'''

This code is part of the SIPN2 project focused on improving sub-seasonal to seasonal predictions of Arctic Sea Ice. 
If you use this code for a publication or presentation, please cite the reference in the README.md on the
main page (https://github.com/NicWayand/ESIO). 

Questions or comments should be addressed to nicway@uw.edu

Copyright (c) 2018 Nic Wayand

GNU General Public License v3.0


'''

# Standard Imports
import os
import xarray as xr
import pandas as pd

# ESIO Imports
from esio import EsioData as ed

E = ed.EsioData.load()

file_in = os.path.join(E.obs['NSIDC_extent']['native'], 'N_seaice_extent_daily_v3.0.csv')
file_out = os.path.join(E.obs['NSIDC_extent']['sipn_nc'], 'N_seaice_extent_daily_v3.0.nc')

dateparse = lambda x: pd.datetime.strptime(x, '%Y     %m   %d')

df = pd.read_csv(file_in,
                skiprows=1,
                parse_dates={'datetime': ['YYYY', '    MM', '  DD']}, date_parser=dateparse)
df.set_index('datetime', inplace=True)
df.columns = ['Extent','Missing','Source']
ds = xr.Dataset.from_dataframe(df)

ds.Extent.attrs['units'] = '10^6 sq km'
ds.Extent.attrs['Missing'] = '10^6 sq km'