def test_getAverageBaseflowUnderflowPerSection(self):
if self.usepandas:
for th in range(-10, 10):
th = th + np.random.uniform(-1, 1, 1)[0]
sig_val = sig.getAverageBaseflowUnderflowPerSection(
self.simulation,
self.observation,
datetime_series=self.dd_daily,
threshold_value=th,
mode="get_signature")
sig_raw = sig.getAverageBaseflowUnderflowPerSection(
self.simulation,
self.observation,
datetime_series=self.dd_daily,
threshold_value=th,
mode="get_raw_data")
sig_dev = sig.getAverageBaseflowUnderflowPerSection(
self.simulation,
self.observation,
datetime_series=self.dd_daily,
threshold_value=th,
mode="calc_Dev")
self.assertTrue(sig_raw.dtypes[0] == "int64"
or sig_raw.dtypes[0] == "float64")
self.assertEqual(sig_raw["baseflow"].__len__(), 730)
self.assertEqual(str(type(sig_raw.index.tolist()[0])),
"<class 'pandas.tslib.Timestamp'>")
self.assertEqual(type(float(sig_dev.astype(float))), type(1.0))
self.assertEqual(type(float(sig_val.astype(float))), type(1.0))
dd_daily,
threshold_factor=5,
section="day"))
print(
sig.getAverageBaseflowDuration(simulation,
observation,
dd_daily,
threshold_factor=0.2,
section="day"))
print(
sig.getAverageBaseflowFrequencyPerSection(simulation, observation,
dd_daily, 3, "day"))
print(
sig.getAverageBaseflowUnderflowPerSection(simulation,
observation,
dd_daily,
threshold_factor=4,
section="day"))
print(
sig.getBaseflowIndex(simulation, observation,
pd.date_range("2015-05-01", periods=timespanlen)))
print(sig.getSlopeFDC(simulation, observation))
print(
sig.getLowFlowVar(simulation, observation,
pd.date_range("2015-05-01", periods=timespanlen)))
print(
sig.getHighFlowVar(simulation, observation,
pd.date_range("2015-05-01", periods=timespanlen)))