Replace evaluate_chu with evalcast::evaluate_covid_predictions

Report/create_reports.R

@@ -134,27 +134,27 @@ if ( "confirmed_admissions_covid_1d" %in% unique(state_scores$signal)) {
 
 
 print("Evaluating national forecasts")
-# COVIDcast does not return national level data, using CovidHubUtils instead
+nation_scores = evaluate_covid_predictions(nation_predictions,
+                                                     err_measures,
+                                                     geo_type = "nation")
 
-nation_scores = evaluate_chu(nation_predictions, signals, err_measures)
-
-if ( "confirmed_incidence_num" %in% unique(state_scores$signal)) {
+if ( "confirmed_incidence_num" %in% unique(nation_scores$signal)) {
     print("Saving nation confirmed incidence...")
     save_score_cards(nation_scores, "nation",
                      signal_name = "confirmed_incidence_num", output_dir = opt$dir)
 } else {
     warning("Nation confirmed incidence should generally be available. Please 
             verify that you expect not to have any cases incidence forecasts")
 }
-if ( "deaths_incidence_num" %in% unique(state_scores$signal)) {
+if ( "deaths_incidence_num" %in% unique(nation_scores$signal)) {
     print("Saving nation deaths incidence...")
     save_score_cards(nation_scores, "nation", signal_name = "deaths_incidence_num",
                      output_dir = opt$dir)
 } else {
     warning("Nation deaths incidence should generally be available. Please 
             verify that you expect not to have any deaths incidence forecasts")
 }
-if ( "confirmed_admissions_covid_1d" %in% unique(state_scores$signal)) {
+if ( "confirmed_admissions_covid_1d" %in% unique(nation_scores$signal)) {
     print("Saving nation hospitalizations...")
     save_score_cards(nation_scores, "nation", signal_name = "confirmed_admissions_covid_1d",
                      output_dir = opt$dir)

Report/score.R

@@ -35,45 +35,3 @@ save_score_cards = function(score_card, geo_type = c("state", "nation"),
        file = output_file_name,
        compress = "xz")
 }
-
-evaluate_chu = function(predictions, signals, err_measures) {
-  allowed_signals = c("confirmed_incidence_num",
-                      "deaths_incidence_num",
-                      "confirmed_admissions_covid_1d")
-  assert_that(all(signals %in% allowed_signals),
-              msg = paste("Signal not allowed:",
-                          setdiff(signals, allowed_signals)))
-
-  target_map <- list("confirmed_incidence_num" = "inc case",
-                     "deaths_incidence_num" = "inc death",
-                     "confirmed_admissions_covid_1d" = "inc hosp")
-  source_map <- list("confirmed_incidence_num" = "JHU",
-                     "deaths_incidence_num" = "JHU",
-                     "confirmed_admissions_covid_1d" = "HealthData")
-  scores = c()
-  for (signal_name in signals) {
-    preds_signal = predictions %>%
-      filter(signal == signal_name)
-    signal <- target_map[[signal_name]]
-    source <- source_map[[signal_name]]
-    chu_truth = covidHubUtils::load_truth(source, signal)
-    chu_truth = chu_truth %>%
-      rename(actual = value) %>%
-      select(-c(model,
-                target_variable,
-                location,
-                location_name,
-                population,
-                geo_type,
-                abbreviation))
-    signal_scores = evaluate_predictions(preds_signal,
-                                         truth_data = chu_truth,
-                                         err_measures,
-                                         grp_vars = c("target_end_date",
-                                                      "geo_value",
-                                                      "ahead",
-                                                      "forecaster"))
-    scores = rbind(scores, signal_scores)
-  }
-  return(scores)
-}