def METHOD_NAME(self):
    name = "dpsec"
    data = np.array([1, 2, 3, 4])
    # run the test but suppress the expected runtime warnings
    with warnings.catch_warnings():
        warnings.filterwarnings("ignore", category=RuntimeWarning)
        self.assertRaises(ValueError, self.ft.transform_feature, data, name, "add_one_inverse")
        assert_array_equal(self.ft.transform_feature(data, name, "inv"), 1 / data)
        assert_array_equal(self.ft.transform_feature(data, name, "raw"), data)
        assert_array_equal(self.ft.transform_feature(data, name, "org"), data)
        assert_array_equal(self.ft.transform_feature(data, name, "log"), np.log(data))
        assert_array_equal(self.ft.transform_feature(data, name, "addOneInv"), 1 / (data + 1))
        assert_array_equal(self.ft.transform_feature(data, name, "addOneLn"), np.log(data + 1))