def test_invalid_mean_with_no_entry_sized_timeseries(self):
""" Sized Timeseries should throw when calling mean and len == 0. """
for i, ts_class in SIZED_CONCRETE_CLASSES:
ts = TimeSeries([], [])
with self.assertRaises(Exception):
ts.mean()
scores.append(('#ts', '%s throws on mean() when len == 0' % i, 1))
def test_valid_mean_with_two_entry_sized_timeseries(self):
""" Sized Timeseries should return mean when len > 1. """
for i, ts_class in SIZED_CONCRETE_CLASSES:
tsa = TimeSeries([1, 2], [1, 2])
tsb = TimeSeries([1, 2, 3, 4], [1, 2, 3, 4])
self.assertEqual(tsa.mean(), 1.5)
self.assertEqual(tsb.mean(), np.array([1, 2, 3, 4]).mean())
scores.append(('#ts', '%s valid mean when len > 1' % i, 1))
def test_mean():
ten = TimeSeries(range(0,11), range(0,11))
assert ten.mean() == 5
def test_valid_mean_with_one_entry_sized_timeseries(self):
""" Sized Timeseries should return mean equal to the value if len == 1. """
for i, ts_class in SIZED_CONCRETE_CLASSES:
ts = TimeSeries([1], [-10])
self.assertEqual(ts.mean(), -10)
scores.append(('#ts', '%s valid mean when len == 1' % i, 1))
def test_mean():
ts = TimeSeries([1, 2, 3])
assert ts.mean() == np.mean([1, 2, 3])
def test_mean():
ts = TimeSeries([1, 2], [3, 4])
assert ts.mean() == 1.5
def test_mean():
ten = TimeSeries(range(0, 11), range(0, 11))
assert ten.mean() == 5
