def test_lnprob(self):
t = np.arange(0, 1, 0.01)
S = np.random.random(t.size)
theta = self.random_theta(4, 3)
kursl = KurSL(theta)
model = ModelWrapper(kursl)
self.assertTrue(
KurslMCMC.lnprob(theta, t, S[:-1], model) < 0,
"Any good theta should return negative value")
def test_lnprob_theta_outside_range(self):
t = np.arange(0, 1, 0.01)
S = np.random.random(t.size)
theta = self.random_theta(4, 3)
kursl = KurSL(theta)
model = ModelWrapper(kursl)
theta[0, 0] = model.MIN_W - 1
self.assertEqual(KurslMCMC.lnprob(theta, t, S[:-1], model), -np.inf,
"Inherit behaviour of lnprob and lnlikelihood")