diff --git a/tests/funcs/test_harm_funcs.py b/tests/funcs/test_harm_funcs.py
index 7cc99a7cf2765691a54a23b5173bf7ba3ad5a4a9..e09177a01c7c8ee83c1eae8fba5aaba7737d106f 100644
--- a/tests/funcs/test_harm_funcs.py
+++ b/tests/funcs/test_harm_funcs.py
@@ -83,7 +83,7 @@ def test_gridInterpolation(data, method):
     ('interpolate', dict(method="spline")),
     ('aggregate', dict(value_func=np.nansum, method="nagg")),
 ])
-def test_flagsSurviveReshaping(reshaper):
+def test_flagsSurviveReshaping(func, kws):
     """
     flagging -> reshaping -> test (flags also was reshaped correctly)
     """
@@ -112,6 +112,8 @@ def test_harmSingleVarIntermediateFlagging(data, reshaper):
     pre_flagger = flagger.copy()
 
     data, flagger = linear(data, field, flagger, freq="15min")
+    checkDataFlaggerInvariants(data, flagger, field, identical=True)
+    assert data[field].index.freq == pd.Timedelta('15min')
 
     # flag something bad
     flagger[data[field].index[3:4], field] = BAD
@@ -172,9 +174,12 @@ def test_harmSingleVarInterpolationAgg(data, params, expected):
     method, freq = params
 
     data_harm, flagger_harm = aggregate(data, field, flagger, freq, value_func=np.sum, method=method)
+    checkDataFlaggerInvariants(data_harm, flagger_harm, field, identical=True)
+    assert data_harm[field].index.freq == pd.Timedelta(freq)
     assert data_harm[field].equals(expected)
 
     data_deharm, flagger_deharm = mapToOriginal(data_harm, "data", flagger_harm, method="inverse_" + method)
+    checkDataFlaggerInvariants(data_harm, flagger_harm, field, identical=True)
     assert data_deharm[field].equals(pre_data[field])
     assert flagger_deharm[field].equals(pre_flaggger[field])