        ...) {
   UseMethod("as_forecast")
 }
 
 #' @rdname as_forecast
+#' @param observed (optional) Name of the column in `data` that contains the
+#' observed values. This column will be renamed to "observed".
+#' @param predicted (optional) Name of the column in `data` that contains the
+#' predicted values. This column will be renamed to "predicted".
+#' @param model (optional) Name of the column in `data` that contains the names
+#' of the models/forecasters that generated the predicted values.
+#' This column will be renamed to "model".
+#' @param forecast_unit (optional) Name of the columns in `data` (after
+#' renaming) that denote the unit of a single forecast.
+#' See [get_forecast_unit()] for details.
+#' @param quantile_level (optional) Name of the column in `data` that contains
+#' the quantile level of the predicted values. This column will be renamed to
+#' "quantile_level". Only applicable to quantile-based forecasts.
+#' @param sample_id (optional) Name of the column in `data` that contains the
+#' sample id. This column will be renamed to "sample_id". Only applicable to
+#' sample-based forecasts.
 #' @export
-as_forecast.default <- function(data, ...) {
+as_forecast.default <- function(data,
+                                observed = NULL,
+                                predicted = NULL,
+                                model = NULL,
+                                forecast_unit = NULL,
+                                quantile_level = NULL,
+                                sample_id = NULL,
+                                ...) {
+  # check inputs
+  data <- ensure_data.table(data)
+  assert_character(observed, len = 1, null.ok = TRUE)
+  assert_subset(observed, names(data), empty.ok = TRUE)
+
+  assert_character(predicted, len = 1, null.ok = TRUE)
+  assert_subset(predicted, names(data), empty.ok = TRUE)
+
+  assert_character(model, len = 1, null.ok = TRUE)
+  assert_subset(model, names(data), empty.ok = TRUE)
+
+  assert_character(quantile_level, len = 1, null.ok = TRUE)
+  assert_subset(quantile_level, names(data), empty.ok = TRUE)
+
+  assert_character(sample_id, len = 1, null.ok = TRUE)
+  assert_subset(sample_id, names(data), empty.ok = TRUE)
+
+  # rename columns
+  if (!is.null(observed)) {
+    setnames(data, old = observed, new = "observed")
+  }
+  if (!is.null(predicted)) {
+    setnames(data, old = predicted, new = "predicted")
+  }
+  if (!is.null(model)) {
+    setnames(data, old = model, new = "model")
+  }
+  if (!is.null(quantile_level)) {
+    setnames(data, old = quantile_level, new = "quantile_level")
+  }
+  if (!is.null(sample_id)) {
+    setnames(data, old = sample_id, new = "sample_id")
+  }
+
+  # assert that everything worked out
   assert(check_data_columns(data))
 
+  # set forecast unit (error handling is done in `set_forecast_unit()`)
+  if (!is.null(forecast_unit)) {
+    data <- set_forecast_unit(data, forecast_unit)
+  }
+
   # find forecast type
   forecast_type <- get_forecast_type(data)