add growth trend chart

dashboard.Rmd

@@ -267,38 +267,6 @@ storm_selection <- reactiveValues(
 )
 ```
 
-```{r}
-###### REACTIVE SETUP
-
-#REACTIVES USE LAZY LOADING
-
-#hurdat.best_track <- dbGetQuery(con, "SELECT *, ST_X(ST_Transform(location::geometry, 4326)) as lon, ST_Y(ST_Transform(location::geometry, 4326)) as lat FROM hurdat.best_track")
-
-
-selected.best_track <- reactive({
-  req(storm_selection$is_selected)
-  
-  query <- paste0("
-                  SELECT *,
-                  ST_X(ST_Transform(location::geometry, 4326)) as lon,
-                  ST_Y(ST_Transform(location::geometry, 4326)) as lat
-                  FROM hurdat.best_track
-                  WHERE storm_basin = '", storm_selection$storm_basin,
-                  "' AND storm_year = ", storm_selection$storm_year,
-                  " AND storm_name = '", storm_selection$storm_name,
-                  "'")
-  
-  result <- dbGetQuery(con, query)
-  
-  cat(paste0("DEBUG: selected.best_track returned ", nrow(result)))
-  
-  return(result)
-})
-
-
-```
-
-
 Home
 =============================================
 
@@ -473,6 +441,13 @@ storm_overview_reactive <- reactiveValues(
   use_normalized_costs = FALSE
 )
 
+growth_trends <- reactiveValues(
+  lf_type = NULL,
+  lf_id = NULL,
+  full_lf_id = NULL
+)
+
+
 ```
 
 Col {data-width=500}
@@ -601,6 +576,10 @@ observe({
   storm_overview_reactive$lf_type = storm_unique_landfalls()$lf_type[1]
   storm_overview_reactive$lf_id = storm_unique_landfalls()$lf_id[1]
   storm_overview_reactive$full_lf_id = storm_unique_landfalls()$full_lf_id[1]
+  
+  growth_trends$lf_type = storm_unique_landfalls()$lf_type[1]
+  growth_trends$lf_id = storm_unique_landfalls()$lf_id[1]
+  growth_trends$full_lf_id = storm_unique_landfalls()$full_lf_id[1]
 })
 
 observe({
@@ -798,12 +777,6 @@ Column {data-width=550}
 ### {data-height=1000 .no-padding}
 
 ```{r}
-growth_trends <- reactiveValues(
-  lf_id = NULL
-)
-
-
-
 dbStormCounties <- reactive({
   req(storm_selection$is_selected)
   
@@ -875,75 +848,111 @@ fillCol(
 Column {data-width=450}
 ----------------------------------
 
-### Landfall Selection {data-height=150}
+### Landfall Selection {data-height=550}
 ```{r}
+#observe({
+#  req(storm_overview_reactive$full_lf_id)
+#  
+#  updateSelectInput(
+#    session,
+#    "storm_overview_cost_index_lf", 
+#    choices = storm_unique_landfalls()$full_lf_id,
+#    selected = storm_overview_reactive$full_lf_id
+#  )
+#})
 
+normalized_growth_metrics_lf_ts <- reactive ({
+  req(growth_trends$full_lf_id)
+  
+  growth_metrics_lf_fips <- gis.affected_area_landfalls %>% 
+    filter(
+      storm_basin == storm_selection$storm_basin,
+      storm_year == storm_selection$storm_year,
+      storm_name == storm_selection$storm_name,
+      lf_type == growth_trends$lf_type,
+      lf_id == growth_trends$lf_id
+    ) %>% 
+    mutate(
+      full_lf_id = paste0(state_fips, county_fips)
+    ) %>% 
+    collect()
 
