def test_full_sigma_numpy(self):
s = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
simulator = GaussianMeanSimulator(self.D, s=s)
true_sigma = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]], dtype=float)
self.assertTrue(np.array_equal(true_sigma, simulator.sigma))
sim_data = simulator(self.theta, self.n_obs)
self.assertTrue((sim_data.shape == self.n_sim, self.n_obs, self.D))
def test_isotropic_sigma(self):
s = 2.5
simulator = GaussianMeanSimulator(self.D, s=s)
true_sigma = np.eye(self.D) * s
self.assertTrue(np.array_equal(true_sigma, simulator.sigma))
sim_data = simulator(self.theta, self.n_obs)
self.assertTrue((sim_data.shape == self.n_sim, self.n_obs, self.D))
def test_diagonal_sigma_list_float(self):
s = [1.0, 2.0, 3.0]
simulator = GaussianMeanSimulator(self.D, s=s)
true_sigma = np.array([[1, 0, 0], [0, 2, 0], [0, 0, 3]], dtype=float)
self.assertTrue(np.array_equal(true_sigma, simulator.sigma))
sim_data = simulator(self.theta, self.n_obs)
self.assertTrue((sim_data.shape == self.n_sim, self.n_obs, self.D))
def test_unit_sigma(self):
simulator = GaussianMeanSimulator(self.D)
true_sigma = np.eye(self.D)
self.assertTrue(np.array_equal(true_sigma, simulator.sigma))
sim_data = simulator(self.theta, self.n_obs)
self.assertTrue((sim_data.shape == self.n_sim, self.n_obs, self.D))