#!/usr/bin/env python
# Wenchang Yang (wenchang@princeton.edu)
# Thu Mar 10 14:18:20 EST 2022
if __name__ == '__main__':
    import sys
    from misc.timer import Timer
    tt = Timer('start ' + ' '.join(sys.argv))
import sys, os.path, os, glob, datetime
import xarray as xr, numpy as np, pandas as pd, matplotlib.pyplot as plt
#more imports
import geoxarray
#
if __name__ == '__main__':
    tt.check('end import')
#
#start from here
#ifile = 'data_precip_FLOR_histRCP45_5ens_1860-2100_Madagascar.nc'
#ifile = 'data_gmst_FLOR_histRCP45_5ens_1860-2100.nc'
ifile = 'data_gmst_AM2p5C360_amipLongChan_10ens_1871-2020.nc'
#ifile = sys.argv[1]
years = slice('1872', '2020')
ofile = ifile.replace('.nc', '_yearlymeanJul-Jun.nc').replace('1871-2020', f'{years.start}-{years.stop}')
if os.path.exists(ofile):
    print('[exists]:', ofile)
    sys.exit()

ds = xr.open_dataset(ifile)
daname = list(ds.data_vars)[0]
da = ds[daname]
#calculation
da = da.resample(time='A-JUN').mean() \
    .pipe(lambda x: x - x.sel(time=slice('1901','2000')).mean('time')) \
    .rolling(time=5, min_periods=1).mean() \
    .sel(time=years)
da['time'] = da.indexes['time'].to_datetimeindex() #cftime -> datetime
da = da.transpose('time', 'ens')
#save
#da = da.astype('float64')
da.attrs['units'] = ds[daname].attrs['units']
da.attrs['long_name'] = f'annual (Jul-Jun) mean {daname}'
encoding = {daname: {'_FillValue': None}}
da.to_dataset(name=daname).to_netcdf(ofile, encoding=encoding)
print('[saved]:', ofile)

 
 
if __name__ == '__main__':
    #from wyconfig import * #my plot settings
    
    #savefig
    if len(sys.argv)>1 and 'savefig' in sys.argv[1:]:
        figname = __file__.replace('.py', f'.png')
        if 'overwritefig' in sys.argv[1:]:
            wysavefig(figname, overwritefig=True)
        else:
            wysavefig(figname)
    tt.check(f'**Done**')
    print()
    plt.show()