-fluidRow(
-  column(4,
-          selectInput("growthTrendLfSelect", "Landfall", choices = NULL)
-  ), 
-  column(4,
-         
-  ),
-  column(4,
-         
+  growth_metrics_lf <- metrics.pop_and_housing %>% 
+    mutate(
+      full_lf_id = paste0(state_fips, county_fips)
+    ) %>% 
+    filter(
+      full_lf_id %in% growth_metrics_lf_fips$full_lf_id,
+      year >= storm_selection$storm_year
+    ) %>% 
+    group_by(
+      year
+    ) %>% 
+    summarize(
+      aggregate_population = sum(population, na.rm = T),
+      aggregate_housing_units = sum(housing_units, na.rm = T),
+      .groups = "drop"
+    ) %>% 
+    collect()
+
+  normalized_growth_metrics_lf <- growth_metrics_lf %>% 
+    arrange(
+      year
+    ) %>% 
+    mutate(
+      base_population = first(aggregate_population),
+      base_housing_units = first(aggregate_housing_units),
+      normalized_population = (aggregate_population / base_population),
+      normalized_housing_units = (aggregate_housing_units / base_housing_units),
+      year = as.Date(paste0(year, "-01-01"))
+    ) %>% 
+    select(
+      year, normalized_population, normalized_housing_units
+    )
+
+  result <- normalized_growth_metrics_lf %>% 
+    select(-year) %>% 
+    xts(order.by = normalized_growth_metrics_lf$year)
+  
+  return(result)
+})
+
+observe({
+  req(growth_trends$full_lf_id)
+  
+  updateSelectInput(
+    session,
+    "growth_trend_lf_select", 
+    choices = storm_unique_landfalls()$full_lf_id,
+    selected = growth_trends$full_lf_id
   )
+})
+
+observeEvent(input$growth_trend_lf_select, {
+  growth_trends$full_lf_id = input$growth_trend_lf_select
+})
+
+fillCol(
+  flex = c(.2, .8),
+  fluidRow(
+    column(6,
+           selectInput("growth_trend_lf_select", "Landfall Select", choices = NULL)
+    ),
+    column(6,
+           # TODO: add button to select normalized costs
+           #checkboxInput("storm_overview_select_base", "Include Normalized Losses", value = F)
+    )
+  ),
+  dygraphOutput("popHu")
 )
 
-observeEvent(input$growthTrendLfSelect, {
-  growth_trends$lf_id = input$growthTrendLfSelect
-  
-  showNotification("Landfall updated", type = "message")
-})
-```
-
-### Time Series {data-height=400 .no-padding}
-```{r}
-
-
-katrinaLfTwoLong <- katrinaLfTwoCountyMetrics %>% 
-  pivot_longer(
-    cols = -c(fips, metric),
-    names_to = "year",
-    values_to = "value"
-  ) %>% 
-  group_by(
-    metric, year
-  ) %>% 
-  summarize(
-    aggregateValue = sum(value, na.rm = T),
-    .groups = "drop"
-  ) %>% 
-  pivot_wider(
-    names_from = metric,
-    values_from = aggregateValue
-  ) 
-
-normalizedKatrinaLfTwo <- xlallLandfallsNormalized %>% 
-  filter(hurdatId == "AL122005" & lfId == "LF2") %>% 
-  select(normalizationYear, affectedPop, affectedHousing)
-
-normalizedKatrinaLfTwoTs <- normalizedKatrinaLfTwo %>% 
-  select(-normalizationYear) %>% 
-  as.matrix() %>% 
-  xts(order.by = as.Date(paste0(normalizedKatrinaLfTwo$normalizationYear, "-01-01")))
-
-katrinaLfTwoLongTs <- katrinaLfTwoLong %>% 
-  select(-year) %>% 
-  as.matrix() %>% 
-  xts(order.by = as.Date(paste0(katrinaLfTwoLong$year, "-01-01")))
-
-
 output$popHu <- renderDygraph({
-  dygraph(normalizedKatrinaLfTwoTs, main = "Normalized LF2 Aggregate Growth") %>% 
-    dySeries("affectedPop", label = "Population") %>% 
-    dySeries("affectedHousing", label = "Housing Units") %>% 
+  dygraph(normalized_growth_metrics_lf_ts(), main = "Normalized Aggregate Growth") %>% 
+    dySeries("normalized_population", label = "Population") %>% 
+    dySeries("normalized_housing_units", label = "Housing Units") %>% 
     dyRangeSelector()
 })
 
-
-#dygraphOutput("popHu")
 ```
 
 ### County Data {data-height=450 .no-padding}