def test_both_directions_e_value_threshold_med_max(self):
results = detect_ts(
self.raw_data,
max_anoms=0.02,
direction='both',
threshold="med_max",
e_value=True)
eq_(len(results['anoms'].columns), 3)
eq_(len(results['anoms'].iloc[:, 1]), 4)
def test_both_directions_with_plot(self):
results = detect_ts(
self.raw_data,
max_anoms=0.02,
direction='both',
only_last='day',
plot=False)
eq_(len(results['anoms'].columns), 2)
eq_(len(results['anoms'].iloc[:, 1]), 21)
def test_both_directions_e_value_longterm(self):
results = detect_ts(
self.raw_data,
max_anoms=0.02,
direction='both',
longterm=True,
plot=False,
e_value=True)
eq_(len(results['anoms'].columns), 3)
eq_(len(results['anoms'].iloc[:, 1]), 114)
def test_handling_of_leading_trailing_nas(self):
for i in list(range(10)) + [len(self.raw_data) - 1]:
self.raw_data.set_value(i, 'count', np.nan)
results = detect_ts(self.raw_data,
max_anoms=0.02,
direction='both',
plot=False)
eq_(len(results['anoms'].columns), 2)
eq_(len(results['anoms'].iloc[:, 1]), 114)
def test_check_midnight_date_format(self):
data = pd.read_csv(os.path.join(self.path,
'midnight_test_data.csv'),
usecols=['date', 'value'])
data.date = date_format(data.date, "%Y-%m-%d %H:%M:%S")
results = detect_ts(data, max_anoms=0.2, threshold=None,
direction='both', plot=False,
only_last="day",
e_value=True)
eq_(len(results['anoms'].anoms), len(results['anoms'].expected_value))
def test_handling_of_middle_nas(self):
self.raw_data.set_value(len(self.raw_data) / 2, 'count', np.nan)
detect_ts(self.raw_data, max_anoms=0.02, direction='both')