update local dev testing env

dashboard.Rmd

@@ -42,13 +42,34 @@ library(scales)
 library(billboarder)
 library(mirai)
 library(promises)
+library(future)
+library(crew)
 
-daemons(3)
+future::plan(multisession)
+
+daemons(3, output = T)
+
+# local testing env setup
+os <- Sys.info()["sysname"]
 
 linuxdir <- "/home/dylan/Personal/Projects/Hurricane Normalization/"
 macdir <- "~/Desktop/Personal/Projects/Hurricane Normalization/"
-#baseDir <- macdir
-baseDir <- linuxdir
+widir <- "E/..."
+
+if(!is.null(os)) {
+  if(grepl("darwin", os, ignore.case = T)) {
+    cat("OS: Mac")
+    baseDir <- macdir
+  } else if(grepl("linux", os, ignore.case = T)) {
+    cat("OS: Linux")
+    baseDir <- linuxdir
+  } else if(grepl("windows", os, ignore.case = T)) {
+    cat("OS: Win")
+    baseDir <- windir 
+  } else {
+    cat("Cannot identify OS")
+  }
+}
 
 config <- config::get(file = paste0(baseDir, "R/dataScripts/restructured/app/config.yml"))
 
@@ -330,6 +351,13 @@ Col {data-width=500}
 HTML('
 
 ')
+
+textOutput("current_time")
+
+output$current_time <- renderText({
+  invalidateLater(100)
+  format(Sys.time(), "%H:%M:%S %p")
+})
 ```
 
 ### Normalization Cost Index {data-height=800}
@@ -418,40 +446,24 @@ DTOutput("landfalls_table")
 
 ### Storm Track {data-height=500 .no-padding}
 ```{r eval=FALSE, include=FALSE}
-track_data <- reactiveVal(NULL)
-mirai_job <- reactiveVal(NULL)
+task <- ExtendedTask$new(
+  function(...) mirai({
+    get_hurdat_track(storm_selection)
+  }, environment())
+)
 
-observe({
-  req(storm_selection$is_selected)
+observeEvent(input$stormSelect, {
+  task$invoke()
   
-  storm <- reactiveValuesToList(storm_selection)
-  
-  cat("starting qry for storm track")
-  
-  m <- async_db_query(get_hurdat_track, storm)
-  
-  mirai_job(m)
-  
-  track_data(NULL)
+  cat("task invoked")
 })
 
 observe({
-  req(mirai_job())
+  req(task$result())
   
-  if(!unresolved(mirai_job())) {
-    result <- mirai_job()$data
+  cat("task result")
   
-    track_data(result)
-    mirai_job(NULL)
-  } else {
-    invalidateLater(100)
-  }
-})
-
-observe({
-  req(track_data())
-  
-  storm_track <- track_data()
+  storm_track <- task$result()
   
   cat("updating map")
     
