def METHOD_NAME(self, df, common_norm):
    ori = "y"
    df = df[[ori, "alpha"]]
    gb = self.get_groupby(df, ori)
    res = KDE(common_norm=common_norm)(df, gb, ori, {})
    areas = (
        res.groupby("alpha")
        .apply(lambda x: self.integrate(x["density"], x[ori]))
    )
    if common_norm:
        assert areas.sum() == pytest.approx(1, abs=1e-3)
    else:
        assert_array_almost_equal(areas, [1, 1], decimal=3)