# Source code for nes.nc_projections.rotated_nested_nes

    #!/usr/bin/env python

    from numpy import linspace, float64
    from netCDF4 import Dataset
    from .rotated_nes import RotatedNes

    class RotatedNestedNes(RotatedNes):

        def __init__(self, comm=None, path=None, info=False, dataset=None, parallel_method="Y",
                     avoid_first_hours=0, avoid_last_hours=0, first_level=0, last_level=None, create_nes=False,
                     balanced=False, times=None, **kwargs):
            """
            Initialize the RotatedNestedNes class.

            Parameters
            ----------
            comm: MPI.COMM
                MPI Communicator.
            path: str
                Path to the NetCDF to initialize the object.
            info: bool
                Indicates if you want to get reading/writing info.
            dataset: Dataset or None
                NetCDF4-python Dataset to initialize the class.
            parallel_method : str
                Indicates the parallelization method that you want. Default: "Y".
                Accepted values: ["X", "Y", "T"].
            avoid_first_hours : int
                Number of hours to remove from first time steps.
            avoid_last_hours : int
                Number of hours to remove from last time steps.
            first_level : int
                Index of the first level to use.
            last_level : int, None
                Index of the last level to use. None if it is the last.
            create_nes : bool
                Indicates if you want to create the object from scratch (True) or through an existing file.
            balanced : bool
                Indicates if you want a balanced parallelization or not.
                Balanced dataset cannot be written in chunking mode.
            times : list, None
                List of times to substitute the current ones while creation.
            """

            super(RotatedNestedNes, self).__init__(comm=comm, path=path,
                                                   info=info, dataset=dataset, balanced=balanced,
                                                   parallel_method=parallel_method,
                                                   avoid_first_hours=avoid_first_hours, avoid_last_hours=avoid_last_hours,
                                                   first_level=first_level, last_level=last_level, create_nes=create_nes,
                                                   times=times, **kwargs)

        @staticmethod
        def _get_parent_attributes(projection_data):
            """
            Get projection attributes from parent grid.

            Parameters
            ----------
            projection_data : dict
                Dictionary with the projection information.

            Returns
            -------
            projection_data : dict
                Dictionary with the projection information, including parameters from the parent grid.
            """

            # Read variables from parent grid
            netcdf = Dataset(projection_data["parent_grid_path"], mode="r")
            rlat = netcdf.variables["rlat"][:]
            rlon = netcdf.variables["rlon"][:]
            rotated_pole = netcdf.variables["rotated_pole"]

            # j_parent_start starts at index 1, so we must subtract 1
            projection_data["inc_rlat"] = (rlat[1] - rlat[0]) / projection_data["parent_ratio"]
            projection_data["1st_rlat"] = rlat[int(projection_data["j_parent_start"]) - 1]

            # i_parent_start starts at index 1, so we must subtract 1
            projection_data["inc_rlon"] = (rlon[1] - rlon[0]) / projection_data["parent_ratio"]
            projection_data["1st_rlon"] = rlon[int(projection_data["i_parent_start"]) - 1]

            projection_data["grid_north_pole_longitude"] = rotated_pole.grid_north_pole_longitude
            projection_data["grid_north_pole_latitude"] = rotated_pole.grid_north_pole_latitude

            netcdf.close()

            return projection_data

        def _get_projection_data(self, create_nes, **kwargs):
            """
            Retrieves projection data based on grid details.

            Parameters
            ----------
            create_nes : bool
                Flag indicating whether to create new object (True) or use existing (False).
            **kwargs : dict
                Additional keyword arguments for specifying projection details.
            """
            if create_nes:
                projection_data = {"grid_mapping_name": "rotated_latitude_longitude",
                                   "parent_grid_path": kwargs["parent_grid_path"],
                                   "parent_ratio": kwargs["parent_ratio"],
                                   "i_parent_start": kwargs["i_parent_start"],
                                   "j_parent_start": kwargs["j_parent_start"],
                                   "n_rlat": kwargs["n_rlat"],
                                   "n_rlon": kwargs["n_rlon"]
                                   }
                projection_data = self._get_parent_attributes(projection_data)
            else:
                projection_data = super()._get_projection_data(create_nes, **kwargs)

            return projection_data

        def _create_rotated_coordinates(self):
            """
            Calculate rotated latitudes and longitudes from grid details.

            Returns
            ----------
            _rlat : dict
                Rotated latitudes dictionary with the "data" key for all the values and the rest of the attributes.
            _rlon : dict
                Rotated longitudes dictionary with the "data" key for all the values and the rest of the attributes.
            """

            # Get grid resolution
            inc_rlon = self.projection_data["inc_rlon"]
            inc_rlat = self.projection_data["inc_rlat"]

            # Get number of rotated coordinates
            n_rlat = self.projection_data["n_rlat"]
            n_rlon = self.projection_data["n_rlon"]

            # Get first coordinates
            first_rlat = self.projection_data["1st_rlat"]
            first_rlon = self.projection_data["1st_rlon"]

            # Calculate rotated latitudes
            rlat = linspace(first_rlat, first_rlat + (inc_rlat * (n_rlat - 1)), n_rlat, dtype=float64)

            # Calculate rotated longitudes
            rlon = linspace(first_rlon, first_rlon + (inc_rlon * (n_rlon - 1)), n_rlon, dtype=float64)

            return {"data": rlat}, {"data": rlon}