#! /usr/bin/env python
"""

"""

# region // imports
import sys
import argparse
from SDToolBox import outputmessages as outputmessages
from SDToolBox import data_acquisition
import netCDF4
import numpy as np

# endregion

# region // variables

# endregion

class ExtractWavesEra5 :

    __lon_key = 'lon'
    __lat_key = 'lat'
   
    def __init__(self, input_data: data_acquisition.DataAcquisition) :
        # verify input_data not none
        self.dataset = dataset
        input_data.lat_key = __lon_key
        input_data.max_longitude = __lat_key

    def extract_wave_era_5(self, directory_path, yearFrom, yearTo) :
        variable_name_list = ["swh","pp1d","mwd","mwp"]
        variable_key_list = ["Hs","Tp","MWD","Tm"]
        years = []
        i = 1
        
        longitude = self.check_for_longitude(self.longitude)
        years = self.generate_years_array(self.year1, self.yearN)
        data_struct = {}
               
        for name_idx, variable_name in enumerate(variable_name_list) :
            for year_idx, year in enumerate(range(yearFrom, yearTo)) :
                variable_idx = 1
                file_name = "era5_Global_" + variable_key_list[variable_idx] + "_" + str(year) + ".nc"
                directory_data_path = directory_path + variable_key_list[variable_idx]
                file_data_path = directory_data_path + file_name
                
                if year_idx == 0 :
                    if variable_idx == 1 :
    
                        with netCDF4.Dataset(file_data_path, 'r') as f:
                            # result = self.data_acquisition.validate(f)
                            # if result is False :
                            #     print("Dataset {} validation failed".format(filepath))
                            #     pass 
                            data_struct.time = f.variables['time'] #time variable
                            data_struct.longitude = f.variables['longitude'] #longitude variable
                            data_struct.latitude = f.variables['latitude'] #latitude variable

                            idlon = np.min(np.abs(data_struct.longitude-__lon_key))
                            idlat = np.min(np.abs(data_struct.latitude-__lat_key))

                            data_struct.longitude = data_struct.longitude[idlon]
                            data_struct.latitude = data_struct.latitude[idlat]

                    #a_squeezed = np.squeeze(netCDF4.Dataset(file_data_path, variable_name, [idlon idlat 1], [1 1 inf] )
                else :
                    #b_squeezed = np.squeeze(netCDF4.Dataset(file_data_path, variable_name, [idlon idlat 1], [1 1 inf] )
                    #b = [b ; a]
                    if variable_idx == 1 :
                        data_struct.time = np.block(1, data_struct.time, netCDF4.Dataset(file_data_path, 'time'))
                        data_struct.time.add(netCDF4.Dataset(file_data_path, 'time'))
        #data_struct.add(variable_name, b)

    @staticmethod
    def check_for_longitude(longitude):
        if longitude > 180 :
            validated_longitude = longitude-180 
            return validated_longitude
        return longitude

    @staticmethod
    def generate_years_array(year1, yearN):
        years = []
        for i in range(yearN - year1) :
            years.append(year1 + i) # fills an array of years
        years.append(yearN)
        return years