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()