Retrieve data from past 100 weeks

Report/predictions.R

@@ -4,7 +4,7 @@ library(dplyr)
 
 # TODO: Use `get_covidhub_forecaster_names()` instead of listing forecasters
 create_prediction_cards = function(){
-  start_date = today() - 12 * 7 # last 12 weeks
+  start_date = today() - 100 * 7 # last 12 weeks
 
   forecasters = get_covidhub_forecaster_names()
 
@@ -79,7 +79,8 @@ create_prediction_cards = function(){
     predictions_cards = predictions_cards_new
   }
   predictions_cards = predictions_cards %>%
-                        filter(forecast_date >= start_date)
+                        filter(forecast_date >= start_date) %>%
+                        filter(!is.na(predictions_cards$target_end_date))
 
   # Hack: must change the response data source to be USAFacts, as JHU-CSSE data is
   # currently unstable. **TODO**: we shouldn't require `evaluate_predictions()` to 

Report/score.R

@@ -3,7 +3,6 @@ library("dplyr")
 library("lubridate")
 
 create_score_cards = function(geo_type, signal_name = NULL, output_file_name = NULL){
-  start_date = today() - 12 * 7 # last 12 weeks
   if (!exists("predictions_cards")){
     predictions_cards = readRDS("predictions_cards.rds")
   }
@@ -80,7 +79,7 @@ create_score_cards = function(geo_type, signal_name = NULL, output_file_name = N
   } else {
     score_cards = score_cards_new
   }
-  score_cards = score_cards %>% filter(forecast_date >= start_date)
+ # score_cards = score_cards %>% filter(forecast_date >= start_date)
 
   saveRDS(score_cards, 
        file = output_file_name,