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Commit 391522b4 authored by Peter Lünenschloß's avatar Peter Lünenschloß
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harm - aggregations test actualized

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3 merge requests!193Release 1.4,!188Release 1.4,!49Dataprocessing features
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test/funcs/test_harm_funcs.py
+ 39
− 24
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......@@ -128,38 +128,53 @@ def test_harmSingleVarInterpolations(data, flagger):
field = data.columns[0]
tests = [
("fshift", "15Min", [np.nan, -37.5, -25.0, 0.0, 37.5, 50.0]),
("fshift", "30Min", [np.nan, -37.5, 0.0, 50.0]),
("bshift", "15Min", [-50.0, -37.5, -25.0, 12.5, 37.5, 50.0]),
("bshift", "30Min", [-50.0, -37.5, 12.5, 50.0]),
#("nshift", "15min", [np.nan, -37.5, -25.0, 12.5, 37.5, 50.0]),
#("nshift", "30min", [np.nan, -37.5, 12.5, 50.0]),
#("nagg", "15Min", [-87.5, -25.0, 0.0, 37.5, 50.0]),
#("nagg", "30Min", [-87.5, -25.0, 87.5]),
("bagg", "15Min", [-50.0, -37.5, -37.5, 12.5, 37.5, 50.0]),
("bagg", "30Min", [-50.0, -75.0, 50.0, 50.0]),
("nagg", "15Min", pd.Series(data=[-87.5, -25.0, 0.0, 37.5, 50.0],
index=pd.date_range('2011-01-01 00:00:00',
'2011-01-01 01:00:00',
freq='15min'))),
("nagg", "30Min", pd.Series(data=[-87.5, -25.0, 87.5],
index=pd.date_range('2011-01-01 00:00:00',
'2011-01-01 01:00:00',
freq='30min'))),
("bagg", "15Min", pd.Series(data=[-50.0, -37.5, -37.5, 12.5, 37.5, 50.0],
index=pd.date_range('2010-12-31 23:45:00',
'2011-01-01 01:00:00',
freq='15min'))),
("bagg", "30Min", pd.Series(data=[-50.0, -75.0, 50.0, 50.0],
index=pd.date_range('2010-12-31 23:30:00',
'2011-01-01 01:00:00',
freq='30min'))),
]
for interpolation, freq, expected in tests:
data_harm, _ = harm_harmonize(
data, "data", flagger, freq, interpolation, "fshift", reshape_shift_comment=False, inter_agg="sum",
)
harm_start = data[field].index[0].floor(freq=freq)
harm_end = data[field].index[-1].ceil(freq=freq)
test_index = pd.date_range(start=harm_start, end=harm_end, freq=freq)
expected = pd.Series(expected, index=test_index)
data_harm, _ = harm_aggregate2Grid(data, field, flagger, freq, value_func=np.sum, method=interpolation)
assert data_harm[field].equals(expected)
data_deharm, flagger_deharm = harm_deharmonize(data, "data", flagger, co_flagging=True)
#tests = [
# ("fshift", "15Min", [np.nan, -37.5, -25.0, 0.0, 37.5, 50.0]),
# ("fshift", "30Min", [np.nan, -37.5, 0.0, 50.0]),
# ("bshift", "15Min", [-50.0, -37.5, -25.0, 12.5, 37.5, 50.0]),
# ("bshift", "30Min", [-50.0, -37.5, 12.5, 50.0]),
# ("nshift", "15min", [np.nan, -37.5, -25.0, 12.5, 37.5, 50.0]),
# ("nshift", "30min", [np.nan, -37.5, 12.5, 50.0])]
#for interpolation, freq, expected in tests:
# data_harm, _ = harm_aggregate2Grid(data, field, flagger, freq, value_func=np.sum, method=interpolation)
# harm_start = data[field].index[0].floor(freq=freq)
# harm_end = data[field].index[-1].ceil(freq=freq)
# test_index = pd.date_range(start=harm_start, end=harm_end, freq=freq)
# expected = pd.Series(expected, index=test_index)
# assert data_harm[field].equals(expected)
flags = flagger.getFlags()
flags_deharm = flagger_deharm.getFlags()
#data_deharm, flagger_deharm = harm_deharmonize(data, "data", flagger, co_flagging=True)
#flags = flagger.getFlags()
#flags_deharm = flagger_deharm.getFlags()
assert data[field].equals(data[field])
assert len(data_deharm[field]) == len(flags[field])
assert (flags[field].index == flags_deharm[field].index).all()
#assert data[field].equals(data[field])
#assert len(data_deharm[field]) == len(flags[field])
#assert (flags[field].index == flags_deharm[field].index).all()
@pytest.mark.parametrize("method", INTERPOLATIONS2)
......
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