#TidyTuesday 2021 W46

#TidyTuesday 2021 W46 Africa

#libraries ----
library(sf)
library(ggspatial)
library(showtext)
library(patchwork)
library(tidyverse)


#data ----
library(afrilearndata)
library(afrihealthsites)


#font ----
font_add_google("Benchnine", "bench")
font_add_google("Lexend Zetta", "lexend")


#colour ----
dark_colour <- "black"
light_colour <- "white"



#create continent shapes ----
shape_1 <- africontinent %>%
  st_cast("POLYGON") %>%
  slice(1) %>%
  st_simplify(., dTolerance = 0.25)


shape_2 <- africontinent %>%
  st_cast("POLYGON") %>%
  slice(1) %>%
  st_simplify(., dTolerance = 2)


#country shapes ----
countries <- africountries %>%
  filter(name %in% c("Dem. Rep. Congo", "Cameroon", "Nigeria")) %>%
  st_cast("POLYGON") %>%
  st_simplify(., dTolerance = 2)




#panel 1: DR Congo ----
shape_congo <- countries %>% filter(name == "Dem. Rep. Congo")
health_congo <- afrihealthsites("Democratic Republic of the Congo", plot = "sf")


p1 <- ggplot() +
  layer_spatial(shape_congo,
                colour = NA,
                fill = light_colour) +
  annotation_spatial(health_congo,
                     shape = 15,
                     size = 1,
                     colour = dark_colour) +
  theme_void() +
  theme(plot.background = element_rect(colour = dark_colour, fill = dark_colour))


#panel 2: Cameroon ----
shape_cam <- countries %>% filter(name == "Cameroon")
health_cam <- afrihealthsites("Cameroon", plot = "sf")


p2 <- ggplot() +
  layer_spatial(shape_cam,
                colour = NA,
                fill = light_colour) +
  annotation_spatial(health_cam,
                     shape = 15,
                     size = 1,
                     colour = dark_colour) +
  theme_void() +
  theme(plot.background = element_rect(colour = dark_colour, fill = dark_colour))


#panel 3: Nigeria ----
shape_nigeria <- countries %>% filter(name == "Nigeria")
health_nigeria <- afrihealthsites("Nigeria", plot = "sf")


p3 <- ggplot() +
  layer_spatial(shape_nigeria,
                colour = NA,
                fill = light_colour) +
  annotation_spatial(health_nigeria,
                     shape = 15,
                     size = 1,
                     colour = dark_colour) +
  theme_void() +
  theme(plot.background = element_rect(colour = dark_colour, fill = dark_colour))


#panel 4 ----
p4 <- ggplot() +
  layer_spatial(countries,
                fill = dark_colour,
                colour = NA,
                show.legend = FALSE) +
  layer_spatial(shape_1,
                size = 3,
                fill = NA,
                colour = dark_colour) +
  layer_spatial(shape_2,
                size = 3,
                fill = NA,
                colour = dark_colour) +
  theme_void() +
  theme(plot.background = element_rect(colour = light_colour, fill = light_colour))




#frame ----
frame <- ggplot() +
  geom_polygon(aes(x = c(0, 0, 100, 100),
                   y = c(0, 160, 160, 0)),
               colour = light_colour,
               fill = light_colour) +
  coord_fixed(expand = FALSE) +
  theme_void()


#annotations ----
showtext_auto()
showtext_opts(dpi = 300)


a1 <- ggplot() +
  annotate("rect", xmin = 5, ymin = 82, xmax = 49, ymax = 155,
           fill = dark_colour,
           colour = NA) +
  annotate("rect", xmin = 51, ymin = 82, xmax = 95, ymax = 155,
           fill = dark_colour,
           colour = NA) +
  annotate("rect", xmin = 5, ymin = 5, xmax = 49, ymax = 78,
           fill = light_colour,
           colour = NA) +
  annotate("rect", xmin = 51, ymin = 5, xmax = 95, ymax = 78,
           fill = dark_colour,
           colour = NA) +
  scale_x_continuous(limits = c(0, 100)) +
  scale_y_continuous(limits = c(0, 160)) +
  coord_cartesian(expand = FALSE) +
  theme_void()


a2 <- ggplot() +
  annotate("text", x = 10, y = 73, label = "AFRICA\nRESPONDS",
           hjust = 0, vjust = 1,
           lineheight = 0.9,
           colour = dark_colour,
           family = "lexend",
           fontface = "bold",
           size = 4) +
  annotate("text", x = 10, y = 62, label = "Accurate healthcare location data is essential for a fast,\ncoordinated response to disease outbreaks.",
           hjust = 0, vjust = 1,
           colour = dark_colour,
           family = "bench",
           size = 2) +
  annotate("text", x = 10, y = 150, label = "NIGERIA",
           hjust = 0, vjust = 1,
           colour = light_colour,
           family = "lexend",
           size = 3) +
  annotate("text", x = 10, y = 143, label = "LASSA FEVER\n3,660 Health Sites",
           hjust = 0, vjust = 1,
           colour = light_colour,
           family = "bench",
           size = 4) +
  annotate("text", x = 55, y = 150, label = "CAMEROON",
           hjust = 0, vjust = 1,
           colour = light_colour,
           family = "lexend",
           size = 3) +
  annotate("text", x = 55, y = 143, label = "CHOLERA\n1,761 Health Sites",
           hjust = 0, vjust = 1,
           colour = light_colour,
           family = "bench",
           size = 4) +
  annotate("text", x = 55, y = 73, label = "DEMOCRATIC\nREPUBLIC\nOF THE\nCONGO",
           hjust = 0, vjust = 1,
           colour = light_colour,
           family = "lexend",
           size = 3) +
  annotate("text", x = 55, y = 20, label = "EBOLA VIRUS DISEASE\n2,739 Health Sites",
           hjust = 0, vjust = 1,
           colour = light_colour,
           family = "bench",
           size = 4) +
  annotate("rect", xmin = 5.5, ymin = 5.5, xmax = 48.5, ymax = 77.5,
           size = 1.5,
           fill = NA,
           colour = dark_colour) +
  annotate("text", x = 5, y = 2.5, label = "Source: WHO Weekly Bulletin (1-7 Nov 2021), afrimapr  |  #TidyTuesday 2021 W46  |   |   #30DayMapChallenge D9   |  @quite_grey",
           hjust = 0,
           colour = dark_colour,
           family = "bench",
           size = 2) +
  scale_x_continuous(limits = c(0, 100)) +
  scale_y_continuous(limits = c(0, 160)) +
  coord_cartesian(expand = FALSE) +
  theme_void()



#compile ----
frame +
  inset_element(a1, 0, 0, 1, 1, align_to = "plot") +
  inset_element(p3, 5/100, 60/160, 45/100, 155/160,
                align_to = "plot") +
  inset_element(p2, 55/100, 70/160, 90/100, 155/160,
                align_to = "plot") +
  inset_element(p1, 58/100, 20/160, 90/100, 55/160,
                align_to = "plot") +
  inset_element(p4, 6/100, 5/160, 47/100, 60/160,
                align_to = "plot") +
  inset_element(a2, 0, 0, 1, 1, align_to = "plot")


#save ----
ggsave("./output/plot/africa_map_bw.png", height = 16, width = 10, unit = "cm")