#!/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 = 1, 'year'
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>nwindow else x
import geoxarray
#
if __name__ == '__main__':
    tt.check('end import')
#
#start from here
daname = 't_surf'
func = lambda x: x.load().geo.fldmean()
funcname = 'glbmean'

cleanup = False #remove cache or not

das = []
labels = []

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)
#ctl1860_v202407
label = 'FLOR_ctl_1860_v202407'
expname = 'CTL1860_v202407_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)
#ctl1860_tiger3
label = 'FLOR_ctl_1860_tg3'
expname = 'CTL1860_tiger3_intelmpi_24_1116PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)#, years=range(100,201))
labels.append(label)
das.append(da)


#ctl1860_v202407_FA
label = 'FLOR_ctl_1860_v202407_FA'
expname = 'CTL1860_v202407_FA_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)
#ctl1860_v202407_FAtrop
label = 'FLOR_ctl_1860_v202407_FAtrop'
expname = 'CTL1860_v202407_FAtrop_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)
#ctl1860_tiger3_FAtrop
label = 'FLOR_ctl_1860_tg3_FAtrop'
expname = 'CTL1860_FAtrop_tiger3_intelmpi_24_1116PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)#, years=range(100,201))
labels.append(label)
das.append(da)

#1990
#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)
#ctl1990_tiger3
label = 'FLOR_ctl_1990_tg3'
expname = 'CTL1990_tiger3_intelmpi_24_1116PE'
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_FA
label = 'FLOR_ctl_1990_v201905_FA'
expname = 'CTL1990_v201905_FA_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_FAtrop
label = 'FLOR_ctl_1990_v201905_FAtrop'
expname = 'CTL1990_v201905_FAtrop_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_tiger3_FAtrop
label = 'FLOR_ctl_1990_tg3_FAtrop'
expname = 'CTL1990_FAtrop_tiger3_intelmpi_24_1116PE'
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)
    if 'tg3' not in label:
        da = da.sel(year=slice(1901,2700))
        da = da.assign_coords(year=da.year.values-1900)
        lw = 1; alpha = 0.5
    else:
        lw = None; alpha = None
    da.plot(label=label, lw=lw, alpha=alpha, **kws)
    
 
if __name__ == '__main__':
    from wyconfig import * #my plot settings
    #ctl
    fig,ax = plt.subplots(figsize=(8,4.5))
    for da,label in zip(das, labels):
        wyplot(da, label, ax=ax)
    ax.legend(ncol=1)
    ax.set_ylabel(f'GMST [degC], {nwindow}-{dimlp}-RunAvg')
    #ax.set_xlim(1900, 3300)

    #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)
    tt.check(f'**Done**')
    print()
    if 'notshowfig' in sys.argv:
        pass
    else:
        plt.show()