#!/usr/bin/env python
# Wenchang Yang (wenchang@princeton.edu)
# Wed Jul  5 12:03:56 EDT 2023
# run this script after finishing FigS01.py and FigS02.py
if __name__ == '__main__':
    import sys,os
    from misc.timer import Timer
    tt = Timer(f'[{os.getcwd()}] 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
wython = '/tigress/wenchang/wython'
if wython not in sys.path: sys.path.append(wython); print('added to python path:', wython)
#from misc import get_kws_from_argv
#
if __name__ == '__main__':
    tt.check('end import')
#
#start from here
forcings = ['co2x2', 'co2x4', 'co2xp5', 'co2xp25', 'p2p0solar', 'p6p0solar', 'm2p0solar', 'm6p0solar']#[:4]
labels = ['2xCO2', '4xCO2', '0.5xCO2', '0.25xCO2', '$+2$%solar', '$+6$%solar', '$-2$%solar', '$-6$%solar']#[:4]
forcingScales = [1, 2, -1, -2, 1, 3, -1, -3]#[:4]

#if True:
#for forcing,label,scale in zip(forcings,labels,forcingScales):
def wyplot(forcing, label, scale, ax=None):
    if ax is None: fig, ax = plt.subplots()
    #forcing, label, scale = 'co2x2', '2xCO2', 1
    #prediction by gmst
    ifile = f'fig_lines_precip__FLOR_{forcing}_glbmeanTs.nc'
    print(ifile)
    ds = xr.open_dataset(ifile)
    #adjustment term
    if 'co2' in forcing:
        A = ds['A_co2']
    else:
        A = ds['A_solar']
    A = A*scale 
    da_actual = ds['pr'].groupby('time.year').mean('time')/ds['pr_ctl_clim'].mean()*100 -100 #% of precip change
    da_predict = ( ds['Ts'].groupby('time.year').mean('time') - ds['Ts_ctl_clim'].mean() ) * ds['eta'] + A

    #prediction by tropical mean SST
    ifile = f'fig_lines_precip__FLOR_{forcing}_tropoceanmeanTs.nc'
    ds = xr.open_dataset(ifile)
    da_actual = ds['pr'].groupby('time.year').mean('time')/ds['pr_ctl_clim'].mean()*100 -100 #% of precip change
    da_predict_to = ( ds['Ts'].groupby('time.year').mean('time') - ds['Ts_ctl_clim'].mean() ) * ds['eta'] + A

    ax.scatter( da_actual, da_predict, c='none', edgecolor='C0', alpha=0.3, label=f'{label}\n$T_s$:GMST', s=10)
    ax.scatter(da_actual, da_predict_to, c='none', edgecolor='C1', alpha=0.3, label=f'$T_s$:TMSST', s=10)
    ax.axline((0,0), slope=1, color='gray', ls='--')
    ax.legend(loc='upper left', borderpad=0)
 
if __name__ == '__main__':
    from wyconfig import * #my plot settings
    figsize = 11, 5
    fig, axes = plt.subplots(2, 4, figsize=figsize)
    for forcing,label,scale,ax in zip(forcings,labels,forcingScales,axes.flat):
        wyplot(forcing, label, scale, ax)

    for ax in axes[0,:]: ax.set_xlabel('')
    for ax in axes[1,:]: ax.set_xlabel('Actual precip change [%]')
    for ax in axes.flat: ax.set_ylabel('')
    for ax in axes.flat[0::4]: ax.set_ylabel('Predicted precip change [%]')
    
    #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 or 'n' in sys.argv:
        pass
    else:
        if 'plt' in globals(): plt.show()