def testMeanStep(self):
prev_mean = np.asarray([[-2], [.4]], dtype=np.float32)
prev_mean_tensor = self.build_tensor(prev_mean)
mean_step = build_kalman_mean_step(
self.get_transition_matrix_for_timestep,
self.get_transition_noise_for_timestep,
self.get_observation_matrix_for_timestep,
self.get_observation_noise_for_timestep)
new_mean, obs_mean = mean_step((prev_mean_tensor, None), t=0)
self.assertAllClose(self.evaluate(new_mean),
np.dot(self.transition_matrix,
prev_mean) + self.bias[:, np.newaxis])
self.assertAllClose(self.evaluate(obs_mean),
np.sum(self.evaluate(new_mean)) +
self.observation_bias[:, np.newaxis])
def testMeanStep(self):
prev_mean = np.asarray([[-2], [.4]], dtype=np.float32)
prev_mean_tensor = self.build_tensor(prev_mean)
mean_step = build_kalman_mean_step(
self.get_transition_matrix_for_timestep,
self.get_transition_noise_for_timestep,
self.get_observation_matrix_for_timestep,
self.get_observation_noise_for_timestep)
new_mean, obs_mean = self.evaluate(mean_step((prev_mean_tensor, None), t=0))
self.assertAllClose(new_mean,
np.dot(self.transition_matrix, prev_mean) +
self.bias[:, np.newaxis])
self.assertAllClose(obs_mean,
np.dot(self.observation_matrix, new_mean) +
self.observation_bias[:, np.newaxis])
