import csv
import numpy as np
import matplotlib.pyplot as plt

from mpl_toolkits.basemap import Basemap

eq_lat, eq_lon = [], []
magnitudes, eq_ts = [], []

# test commit

with open('2.5_week.csv', encoding='utf-8') as csvfile:
    reader = csv.DictReader(csvfile)
    for row in reader:
      eq_lat.append(float(row["latitude"]))
      eq_lon.append(float(row["longitude"]))
      magnitudes.append(float(row["mag"]))
      eq_ts.append(row["time"])


def mk_color(magnitude):
    # red color for significant earthquakes, yellow for earthquakes below 4.5 and above 3.0
    # and green for earthquakes below 3.0
    if magnitude < 3.0: return ('go')
    elif magnitude < 4.5: return ('yo')
    else: return ('ro')


plt.figure(figsize=(15,11))
my_map = Basemap(projection='robin', resolution='l', area_thresh=1000.0, lat_0=0, lon_0=-10)
my_map.drawcoastlines()
my_map.drawcountries()
my_map.fillcontinents(color='#aa96da')
my_map.drawmapboundary()
my_map.drawmeridians(np.arange(0, 360, 30))
my_map.drawparallels(np.arange(-90, 90, 30))
mk_size = 2.4
for lon, lat, mag in zip(eq_lon, eq_lat, magnitudes):
  x,y = my_map(lon, lat)
  msize = mag * mk_size
  marker_string = mk_color(mag)
  my_map.plot(x, y, marker_string, markersize=msize)
    
plt.title('Earthquakes of magnitude 2.5 or above in the last week')
# we can save the image as png file locally to the directory we are working in
plt.savefig('eq_data.png')
plt.show()