#!/usr/bin/env python
# Wenchang Yang (wenchang@princeton.edu)
# Sat May  7 12:43:43 EDT 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
#from misc.landmask import flagland
import geoxarray
#
if __name__ == '__main__':
    tt.check('end import')
#
#start from here
#to_degC = lambda x: (x-273.15).assign_attrs(units='degC')
#mask = lambda x: x.where(flagland(x)>0.5)
#ifile = 't_ref_max_FLOR_HistRCP45_tigercpu_intelmpi_18_576PE_5ens_1860-2100_SouthAsia.nc'
#ifile = 'precip_FLOR_HistRCP45_tigercpu_intelmpi_18_576PE_5ens_1860-2100_Pernambuco_masked.nc'
#ifile = 'precip_AM2.5C360_amipHadISSTlong_chancorr_tigercpu_intelmpi_18_1080PE_10ens_1871-2021_Pernambuco_masked.nc'
#daname = 'precip'
#units = 'mm/day'
daname = 't_ref' if 't_ref' in sys.argv else 't_ref_max'
model = 'AM2.5C360' if 'AM2.5C360' in sys.argv else 'FLOR'
nens = 5 if model == 'FLOR' else 10
units = '$^\circ$C'
func_units = lambda x: (x-273.15).assign_attrs(units=units)
ifile = f'{daname}_FLOR_HistRCP45_tigercpu_intelmpi_18_576PE_{nens}ens_1860-2100_UK.nc' if model=='FLOR' \
    else f'{daname}_AM2.5C360_amipHadISSTlong_chancorr_tigercpu_intelmpi_18_1080PE_{nens}ens_1871-2021_UK.nc' 
#select = lambda x: x.load().isel(time=(x.time.dt.month==3)|(x.time.dt.month==4)) \
#    .sel(lon=slice(65, 85), lat=slice(20,37)).pipe(mask)
#select = lambda x:  x.load().isel(time=(x.time.dt.month==3)|(x.time.dt.month==4)) #*_masked.nc data already subseted and masked
if daname == 't_ref':
    ndays = 2
    func = lambda x: x.load().geo.fldmean() \
        .rolling(time=ndays).mean() \
        .groupby('time.year').max('time') \
        .pipe(func_units)
elif daname == 't_ref_max':
    func = lambda x: x.load().geo.fldmean() \
        .groupby('time.year').max('time') \
        .pipe(func_units)
#ofile = ifile.replace('.nc', '_index.nc') 
ofile = ifile.replace('.nc', f'_index.nc') 
if os.path.exists(ofile):
    da = xr.open_dataarray(ofile)
    print('[loaded]:', ofile)
else:
    da = xr.open_dataarray(ifile).pipe(func)
    da.to_dataset(name=daname).to_netcdf(ofile)
    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()