def test_log_2d_radial_symmetry(self):
mu_angle = np.random.uniform(0, RIGHT_ANGLE)
mu = angle_to_vector(mu_angle)
kappa = 0.5
max_angle = min(acos(mu[0]), RIGHT_ANGLE - acos(mu[0]))
angle_perturb = np.random.uniform(0, max_angle)
angle_1 = max_angle + angle_perturb
angle_2 = max_angle - angle_perturb
x1 = np.array([cos(angle_1), sin(angle_1)])
x2 = np.array([cos(angle_2), sin(angle_2)])
print(mu_angle, max_angle, angle_perturb, angle_1, angle_2)
self.assertAlmostEqual(vmf_log_pdf(x1, mu, kappa), vmf_log_pdf(x2, mu, kappa), delta=0.1) # There can be a high delta here due to numerical error
def test_log_2d_radial_symmetry(self):
mu_angle = np.random.uniform(0, RIGHT_ANGLE)
mu = angle_to_vector(mu_angle)
kappa = 0.5
max_angle = min(acos(mu[0]), RIGHT_ANGLE - acos(mu[0]))
angle_perturb = np.random.uniform(0, max_angle)
angle_1 = max_angle + angle_perturb
angle_2 = max_angle - angle_perturb
x1 = np.array([cos(angle_1), sin(angle_1)])
x2 = np.array([cos(angle_2), sin(angle_2)])
print(mu_angle, max_angle, angle_perturb, angle_1, angle_2)
self.assertAlmostEqual(
vmf_log_pdf(x1, mu, kappa), vmf_log_pdf(x2, mu, kappa),
delta=0.1) # There can be a high delta here due to numerical error
def test_3d_log_radial_symmetry(self):
kappa = 0.5
mu = np.array([1, 0, 0])
x1 = np.array([0, 1, 0])
x2 = np.array([0, 0, 1])
self.assertAlmostEqual(vmf_log_pdf(x1, mu, kappa), vmf_log_pdf(x2, mu, kappa), delta=0.01)
self.assertAlmostEqual(vmf_log_pdf(-x1, mu, kappa), vmf_log_pdf(-x2, mu, kappa), delta=0.01)
self.assertAlmostEqual(vmf_log_pdf(-x1, mu, kappa), vmf_log_pdf(x2, mu, kappa), delta=0.01)
def test_3d_log_radial_symmetry(self):
kappa = 0.5
mu = np.array([1, 0, 0])
x1 = np.array([0, 1, 0])
x2 = np.array([0, 0, 1])
self.assertAlmostEqual(vmf_log_pdf(x1, mu, kappa),
vmf_log_pdf(x2, mu, kappa),
delta=0.01)
self.assertAlmostEqual(vmf_log_pdf(-x1, mu, kappa),
vmf_log_pdf(-x2, mu, kappa),
delta=0.01)
self.assertAlmostEqual(vmf_log_pdf(-x1, mu, kappa),
vmf_log_pdf(x2, mu, kappa),
delta=0.01)
