#!/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')
#
case = '1034'#'10'# '0134' #
model = 'AM2.5'
#start from here
def func_anom(ifile, ifile_ctl): 
    #tspan = slice('0111', None) # omit the first 10 years 0101-0110
    tspan = slice(None, None)
    da = xr.open_dataarray(ifile).sel(time=tspan).mean('time') 
    da0 = xr.open_dataarray(ifile_ctl).sel(time=tspan).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
    #normalized by dgmst
    daa = daa/dgmst
    daa.attrs['units'] = '%/K'
    """
    daa.attrs['units'] = '%'
    return daa

das = []
bases = []

#plus2K
base = '+2K'
ifile_ctl = 'precip_AM2.5_CTL1860_florSST_tigercpu_intelmpi_18_540PE_0101-0200_glbmean.nc'
ifile = 'precip_AM2.5_CTL1860_florSST_plus2K_tigercpu_intelmpi_18_540PE_0101-0150_glbmean.nc'
da = func_anom(ifile, ifile_ctl)
das.append(da)
bases.append(base)
 
#2xCO2
base = '2xCO2'
ifile_ctl = 'precip_AM2.5_CTL1860_florSST_tigercpu_intelmpi_18_540PE_0101-0200_glbmean.nc'
ifile = 'precip_AM2.5_CTL1860_florSST_2xCO2_tigercpu_intelmpi_18_540PE_0101-0150_glbmean.nc'
da = func_anom(ifile, ifile_ctl)
das.append(da)
bases.append(base)
 
#+2%solar
base = '+2%solar'
ifile_ctl = 'precip_AM2.5_CTL1860_florSST_tigercpu_intelmpi_18_540PE_0101-0200_glbmean.nc'
ifile = 'precip_AM2.5_CTL1860_florSST_solar2pctplus_tigercpu_intelmpi_18_540PE_0101-0150_glbmean.nc'
da = func_anom(ifile, ifile_ctl)
das.append(da)
bases.append(base)
 
#plus2Ktrop
base = '+2Ktrop'
ifile_ctl = 'precip_AM2.5_CTL1860_florSST_tigercpu_intelmpi_18_540PE_0101-0200_glbmean.nc'
ifile = 'precip_AM2.5_CTL1860_florSST_plus2Ktrop_tigercpu_intelmpi_18_540PE_0101-0150_glbmean.nc'
da = func_anom(ifile, ifile_ctl)
das.append(da)
bases.append(base)
 
#plus2Kextr
base = '+2Kextr'
ifile_ctl = 'precip_AM2.5_CTL1860_florSST_tigercpu_intelmpi_18_540PE_0101-0200_glbmean.nc'
ifile = 'precip_AM2.5_CTL1860_florSST_plus2Kextr_tigercpu_intelmpi_18_540PE_0101-0150_glbmean.nc'
da = func_anom(ifile, ifile_ctl)
das.append(da)
bases.append(base)
 
"""
#2% solar
base = '+2%solar'
ifile_ctl = 'precip_AM2.5_CTL1990s_tigercpu_intelmpi_18_540PE_0101-0200_glbmean.nc'
ifile = 'precip_AM2.5_CTL1990s_solar2pctplus_tigercpu_intelmpi_18_540PE_0101-0150_glbmean.nc'
da = func_anom(ifile, ifile_ctl)
das.append(da)
bases.append(base)
"""
 

da = xr.concat(das, dim=pd.Index(bases, name='base'))
if case is not None: da = da.isel(base=[int(s) for s in case]) #only show a subset results
df = da.to_pandas()

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

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

    ax.set_ylabel(f'dprecip [%]')
    ax.set_xlabel(f'{model} experiment')
    ax.axhline(0, color='gray', ls='--')
    
    
    #savefig
    if 'savefig' in sys.argv or 's' in sys.argv:
        figname = __file__.replace('.py', f'.png')
        if case is not None: figname = figname.replace('.png', f'__{case}.png')
        if 'pdf' in sys.argv:
            figname = figname.replace('.png', '.pdf')
        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()