#!/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 = 9, 'year'
#lowpass = lambda x: x.filter.lowpass(1/nwindow, dim=dimlp, padtype='odd')
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', '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 = '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_ctl = da

das = []
labels = []
emissions = []
expnames = """
CTL1990_BC_lat0_L8_0p1Tg_Y0011plus_tiger3_intel24ifort_openmpi_1536PE
CTL1990_BC_lat0_L6_0p1Tg_Y0011plus_tiger3_intel24ifort_openmpi_1536PE
CTL1990_BC_lat0_L2_0p1Tg_Y0011plus_tiger3_intel24ifort_openmpi_1536PE
CTL1990_BC_lat0_L8_0p2Tg_Y0011plus_tiger3_intel24ifort_openmpi_1536PE
CTL1990_BC_lat0_L6_0p2Tg_Y0011plus_tiger3_intel24ifort_openmpi_1536PE
CTL1990_BC_lat0_L2_0p2Tg_Y0011plus_tiger3_intel24ifort_openmpi_1536PE
CTL1990_BC_lat0_L8_0p5Tg_Y0011plus_tiger3_intel24ifort_openmpi_1536PE
CTL1990_BC_lat0_L6_0p5Tg_Y0011plus_tiger3_intel24ifort_openmpi_1536PE
"""
for expname in expnames.split():
    print(expname)
    da = update_modelout_data(daname=daname, model=model, expname=expname, dsname=dsname, func=func, funcname=funcname)#, odir='BC_lat0_L8_0p1Tg_Y0011plus')
    das.append(da.sel(time='0031'))
    label = expname.split("_tiger3")[0]
    labels.append(label)
    if '0p1Tg' in label:
        emissions.append(0.1)
    elif '0p2Tg' in label:
        emissions.append(0.2)
    elif '0p5Tg' in label:
        emissions.append(0.5)
da = xr.concat(das, dim=pd.Index(labels, name='case'))
da = da.groupby('time.month') - da_ctl.groupby('time.month').mean('time') #mon anom
da = da.mean('time') * 0.51e6 #time mean and convert units from kg/m^2 to Tg
emission = xr.DataArray(emissions, dims=['case',], coords=(labels,))
#print(da, emission, da/emission); sys.exit()
 
if __name__ == '__main__':
    from wyconfig import * #my plot settings
    fig, ax = plt.subplots()
    #df = (da/emission).to_pandas().plot.bar(rot=30)
    for ii in range(da.size):
        label = labels[ii].split('_')[3] if ii<3 else None 
        plt.plot(emission.isel(case=ii), (da/emission).isel(case=ii), marker='o', fillstyle='none', color=f'C{ii%3}', label=label, ls='none')

    ax.legend(frameon=True)
    ax.set_xlabel('emission rate [Tg per year]')
    ax.set_ylabel('e-folding years')

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