mps_bcu_locator_maps.R

library(imguR)
library(sf)
library(tidyverse)

boroughs <- read_sf("https://data.london.gov.uk/download/london_boroughs/9502cdec-5df0-46e3-8aa1-2b5c5233a31f/London_Boroughs.gpkg") |> 
  mutate(
    bcu = case_match(
      name,
      c("Hackney", "Tower Hamlets") ~ "Central East",
      c("Camden", "Islington") ~ "Central North",
      c("Lambeth", "Southwark") ~ "Central South",
      c("Hammersmith and Fulham", "Kensington and Chelsea", "Westminster") ~ 
        "Central West",
      c("Barking and Dagenham", "Havering", "Redbridge") ~ "East Area",
      c("Enfield", "Haringey") ~ "North Area",
      c("Newham", "Waltham Forest") ~ "North East",
      c("Barnet", "Brent", "Harrow") ~ "North West",
      c("Bromley", "Croydon", "Sutton") ~ "South Area",
      c("Bexley", "Greenwich", "Lewisham") ~ "South East",
      c(
        "Kingston upon Thames", 
        "Merton", 
        "Richmond upon Thames", 
        "Wandsworth"
      ) ~ "South West",
      c("Ealing", "Hillingdon", "Hounslow") ~ "West Area",
      .default = name
    ),
    name = case_match(
      name,
      "Barking and Dagenham" ~ "Barking & Dagenham",
      "Hammersmith and Fulham" ~ "Hammersmith & Fulham",
      "Kensington and Chelsea" ~ "Kensington & Chelsea",
      "Kingston upon Thames" ~ "Kingston",
      "Richmond upon Thames" ~ "Richmond",
      .default = name
    )
  )

borough_centroids <- boroughs |> 
  st_centroid() |> 
  st_coordinates() |> 
  as_tibble()

bcu_boundaries <- boroughs |> 
  group_by(bcu) |> 
  summarise()

london_boundary <- summarise(boroughs)
  
boroughs <- bind_cols(boroughs, borough_centroids)

borough_urls <- boroughs |> 
  filter(name != "City of London") |> 
  pull("bcu") |> 
  unique() |> 
  set_names() |> 
  map(function(this_bcu) {
    
    bcu_plot <- ggplot() + 
      geom_sf(
        data = london_boundary, 
        colour = "white", 
        fill = NA, 
        linewidth = 1.5
      ) +
      geom_sf(data = boroughs, colour = "grey60", fill = "grey97") +
      geom_sf(
        data = filter(boroughs, bcu == this_bcu), 
        colour = "grey50", 
        fill = "#F6BE00"
      ) +
      geom_sf(
        data = bcu_boundaries,
        colour = "grey50",
        fill = NA,
        linewidth = 0.5
      ) +
      ggrepel::geom_label_repel(
        aes(x = X, y = Y, label = str_wrap(name, 10)),
        data = filter(boroughs, bcu == this_bcu),
        alpha = 0.67,
        colour = "black",
        force = 0.5,
        force_pull = 100,
        label.padding = unit(0.1, "lines"),
        label.size = NA,
        lineheight = 0.9,
        size = 3
      ) +
      scale_x_continuous(expand = c(0.01, 0)) +
      scale_y_continuous(expand = c(0.01, 0)) +
      labs(title = str_glue("{this_bcu} BCU")) +
      theme_void() +
      theme(plot.title = element_text(face = "bold"))

    # The imgur package works with base graphics or image files, so save the
    # plot to a temporary file and then upload that file next
    ggsave(bcu_file <- tempfile(fileext = ".png"), bcu_plot, bg = "transparent")
    
    url <- imgur_upload(
      bcu_file, 
      title = str_glue(
        "Metropolitan Police Service {this_bcu} Basic Command Unit"
      ),
      description = str_glue(
        "Locator map for the Metropolitan Police Service {this_bcu} Basic ",
        "Command Unit"
      )
    )
    
    url$link[[1]]

  })