# ---- Load ----
library(tidyverse)
library(httr)
library(sf)
library(rmapshaper)
library(lobstr)
library(devtools)
# Load package
load_all(".")
# Set query url
query_url <-
query_urls |>
filter(id == "hb19") |>
pull(query)
# GET and unzip shapefiles
GET(
query_url,
write_disk(
zip_folder <- tempfile(fileext = ".zip")
)
)
unzip(zip_folder, exdir = tempdir())
shp <- paste0(tempdir(), "/SG_NHS_HealthBoards_2019.shp")
hb <-
read_sf(shp) |>
st_transform(crs = 4326)
# Select and rename vars
hb <-
hb |>
select(
hb19_name = HBName,
hb19_code = HBCode,
geometry
)
# Make sure geometries are valid
hb <- st_make_valid(hb)
# Simplify shape to reduce file size
hb <- ms_simplify(hb)
# Check geometry types are homogenous
if (hb |>
st_geometry_type() |>
unique() |>
length() > 1) {
stop("Incorrect geometry types")
}
if (hb |>
st_geometry_type() |>
unique() != "MULTIPOLYGON") {
stop("Incorrect geometry types")
}
# Check object is below 50Mb GitHub warning limit
if (obj_size(hb) > 50000000) {
stop("File is too large")
}
# Rename
boundaries_hb19 <- hb
# Save output to data/ folder
usethis::use_data(boundaries_hb19, overwrite = TRUE)
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