def test_getAverageFloodOverflowPerSection(self):
if self.usepandas:
for th in range(-10, 10):
sig_val = sig.getAverageFloodOverflowPerSection(
self.simulation,
self.observation,
mode="get_signature",
datetime_series=self.dd_daily,
threshold_value=th)
sig_raw = sig.getAverageFloodOverflowPerSection(
self.simulation,
self.observation,
mode="get_raw_data",
datetime_series=self.dd_daily,
threshold_value=th)
sig_dev = sig.getAverageFloodOverflowPerSection(
self.simulation,
self.observation,
mode="calc_Dev",
datetime_series=self.dd_daily,
threshold_value=th)
self.assertEqual(type(float(sig_val.astype(float))), type(1.0))
self.assertEqual(sig_raw.dtypes[0], "float64")
self.assertEqual(sig_raw["flood"].__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))
observation = spot_setup.evaluation()
timespanlen = simulation.__len__()
ddd = pd.date_range("2015-01-01 11:00", freq="5min", periods=timespanlen)
dd_daily = pd.date_range("2015-05-01", periods=timespanlen)
print(sig.getMedianFlow(simulation, observation))
print(
sig.getFloodFrequency(simulation, observation,
pd.date_range("2015-05-01", periods=timespanlen), 3,
"day"))
sig.__calcFloodDuration(simulation, ddd, 3, "year", "drought")
print(
sig.getAverageFloodOverflowPerSection(simulation,
observation,
dd_daily,
threshold_factor=1,
section="day"))
print(
sig.getAverageFloodDuration(simulation,
observation,
dd_daily,
threshold_factor=3,
section="day"))
print(
sig.getAverageBaseflowDuration(simulation,
observation,
dd_daily,
threshold_factor=5,
section="day"))