def structure_from_ncdata(ncdata, site_properties=None, cls=Structure):
    """
    Reads and returns a pymatgen structure from a NetCDF file
    containing crystallographic data in the ETSF-IO format.

    Args:
        ncdata: filename or NetcdfReader instance.
        site_properties: Dictionary with site properties.
        cls: The Structure class to instanciate.
    """
    ncdata, closeit = as_ncreader(ncdata)

    # TODO check whether atomic units are used
    lattice = ArrayWithUnit(ncdata.read_value("primitive_vectors"), "bohr").to("ang")

    red_coords = ncdata.read_value("reduced_atom_positions")
    natom = len(red_coords)

    znucl_type = ncdata.read_value("atomic_numbers")

    # type_atom[0:natom] --> index Between 1 and number of atom species
    type_atom = ncdata.read_value("atom_species")

    # Fortran to C index and float --> int conversion.
    species = natom * [None]
    for atom in range(natom):
        type_idx = type_atom[atom] - 1
        species[atom] = int(znucl_type[type_idx])

    d = {}
    if site_properties is not None:
        for prop in site_properties:
            d[property] = ncdata.read_value(prop)

    structure = cls(lattice, species, red_coords, site_properties=d)

    # Quick and dirty hack.
    # I need an abipy structure since I need to_abivars and other methods.
    try:
        from abipy.core.structure import Structure as AbipyStructure
        structure.__class__ = AbipyStructure
    except ImportError:
        pass

    if closeit:
        ncdata.close()

    return structure
Reads and returns a pymatgen structure from a NetCDF file
    containing crystallographic data in the ETSF-IO format.

    Args:
        ncdata: filename or NetcdfReader instance.
        site_properties: Dictionary with site properties.
        cls: The Structure class to instanciate.