#!/usr/bin/env python
# Wenchang Yang (wenchang@princeton.edu)
# Wed Jun 19 14:26:51 EDT 2024
# model correction of tau_x used in model running: obs - model
if __name__ == '__main__':
    import sys,os
    try:
        from misc.timer import Timer
        tt = Timer(f'[{os.getcwd()}] start ' + ' '.join(sys.argv))
    except:
        pass
import sys, os.path, os, glob, datetime
import xarray as xr, numpy as np, pandas as pd, matplotlib.pyplot as plt
#more imports
wython = '/tigress/wenchang/wython'
if wython not in sys.path: sys.path.append(wython); print('added to python path:', wython)
#from misc import get_kws_from_argv
#
if __name__ == '__main__':
    try:
        tt.check('end import')
    except:
        pass
#
#start from here
#ifile = 'FLOR.ocean.bias.tau_x.mclim.1980-2016.e2.nc'
#ofile = 'tau_x_correction.nc'
#ifile = 'FLOR.ocean.pme_restore.mclim.1980-2016.e2.nc'
#ofile = 'salt_sfc_correction.nc'
#daname = 'pme_restore'
#daname_new = 'pme'
ifile = 'FLOR.ocean.sfc_hflux_restore.mclim.1980-2016.e2.nc'
ofile = 'temp_sfc_correction.nc'
daname = 'sfc_hflux_restore'
daname_new = 'sfc_hflux'
ds = xr.open_dataset(ifile)
#daname = list(ds.data_vars)[0]
#remove the global mean (area weighted), annual mean
da_area = xr.open_dataset('/home/wenchang/scratch/FLOR/work/nudgeAll_FAtau_e2_newdiag_tigercpu_intelmpi_18_576PE/POSTP/19980101.ocean_grid.nc')['area_t']
with xr.set_options(keep_attrs=True):
    da_mean = ds[daname].weighted(da_area).mean(['xt_ocean', 'yt_ocean']).mean('month')# remove the global annual mean
    print('global annual mean:', da_mean)
    ds[daname] = ds[daname] - da_mean
#rename to be consistent with ocean model output
#ds = ds.rename(x='xu_ocean', y='yu_ocean', lon='geolon_c', lat='geolat_c') #uv grids
#convert the month axis to time
new_time_axis = xr.open_dataset('/home/wenchang/scratch/FLOR/work/nudgeAll_FAtau_e2_newdiag_tigercpu_intelmpi_18_576PE/POSTP/19980101.ocean.nc')['time']
ds = ds.rename(month='time').assign_coords(time=new_time_axis) # change the month axis to time
ds['time'].attrs['modulo'] = ' '  #so the GCM knows the monthly climatology is repeated

#save
ds[daname].attrs['long_name'] = f'FLOR {daname_new} correction from {daname}'
ds = ds.rename({daname: daname_new})
encoding = {dname: {'_FillValue': None} for dname in list(ds.variables)}
encoding['time']['dtype'] = 'double'
encoding['time']['units'] = 'days since 1998-01-01'
ds.to_netcdf(ofile, encoding=encoding, unlimited_dims='time')
print('[saved]:', ofile)
 
if __name__ == '__main__':
    #from wyconfig import * #my plot settings
    
    #savefig
    if 'savefig' in sys.argv or 's' in sys.argv:
        figname = __file__.replace('.py', f'.png')
        if 'overwritefig' in sys.argv or 'o' in sys.argv:
            wysavefig(figname, overwritefig=True)
        else:
            wysavefig(figname)
 
    try:
        tt.check(f'**Done**')
    except:
        pass
    print()
    if 'notshowfig' in sys.argv or 'n' in sys.argv:
        pass
    else:
        if 'plt' in globals(): plt.show()