docs: def _combine_nd(combined_ids, concat_dims, data_vars='all',
                  coords='different', compat='no_conflicts'):
      """
      Concatenates and merges an N-dimensional structure of datasets.
  
      No checks are performed on the consistency of the datasets, concat_dims or
      tile_IDs, because it is assumed that this has already been done.
  
      Parameters
      ----------
      combined_ids : Dict[Tuple[int, ...]], xarray.Dataset]
          Structure containing all datasets to be concatenated with "tile_IDs" as
          keys, which specify position within the desired final combined result.
      concat_dims : sequence of str
          The dimensions along which the datasets should be concatenated. Must be
          in order, and the length must match
  
      Returns
      -------
      combined_ds : xarray.Dataset
      """
  
      # Perform N-D dimensional concatenation
      # Each iteration of this loop reduces the length of the tile_ids tuples
      # by one. It always combines along the first dimension, removing the first
      # element of the tuple
      for concat_dim in concat_dims:
          combined_ids = _auto_combine_all_along_first_dim(combined_ids,
                                                           dim=concat_dim,
                                                           data_vars=data_vars,
                                                           coords=coords,
                                                           compat=compat)
      combined_ds = list(combined_ids.values())[0]
      return combined_ds