#!/usr/bin/env python
# Wenchang Yang (wenchang@princeton.edu)
# Mon Oct  7 16:05:12 EDT 2024
if __name__ == '__main__':
    import sys,os
    try:
        from misc.timer import Timer
        tt = Timer(f'[{os.getcwd()}] start ' + ' '.join(sys.argv))
    except:
        pass
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
import xlinregress
from modelout.getdata import funcs
#
if __name__ == '__main__':
    try:
        tt.check('end import')
    except:
        pass
#
#start from here
#nonFA EW
ifile = '/tigress/wenchang/analysis/FLOR/ens/indexEW/t_surf_FLOR_HistRCP45_tigercpu_intelmpi_18_576PE_10ens_1860-2100_indexEW.nc'
da = xr.open_dataarray(ifile).sel(time=slice('1970', '2020')).groupby('time.year').mean('time')
rg = da.linregress.on(da.year, dim='year')
rgEW0 = rg
#NS
ifile = '/tigress/wenchang/analysis/FLOR/ens/indexNS/t_surf_FLOR_HistRCP45_tigercpu_intelmpi_18_576PE_10ens_1860-2100_indexNS.nc'
da = xr.open_dataarray(ifile).sel(time=slice('1970', '2020')).groupby('time.year').mean('time')
rg = da.linregress.on(da.year, dim='year')
rgNS0 = rg
#wrap to dataset
indexes0 = xr.Dataset(dict(
    EW=rgEW0.slope.pipe(lambda x: x*50).assign_attrs(units='K per 50 years', long_name='EW index'),
    NS=rgNS0.slope.pipe(lambda x: x*50).assign_attrs(units='K per 50 years', long_name='NS index')
    ))

#FA EW
ifiles = [glob.glob(f'/tigress/wenchang/analysis/active_monitor/indexEW/t_surf_FLOR_HistRCP45_FA_tigercpu_intelmpi_18_576PE_e{ii}_1860-????_indexEW.nc')[0]
    for ii in range(1,3+1)]
das = [xr.open_dataarray(ifile).sel(time=slice('1970','2020')).groupby('time.year').mean('time') for ifile in ifiles]
da = xr.concat(das, dim=pd.Index(range(1,3+1), name='ens'))
rg = da.linregress.on(da.year, dim='year')
rgEW_FA = rg
#NS
ifiles = [glob.glob(f'/tigress/wenchang/analysis/active_monitor/indexNS/t_surf_FLOR_HistRCP45_FA_tigercpu_intelmpi_18_576PE_e{ii}_1860-????_indexNS.nc')[0]
    for ii in range(1,3+1)]
das = [xr.open_dataarray(ifile).sel(time=slice('1970','2020')).groupby('time.year').mean('time') for ifile in ifiles]
da = xr.concat(das, dim=pd.Index(range(1,3+1), name='ens'))
rg = da.linregress.on(da.year, dim='year')
rgNS_FA = rg
#wrap to dataset
indexesFA = xr.Dataset(dict(
    EW=rgEW_FA.slope.pipe(lambda x: x*50).assign_attrs(units='K per 50 years', long_name='EW index'),
    NS=rgNS_FA.slope.pipe(lambda x: x*50).assign_attrs(units='K per 50 years', long_name='NS index')
    ))
 
#HadISST
ifile = '/tigress/wenchang/modelInput/HadISST/HadISST_sst.187001-202403.wy.nc'
da = xr.open_dataarray(ifile).sel(time=slice('1970', '2020')).groupby('time.year').mean('time')
#EW
daEW = da.pipe(funcs['indexEW'])
rg = daEW.linregress.on(daEW.year, dim='year')
rgEW = rg
#NS
daNS = da.pipe(funcs['indexNS'])
rg = daNS.linregress.on(daNS.year, dim='year')
rgNS = rg
#wrap
indexesHadISST = xr.Dataset(dict(
    EW=rgEW.slope.pipe(lambda x: x*50).assign_attrs(units='K per 50 years', long_name='EW index'),
    NS=rgNS.slope.pipe(lambda x: x*50).assign_attrs(units='K per 50 years', long_name='NS index')
    ))

