perform_sanity_checks -> sanitize_args_predictors_trainer

Author: dsweber2

NAMESPACE

@@ -28,12 +28,12 @@ export(make_shared_grids)
 export(make_target_ensemble_grid)
 export(make_target_param_grid)
 export(overprediction)
-export(perform_sanity_checks)
 export(read_external_predictions_data)
 export(rolling_mean)
 export(rolling_sd)
 export(run_evaluation_measure)
 export(run_workflow_and_format)
+export(sanitize_args_predictors_trainer)
 export(scaled_pop)
 export(sharpness)
 export(single_id)

R/data_validation.R

@@ -13,7 +13,7 @@
 #'   include empty strings
 #' @param args_list the args list created by [`epipredict::arx_args_list`]
 #' @export
-perform_sanity_checks <- function(epi_data,
+sanitize_args_predictors_trainer <- function(epi_data,
                                   outcome,
                                   predictors,
                                   trainer,

R/forecaster_flatline.R

@@ -40,9 +40,7 @@ flatline_fc <- function(epi_data,
   args_list <- do.call(flatline_args_list, args_input)
   # if you want to ignore extra_sources, setting predictors is the way to do it
   predictors <- c(outcome, extra_sources)
-  argsPredictorsTrainer <- perform_sanity_checks(epi_data, outcome, predictors, NULL, args_list)
-  args_list <- argsPredictorsTrainer[[1]]
-  predictors <- argsPredictorsTrainer[[2]]
+  c(args_list, predictors) %<-% sanitize_args_predictors_trainer(epi_data, outcome, predictors, NULL, args_list)
   # end of the copypasta
   # finally, any other pre-processing (e.g. smoothing) that isn't performed by
   # epipredict

R/forecaster_scaled_pop.R

@@ -35,7 +35,7 @@
 #' @param quantile_levels The quantile levels to predict. Defaults to those required by
 #'   covidhub.
 #' @seealso some utilities for making forecasters: [format_storage],
-#'   [perform_sanity_checks]
+#'   [sanitize_args_predictors_trainer]
 #' @importFrom epipredict epi_recipe step_population_scaling frosting arx_args_list layer_population_scaling
 #' @importFrom tibble tibble
 #' @importFrom recipes all_numeric
@@ -76,10 +76,7 @@ scaled_pop <- function(epi_data,
   # if you want to hardcode particular predictors in a particular forecaster
   predictors <- c(outcome, extra_sources)
   # TODO: Partial match quantile_level coming from here (on Dmitry's machine)
-  argsPredictorsTrainer <- perform_sanity_checks(epi_data, outcome, predictors, trainer, args_list)
-  args_list <- argsPredictorsTrainer[[1]]
-  predictors <- argsPredictorsTrainer[[2]]
-  trainer <- argsPredictorsTrainer[[3]]
+  c(args_list, predictors, trainer) <- sanitize_args_predictors_trainer(epi_data, outcome, predictors, trainer, args_list)
   # end of the copypasta
   # finally, any other pre-processing (e.g. smoothing) that isn't performed by
   # epipredict

R/forecaster_smoothed_scaled.R

@@ -41,7 +41,7 @@
 #' @param ... any additional arguments as used by [arx_args_list]
 #'   required by covidhub.
 #' @seealso some utilities for making forecasters: [format_storage],
-#'   [perform_sanity_checks]
+#'   [sanitize_args_predictors_trainer]
 #' @importFrom epipredict epi_recipe step_population_scaling frosting arx_args_list layer_population_scaling
 #' @importFrom tibble tibble
 #' @importFrom recipes all_numeric
@@ -110,7 +110,7 @@ smoothed_scaled <- function(epi_data,
   # and need to make sure we exclude the original variables as predictors
   predictors <- update_predictors(epi_data, c(smooth_cols, sd_cols), predictors)
   # TODO: Partial match quantile_level coming from here (on Dmitry's machine)
-  c(args_list, predictors, trainer) %<-% perform_sanity_checks(epi_data, outcome, predictors, trainer, args_list)
+  c(args_list, predictors, trainer) %<-% sanitize_args_predictors_trainer(epi_data, outcome, predictors, trainer, args_list)
   # preprocessing supported by epipredict
   preproc <- epi_recipe(epi_data)
   if (pop_scaling) {

man/perform_sanity_checks.Rd renamed to man/sanitize_args_predictors_trainer.Rd

@@ -1,10 +1,10 @@
-test_that("perform_sanity_checks", {
+test_that("sanitize_args_predictors_trainer", {
   epi_data <- epipredict::case_death_rate_subset
   # don't need to test validate_forecaster_inputs as that's inherited
   # testing args_list inheritance
   ex_args <- arx_args_list()
-  expect_error(perform_sanity_checks(epi_data, "case_rate", c("case_rate"), 5, ex_args))
-  argsPredictors <- perform_sanity_checks(
+  expect_error(sanitize_args_predictors_trainer(epi_data, "case_rate", c("case_rate"), 5, ex_args))
+  argsPredictors <- sanitize_args_predictors_trainer(
     epi_data, "case_rate", c("case_rate", ""), parsnip::linear_reg(), ex_args
   )
   args_list <- argsPredictors[[1]]