#import json
#from netCDF4 import Dataset
import RY15
import xarray
#from cdo import *
import os
import numpy as np
#import sys
#from netCDF4 import date2num,num2date
#import datetime as dt
import pandas as pd


#cdo = Cdo()


def dic2netcdf2(dataset,filename):

	for key,value in dataset.items():
		if (key == 'lat') or (key == 'lon')  or (key == "time") or ('lat' in key):
			continue
		print(key,value.shape)
		ds = xarray.Dataset()
		value = np.squeeze(value)
		print(value.shape)
		ds[key] =  (( 'time','lat', 'lon'), value)
		ds['lat'] = (('lat'), dataset['lat'])
		ds['lon'] = (('lon'), dataset['lon'])
		ds['time'] = (('time'), dataset['time'])


		ds.coords['lat'] = (('lat'), dataset['lat'])
		ds.coords['lon'] = (('lon'), dataset['lon'])
		ds.coords['time'] = ds['time']
		ds.coords['reference_time'] = pd.Timestamp('2000-01-01')
		print("write netcdf "+key+" "+filename)
		ds.load().to_netcdf(filename+"_"+key+".nc",format='NETCDF3_64BIT')
		ds.close()
		os.system("bash fix_axies.sh "+filename+"_"+key+".nc")
		print("end writing netcdf")




exps = ["SP2005","NOASIA"]
exps=['NOASIA']
data = {}
data["SP2005"] = xarray.open_dataset('RENAMED_RECIA_MLO_SP2005_yearly2.nc')
data["NOASIA"] = xarray.open_dataset('RENAMED_RECIA_MLO_NOASIA_yearly2.nc')
#data["SP2005"] = xarray.open_dataset('RENAMED_RECIA_MLO_SP2005_41.nc')
#data["NOASIA"] = xarray.open_dataset('RENAMED_RECIA_MLO_NOASIA_41.nc')

data['lat'] = data["SP2005"]['lat']
data['lon'] = data["SP2005"]['lon']
data['time'] = data["SP2005"]['time']

for exp in exps:
	analysis = RY15.RY15(data[exp],data['SP2005'])
	analysis.results['lat'] = data['lat']
	analysis.results['lon'] = data['lon']
	analysis.results['time'] = data['time']

	dic2netcdf2(analysis.results,'RESULTS_NORESM_yearmean')