#!/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
from misc.seasons import sel_season
#
if __name__ == '__main__':
    tt.check('end import')
#
#start from here
season = get_kws_from_argv('season', 'annual')
#daname = 't_surf'
from modelout.getdata import funcs
daname = get_kws_from_argv('daname', 'qo3')# 'blk_crb') #temp,qo3
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'):
    dsname = 'atmos_month_aer'


model = 'AM4.1'
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

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

units = da.attrs['units']

 
if __name__ == '__main__':
    from wyconfig import * #my plot settings
    #ctl
    fig,axes = plt.subplots(1,2)#figsize=(8,4))
    yname = 'lat' if funcname=='zonalmean' else 'pfull'
    with xr.set_options(keep_attrs=True):
        ax = axes[0]
        #ctl1990
        da = da_ctl1990
        da = da.sel(time=slice('0011', None)).pipe(sel_season, season).mean('time')
        if yname == 'lat':
            da.plot(x=yname, label='CTL1990', ax=ax)
        else:
            da.plot(y=yname, yincrease=False, yscale='log', label='CTL1990', ax=ax)
        #ctl1990v202604
        da = da_ctl1990v202604
        da = da.sel(time=slice('0002', None)).pipe(sel_season, season).mean('time')
        if yname == 'lat':
            da.plot(x=yname, label='CTL1990v202604', ax=ax)
        else:
            da.plot(y=yname, yincrease=False, yscale='log', label='CTL1990v202604', ax=ax)

        ax = axes[1]
        da = da_ctl1990v202604.sel(time=slice('0002', None)).pipe(sel_season, season).mean('time') \
            - da_ctl1990.sel(time=slice('0011', None)).pipe(sel_season, season).mean('time')
        if yname == 'lat':
            da.plot(x=yname, label='CTL1990v202604$-$CTL1990', ax=ax, color='C2')
        else:
            da.plot(y=yname, yincrease=False, yscale='log', label='CTL1990v202604$-$CTL1990', ax=ax, color='C2')

    title = f'{model} {funcname} {season} {daname}'
    axes[0].set_title(title)
    #ax.legend(loc='upper left', bbox_to_anchor=(1,1))
    for ax in axes: ax.legend()

    #savefig
    if 'savefig' in sys.argv or 's' in sys.argv:
        figname = __file__.replace('.py', f'__{daname}_{funcname}.png')
        if season != 'annual': figname = figname.replace('.png', f'_{season}.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()