import numpy
import scipy.stats
import pandas
import matplotlib.pyplot as plt
plt.style.use("bmh")
dateCols = ['date', 'time']

OUTDIR = "catalogs/MAG"

range = [2019, 2019]
i = range[0]

while i <= range[1]:
    YEAR = i
    infile = "catalogs/%s.exp" % (YEAR)
    infile = "https://earthquake.batjorge.com/canarias/catalogs/%s.exp" % (YEAR)
    out_png = "%s/%s.magnitude.png" % (OUTDIR,YEAR)


    headers = ['file', 'date', 'time', 'latitude', 'longitude', 'depth', 'magType', 'mag', 'status', 'location']

    def dateparse(d,t):
        print "d=%s t=%s"%(d,t)
        if str(d) == "nan" or str(t) == "nan":
            dt = "01/01/1970 00:00:00"
        else:
            dt = "%s %s"%(d.strip(),t.strip())
        print "dt=%s"%dt
        return pandas.datetime.strptime(dt, '%d/%m/%Y %H:%M:%S')

    data = pandas.read_csv(infile, sep=';', parse_dates={'datetime': ['date', 'time']}, date_parser=dateparse, header=None, names=headers)
    data.head()
    data.time = pandas.to_datetime(data.datetime)
    data.sort_values("datetime", inplace=True)

    fig = plt.figure()
    fig.set_size_inches(24, 5)
    plt.plot(data.time, data.mag, ".");
    plt.ylabel("Canary\nIslands\n%s\n\nMagnitude Earthquakes"%(YEAR));

    plt.savefig(out_png)
    i += 1
    
plt.show()