def test_chunking(self): s = {key: pd.Series(np.arange(0, 100), index=date_range(0, 99)) for key in np.arange(0, 10)} for i in np.arange(1,10): tses = {key: discretize(1, i, ts=value, df=value[1], forecast_detector=lambda x: 0) for key, value in list(s.items())} chunked = chunk_series_as_sla(tses) self.assertEqual(len(chunked), 10) for chunky in list(chunked.values()): self.assertEqual(len(chunky), i)
def test_something(self): s0 = pd.Series(np.array([1, 2, 3, 2]), index=date_range(1, 4)) s1 = pd.Series(np.array([4, 3, 3, 2]), index=date_range(1, 4)) s2 = pd.Series.add(s0, s1, fill_value=0) slas = chunk_series_as_sla({"1": s0, "2": s1}) s3 = pd.Series() for sla in [item for sublist in list(slas.values()) for item in sublist]: s3 = pd.Series.add(s3, sla, fill_value=0) for i in s0.index: self.assertEqual(s2[i], s3[i])
def test_something(self): s0 = pd.Series(np.array([1, 2, 3, 2]), index=date_range(1, 4)) s1 = pd.Series(np.array([4, 3, 3, 2]), index=date_range(1, 4)) s2 = pd.Series.add(s0, s1, fill_value=0) slas = chunk_series_as_sla({"1": s0, "2": s1}) s3 = pd.Series() for sla in [ item for sublist in list(slas.values()) for item in sublist ]: s3 = pd.Series.add(s3, sla, fill_value=0) for i in s0.index: self.assertEqual(s2[i], s3[i])
def test_chunking(self): s = { key: pd.Series(np.arange(0, 100), index=date_range(0, 99)) for key in np.arange(0, 10) } for i in np.arange(1, 10): tses = { key: discretize(1, i, ts=value, df=value[1], forecast_detector=lambda x: 0) for key, value in list(s.items()) } chunked = chunk_series_as_sla(tses) self.assertEqual(len(chunked), 10) for chunky in list(chunked.values()): self.assertEqual(len(chunky), i)