Add meta_pin_num_card to proration grouping

pipeline/02-assess.R

@@ -91,7 +91,7 @@ assessment_card_data_mc <- assessment_card_data_pred %>%
   # For prorated PINs with multiple cards, take the average of the card
   # (building) across PINs. This is because the same prorated building spread
   # across multiple PINs sometimes receives different values from the model
-  group_by(meta_tieback_key_pin, meta_card_num, char_land_sf) %>%
+  group_by(meta_tieback_key_pin, meta_card_num, char_bldg_sf) %>%
   mutate(
     pred_card_intermediate_fmv = ifelse(
       is.na(meta_tieback_key_pin),

testing_file.R

@@ -0,0 +1,92 @@
+#–– PARAMETERS ––#
+run_id_val   <- "2025-05-30-exciting-dan"
+grouping_col <- "char_bldg_sf"
+
+# 2025-02-11-charming-eric
+
+
+#–– SETUP ––#
+tictoc::tic.clearlog()
+tictoc::tic("Ingest")
+
+purrr::walk(list.files("R/", "\\.R$", full.names = TRUE), source)
+
+suppressPackageStartupMessages({
+  library(DBI)
+  library(igraph)
+  library(noctua)
+  library(glue)
+  library(dplyr)
+})
+
+noctua_options(unload = TRUE)
+
+AWS_ATHENA_CONN_NOCTUA <- dbConnect(
+  noctua::athena(),
+  rstudio_conn_tab = FALSE
+)
+
+
+#–– LOAD DATA WITH PARAMETERIZED run_id ––#
+data <- dbGetQuery(
+  conn = AWS_ATHENA_CONN_NOCTUA,
+  glue("
+    SELECT
+      v.meta_tieback_key_pin,
+      card.meta_pin,
+      card.meta_card_num,
+      card.char_bldg_sf,
+      card.char_land_sf,
+      v.meta_tieback_proration_rate,
+      card.pred_card_initial_fmv   AS pred_card_initial_fmv,
+      card.pred_card_final_fmv     AS pred_card_final_fmv,
+      pin.pred_pin_initial_fmv     AS pred_pin_initial_fmv,
+      pin.pred_pin_final_fmv       AS pred_pin_final_fmv
+    FROM model.assessment_card AS card
+    JOIN model.vw_card_res_input AS v
+      ON CAST(card.meta_card_num AS VARCHAR) = CAST(v.meta_card_num AS VARCHAR)
+      AND CAST(card.meta_pin        AS VARCHAR) = v.meta_pin
+      AND v.year = '2025'
+    JOIN model.assessment_pin AS pin
+      ON card.meta_pin = pin.meta_pin
+      AND card.run_id  = pin.run_id
+    WHERE
+      v.meta_tieback_key_pin IS NOT NULL
+      AND card.run_id       = '{run_id_val}'
+  ")
+)
+
+
+group_cols <- c("meta_tieback_key_pin", grouping_col, "meta_card_num")
+
+
+test <- data %>%
+  group_by(across(all_of(group_cols))) %>%
+  filter(n_distinct(pred_pin_initial_fmv) != 1) %>%
+  mutate(group_label = cur_group_id()) %>%
+  ungroup()
+
+
+test_1 <- data %>%
+  group_by(across(all_of(group_cols))) %>%
+  filter(n_distinct(pred_card_initial_fmv) != 1) %>%
+  mutate(group_label = cur_group_id()) %>%
+  ungroup()
+
+
+test_2 <- data %>%
+  group_by(across(all_of(group_cols))) %>%
+  filter(n_distinct(pred_card_final_fmv) != 1) %>%
+  mutate(group_label = cur_group_id()) %>%
+  ungroup()
+
+
+test_3 <- data %>%
+  group_by(across(all_of(group_cols))) %>%
+  filter(n_distinct(pred_pin_final_fmv) != 1) %>%
+  mutate(group_label = cur_group_id()) %>%
+  ungroup()
+
+
+tictoc::toc()
+