update growth map to use materialized county view

app/queries.R

@@ -418,41 +418,9 @@ get_normalized_metric_growth <- function(storm, full_lf_id) {
       ) %>%
       select(state_fips, county_fips)
 
-    baseline_metrics <- get_tbl("pop_and_housing", "metrics") %>%
-      filter(
-        year == storm$storm_year
-      ) %>%
+    query <- get_tbl("pop_housing_normalized_growth", "metrics") %>%
+      filter(base_year == storm$storm_year) %>%
       inner_join(affected_counties, by = c("state_fips", "county_fips")) %>%
-      select(
-        state_fips,
-        county_fips,
-        baseline_population = population,
-        baseline_housing = housing_units
-      )
-
-    normalized_metrics <- get_tbl("pop_and_housing", "metrics") %>%
-      filter(
-        year >= storm$storm_year
-      ) %>%
-      inner_join(affected_counties, by = c("state_fips", "county_fips")) %>%
-      inner_join(baseline_metrics, by = c("state_fips", "county_fips")) %>%
-      mutate(
-        normalized_population = as.numeric(population) /
-          as.numeric(baseline_population),
-        normalized_housing = as.numeric(housing_units) /
-          as.numeric(baseline_housing)
-      ) %>%
-      select(
-        state_fips,
-        county_fips,
-        year,
-        population,
-        housing_units,
-        normalized_population,
-        normalized_housing
-      )
-
-    query <- normalized_metrics %>%
       inner_join(
         get_tbl("counties", "public"),
         by = c("state_fips" = "statefp", "county_fips" = "countyfp")
@@ -469,11 +437,31 @@ get_normalized_metric_growth <- function(storm, full_lf_id) {
         name,
         population,
         housing_units,
-        normalized_population,
-        normalized_housing,
+        base_year_population,
+        base_year_housing,
+        normalized_population = population_normalized,
+        normalized_housing = housing_units_normalized,
         geom_wkt
       ) %>%
       arrange(state_fips, county_fips, year)
+
+    result <- query %>%
+      collect() %>%
+      mutate(
+        normalized_population = if_else(
+          is.na(base_year_population) | is.na(base_year_housing),
+          NA_real_,
+          normalized_population / 100
+        ),
+        normalized_housing = if_else(
+          is.na(base_year_population) | is.na(base_year_housing),
+          NA_real_,
+          normalized_housing / 100
+        )
+      ) %>%
+      select(-base_year_population, -base_year_housing)
+
+    return(result)
   } else {
     affected_state <- get_tbl("indirect_landfalls", "gis") %>%
       filter(