#!/usr/bin/env rscript

library(maps)
library(mapdata)
library(ggmap)

stations <- read.csv('../data/stations.csv', header=TRUE, stringsAsFactors=FALSE)

for (i in 0:23) {
  in_filename <- paste('../data/by_hour/activity_', sprintf("%02d", i), '.tsv', sep = '')
  out_filename <- paste('../data/by_hour/png/activity_', sprintf("%02d", i), '.png', sep = '')

  activity <- read.table(in_filename, header=TRUE, sep='\t', stringsAsFactors=FALSE)

  print(in_filename)
  print(out_filename)

  # With the activity loaded, we need to go through each unique
  # station_id to get the total activity. Total activity will be the
  # sum of the absolute values of change.

  appended_stations=c()

  for (i in 1:nrow(stations)) {
    station <- stations[i,]
    station_id <- as.character(station$station_id)

    station_activity <- activity[which(activity$station_id == station_id),]

    # Now that we have the activity for this particular station, we can
    # find the net and absolute amounts of activity
    station$net_activity <- sum(station_activity$num_bikes_available_change)
    station$abs_activity <- sum(abs(station_activity$num_bikes_available_change))

    appended_stations <- rbind(appended_stations, station)
  }
  
  # Make another field on the appended stations that rank activity on
  # a scale of 0 to 1.
  appended_stations$abs_activity_percent = (appended_stations$abs_activity - min(appended_stations$abs_activity)) / (max(appended_stations$abs_activity) - min(appended_stations$abs_activity))
  appended_stations$net_activity_percent = (appended_stations$net_activity - min(appended_stations$net_activity)) / (max(appended_stations$net_activity) - min(appended_stations$net_activity))

  sb_box <- make_bbox(appended_stations$lon, appended_stations$lat, f = 1)
  sq_map <- get_map(location = sb_box, maptype = "satellite", source = "google")
  
  png(out_filename, 1024, 1024)
  plot(ggmap(sq_map) +
    geom_point(data = appended_stations, mapping = aes(x = lon, y = lat), color = "yellow", size = ((10 * appended_stations$abs_activity_percent))) +
    geom_point(data = appended_stations, mapping = aes(x = lon, y = lat), color = "black", size = 1))

  dev.off()
}