#!/usr/bin/env python
# Wenchang Yang (wenchang@princeton.edu)
# Mon Sep 27 21:44:05 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
#
if __name__ == '__main__':
    tt.check('end import')
#
#start from here
ifile = 'data_precip_AM4urban_amip_5ens_1870-202107.masked.south.nc'
da = xr.open_dataarray(ifile).load() \
    .sel(time=slice('1991', '2020')).groupby('time.month')
da_mclim = da.mean(['time', 'en']).roll(month=6).assign_attrs(units='mm/day')
months_roll = da_mclim.month.where(da_mclim.month<7, other=da_mclim.month-12).values#new months: -5, -4, ..., 6
da_mclim = da_mclim.assign_coords(month=months_roll)
ci = da.quantile([0.025, 0.975], dim=['time', 'en']).roll(month=6).assign_coords(month=months_roll)
mon_names = ['Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec',
    'Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun']
 
 
if __name__ == '__main__':
    from wyconfig import * #my plot settings
    plt.close()
    fig, ax = plt.subplots()
    ax.fill_between(ci.month, ci.isel(quantile=0), ci.isel(quantile=1), color='C0', alpha=0.2, label='95% range')
    da_mclim.plot(marker='o', fillstyle='none', label='ens mean mclim')

    ax.set_xticks(months_roll)
    ax.set_xticklabels(mon_names)
    ax.legend()
    ax.set_title('annual cycle from AM4: 1991-2020, 5ens')
    
    #savefig
    if 'savefig' in sys.argv:
        figname = __file__.replace('.py', f'.png')
        wysavefig(figname)
    tt.check(f'**Done**')
    plt.show()