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"))