#!/usr/bin/env python
# Wenchang Yang (wenchang@princeton.edu)
# Wed Oct  5 11:09:59 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 modelout import get_modelout_data, update_modelout_data
from misc import get_kws_from_argv
import xfilter
nwindow, dimlp = 12*1, 'time'
lowpass = lambda x: x.filter.lowpass(1/nwindow, dim=dimlp, padtype=None)
#lowpass = lambda x: x.filter.lowpass(1/nwindow, dim=dimlp, method='gust')
#lowpass = lambda x: x.rolling(year=nwindow, center=True, min_periods=1).mean() if x.year.size>9 else x
import geoxarray
#
if __name__ == '__main__':
    tt.check('end import')
#
#start from here
#daname = 't_surf'
from modelout.getdata import funcs
daname = get_kws_from_argv('daname','qo3_col') # 'blk_crb_col') #qo3_col
funcname = get_kws_from_argv('funcname', 'glbmean')
#func = lambda x: x.load().geo.fldmean()
func = funcs[funcname]
dsname = 'atmos_month'
if daname in ('blk_crb_col'):
    dsname = 'atmos_month_aer'


model = 'AM4.1'
"""
expname = 'CTL1850_tiger3_intel24ifort_openmpi_1536PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, dsname=dsname, func=func, funcname=funcname, odir='../SRM/CTL')#, years=range(100,201))
da_ctl1850 = da
"""
expname = 'CTL1990_tiger3_intel24ifort_openmpi_1536PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, dsname=dsname, func=func, funcname=funcname, odir='CTL')#, years=range(100,201))
da_ctl1990 = da
units = da.attrs['units']

expname = 'CTL1990v202604_tiger3_intel24ifort_openmpi_1536PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, dsname=dsname, func=func, funcname=funcname, odir='CTL')#, years=range(100,201))
da_ctl1990v202604 = da
#expname = 'CTL1990v202604_volc1991_tiger3_intel24ifort_openmpi_1536PE'
#da = update_modelout_data(daname=daname, model=model, expname=expname, dsname=dsname, func=func, funcname=funcname, odir='CTL')#, years=range(100,201))
#da_ctl1990v202604_volc1991 = da
expname = 'CTL1990v202604v2_tiger3_intel24ifort_openmpi_1536PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, dsname=dsname, func=func, funcname=funcname, odir='CTL')#, years=range(100,201))
da_ctl1990v202604v2 = da

das = []; labels = []
#
for yy in range(11, 100, 2):
    ifile = f'/scratch/gpfs/GEOCLIM/wenchang/tiger3/AM4.1/work/CTL1990_BC_L2_Y{yy:04d}_tiger3_intel24ifort_openmpi_1536PE/POSTP/{yy+1:04d}0101.atmos_month.nc'
    if yy == 11 or os.path.exists(ifile): #experiment available
        expname = f'CTL1990_BC_L2_Y{yy:04d}_tiger3_intel24ifort_openmpi_1536PE'
        da = update_modelout_data(daname=daname, model=model, expname=expname, dsname=dsname, func=func, funcname=funcname)#, odir='BC_lat0_L6_Y0011plus')
        #das.append(da.sel(time=slice(f'{yy:04d}', f'{yy+1:04d}')).drop('time')) #sel two years
        das.append(da)
        labels.append(expname.split("_tiger3")[0])
    else:
        continue
N = len(das)
#da_ens = xr.concat(das, dim=pd.Index(range(1, N+1), name='ens'))
#da_ens['time'] = da_ctl1990.sel(time=slice('0001', '0002')).time
#print(da_ens); sys.exit()

"""
#ctl ens
das = []
for yy in range(11, 11+N*2, 2):
    da = da_ctl1990.sel(time=slice(f'{yy:04d}', f'{yy+1:04d}')).drop('time')
    das.append(da)
da_ctl1990_ens = xr.concat(das, dim=pd.Index(range(1, N+1), name='ens'))
da_ctl1990_ens['time'] = da_ctl1990.sel(time=slice('0001', '0002')).time
#print(da_ctl1990_ens); sys.exit()

#
daa_ens = da_ens - da_ctl1990_ens
da_ref = da_ctl1990_ens.groupby('time.month').mean(['time', 'ens'])
if daname in ('blk_crb_col',):
    daa_ens = (daa_ens*0.51e6).assign_attrs(units='Tg')
    da_ref = (da_ref*0.51e6).assign_attrs(units='Tg')
else:
    daa_ens.attrs['units'] = units
    da_ref.attrs['units'] = units
"""
    
 
if __name__ == '__main__':
    from wyconfig import * #my plot settings
    #ctl
    fig,ax = plt.subplots()#figsize=(8,4))
    with xr.set_options(keep_attrs=True):
        if daname in ('blk_crb_col',):
            da_ctl1990 = (da_ctl1990*0.51e6).assign_attrs(units='Tg', long_name='BC')
            units = 'Tg'
        da = da_ctl1990
        da.plot(color='k', label='CTL1990')
        da = da_ctl1990v202604
        da.plot(color='C0', label='CTL1990v202604')
        #da = da_ctl1990v202604_volc1991
        #da.plot(color='C1', label='CTL1990v202604_volc1991')
        da = da_ctl1990v202604v2
        da.plot(color='C1', label='CTL1990v202604v2')
        colors = plt.colormaps['turbo'](np.linspace(0.1, 0.9, N))
        for da_bc,label,color in zip(das, labels, colors):
            da = da_bc
            if daname in ('blk_crb_col',):
                da = (da*0.51e6).assign_attrs(units='Tg', long_name='BC')
            da.plot(color=color, ls='-')

    title = f'{model} {funcname} {daname}'
    ax.set_title(title)
    #ax.legend(loc='upper left', bbox_to_anchor=(1,1))
    ax.legend()
    ax.set_xlim(None, da_ctl1990.time[(10+N*2+10)*12].item())
    if daname in ('blk_crb_col',):
        ax.set_ylim(0,None)
    if daname in ('blk_crb_col', 'qo3_col'):
        mean = da_ctl1990.sel(time=slice('0011', None)).mean('time').item()
        ax.axhline(mean, color='k', ls='--')
        ax.text(da_ctl1990.time[0].item(), mean, f'\n{mean:.3g}{units}', va='bottom', ha='right')

    #savefig
    if 'savefig' in sys.argv or 's' in sys.argv:
        figname = __file__.replace('.py', f'__{daname}_{funcname}.png')
        if 'overwritefig' in sys.argv or 'o' in sys.argv:
            wysavefig(figname, overwritefig=True)
        else:
            wysavefig(figname)
    tt.check(f'**Done**')
    print()
    if 'notshowfig' in sys.argv:
        pass
    else:
        plt.show()