def check_sample(sigmasq_states, sigmasq_obs, mu_init, sigmasq_init, data): rngstate = np.random.get_state() dense_ll, dense_sample = dense_sample_states( sigmasq_states, sigmasq_obs, mu_init, sigmasq_init, data) np.random.set_state(rngstate) rw_ll, rw_sample = filter_and_sample_randomwalk( mu_init, sigmasq_init, sigmasq_states, sigmasq_obs, data) assert np.isclose(dense_ll, rw_ll) assert np.allclose(dense_sample, rw_sample)
def resample_psi(self): mu_init, sigma_init, sigma_states, sigma_obs, y = \ self._get_lds_effective_params() _, psi_flat = filter_and_sample_randomwalk(mu_init, sigma_init, sigma_states, sigma_obs, y) self.psi = psi_flat.reshape(self.psi.shape)
def resample_psi(self): mu_init, sigma_init, sigma_states, sigma_obs, y = self._get_lds_effective_params() _, psi_flat = filter_and_sample_randomwalk(mu_init, sigma_init, sigma_states, sigma_obs, y) self.psi = psi_flat.reshape(self.psi.shape)