#!/usr/bin/env python
# Wenchang Yang (wenchang@princeton.edu)
# Tue May 16 10:52:37 EDT 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
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
#
if __name__ == '__main__':
    tt.check('end import')
#
#start from here
csvfile = 'african_cities_latlon.csv'
ncfile = csvfile.replace('.csv', '.nc')
if os.path.exists(ncfile) and 'o' not in sys.argv:
    print('[exists]:', ncfile)
    sys.exit()
df = pd.read_csv(csvfile, encoding='unicode_escape') #default encoding failed
#create dataarray of lon/lat using location ({City}_{Country}) as coords
locations = [f'{r[1].City.strip()} ({r[1].Country.strip()})' for r in df.iterrows()]
lat = xr.DataArray(df.Latitude, dims='location', coords=[locations,])
lon = xr.DataArray(df.Longitude, dims='location', coords=[locations,])
lon = lon.where(lon>0, other=lon+360) #lon range from -180/180 to 0/360
#convert to dataset and save it
ds = xr.Dataset(dict(lat=lat, lon=lon))
ds.to_netcdf(ncfile)
print('[saved]', ncfile)
 
 
if __name__ == '__main__':
    #from wyconfig import * #my plot settings
    
    #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()