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")