#nonFA 2xCO2 EW
ifile = glob.glob(f'/projects2/w/wenchang/analysis/active_monitor/indexEW/t_surf_FLOR_CTL1860_v202407_tigercpu_intelmpi_18_576PE_1901-????_indexEW.nc')[0]
da = xr.open_dataarray(ifile).sel(time=slice('1951', '2050')).mean('time')
da_ref = da
ifile = '/projects2/w/wenchang/analysis/active_monitor/indexEW/t_surf_FLOR_CTL1860_v202407_2xCO2_tigercpu_intelmpi_18_576PE_2001-2200_indexEW.nc'
da = xr.open_dataarray(ifile).sel(time=slice('2101', '2200')).mean('time')
da = da - da_ref
daEW = da
#NS
ifile = glob.glob(f'/projects2/w/wenchang/analysis/active_monitor/indexNS/t_surf_FLOR_CTL1860_v202407_tigercpu_intelmpi_18_576PE_1901-????_indexNS.nc')[0]
da = xr.open_dataarray(ifile).sel(time=slice('1951', '2050')).mean('time')
da_ref = da
ifile = '/projects2/w/wenchang/analysis/active_monitor/indexNS/t_surf_FLOR_CTL1860_v202407_2xCO2_tigercpu_intelmpi_18_576PE_2001-2200_indexNS.nc'
da = xr.open_dataarray(ifile).sel(time=slice('2101', '2200')).mean('time')
da = da - da_ref
daNS = da
indexes2xCO2 = xr.Dataset(dict(
    EW=daEW.assign_attrs(units='K', long_name='EW index'),
    NS=daNS.assign_attrs(units='K', long_name='EW index')
    ))

#FA 2xCO2 EW
ifile = glob.glob(f'/projects2/w/wenchang/analysis/active_monitor/indexEW/t_surf_FLOR_CTL1860_v202407_FA_tigercpu_intelmpi_18_576PE_1901-????_indexEW.nc')[0]
da = xr.open_dataarray(ifile).sel(time=slice('1951', '2050')).mean('time')
da_ref = da
ifile = '/projects2/w/wenchang/analysis/active_monitor/indexEW/t_surf_FLOR_CTL1860_v202407_FA_2xCO2_tigercpu_intelmpi_18_576PE_2001-2200_indexEW.nc'
da = xr.open_dataarray(ifile).sel(time=slice('2101', '2200')).mean('time')
da = da - da_ref
daEW = da
#NS
ifile = glob.glob(f'/projects2/w/wenchang/analysis/active_monitor/indexNS/t_surf_FLOR_CTL1860_v202407_FA_tigercpu_intelmpi_18_576PE_1901-????_indexNS.nc')[0]
da = xr.open_dataarray(ifile).sel(time=slice('1951', '2050')).mean('time')
da_ref = da
ifile = '/projects2/w/wenchang/analysis/active_monitor/indexNS/t_surf_FLOR_CTL1860_v202407_FA_2xCO2_tigercpu_intelmpi_18_576PE_2001-2200_indexNS.nc'
da = xr.open_dataarray(ifile).sel(time=slice('2101', '2200')).mean('time')
da = da - da_ref
daNS = da
indexes2xCO2FA = xr.Dataset(dict(
    EW=daEW.assign_attrs(units='K per 50 years', long_name='EW index'),
    NS=daNS.assign_attrs(units='K per 50 years', long_name='EW index')
    ))

if __name__ == '__main__':
    from wyconfig import * #my plot settings
    fig,ax = plt.subplots(figsize=(6,4.5))
    indexesHadISST.plot.scatter(x='EW', y='NS', ax=ax, label='HadISST', color='none', edgecolors='k')
    indexes2xCO2.plot.scatter(x='EW', y='NS', ax=ax, label='nonFA 2xCO2', color='none', edgecolors='C0', marker='^')
    indexes0.plot.scatter(x='EW', y='NS', ax=ax, label='nonFA', color='none', edgecolors='C0')
    indexes0.mean('ens', keep_attrs=True).plot.scatter(x='EW', y='NS', ax=ax, label='nonFA ensemble mean', color='C0')
    indexes2xCO2FA.plot.scatter(x='EW', y='NS', ax=ax, label='FA 2xCO2', color='none', edgecolors='C1', marker='^')
    indexesFA.plot.scatter(x='EW', y='NS', ax=ax, label='FA', color='none', edgecolors='C1')
    indexesFA.mean('ens', keep_attrs=True).plot.scatter(x='EW', y='NS', ax=ax, label='FA ens mean', color='C1')

    ax.legend()
    ax.axhline(0, ls='--', color='gray')
    ax.axvline(0, ls='--', color='gray')
    ax.set_title('FLOR EW vs NS indexes linear trends over 1970-2020')
    ax.set_xlim(-1.5, 1.5)
    ax.set_ylim(-0.6, 0.6)
    
    #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)
 
    try:
        tt.check(f'**Done**')
    except:
        pass
    print()
    if 'notshowfig' in sys.argv or 'n' in sys.argv:
        pass
    else:
        if 'plt' in globals(): plt.show()