#!/usr/bin/env python
# Wenchang Yang (wenchang@princeton.edu)
# Tue Jun 29 16:14:32 EDT 2021
if __name__ == '__main__':
    from misc.timer import Timer
    tt = Timer(f'start {__file__}')
import sys, os.path, os, glob, datetime
import xarray as xr, numpy as np, pandas as pd, matplotlib.pyplot as plt
#more imports
import geoxarray
from misc.landmask import flagland
#
if __name__ == '__main__':
    tt.check('end import')
#
#start from here
#ifile = 'data_precip_FLOR_histRCP45_5ens_1860-2100_SouthAfrica.nc'
ifile = 'data_precip_AM2p5C360_amipLongChan_10ens_1871-2020_SouthAfrica.nc'
dsname =  'precip'
daname = dsname
units = 'mm/day'
years = slice('1981', '2010')
title = f'AM2.5C360 AMIP 10ens South Africa {years.start}-{years.stop}'
tag = '_' + title.replace(' ', '_')
ofile_nc = __file__.replace('.py', f'{tag}.nc')

if os.path.exists(ofile_nc):
    da = xr.open_dataarray(ofile_nc)
    print('[loaded]:', ofile_nc)
else:
    print('loading...')
    da = xr.open_dataarray(ifile).sel(time=years).load()
    da = da.groupby('time.month').mean('time').mean('ens')
    print('calculating...')
    """
    #da = da.where(landflag(da)>0.5).geo.fldmean()
    da = da.geo.fldmean()
    damean = da.groupby('time.dayofyear').mean(['time', 'ens'])
    da_quantile = da.groupby('time.dayofyear').quantile([0.025, 0.17, 0.83, 0.975], dim=['time', 'ens'])
    ds = xr.Dataset(dict(m=damean, q=da_quantile))
    print('saving...')
    """
    ds = da.to_dataset(name=daname)
    ds.to_netcdf(ofile_nc)
    print('[saved]:', ofile_nc)
 
if __name__ == '__main__':
    from wyconfig import * #my plot settings
    from geoplots import mapplot
    figsize = (10,3.5)
    #fig, ax = plt.subplots(figsize=(8,6))
    g = da.roll(month=6, roll_coords=True) \
        .assign_attrs(units=units) \
        .plot(col='month', col_wrap=6, cmap='YlGnBu', vmin=0, vmax=10, levels=11, figsize=figsize)
    for ax in g.axes.flat:
        plt.sca(ax)
        mapplot(xticks=np.arange(26,34,3))
        ax.set_xlabel('')
        ax.set_ylabel('')
    #mapplot(xticks=np.arange(26,34))
    plt.suptitle(title, x=0.05, va='bottom', ha='left')

    """
    #rotate dayofyear
    ndays = 31+29+31+30+31+30 #Jan-Jun days
    ds = ds.roll(dayofyear=-ndays, roll_coords=True)
    ds = ds.assign_coords(dayofyear=ds.dayofyear.where(ds.dayofyear>ndays, other=ds.dayofyear+366))
    ds.m.plot(color='k', lw=2, label='mean')
    for ii,qi in enumerate(ds['quantile'].values):
        ds.q.sel(quantile=qi).plot(ax=ax, color=f'C{ii}', label=f'{qi*100:.1f}%')
    xticks = np.cumsum([1, 31, 29, 31, 30, 31, 30, 31, 31, 30, 31, 30])
    xticklabels = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
    xticklabels = xr.DataArray(xticklabels, dims='dayofyear', coords=[xticks,])
    xticklabels = xticklabels.roll(dayofyear=6, roll_coords=True)
    xticklabels = xticklabels.assign_coords(dayofyear=xticklabels.dayofyear.where(xticklabels.dayofyear>ndays, other=xticklabels.dayofyear+366))
    ax.set_xticks(xticklabels.dayofyear.values)
    ax.set_xticklabels(xticklabels.values, ha='left')
    ax.set_xlim(1+ndays, 366+ndays)
    ax.set_xlabel('')
    ax.set_ylabel(f'{daname} [{units}]')
    ax.set_title('')
    #ax.text(0,1, f' {360-lons.start}-{360-lons.stop}W, {lats.start}-{lats.stop}N, land', transform=ax.transAxes,
    #    ha='left', va='top')
    ax.legend(loc='upper left')
    ax.set_title(title, loc='left')
    """
    
    #savefig
    if 'savefig' in sys.argv:
        figname = __file__.replace('.py', f'{tag}.png')
        wysavefig(figname)
    tt.check(f'**Done**')
    plt.show()