Refactor validate_ensemble_outputs() to reduce cyclomatic complexity

R/validate_ensemble_inputs.R

@@ -25,6 +25,7 @@
 #' @param valid_output_types `character` vector with the names of valid output
 #'   types for the particular ensembling method used. See the details for more
 #'   information.
+#'
 #' @details If the ensembling function intended to be used is `"simple_ensemble"`,
 #'   the valid output types are `mean`, `median`, `quantile`, `cdf`, and `pmf`.
 #'   If the ensembling function will be `"linear_pool"`, the valid output types
@@ -90,38 +91,7 @@ validate_ensemble_inputs <- function(model_out_tbl, weights = NULL,
   }
 
   if (!is.null(weights)) {
-    req_weight_cols <- c("model_id", weights_col_name)
-    if (!all(req_weight_cols %in% colnames(weights))) {
-      cli::cli_abort(c(
-        "x" = "{.arg weights} did not include required columns
-               {.val {req_weight_cols}}."
-      ))
-    }
-
-    weight_by_cols <- colnames(weights)[colnames(weights) != weights_col_name]
-
-    if ("value" %in% weight_by_cols) {
-      cli::cli_abort(c(
-        "x" = "{.arg weights} included a column named {.val {\"value\"}},
-               which is not allowed."
-      ))
-    }
-
-    invalid_cols <- weight_by_cols[!weight_by_cols %in% colnames(model_out_tbl)]
-    if (length(invalid_cols) > 0) {
-      cli::cli_abort(c(
-        "x" = "{.arg weights} included {length(invalid_cols)} column{?s} that
-               {?was/were} not present in {.arg model_out_tbl}:
-               {.val {invalid_cols}}"
-      ))
-    }
-
-    if (weights_col_name %in% colnames(model_out_tbl)) {
-      cli::cli_abort(c(
-        "x" = "The specified {.arg weights_col_name}, {.val {weights_col_name}},
-               is already a column in {.arg model_out_tbl}."
-      ))
-    }
+    validate_weights(model_out_cols, weights, weights_col_name)
 
     if (any(c("cdf", "pmf") %in% unique_output_types) && "output_type_id" %in% colnames(weights)) {
       # nolint start
@@ -141,3 +111,53 @@ validate_ensemble_inputs <- function(model_out_tbl, weights = NULL,
                            comp_unit_cols = comp_unit_cols)
   return(validated_inputs)
 }
+
+
+#' Perform basic validations on the model weights used to calculate an ensemble of
+#' component model outputs for each combination of model task, output type,
+#' and output type id.
+#'
+#' @param model_out_cols `character` string naming columns in a `model_out_tbl`
+#'   object of component predictions that will be ensembled using the model weights
+#'   in `weights`
+#' @param weights a `data.frame` of component model weights to be validated. It must
+#'   contain a `model_id` column and a column giving weights, but may also contain
+#'   additional columns corresponding to task id variables, `output_type`, or
+#'   `output_type_id`, if weights are specific to values of those variables.
+#' @param weights_col_name `character` string naming the column in `weights`
+#'   with model weights. Defaults to `"weight"`
+#'
+#' @return no return value
+#' @noRd
+
+validate_weights <- function(model_out_cols, weights = NULL, weights_col_name = "weight") {
+  req_weight_cols <- c("model_id", weights_col_name)
+  if (!all(req_weight_cols %in% colnames(weights))) {
+    cli::cli_abort(c(
+      "x" = "{.arg weights} did not include required columns {.val {req_weight_cols}}."
+    ))
+  }
+
+  weight_by_cols <- colnames(weights)[colnames(weights) != weights_col_name]
+
+  if ("value" %in% weight_by_cols) {
+    cli::cli_abort(c(
+      "x" = "{.arg weights} included a column named {.val {\"value\"}}, which is not allowed."
+    ))
+  }
+
+  invalid_cols <- weight_by_cols[!weight_by_cols %in% model_out_cols]
+  if (length(invalid_cols) > 0) {
+    cli::cli_abort(c(
+      "x" = "{.arg weights} included {length(invalid_cols)} column{?s} that
+             {?was/were} not present in {.arg model_out_tbl}: {.val {invalid_cols}}"
+    ))
+  }
+
+  if (weights_col_name %in% model_out_cols) {
+    cli::cli_abort(c(
+      "x" = "The specified {.arg weights_col_name}, {.val {weights_col_name}},
+             is already a column in {.arg model_out_tbl}."
+    ))
+  }
+}