def test_vmf_rvs():
mu, kappa = random_pars()
n_pts = int(1e4)
tolerance = 0.1
#... acceptable angular deviation between set mean and sample mean
P_i = vmf_rvs(mu, kappa, n_pts)
sample_mean = mean_dir(P_i)
angle_between = np.arccos(np.dot(mu, sample_mean))
assert(angle_between < tolerance)
def test_estimate_kappa():
mus = [[0., 0., 1.],[0., 1., 0.], [1., 0., 0.]]
kappas = [1.,]
for mu, kappa in zip(mus, kappas):
n_pts = int(1e4)
tolerance = 0.1
# acceptable deviation between set kappa (hopefully),
# and estimated kappa.
# Could really do with a way to define a
# set of points with an established kappa.
P_i = vmf_rvs(mu, kappa, n_pts)
khat = estimate_kappa(P_i, mu=mu)
diff = np.abs(khat - kappa)
assert(diff < tolerance)
