def test_rolling_mean_returns_nan():
"""
Tests for rolling mean class.
"""
mean_buffer = reg.RollingMean(vector_size=3, buffer_size=5)
assert np.isnan(mean_buffer.getmean()).all
def test_rolling_mean_single_value():
"""
Test rolling mean returns vector value for single entry
"""
vector = [5.4, 1.2, 3.4]
mean_buffer = reg.RollingMean(vector_size=3, buffer_size=5)
mean_buffer.pop(vector)
assert np.allclose(vector, mean_buffer.getmean(), rtol=1e-05, atol=1e-10)
def test_rolling_mean_four_values():
"""
Test rolling mean returns vector value for single entry
"""
vector0 = [5.4, 1.2, 3.4]
vector1 = [7.4, -1.2, -1.4]
vector2 = [-2.6, 4.2, 2.6]
vector3 = [9.0, 3.3, 3.6]
expected_answer0 = [3.4, 1.4, 1.533333]
expected_answer1 = [4.6, 2.1, 1.6]
mean_buffer = reg.RollingMean(vector_size=3, buffer_size=3)
mean_buffer.pop(vector0)
mean_buffer.pop(vector1)
mean_buffer.pop(vector2)
assert np.allclose(expected_answer0, mean_buffer.getmean(), rtol=1e-05,
atol=1e-6)
mean_buffer.pop(vector3)
assert np.allclose(expected_answer1, mean_buffer.getmean(), rtol=1e-05,
atol=1e-10)
def test_rolling_mean_no_buffer():
"""
Try doing a rolling mean with zero buffer.
"""
with pytest.raises(ValueError):
_ = reg.RollingMean(vector_size=3, buffer_size=0)