@@ -499,11 +511,111 @@ leafletOutput("track_map", height="100%")
 ```
 
 ```{r}
+#a <- reactiveVal(NULL)
+
+observe({
+  req(storm_selection, storm_selection$is_selected)
+  
+  storm_basin <- storm_selection$storm_basin
+  storm_name <- storm_selection$storm_name
+  storm_year <- storm_selection$storm_year
+  
+  mirai({
+    library(tidyverse)
+    library(dplyr)
+    library(DBI)
+    
+    Sys.sleep(5)
+    
+    linuxdir <- "/home/dylan/Personal/Projects/Hurricane Normalization/"
+    macdir <- "~/Desktop/Personal/Projects/Hurricane Normalization/"
+    #baseDir <- macdir
+    baseDir <- linuxdir
+    
+    config <- config::get(file = paste0(baseDir, "R/dataScripts/restructured/app/config.yml"))
+    
+    # SUPABASE CON
+    con <- dbConnect(
+      RPostgres::Postgres(),
+      host = config$db_host,
+      port = config$db_port,
+      dbname = config$db_dbname,
+      user = config$db_user,
+      password = config$db_password
+    )
+    
+    # lazy load DB tables
+    
+    econ.normalized_landfalls <- tbl(con, I("econ.normalized_landfalls"))
+    econ.storm_base_loss <- tbl(con, I("econ.storm_base_loss"))
+    econ.usa_yearly <- tbl(con, I("econ.usa_yearly"))
+    
+    fatal.storm_fatalities_type <- tbl(con, I("fatal.storm_fatalities_type"))
+    fatal.storm_total_fatalities <- tbl(con, I("fatal.storm_total_fatalities"))
+    
+    fips.counties <- tbl(con, I("fips.counties"))
+    fips.states <- tbl(con, I("fips.states"))
+    
+    gis.affected_area_landfalls <- tbl(con, I("gis.affected_area_landfalls"))
+    
+    hurdat.best_track <- tbl(con, I("hurdat.best_track"))
+    hurdat.hurdat_storms <- tbl(con, I("hurdat.hurdat_storms"))
+    
+    metrics.geo_attributes <- tbl(con, I("metrics.geo_attributes"))
+    metrics.pop_and_housing <- tbl(con, I("metrics.pop_and_housing"))
+    
+    public.counties <- tbl(con, I("public.counties"))
+    
+    track_data <- hurdat.best_track %>% 
+    filter(
+      storm_basin == !!storm_basin,
+      storm_year == !!storm_year,
+      storm_name == !!storm_name
+    ) %>% 
+    mutate(
+      lon = sql("ST_X(ST_Transform(location::geometry, 4326))"),
+      lat = sql("ST_Y(ST_Transform(location::geometry, 4326))"),
+      rmw_meters = (rmw * 1852) # convert nautical miles to meters
+    ) %>% 
+    select(
+      datetime,
+      lon,
+      lat,
+      rmw,
+      record_identifier,
+      rmw_meters
+    ) %>% collect()
+    
+    dbDisconnect(con)
+    
+    track_data
+  }, storm_basin = storm_basin, storm_name = storm_name, storm_year = storm_year) %...>% (function(track_data) {
+    leafletProxy("track_map") %>% 
+    clearShapes() %>% 
+    clearMarkers() %>%
+    addPolylines(
+      data = track_data,
+      lng = ~lon,
+      lat = ~lat,
+      weight = 4,
+      color = "blue"
+    )
+  })
+})
+
+output$track_map <- renderLeaflet({
+  leaflet() %>% 
+    addProviderTiles("CartoDB.Positron", option = providerTileOptions(minZoom = 2, maxZoom = 18)) %>% 
+    setView(lng = -80, lat = 32, zoom = 4)
+})
+
+leafletOutput("track_map", height="100%")
+```
+
+```{r eval=FALSE, include=FALSE}
 observe({
   req(storm_selection$is_selected)
     
-  storm_track <- get_hurdat_track(storm_selection)
-    
   leafletProxy("track_map", data = storm_track) %>% 
   clearShapes() %>% 
   clearMarkers() %>%
@@ -535,15 +647,8 @@ observe({
     fillOpacity = 0.3
   ) 
 })
-
-output$track_map <- renderLeaflet({
-  leaflet() %>% 
-    addProviderTiles("CartoDB.Positron", option = providerTileOptions(minZoom = 2, maxZoom = 18)) %>% 
-    setView(lng = -80, lat = 32, zoom = 4)
-})
-
-leafletOutput("track_map", height="100%")
 ```
+
 Growth Trends {data-navmenu="Storm Details"}
 ================================
 
@@ -617,7 +722,7 @@ katrina_counties <- reactive({
   counties <- get_normalized_metric_growth(test_storm, "LF2")
   
   result <- counties %>% 
-    filter(year == 2006) %>% 
+    filter(year == 2024) %>% 
     mutate(
       population_opacity = rescale(normalized_population, to = c(0.2, 0.8), from = range(normalized_population, na.rm = T)),
       housing_opacity = rescale(normalized_housing, to = c(0.2, 0.8), from = range(normalized_housing, na.rm = T))