def METHOD_NAME(self, df, common_norm):
    ori = "y"
    df = df[[ori, "alpha"]]
    gb = self.get_groupby(df, ori)
    res = KDE(cumulative=True, common_norm=common_norm)(df, gb, ori, {})
    for _, group_res in res.groupby("alpha"):
        assert (group_res["density"].diff().dropna() >= 0).all()
        if not common_norm:
            assert group_res["density"].max() == pytest.approx(1, abs=1e-3)