data-raw/base_map_params.r

In baslat/sak: The Swiss Army Knife of R

## code to prepare `base_map_params` dataset goes here
library(sf)
ucl <- absmapsdata::ucl2016 %>%
  normalise_geo_names()

# Prep ----

# ucl capital cities ----
melb <- tibble::tibble(
  geo_level = "ucl",
  geo_name = "Melbourne",
  bbox = dplyr::filter(ucl, .data$ucl_name == "Melbourne") %>% sf::st_bbox() %>% list(),
  zoom = 11
)

adelaide <- tibble::tibble(
  geo_level = "ucl",
  geo_name = "Adelaide",
  bbox = dplyr::filter(ucl, .data$ucl_name == "Adelaide") %>% sf::st_bbox() %>% list(),
  zoom = 11
)

brisbane <- tibble::tibble(
  geo_level = "ucl",
  geo_name = "Brisbane",
  bbox = dplyr::filter(ucl, .data$ucl_name == "Brisbane") %>% sf::st_bbox() %>% list(),
  zoom = 11
)
hobart <- tibble::tibble(
  geo_level = "ucl",
  geo_name = "Hobart",
  bbox = dplyr::filter(ucl, .data$ucl_name == "Hobart") %>% sf::st_bbox() %>% list(),
  zoom = 12
)
darwin <- tibble::tibble(
  geo_level = "ucl",
  geo_name = "Darwin",
  bbox = dplyr::filter(ucl, .data$ucl_name == "Darwin") %>% sf::st_bbox() %>% list(),
  zoom = 13
)


cbr <- osmdata::getbb("Canberra, Australia")
cbr_bb <- c(
  xmin = cbr[1, 1],
  ymin = cbr[2, 1],
  xmax = cbr[1, 2],
  ymax = cbr[2, 2]
)

canberra <- tibble::tibble(
  geo_level = "ucl",
  geo_name = "Canberra",
  bbox = cbr_bb %>% list(),
  zoom = 12
)

perth <- tibble::tibble(
  geo_level = "ucl",
  geo_name = "Perth",
  bbox = dplyr::filter(ucl, .data$ucl_name == "Perth (WA)") %>% sf::st_bbox() %>% list(),
  zoom = 11
)
sydney <- tibble::tibble(
  geo_level = "ucl",
  geo_name = "Sydney",
  bbox = dplyr::filter(ucl, .data$ucl_name == "Sydney") %>% sf::st_bbox() %>% list(),
  zoom = 11
)

# States ----
nsw <- tibble::tibble(
  geo_level = "state",
  geo_name = "NSW",
  bbox = dplyr::filter(
    ucl,
    .data$state_name == "New South Wales" &
      .data$sos_name == "Rural Balance"
  ) %>%
    sf::st_bbox() %>%
    list(),
  zoom = 7
)

vic <- tibble::tibble(
  geo_level = "state",
  geo_name = "Vic",
  bbox = dplyr::filter(
    ucl,
    .data$state_name == "Victoria" &
      .data$sos_name == "Rural Balance"
  ) %>%
    sf::st_bbox() %>%
    list(),
  zoom = 8
)

sa <- tibble::tibble(
  geo_level = "state",
  geo_name = "SA",
  bbox = dplyr::filter(
    ucl,
    .data$state_name == "South Australia" &
      .data$sos_name == "Rural Balance"
  ) %>%
    sf::st_bbox() %>%
    list(),
  zoom = 7
)

qld <- tibble::tibble(
  geo_level = "state",
  geo_name = "Qld",
  bbox = dplyr::filter(
    ucl,
    .data$state_name == "Queensland" &
      .data$sos_name == "Rural Balance"
  ) %>%
    sf::st_bbox() %>%
    list(),
  zoom = 7
)

wa <- tibble::tibble(
  geo_level = "state",
  geo_name = "WA",
  bbox = dplyr::filter(
    ucl,
    .data$state_name == "Western Australia" &
      .data$sos_name == "Rural Balance"
  ) %>%
    sf::st_bbox() %>%
    list(),
  zoom = 7
)

tas <- tibble::tibble(
  geo_level = "state",
  geo_name = "Tas",
  bbox = dplyr::filter(
    ucl,
    .data$state_name == "Tasmania" &
      .data$sos_name == "Rural Balance"
  ) %>%
    sf::st_bbox() %>%
    list(),
  zoom = 8
)

nt <- tibble::tibble(
  geo_level = "state",
  geo_name = "NT",
  bbox = dplyr::filter(
    ucl,
    .data$state_name == "Northern Territory" &
      .data$sos_name == "Rural Balance"
  ) %>%
    sf::st_bbox() %>%
    list(),
  zoom = 7
)


# Mapping -----
base_map_params <- dplyr::bind_rows(
  melb,
  wa,
  brisbane,
  hobart,
  darwin,
  # canberra,
  sydney,
  perth,
  nsw,
  vic,
  sa,
  qld,
  tas,
  nt,
  adelaide
) %>%
  # slice(6:7) %>%
  tidyr::unnest_wider(bbox) %>%
  dplyr::transmute(geo_level,
    geo_name,
    left = xmin,
    bottom = ymin,
    right = xmax,
    top = ymax,
    zoom,
    maptype = "toner-lite"
  ) %>%
  dplyr::arrange(desc(geo_level), geo_name) %>%
  dplyr::rowwise()


usethis::use_data(base_map_params, overwrite = TRUE)