def test_circ_mean(self):
"""Test function circ_mean."""
x = [0.785, 1.570, 3.141, 0.839, 5.934]
mu = circ_mean(x)
# Compare with the CircStats MATLAB toolbox
assert np.round(mu, 3) == 1.013
# Wrong argument
with pytest.raises(ValueError):
circ_mean(x, w=[0.1, 0.2, 0.3])
def test_circ_mean(self):
"""Test function circ_mean."""
x = [0.785, 1.570, 3.141, 0.839, 5.934]
x_nan = np.array([0.785, 1.570, 3.141, 0.839, 5.934, np.nan])
# Compare with the CircStats MATLAB toolbox
assert np.round(circ_mean(x), 3) == 1.013
assert np.round(circ_mean(x_nan), 3) == 1.013
# Binned data
np.random.seed(123)
nbins = 18 # Number of bins to divide the unit circle
angles_bins = np.linspace(-np.pi, np.pi, nbins)
# w represents the number of incidences per bins, or "weights".
w = np.random.randint(low=0, high=5, size=angles_bins.size)
assert round(circ_mean(angles_bins, w), 4) == -2.5355
def assert_circmean(x, low, high, axis=-1):
m1 = convert_angles(
circmean(x, low=low, high=high, axis=axis, nan_policy='omit'),
low, high)
m2 = circ_mean(convert_angles(x, low, high), axis=axis)
assert (np.round(m1, 4) == np.round(m2, 4)).all()
def test_circ_mean(self):
"""Test function circ_mean."""
x = [0.785, 1.570, 3.141, 0.839, 5.934]
mu = circ_mean(x)
# Compare with the CircStats MATLAB toolbox
assert np.round(mu, 3) == 1.013