import warnings

warnings.simplefilter("ignore")

import os

import pyart

import matplotlib.pyplot

import matplotlib as mpl

import numpy as np

import gzip

import shutil

import xarray as xr

from funcs import read_casa_netcdf

import json

import pandas as pd

# import gyzip

#import gridded netcdf data from a file

grid_file = 'xmdl_grid.nc'

#read netcdf data

grid = pyart.io.grid_io.read_grid('xmdl_grid.nc')

#open dataset within gridded file

dataset = xr.open_dataset(grid_file)

#set the list of all the variables in the dataset to another variable

variables = list(dataset.variables)

#get the longitude, latitude and horizontal reflectivity of the data into variables

lats = grid.point_latitude['data']

lons = grid.point_longitude['data']

zh = grid.fields['Reflectivity']['data']

# time = grid.variables['units']

#create empty arrays for holding the latitude, longitude, reflectivity and timestamp data

latitude = []

longitude = []

reflectivity = []

times = []

# print(variables)

# print(grid.origin_longitude['data'][0])

#Create an array with all of the data in a stacked format compatible with converting to JSON

latLonRefArray = np.stack([lats.ravel(), lons.ravel(), zh.ravel()], axis = 1)

# arrangedArray = pd.DataFrame(latLonRefArray, columns=['latitude', 'longitude', 'zh'])

# arrangedArray= arrangedArray.dropna()

# print(latLonRefArray)

# print(lats)

# print(lons)

# f = open("jsonVersionTest.json", "w+")

#create an object of all of the data and save it to a variable called results

results = {"outputData": latLonRefArray.tolist()}

#format the data with indentation

json_string = json.dumps(results, indent=2)

#encode the json string into utf-8 format

json_bytes = json_string.encode('utf-8')

# json_string = json.dumps(results, indent=2)

# f.write(json_string)

# with gzip.open("outputTest.json", 'w+') as fout:

# # json_string = json.dumps(results, indent=2)

# fout.write(json_string)

#write the resulting JSON to a zipped file

with gzip.GzipFile("nextTest.json.gz", 'w') as fout:

fout.write(json_bytes)

# arrangedArray.to_json('pandasFileTest.json', index=False, orient='table', double_precision=6)