def test_rolling_mean(self):
stream = np.asarray([1, 2, 3, 4, 5])
expected = np.asarray([1, 1.5, 2.5, 3.5, 4.5])
rv = rolling_mean(stream, 2)
assert (rv == expected).all()
def test_rolling_mean_with_mask(self):
stream = np.asarray([1, 2, 3, 4, 5])
mask = np.asarray([True, True, False, True, True], dtype=bool)
expected = np.asarray([1, 1.5, 1.0, 2.0, 4.5])
rv = rolling_mean(stream, window=2, mask=mask)
assert (rv == expected).all()
def test_rolling_mean_real_data(self, test_stream):
rv = rolling_mean(test_stream['watts'],
mask=test_stream['moving'],
window=1)
assert type(rv) == list
assert rv == test_stream['watts']
def test_rolling_mean_list_emwa(self):
stream = list(np.ones(30))
expected = list(np.ones(30))
rv = rolling_mean(stream, 2, type='ewma')
assert type(rv) == list
assert rv == expected
def test_rolling_mean_list(self):
stream = [1, 2, 3, 4, 5]
expected = [1, 1.5, 2.5, 3.5, 4.5]
rv = rolling_mean(stream, 2)
assert type(rv) == list
assert rv == expected
def test_rolling_mean_list_with_mask(self):
stream = [1, 2, 3, 4, 5]
mask = [True, True, False, True, True]
expected = [1, 1.5, 1.0, 2.0, 4.5]
rv = rolling_mean(stream, window=2, mask=mask)
assert type(rv) == list
assert rv == expected
def test_rolling_mean_list_emwa(self):
stream = np.ones(30)
expected = np.ones(30)
rv = rolling_mean(stream, 2, algorithm="ewma")
assert (rv == expected).all()
def test_rolling_mean_real_data(self, test_stream):
rv = rolling_mean(np.asarray(test_stream['watts']),
mask=test_stream['moving'],
window=1)
assert (rv == test_stream['watts']).all()
