from __future__ import absolute_import
from datetime import datetime
import numpy as np
from numpy.lib.recfunctions import drop_fields, append_fields
class NLDNdataFile(object):
stroke_DC3 = {'columns':[ ('date','S10'), ('time','S20'),
('lat','f4'), ('lon','f4'),
('peak_current','f4'), ('ellipse','f4'),
],
'date_dtype':[('year','i2'),('month','i1'),('day','i1')],
'time_dtype':[('hour','i1'),('minute','i1'),('second','float64')]
}
stroke_ICCG = {'columns':[ ('date','S10'), ('time','S20'),
('lat','f4'), ('lon','f4'),
('peak_current','f4'), ('ICCG','S1'),
],
'date_dtype':[('year','i2'),('month','i1'),('day','i1')],
'time_dtype':[('hour','i1'),('minute','i1'),('second','float64')]
}
def __init__(self, filename, date_sep='-', time_sep=':', format='stroke_DC3'):
""" Load NLDN data from a file, into a numpy named array stored in the
*data* attribute. *data*['time'] is relative to the *basedate* datetime
attribute
"""
self.format=format
dtype_specs = getattr(self, format)
nldn_initial = np.genfromtxt(filename, dtype=dtype_specs['columns'])
date_part = np.genfromtxt(nldn_initial['date'],
delimiter=date_sep, dtype=dtype_specs['date_dtype'])
time_part = np.genfromtxt(nldn_initial['time'],
delimiter=time_sep, dtype=dtype_specs['time_dtype'])
dates = [datetime(a['year'], a['month'], a['day'], b['hour'], b['minute'])
for a, b in zip(date_part, time_part)]
min_date = min(dates)
min_date = datetime(min_date.year, min_date.month, min_date.day)
t = np.fromiter( ((d-min_date).total_seconds() for d in dates), dtype='float64')
t += time_part['second']
self.basedate = min_date
data = drop_fields(nldn_initial, ('date', 'time'))
data = append_fields(data, 'time', t)
self.data = data
