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)
