small fix to reverse geocode

R/reverse_geocode.R

@@ -61,12 +61,11 @@ reverse_geocode <- function(input_table,
 
   # create a small range around coordinates
 
-  data.table::setDT(input_table)
   margin <- 0.001 # 0.0001
-  input_table[, lon_min := lon - margin]
-  input_table[, lon_max  :=  lon + margin]
-  input_table[, lat_min := lat - margin]
-  input_table[, lat_max  :=  lat + margin]
+
+  data.table::setDT(input_table)
+  input_table[, c("lon_min", "lon_max", "lat_min", "lat_max") :=
+                .(lon - margin, lon + margin, lat - margin, lat + margin)]
 
 
   # Narrow search scope in cnefe to bounding box
@@ -117,13 +116,13 @@ reverse_geocode <- function(input_table,
     cnefe_nearby <- duckdb::dbSendQuery(con, query_filter_cases_nearby)
     cnefe_nearby <- duckdb::dbFetch(cnefe_nearby)
 
-    # find closest point
+    # find closest points
     data.table::setDT(cnefe_nearby)
     cnefe_nearby[, lon_diff := abs(lon_inp - lon)]
     cnefe_nearby[, lat_diff := abs(lat_inp - lat)]
 
     cnefe_nearest <- cnefe_nearby[, .SD[which.min(lon_diff)]]
-    cnefe_nearest <- cnefe_nearest[, .SD[which.min(lon_diff)]]
+    cnefe_nearest <- cnefe_nearest[, .SD[which.min(lat_diff)]]
 
     # organize output
     cnefe_nearest[, c('lon_diff', 'lat_diff') := NULL]

tests/tests_rafa/reverse_geocode_tests.R

@@ -2,21 +2,27 @@ library(arrow)
 library(duckdb)
 library(DBI)
 library(dplyr)
-library(data.table)
+
 
 # input -------------------------------------------------------
 
-lonlat_df <- data.table(
+df_coords <- data.frame(
   id = 1:6,
   lon = c(-67.83112, -67.83559, -67.81918, -43.47110, -51.08934, -67.8191),
   lat = c(-9.962392, -9.963436, -9.972736, -22.695578, -30.05981, -9.97273)
   )
 
 
+tictoc::tic()
+a <- reverse_geocode(lonlat_df)
+tictoc::toc()
+# 37.78 sec elapsed
 
 
-
-a <- reverse_geocode(lonlat_df)
+tictoc::tic()
+b <- reverse_geocode2(lonlat_df)
+tictoc::toc()
+# 37.78 sec elapsed
 
 
 ttt <- data.frame(id=1, lat=-15.814192047159876, lon=-47.90534614672923)

tests/tests_rafa/states_bbox.R

@@ -0,0 +1,35 @@
+library(sf)
+library(dplyr)
+
+# Load the state polygons
+df <- geobr::read_state()
+
+# Calculate bounding boxes of states
+bounding_boxes <- df |>
+  st_as_sf() |>                           # Ensure df is an sf object
+  rowwise() |>                            # Process each polygon individually
+  mutate(
+    xmin = st_bbox(geom)["xmin"],      # Extract xmin from the bounding box
+    ymin = st_bbox(geom)["ymin"],      # Extract ymin from the bounding box
+    xmax = st_bbox(geom)["xmax"],      # Extract xmax from the bounding box
+    ymax = st_bbox(geom)["ymax"]       # Extract ymax from the bounding box
+  ) |>
+  ungroup() |>                            # Unrowwise after rowwise operations
+  select(abbrev_state, xmin, ymin, xmax, ymax) |> # Select desired columns
+  st_drop_geometry()
+
+# View the resulting bounding box data.frame
+bounding_boxes
+
+data.table::fwrite(bounding_boxes, './inst/extdata/states_bbox.csv')
+
+
+head(input_table)
+
+candidate_states <-
+  subset(x = bounding_boxes,
+         (xmin < bbox_lon_min | xmax > bbox_lon_max) &
+         (ymin < bbox_lat_min | ymax > bbox_lat_max)
+         )
+
+