def test_rayleigh_mean_high_noise(self):
sigma = 20
rv = rayleigh_scipy()
M_scipy = rv.mean() * sigma
# Do ours
M = rayleigh_mean(sigma)
self.assertEqual(M, M_scipy)
def test_rayleigh_mean_high_noise(self):
'''Verify mean of high noise case with scipy's statistics module.'''
sigma = 20
rv = rayleigh_scipy()
M_scipy = rv.mean() * sigma
# Do ours
M = rayleigh_mean(sigma)
self.assertEqual(M, M_scipy)
def test_rayleigh_high_noise(self):
sigma = 20
rv = rayleigh_scipy()
pM_scipy = rv.pdf(self.M)
# Expressions for dist are different in paper and scipy, correction
# factor to convert between them
pM_scipy *= np.exp(self.M**2 / 2 - self.M**2 /
(2 * sigma**2)) / (sigma**2)
# Do ours
pM = rayleigh(self.M, sigma)
self.assertTrue(np.allclose(pM, pM_scipy))
def test_rayleigh_low_noise(self):
'''Verify rayleigh low noise case against scipy's statistics module.'''
sigma = .8
rv = rayleigh_scipy()
pM_scipy = rv.pdf(self.M)
# Expressions for dist are different in paper and scipy, correction
# factor to convert between them
pM_scipy *= np.exp(self.M**2 / 2 - self.M**2 /
(2 * sigma**2)) / (sigma**2)
# Do ours
pM = rayleigh(self.M, sigma)
self.assertTrue(np.allclose(pM, pM_scipy))