#!/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
import xlinregress
#
if __name__ == '__main__':
    tt.check('end import')
#
#start from here
case = '2xCO2'
model = 'FLOR'
daname = 't_surf'
func = lambda x: x.load().geo.fldmean()
funcname = 'trop50mst'


#T
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)
ifile_ctl = 't_surf_FLOR_CTL1860_newdiag_tigercpu_intelmpi_18_576PE_0101-0200_trop50mean.nc'
da = xr.open_dataarray(ifile_ctl).load()
da_ctl = da#.sel(time=slice('0100', '1000'))

expname = 'CTL1860_4xCO2_tigercpu_intelmpi_18_80PE'
#da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
ifile = 't_surf_FLOR_co2x2_CTL1860_tigercpu_intelmpi_18_576PE_0101-0600_trop50mean.nc'
da = xr.open_dataarray(ifile).load()
tropmst = da.groupby('time.year').mean('time') - da_ctl.groupby('time.year').mean('time').sel(year=slice(101,200)).mean('year')

#N
daname = 'netrad_toa'
funcname = 'glbmean'
expname = 'CTL1860_tigercpu_intelmpi_18_80PE'
#da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
#ifile_ctl = ifile_ctl.replace('t_surf', daname).replace('0001-2571', '0101-0200')
ifile_ctl = ifile_ctl.replace('t_surf', f'../{daname}').replace('trop50mean', 'glbmean')
da = xr.open_dataarray(ifile_ctl).load()
da_ctl = da#.sel(time=slice('0100', '1000'))

expname = 'CTL1860_4xCO2_tigercpu_intelmpi_18_80PE'
#da = update_modelout_data(daname=daname, model=model, expname=expname, func=func, funcname=funcname)
#ifile = ifile.replace('t_surf', daname)
ifile = ifile.replace('t_surf', f'../{daname}').replace('trop50mean', 'glbmean')
da = xr.open_dataarray(ifile).load()
netradtoa = da.groupby('time.year').mean('time') - da_ctl.groupby('time.year').mean('time').sel(year=slice(101,200)).mean('year')

#wrap data
ds = xr.Dataset(dict(
    trop50mst=tropmst.assign_attrs(units='K', long_name='TROP50MST anom'),
    netradtoa=netradtoa.assign_attrs(units='W/m^2', long_name='TOA net radiation anom')
    ))


def wyplot(**kws):
    ax = kws.pop('ax', plt.gca())
    #ax.scatter(das['tropmst'], das['netradtoa'])
    ds.plot.scatter(x='trop50mst', y='netradtoa', c='none', edgecolors='C0', alpha=0.5)
def wyplot_linregress(yearstart=None, yearstop=None, **kws):
    color = kws.pop('color', 'C0')
    if yearstart is None:
        yearstart = 1
    if yearstop is None:
        yearstop = ds.year.size
    ds_ = ds.isel(year=slice(yearstart-1, yearstop))
    ax = kws.pop('ax', plt.gca())

    x = ds_['trop50mst']
    y = ds_['netradtoa']
    #ax.plot(x, y, marker='o', ls='none', fillstyle='none', alpha=0.5)
    ds_.plot.scatter(x='trop50mst', y='netradtoa', c='none', edgecolors=color, alpha=0.5)
    reg = y.linregress.on(x, dim='year')
    y0 = reg.intercept.item()
    b = reg.slope.item()
    ax.axline((0,y0), slope=b, ls='--', color=color)
    s = f' years{yearstart}-{yearstop}: y = {b:.2g}x + {y0:.2g}; ECS = {-y0/b:.2g}K'
    if yearstart==1:
        s = s + '\n'
        print(s)
    ax.text(0, y0, s, color=color)

    
    
 
if __name__ == '__main__':
    from wyconfig import * #my plot settings
    fig,ax = plt.subplots()
    #wyplot()
    wyplot_linregress(1, 20, color='C0')
    wyplot_linregress(21, 150, color='C1')
    wyplot_linregress(151, None, color='C2')

    ax = plt.gca()
    ax.axhline(0, color='gray', ls='--')
    ax.set_xlim(0, None)

    
    #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()