Update R/setup.R

R/setup.R

@@ -1,4 +1,10 @@
-# setup
+# ============================================================================
+# Setup: HuggingFace-optimized data loading
+# ============================================================================
+# This version uses GDAL virtual file system and temporary downloads
+# for efficient loading in cloud/ephemeral environments like HuggingFace Spaces.
+# For local development with persistent caching, use setup_local.R instead.
+
 require(shinyjs)
 library(shiny)
 library(shinydashboard)
@@ -17,37 +23,39 @@ library(sjlabelled)
 library(bslib)
 library(shinycssloaders)
 
-# ------------------------------------------------
-# 1) API Keys
-# ------------------------------------------------
+# ============================================================================
+# API Keys
+# ============================================================================
 mapbox_token <- "pk.eyJ1Ijoia3dhbGtlcnRjdSIsImEiOiJjbHc3NmI0cDMxYzhyMmt0OXBiYnltMjVtIn0.Thtu6WqIhOfin6AykskM2g" 
-# mb_access_token(mapbox_token, install = FALSE)
 
-# ------------------------------------------------
-# 2) Load Data
-# ------------------------------------------------
-# -- Greenspace
-getwd()
-osm_greenspace <- st_read("/vsicurl/https://huggingface.co/datasets/boettiger-lab/sf_biodiv_access/resolve/main/greenspaces_osm_nad83.shp", quiet = TRUE) %>%
+# ============================================================================
+# Load Data from HuggingFace
+# ============================================================================
 
+# -- Greenspace (read directly from URL via GDAL virtual file system)
+osm_greenspace <- st_read("/vsicurl/https://huggingface.co/datasets/boettiger-lab/sf_biodiv_access/resolve/main/greenspaces_osm_nad83.shp", quiet = TRUE) |>
   st_transform(4326)
+
 if (!"name" %in% names(osm_greenspace)) {
   osm_greenspace$name <- "Unnamed Greenspace"
 }
 
-# -- NDVI Raster
-ndvi <- terra::rast("/vsicurl/https://huggingface.co/datasets/boettiger-lab/sf_biodiv_access/resolve/main/SF_EastBay_NDVI_Sentinel_10.tif")
+# -- Greenspace Distance Rasters (read directly from URL via GDAL virtual file system)
+greenspace_dist_raster <- terra::rast("/vsicurl/https://huggingface.co/datasets/boettiger-lab/sf_biodiv_access/resolve/main/nearest_greenspace_dist.tif")
+greenspace_osmid_raster <- terra::rast("/vsicurl/https://huggingface.co/datasets/boettiger-lab/sf_biodiv_access/resolve/main/nearest_greenspace_osmid.tif")
 
+# -- NDVI Raster (read directly from URL via GDAL virtual file system)
+ndvi <- terra::rast("/vsicurl/https://huggingface.co/datasets/boettiger-lab/sf_biodiv_access/resolve/main/SF_EastBay_NDVI_Sentinel_10.tif")
 
-# -- GBIF data
-# Load what is basically inter_gbif !!!!! 
-# load("data/sf_gbif.Rdata")  # => sf_gbif
+# -- GBIF data (loaded via DuckDB parquet in app.R server function)
+# DuckDB can read parquet files directly from URLs
+gbif_parquet <- "https://huggingface.co/datasets/boettiger-lab/sf_biodiv_access/resolve/main/gbif_census_ndvi_anno.parquet"
 
-download.file('https://huggingface.co/datasets/boettiger-lab/sf_biodiv_access/resolve/main/gbif_census_ndvi_anno.Rdata', '/tmp/gbif_census_ndvi_anno.Rdata')
-load('/tmp/gbif_census_ndvi_anno.Rdata')
-vect_gbif <- vect(sf_gbif)
-# -- Precomputed CBG data
-download.file('https://huggingface.co/datasets/boettiger-lab/sf_biodiv_access/resolve/main/cbg_vect_sf.Rdata', '/tmp/cbg_vect_sf.Rdata')
+# -- Precomputed CBG data (download to /tmp and load)
+download.file(
+  'https://huggingface.co/datasets/boettiger-lab/sf_biodiv_access/resolve/main/cbg_vect_sf.Rdata',
+  '/tmp/cbg_vect_sf.Rdata'
+)
 load('/tmp/cbg_vect_sf.Rdata')
 
 if (!"unique_species" %in% names(cbg_vect_sf)) {
@@ -63,59 +71,13 @@ if (!"ndvi_mean" %in% names(cbg_vect_sf)) {
   cbg_vect_sf$ndvi_mean <- cbg_vect_sf$ndvi_sentinel
 }
 
