#!/usr/bin/env python
# Wenchang Yang (wenchang@princeton.edu)
# Fri Mar  3 18:57:00 EST 2023
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
#from misc import get_kws_from_argv
#
if __name__ == '__main__':
    tt.check('end import')
#
#start from here
def func_anom(ifile, ifile_ctl): 
    da = xr.open_dataarray(ifile).mean('time') 
    da0 = xr.open_dataarray(ifile_ctl).mean('time')
    daa = (da/da0-1)*100
    """
    #dgmst
    da = xr.open_dataarray(ifile.replace('precip_', 't_surf_')).mean('time') 
    da0 = xr.open_dataarray(ifile_ctl.replace('precip_', 't_surf_')).mean('time')
    dgmst = da - da0
    daa = daa/dgmst
    """
    daa.attrs['units'] = '%/2xCO2'
    return daa

das = []
models = []

#AM2.1
ifile_ctl = '../AM2.1/precip_AM2.1p1_CTL1990_tigercpu_intelmpi_18_30PE_0101-0150_glbmean.nc'
#ifile = '../AM2.1/precip_AM2.1p1_CTL1990_plus2K_tigercpu_intelmpi_18_30PE_0101-0150_glbmean.nc'
ifile = '../AM2.1/precip_AM2.1p1_CTL1990_2xCO2_tigercpu_intelmpi_18_30PE_0101-0150_glbmean.nc'
model = ifile.split('/')[0]
da = func_anom(ifile, ifile_ctl)
das.append(da)
models.append(model)
 
#AM2.5
ifile_ctl = '../AM2.5/precip_AM2.5_CTL1990s_tigercpu_intelmpi_18_540PE_0101-0200_glbmean.nc'
ifile = '../AM2.5/precip_AM2.5_CTL1990s_2xCO2_tigercpu_intelmpi_18_540PE_0101-0150_glbmean.nc'
model = ifile.split('/')[0]
da = func_anom(ifile, ifile_ctl)
das.append(da)
models.append(model)

#HIRAM
ifile_ctl = '../HIRAM/precip_HIRAM_CTL1990s_v201910_tigercpu_intelmpi_18_540PE_0101-0300_glbmean.nc'
ifile = '../HIRAM/precip_HIRAM_CTL1990s_v201910_2xCO2_tigercpu_intelmpi_18_540PE_0101-0150_glbmean.nc'
model = ifile.split('/')[0]
da = func_anom(ifile, ifile_ctl)
das.append(da)
models.append(model)

#AM2.5C360
ifile_ctl = '../AM2.5C360/precip_AM2.5C360_CTL1990s_tigercpu_intelmpi_18_1080PE_0101-0200_glbmean.nc'
ifile = '../AM2.5C360/precip_AM2.5C360_CTL1990s_2xCO2_tigercpu_intelmpi_18_1080PE_0101-0150_glbmean.nc'
model = ifile.split('/')[0]
da = func_anom(ifile, ifile_ctl)
das.append(da)
models.append(model)

#AM2.5 p5xCO2
ifile_ctl = '../AM2.5/precip_AM2.5_CTL1990s_tigercpu_intelmpi_18_540PE_0101-0200_glbmean.nc'
ifile = '../AM2.5/precip_AM2.5_CTL1990s_p5xCO2_tigercpu_intelmpi_18_540PE_0101-0150_glbmean.nc'
model = ifile.split('/')[0] + '(0.5xCO2)'
da = func_anom(ifile, ifile_ctl) * (-1)
das.append(da)
models.append(model)

da = xr.concat(das, dim=pd.Index(models, name='model'))
df = da.to_pandas()

if __name__ == '__main__':
    from wyconfig import * #my plot settings
    fig,ax = plt.subplots()
    n_models = da.model.size
    df.plot.bar(rot=0, color=[f'C{ii}' for ii in range(n_models)])

    for ii in range(n_models):
        y = da.isel(model=ii).item()
        ax.text(ii, y, f'{y:.2f}', va='top', ha='center')

    ax.axhline(0, color='gray', ls='--')
    ax.set_ylabel('dprecip [% per 2xCO2]')
    ax.set_xlabel('')
    
    
    #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()