#!/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 misc.modelout import get_modelout_data, update_modelout_data
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()
import geoxarray
#
if __name__ == '__main__':
    tt.check('end import')
#
#start from here
daname = 't_surf'
func = lambda x: x.load().geo.fldmean()
funcname = 'gmst'

cleanup = False #remove cache or not

das = dict()

model = 'CM2.1p1'
#ctl
expname = 'CTL1860_tigercpu_intelmpi_18_80PE'
#da = get_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
das['cm2p1_ctl'] =  da
#ctl1990
expname = 'CTL1990_tigercpu_intelmpi_18_80PE'
#da = get_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
das['cm2p1_ctl_1990'] =  da
#pert
exps = [
    ('cm2p1_p6solar', 'CM2.1 +6% Solar', 'CTL1860_p6pctSolar_tigercpu_intelmpi_18_80PE'),
    ('cm2p1_m6solar', 'CM2.1 -6% Solar', 'CTL1860_m6pctSolar_tigercpu_intelmpi_18_80PE'),
    ]
for key,label,expname in exps:
    da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)#, cleanup=cleanup)
    das[key] = da
exps_cm2p1 = exps

model = 'FLOR'
#ctl
expname = 'CTL1860_newdiag_tigercpu_intelmpi_18_576PE'
#da = get_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)#, years=range(100,201))
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)#, years=range(100,201))
das['flor_ctl'] =  da
#ctl1860_v201904
expname = 'CTL1860_v201904_tigercpu_intelmpi_18_576PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)#, years=range(100,201))
das['flor_ctl_v201904'] =  da
#ctl1990
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))
das['flor_ctl_1990'] =  da
#pert
exps = [
    ('flor_p6solar', 'FLOR +6% Solar', 'p6p0sol_CTL1860_tigercpu_intelmpi_18_576PE'),
    ('flor_m6solar', 'FLOR -6% Solar', 'm6p0sol_CTL1860_tigercpu_intelmpi_18_576PE'),
    ]
for key,label,expname in exps:
    #da = get_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
    da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
    das[key] = da
exps_flor = exps
exps = exps_cm2p1 + exps_flor

 
def wyplot(key, label, flip=False, **kws):
    ax = kws.pop('ax', plt.gca())
    da = das[key]
    if key.startswith('cm2p1'):
        da_ctl = das['cm2p1_ctl']
    elif key.startswith('flor'):
        da_ctl = das['flor_ctl']
    da = da.groupby('time.year').mean('time') - da_ctl.sel(time=slice('0101','0200')).mean('time') #anom
    if da.year[0] == 101:
        da = xr.concat([da_ctl.sel(time='0100').groupby('time.year').mean('time')*0, da], dim='year')
    #da = da.groupby('time.month') - da_ctl.sel(time=slice('0101','0200')).groupby('time.month').mean('time') #anom
    if flip: da = -da
    da = da.pipe(lowpass)
    #da = da.assign_coords(year=da.year-100) #shift the year axis to start with 0 (instead of 100)
    da.plot(label=label, **kws)
    #ax.plot(da.isel(year=-1).year, da.isel(year=-1), marker='o', fillstyle='none', color='gray')
    #ax.text(da.year.values[-1], da.values[-1], f'{da.year.values[-1]}', color='gray')
def wyplot_ctl(key,**kws):
    da = das[key]
    da = da.groupby('time.year').mean('time')
    da = da.pipe(lowpass)
    da.plot(label=key, **kws)
    
 
if __name__ == '__main__':
    from wyconfig import * #my plot settings
    fig,ax = plt.subplots(figsize=(8,4))

    wyplot('cm2p1_ctl', 'cm2p1_ctl', ls='-', color='k')
    wyplot('flor_ctl', 'flor_ctl', ls='-', color='gray')
    for key,label,expname in exps:
        if '-' in label:
            flip = False
            ls = '--'
        else:
            flip = True
            ls = '-'
        wyplot(key, label, flip=flip, ls=ls)

    ax.legend(ncol=1)
    #ax.set_xlim(100, 250)
    #ax.set_ylabel(f'GMST anom [K], {nwindow}-{dimlp}-lp')
    ax.set_ylabel(f'GMST anom [K], {nwindow}-{dimlp}-RunAvg')
    #ax.set_xlim(None, 1000)
    
    #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)
    
    #ctl
    fig,ax = plt.subplots(figsize=(8,4))
    for key in ('cm2p1_ctl', 'cm2p1_ctl_1990', 'flor_ctl', 'flor_ctl_v201904', 'flor_ctl_1990'):
        wyplot_ctl(key)
    ax.legend()
    #ax.set_ylabel(f'GMST [K], {nwindow}-{dimlp}-lp')
    ax.set_ylabel(f'GMST [K], {nwindow}-{dimlp}-RunAvg')

    #savefig
    if 'savefig' in sys.argv or 's' in sys.argv:
        figname = __file__.replace('.py', f'__ctls.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()