Drop proration handling in pipeline

All prorated PINs will now be handled inside of iasWorld. As such, we
need the pipeline to produce the full (unprorated) value for each PIN
for upload

pipeline/02-assess.R

@@ -105,7 +105,7 @@ assessment_data_mc <- assessment_data_pred %>%
   group_by(meta_pin) %>%
   mutate(
     pred_pin_final_fmv = ifelse(
-      sum(pred_card_intermediate_fmv) * meta_tieback_proration_rate <=
+      sum(pred_card_intermediate_fmv) <=
         params$pv$multicard_yoy_cap * first(meta_1yr_pri_board_tot * 10) |
         is.na(meta_1yr_pri_board_tot),
       sum(pred_card_intermediate_fmv),
@@ -125,23 +125,22 @@ complex_id_data <- read_parquet(paths$input$complex_id$local) %>%
   select(meta_pin, meta_complex_id)
 
 # Join complex IDs to the predictions, then for each complex, set the
-# prediction to the average prediction of the complex. Also, multiply
-# the PIN-level value by the PIN's proration rate
+# prediction to the average prediction of the complex
 assessment_data_cid <- assessment_data_mc %>%
   left_join(complex_id_data, by = "meta_pin") %>%
-  group_by(meta_complex_id, meta_tieback_proration_rate) %>%
+  group_by(meta_complex_id) %>%
   mutate(
     pred_pin_final_fmv = ifelse(
       is.na(meta_complex_id),
-      pred_pin_final_fmv * meta_tieback_proration_rate,
-      mean(pred_pin_final_fmv) * meta_tieback_proration_rate
+      pred_pin_final_fmv,
+      mean(pred_pin_final_fmv)
     )
   ) %>%
   ungroup()
 
 
-## 3.3. Prorate/Round ----------------------------------------------------------
-message("Rounding and prorating predictions")
+## 3.3. Round ------------------------------------------------------------------
+message("Rounding predictions")
 
 # Round PIN-level predictions using the breaks and amounts specified in params
 assessment_data_final <- assessment_data_cid %>%