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

"""

# region // imports
import sys
import os

from SDToolBox import outputmessages as outputmessages
from SDToolBox import data_acquisition
from netCDF4 import Dataset
import numpy as np

# endregion

# region // variables

# endregion


class ExtractSeaLevelPressureERA5:

    __lon_key = 'longitude'
    __lat_key = 'latitude'
    __input_lon = None
    __input_lat = None
    __area_longitude = None
    __area_latitude = None
    __input_data = None

    def __init__(self, input_data: data_acquisition.InputData, area_longitude, area_latitude) :
        """Initialize the waves extraction.
        
        Arguments:
            input_data {data_acquisition.InputData} -- Required.
        """
        # verify input_data not none
        if not input_data or \
            not input_data.coord_list or \
                len(input_data.coord_list) < 1:
            raise IOError('No valid input data.')

        input_data.lon_key = self.__lon_key
        input_data.lat_key = self.__lat_key
        self.__input_data = input_data
        self.__input_lon, self.__input_lat = input_data.coord_list[0]
        self.__area_longitude = area_longitude
        self.__area_latitude = area_latitude

    def subset_slp_era5(self, area_latitude, area_longitude, year_from, year_to, pathSLP, resR, resT, redR, redT) :
        """Extracts a collection of netCDF4 subsets based on the input data
        set when creating the extract_sea_level_pressure object.

        Arguments:
            directory_path {str} -- Location of all the variable diretories.
            area_latitude {list} -- List with x,y coordinate for the latitude
            area_longitude {list} -- List with x,y coordinate for the longitude
            year_from {int} -- Start of time data to substract.
            year_to {int} -- End of time data to substract.

            TODO other parameters to be determined (probably floats as they are probably steps)

        Returns:
            list(Dataset) -- collection of netCDF4 subsets per variable.
        """    
        with Dataset(pathSLP, 'r', format='netCDF4') as case_dataset:

            filename = pathSLP + 'era5_Global_msl_p_1979.nc'
            latitude_ERA  = case_dataset.variables[self.__lat_key][:]
            longitude_ERA = case_dataset.variables[self.__lon_key][:]

            position_longitude1 = find_indices_that_meet_condition(longitude_ERA, lambda longitude_ERA, area_longitude: longitude_ERA == area_longitude[0])
            position_longitude2 = find_indices_that_meet_condition(longitude_ERA, lambda longitude_ERA, area_longitude : longitude_ERA == area_longitude[1])
            position_latitude1 = find_indices_that_meet_condition(latitude_ERA, lambda latitude_ERA, area_latitude: latitude_ERA == area_latitude[0])
            position_latitude2 = find_indices_that_meet_condition(latitude_ERA, lambda latitude_ERA, area_latitude: latitude_ERA == area_latitude[1])

            latitude_in_selected_area = np.arange(position_latitude1, position_latitude2).tolist()
            longitude_in_selected_area = np.arange(position_longitude1, position_longitude2).tolist()

            latitude_ERA.clear()
            longitude_ERA.clear()

            [x, y] = np.meshgrid(longitude_in_selected_area, latitude_in_selected_area)

            longitude_in_selected_area.clear()
            latitude_in_selected_area.clear()

            X = []
            Y = []

            for element in range(len(x)) :
                X.append(element)

            for element in range(len(y)) :
                Y.append(element)

            x.clear()
            y.clear()

    def extract_slp_data(self, year_from, year_to, position_longitude1, position_latitude1, position_longitude2, position_latitude2):
        years = generate_years_array(year_from, year_to)

        #extracts for all the years
        for year_idx, year in range(len(years)):
            base_file_name = 'era5_Global_msl_p_{}.nc'.format(year)
            #with Dataset(base_file_name, 'r', format='netCDF4') as case_dataset:
                #position = case_dataset.variables['msl'][[position_longitude1, position_latitude1, 1]  # don't really get the following parameter to ncread in the matlab script [((position_longitude2-position_longitude1)+1), ((position_latitude2-position_latitude1)+1), ~]
        
    def find_indices_that_meet_condition(self, input_list, condition):
        '''
        find all the indices in a list that meet the condition (similar to matlab find())
        '''
        return [index for (index, val) in enumerate(input_list) if condition(val)]

# this method could be moved in a generic utils stript outside here
    @staticmethod
    def generate_years_array(year_from, year_to):
        years = []
        for i in range(year_to - year_from):
            years.append(year_from + i) # fills an array of years
        years.append(year_to)
        return years