library(jsonlite)
library(sf)
library(dplyr)
library(tidyr)
library(ggplot2)
library(geosphere)
library(rnaturalearth)

# API URL from the last 60 minutes
api_spots <- "http://[300:6f6a:b087:4dda::8]/api/v1/spots?max_age=3600"

# What time is it?
time <- `attr<-`(Sys.time(),"tzone","UTC")

# Get the spots 
spots_raw <- fromJSON(api_spots) %>% mutate(across(c(de_longitude, de_latitude,
                                                            dx_longitude, dx_latitude),
                                                   as.numeric))

# Convert to spatial
spots <- spots_raw %>% st_as_sf(coords = c("dx_longitude", "dx_latitude"),
                                crs = "EPSG:4326") %>% 
                        mutate(color = band_color) %>% 
                        select(c(-dx_flag, -de_flag))
spotters <- spots_raw %>% st_as_sf(coords = c("de_longitude", "de_latitude"),
                                   crs = "EPSG:4326")
# Make lines
# https://stackoverflow.com/a/76197010
lines <- bind_rows(spots, spotters) %>% 
            group_by(id) %>% 
            dplyr::summarize(do_union=FALSE) %>%  # do_union=FALSE doesn't work as well
            st_cast("LINESTRING") 

# Make geodesic lines
great_circles_list <- list()
for(i in 1:nrow(spots_raw)){
    great_circles_list[[i]] <- as.data.frame(gcIntermediate(c(spots_raw[i,"dx_longitude"], spots_raw[i,"dx_latitude"]),
                                      c(spots_raw[i,"de_longitude"], spots_raw[i,"de_latitude"])))
    names(great_circles_list)[[i]] <- spots_raw[i,"id"]
}
great_circles <- bind_rows(great_circles_list,
                           .id = "id") %>% 
                st_as_sf(coords = c("lon", "lat"),
                         crs = "EPSG:4326") %>% 
                group_by(id) %>% 
                dplyr::summarize(do_union=FALSE) %>%  # do_union=FALSE doesn't work as well
                st_cast("LINESTRING") %>% 
                left_join(spots_raw, by = "id") %>% 
                mutate(color = band_color)

station_bbox <- matrix(c(st_bbox(spots),
            st_bbox(spotters)),
            nrow = 4,
            ncol = 2) %>%
        t() %>% 
        as.data.frame() %>% 
        summarize(xmin = min(V1),
                  ymin = min(V2),
                  xmax = max(V3),
                  ymax = max(V4))
        

# Pull in GIS basemaps etc.
countries <- ne_download(
                scale = 50,
                type = "admin_0_countries",
                category = "cultural",
                returnclass = "sf"
            )
borders <- ne_download(
            scale = 50,
            type = "admin_1_states_provinces",
            category = "cultural",
            returnclass = "sf"
        )

# Make simple map
ggplot() +
    geom_sf(data = countries) +
    geom_sf(data = borders) +
    geom_sf(data = great_circles,
            aes(color = band)) +
    geom_sf(data = spots) +
    geom_sf(data = spotters,
            color = "green") +
    geom_sf_text(data = spotters,
               aes(label = de_call)) +
    coord_sf(crs = "EPSG:4269",
             xlim = c(station_bbox$xmin, station_bbox$xmax),
             ylim = c(station_bbox$ymin, station_bbox$ymax)) +
    theme_bw() +
    theme(#axis.title.x=element_blank(),
          axis.title.y=element_blank()) +
    labs(x = time)
ggsave("out/farpn_map_simple.png",
       scale = 0.75)

# Export spatial data
st_write(spots, "out/spots.geojson", delete_dsn = T)
st_write(spotters, "out/spotters.geojson", delete_dsn = T)
st_write(great_circles, "out/great_circles.geojson", delete_dsn = T)

# Try to combine in one file
st_write(spots %>% bind_rows(spotters) %>% bind_rows(great_circles), "out/all.geojson", delete_dsn = T)