#!/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
import xfilter
#nwindow, dimlp = 9, 'year'
nwindow, dimlp = 1, '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_ref'
func = lambda x: x.load().geo.fldmean()
funcname = 'glbmean'

cleanup = False #remove cache or not

das = []
labels = []

"""
model = 'CM2.1p1'
#ctl
label = 'CM2.1_ctl_1860'
expname = 'CTL1860_tigercpu_intelmpi_18_80PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
#ctl1990
label = 'CM2.1_ctl_1990'
expname = 'CTL1990_tigercpu_intelmpi_18_80PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)

model = 'FLOR'
#ctl1860_newdiag
label = 'FLOR_ctl_1860_newdiag'
expname = 'CTL1860_newdiag_tigercpu_intelmpi_18_576PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)#, years=range(100,201))
labels.append(label)
das.append(da)
#ctl1990_v201905
label = 'FLOR_ctl_1990_v201905'
expname = 'CTL1990_v201905_tigercpu_intelmpi_18_576PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)#, years=range(100,201))
labels.append(label)
das.append(da)
"""

model = 'ESM4'
#CTL1850, t_ref
label = 'ESM4_ctl_1850 t_ref'
expname = 'CTL1850_tiger3_intel24ifort_openmpi_2296PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)#, years=range(100,201))
labels.append(label)
das.append(da)
#CTL1850, t_surf
daname = 't_surf'
label = 'ESM4_ctl_1850 t_surf'
expname = 'CTL1850_tiger3_intel24ifort_openmpi_2296PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)#, years=range(100,201))
labels.append(label)
das.append(da)

 
def wyplot(da, label,**kws):
    da = da.groupby('time.year').mean('time')
    #da = da - 273.15 #K -> degC
    #da = da.pipe(lowpass)
    da.plot(label=label, **kws)
    
 
if __name__ == '__main__':
    from wyconfig import * #my plot settings
    #ctl
    fig,ax = plt.subplots(figsize=(8,4))
    for da,label in zip(das, labels):
        alpha = 1 if label.startswith('ESM4') else 0.3
        wyplot(da, label, ax=ax, alpha=alpha)
    dT = (das[1].mean('time') - das[0].mean('time')).item()
    wyplot(das[1]-dT, labels[1]+f'$-${dT:.2g}K', ax=ax, alpha=alpha, ls=':', color='C1')
    ax.legend(ncol=3)
    #ax.set_ylabel(f'GMSAT [K], {nwindow}-{dimlp}-RunAvg')
    ax.set_ylabel(f'GMSAT/GMST [K]')
    ax.set_xlim(0, 200) 

    #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)

    #fig,ax = plt.subplots()
    #(das[1] - das[0]).groupby('time.month').mean('time').plot()
    tt.check(f'**Done**')
    print()
    if 'notshowfig' in sys.argv:
        pass
    else:
        plt.show()