#!/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
model = 'CM2.1p1'
daname = 'netrad_toa'
func = lambda x: x.load().geo.fldmean()
funcname = 'glbmean'

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

label = 'CTL1860'
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)
dass[label] = da
da_ctl = da

label = '4xCO2'
expname = 'CTL1860_4xCO2_tigercpu_intelmpi_18_80PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
das.append(da)
labels.append(label)
dass[label] = da
 
label = '2xCO2'
expname = 'CTL1860_2xCO2_tigercpu_intelmpi_18_80PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
label = '0.5xCO2'
expname = 'CTL1860_p5xCO2_tigercpu_intelmpi_18_80PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
label = '0.25xCO2'
expname = 'CTL1860_p25xCO2_tigercpu_intelmpi_18_80PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
label = '0.125xCO2'
expname = 'CTL1860_p125xCO2_tigercpu_intelmpi_18_80PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
 
label = '+6% Solar'
expname = 'CTL1860_p6pctSolar_tigercpu_intelmpi_18_80PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
label = '+4% Solar'
expname = 'CTL1860_p4pctSolar_tigercpu_intelmpi_18_80PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
label = '+2% Solar'
expname = 'CTL1860_p2pctSolar_tigercpu_intelmpi_18_80PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
label = '+1% Solar'
expname = 'CTL1860_p1pctSolar_tigercpu_intelmpi_18_80PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
label = '-1% Solar'
expname = 'CTL1860_m1pctSolar_tigercpu_intelmpi_18_80PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
label = '-2% Solar'
expname = 'CTL1860_m2pctSolar_tigercpu_intelmpi_18_80PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
label = '-4% Solar'
expname = 'CTL1860_m4pctSolar_tigercpu_intelmpi_18_80PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
label = '-6% Solar'
expname = 'CTL1860_m6pctSolar_tigercpu_intelmpi_18_80PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
label = '1%to4xCO2'
expname = 'CTL1860_1pct4xCO2_tigercpu_intelmpi_18_80PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
label = '1%to4xCO2back'
expname = 'CTL1860_1pct4xCO2back_tigercpu_intelmpi_18_80PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
label = '1%to4xCO2new'
expname = 'CTL1860_1pct4xCO2new_tigercpu_intelmpi_18_80PE'
da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
labels.append(label)
das.append(da)
dass[label] = da
 
label = '1%to4xCO2newback'
expname = 'CTL1860_1pct4xCO2newback_tigercpu_intelmpi_18_80PE'
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, **kws):
    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
    da = da.groupby('time.year').mean('time')
    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(**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))

    for label,da in dass.items():
        if label=='CTL1860':
            da.pipe(wyplot, label=label, color='k', lw=1)
            ax.set_prop_cycle(None)
        else:
            da.pipe(wyplot, label=label, lw=1, alpha=0.8)

    ax.legend(ncol=3)
    ax.set_ylabel('W m$^{-2}$')
    ax.set_xlim(None, da_ctl.time.dt.year.values[-1]+500*0)
    ax.set_title(f'CM2.1 netrad_toa, {nwindow}-{dimlp}-lp')
    
    #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)
    """
    #mirror the negative forcing
    fig,ax = plt.subplots(figsize=(8,4))

    label = 'CTL1860'
    da = dass[label]
    da.pipe(wyplot, label=label, color='k')

    label = '2xCO2'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C0', ls='-')
    label = '0.5xCO2'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C0', ls='--', flip=True)

    label = '4xCO2'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C1', ls='-')
    label = '0.25xCO2'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C1', ls='--', flip=True)

    label = '0.125xCO2'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C2', ls='--', flip=True)

    label = '+1% Solar'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C3', ls='-')
    label = '-1% Solar'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C3', ls='--', flip=True)

    label = '+2% Solar'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C4', ls='-')
    label = '-2% Solar'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C4', ls='--', flip=True)

    label = '+4% Solar'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C5', ls='-')
    label = '-4% Solar'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C5', ls='--', flip=True)

    label = '+6% Solar'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C6', ls='-')
    label = '-6% Solar'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C6', ls='--', flip=True)

    label = '1%to4xCO2'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C7', ls='-')

    label = '1%to4xCO2back'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C8', ls='-')

    label = '1%to4xCO2new'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C9', ls='-')

    label = '1%to4xCO2newback'
    da = dass[label]
    da.pipe(wyplot, label=label, color='C10', ls='-')

    ax.legend(ncol=3)
    ax.set_ylabel('W m$^{-2}$')
    ax.set_xlim(None, da_ctl.time.dt.year.values[-1]+500*0)
    ax.set_title(f'CM2.1 netrad_toa anom, {nwindow}-{dimlp}-lp')
    
    #savefig
    if 'savefig' in sys.argv or 's' in sys.argv:
        figname = __file__.replace('.py', f'__mirror.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()