-# -- Hotspots/Coldspots
-biodiv_hotspots  <- st_read("/vsicurl/https://huggingface.co/datasets/boettiger-lab/sf_biodiv_access/resolve/main/hotspots.shp",  quiet = TRUE) %>% st_transform(4326)
-biodiv_coldspots <- st_read("/vsicurl/https://huggingface.co/datasets/boettiger-lab/sf_biodiv_access/resolve/main/coldspots.shp", quiet = TRUE) %>% st_transform(4326)
-
+# -- Hotspots/Coldspots (read directly from URL via GDAL virtual file system)
+biodiv_hotspots <- st_read("/vsicurl/https://huggingface.co/datasets/boettiger-lab/sf_biodiv_access/resolve/main/hotspots.shp", quiet = TRUE) |>
+  st_transform(4326)
 
+biodiv_coldspots <- st_read("/vsicurl/https://huggingface.co/datasets/boettiger-lab/sf_biodiv_access/resolve/main/coldspots.shp", quiet = TRUE) |>
+  st_transform(4326)
 
-# 
-# # Community Organizations shapefile
-# # For now simulate
-# 
-# # Define San Francisco bounding box coordinates
-# sf_bbox <- st_bbox(c(
-#   xmin = -122.5247,  # Western longitude
-#   ymin = 37.7045,     # Southern latitude
-#   xmax = -122.3569,   # Eastern longitude
-#   ymax = 37.8334       # Northern latitude
-# ), crs = st_crs(4326))  # WGS84 CRS
-# 
-# # Convert bounding box to polygon
-# sf_boundary <- st_as_sfc(sf_bbox) %>% st_make_valid()
-# 
-# # Transform boundary to projected CRS for accurate buffering (EPSG:3310)
-# sf_boundary_proj <- st_transform(sf_boundary, 3310)
-# 
-# # Set seed for reproducibility
-# set.seed(123)
-# 
-# # Simulate 20 random points within San Francisco boundary
-# community_points <- st_sample(sf_boundary_proj, size = 20, type = "random")
-# 
-# # Convert to sf object with POINT geometry and assign unique names
-# community_points_sf <- st_sf(
-#   NAME = paste("Community Org", 1:20),
-#   geometry = community_points
-# )
-# # Select first 3 points to buffer
-# buffered_points_sf <- community_points_sf[1:3, ] %>%
-#   st_buffer(dist = 100)  # Buffer distance in meters
-# 
-# # Update the NAME column to indicate buffered areas
-# buffered_points_sf$NAME <- paste(buffered_points_sf$NAME, "Area")
-# community_points_sf <- st_transform(community_points_sf, 4326)
-# buffered_points_sf <- st_transform(buffered_points_sf, 4326)
-# 
-# # Combine points and polygons into one sf object
-# community_orgs <- bind_rows(
-#   community_points_sf,
-#   buffered_points_sf
-# )
-# 
-# # View the combined dataset
-# print(community_orgs)
-# 
-# community_points_only <- community_orgs %>% filter(st_geometry_type(geometry) == "POINT")
-# community_polygons_only <- community_orgs %>% filter(st_geometry_type(geometry) == "POLYGON")
-# 
+# -- RSF Program Projects (read directly from URL via GDAL virtual file system)
+rsf_projects <- st_read("/vsicurl/https://huggingface.co/datasets/boettiger-lab/sf_biodiv_access/resolve/main/RSF_Program_Projects_polygons.gpkg", quiet = TRUE) |> 
+  st_transform(4326)