#!/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=False, 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 = 'glbmean'

labels = []
das = []
dass = {}

model = 'FLOR'
expname = 'CTL1860_newdiag_tigercpu_intelmpi_18_576PE'
label = 'CTL1860_FLOR'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
da_ctl_flor = da

model = 'CM2.1p1'
expname = 'CTL1860_tigercpu_intelmpi_18_80PE'
label = 'CTL1860_CM2.1p1'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
da_ctl_cm2p1 = da

model = 'FLOR'
expname = 'm2p0sol_CTL1860_tigercpu_intelmpi_18_576PE'
label = '-2% Solar FLOR'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da

model = 'CM2.1p1'
expname = 'CTL1860_m2pctSolar_tigercpu_intelmpi_18_80PE'
label = '-2% Solar CM2.1'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
model = 'FLOR'
expname = 'm4p0sol_CTL1860_tigercpu_intelmpi_18_576PE'
label = '-4% Solar FLOR'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da

model = 'CM2.1p1'
expname = 'CTL1860_m4pctSolar_tigercpu_intelmpi_18_80PE'
label = '-4% Solar CM2.1'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
model = 'FLOR'
expname = 'm6p0sol_CTL1860_tigercpu_intelmpi_18_576PE'
label = '-6% Solar FLOR'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da

model = 'CM2.1p1'
expname = 'CTL1860_m6pctSolar_tigercpu_intelmpi_18_80PE'
label = '-6% Solar CM2.1'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
model = 'FLOR'
expname = 'p6p0sol_CTL1860_tigercpu_intelmpi_18_576PE'
label = '+6% Solar FLOR'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da

model = 'CM2.1p1'
expname = 'CTL1860_p6pctSolar_tigercpu_intelmpi_18_80PE'
label = '+6% Solar CM2.1'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
def wyplot(da, flip=False, reset_year=True, normalize=True, **kws):
    label = kws.pop('label')
    lw = 1.5 if 'FLOR' in label else 1
    da_ctl = da_ctl_flor if 'FlOR' in label else da_ctl_cm2p1
    ax = kws.pop('ax', plt.gca())
    da = da.groupby('time.year').mean('time') - da_ctl.groupby('time.year').mean('time').sel(year=slice(101,200)).mean('year') #anom
    if reset_year: da = da.assign_coords(year=range(1, da.year.size+1))
    if normalize: #normalize to 2% solar radiation
        if '4%' in label:
            da = da/2
        elif '6%' in label:
            da = da/3
    if '+' not in label:
        da = -da
    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, lw=lw, **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')
    
 
if __name__ == '__main__':
    from wyconfig import * #my plot settings
    fig,ax = plt.subplots(figsize=(8,4))

    label = '-2% Solar FLOR'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C0')
    label = '-2% Solar CM2.1'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C0')

    label = '-4% Solar FLOR'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C1')
    label = '-4% Solar CM2.1'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C1')

    label = '-6% Solar FLOR'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C2')
    label = '-6% Solar CM2.1'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C2')

    label = '+6% Solar FLOR'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C3')
    label = '+6% Solar CM2.1'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C3')

    ax.legend()
    ax.set_ylabel(f'K')
    #ax.set_xlim(None, da_ctl.time.dt.year.values[-1]+500*0)
    ax.set_title(f'GMST anom, {nwindow}-{dimlp}-lp, scaled to +2% Solar')
    ax.set_ylim(None, 5)
    
    #savefig
    if 'savefig' in sys.argv or 's' in sys.argv:
        figname = __file__.replace('.py', f'__norm.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()