def METHOD_NAME(self):
    # standard unk file
    assert self.unk_std.ik == 1
    assert self.unk_std.nbnd == 10
    assert self.unk_std.ng[0] == 5
    assert self.unk_std.ng[1] == 5
    assert self.unk_std.ng[2] == 5
    assert_allclose(self.unk_std.data.shape, (10, 5, 5, 5))
    assert_allclose(self.unk_std.data, self.data_std)
    assert not self.unk_std.is_noncollinear
    # too small data
    data_bad_shape = np.random.rand(2, 2, 2).astype(np.complex128)
    with pytest.raises(
        ValueError,
        match=r"invalid data shape, must be \(nbnd, ngx, ngy, ngz\) or \(nbnd, 2, ngx, ngy, ngz\) "
        r"for noncollinear data, given \(2, 2, 2\)",
    ):
        Unk(1, data_bad_shape)
    # too big data
    data_bad_shape = np.random.rand(2, 2, 2, 2, 2, 2).astype(np.complex128)
    with pytest.raises(
        ValueError,
        match=r"invalid data shape, must be \(nbnd, ngx, ngy, ngz\) or \(nbnd, 2, ngx, ngy, ngz\) for noncollinear",
    ):
        Unk(1, data_bad_shape)
    # noncollinear unk file
    assert self.unk_ncl.ik == 1
    assert self.unk_ncl.nbnd == 10
    assert self.unk_ncl.ng[0] == 5
    assert self.unk_ncl.ng[1] == 5
    assert self.unk_ncl.ng[2] == 5
    assert_allclose(self.unk_ncl.data.shape, (10, 2, 5, 5, 5))
    assert_allclose(self.unk_ncl.data, self.data_ncl)
    assert self.unk_ncl.is_noncollinear
    # too big data
    data_bad_ncl = np.random.rand(2, 3, 2, 2, 2).astype(np.complex128)
    with pytest.raises(
        ValueError,
        match=r"invalid noncollinear data, shape should be \(nbnd, 2, ngx, ngy, ngz\), given \(2, 3, 2, 2, 2\)",
    ):
        Unk(1, data_bad_ncl)