def test_lds(T=1000, D=1, N=10, U=3):
args = make_lds_parameters(T, D, N, U)
# Test the standard Kalman filter
from pylds.lds_messages_interface import kalman_filter as kalman_filter_ref
ll1, filtered_mus1, filtered_Sigmas1 = kalman_filter_ref(*args)
ll2, filtered_mus2, filtered_Sigmas2 = kalman_filter(*args)
assert np.allclose(ll1, ll2)
assert np.allclose(filtered_mus1, filtered_mus2)
assert np.allclose(filtered_Sigmas1, filtered_Sigmas2)
# Sample
xs = kalman_sample(*args)
# Test the standard Kalman smoother
from pylds.lds_messages_interface import E_step as kalman_smoother_ref
ll1, smoothed_mus1, smoothed_Sigmas1, ExnxT1 = kalman_smoother_ref(*args)
ll2, smoothed_mus2, smoothed_Sigmas2, ExxnT2 = kalman_smoother(*args)
assert np.allclose(ll1, ll2)
assert np.allclose(smoothed_mus1, smoothed_mus2)
assert np.allclose(smoothed_Sigmas1, smoothed_Sigmas2)
assert np.allclose(ExnxT1, np.swapaxes(ExxnT2, 1, 2))
# Test the info form filter
info_args = convert_mean_to_info_args(*args)
from pylds.lds_messages_interface import kalman_info_filter as kalman_info_filter_ref
log_Z1, filtered_Js1, filtered_hs1 = kalman_info_filter_ref(*info_args)
log_Z2, filtered_Js2, filtered_hs2 = kalman_info_filter(*info_args)
assert np.allclose(log_Z1, log_Z2)
assert np.allclose(filtered_Js1, filtered_Js2)
assert np.allclose(filtered_hs1, filtered_hs2)
# Test the info form smoother
_, smoothed_mus3, smoothed_Sigmas3, ExxnT3 = kalman_info_smoother(
*info_args)
assert np.allclose(smoothed_mus1, smoothed_mus3)
assert np.allclose(smoothed_Sigmas1, smoothed_Sigmas3)
assert np.allclose(ExxnT2, ExxnT3)
# Plot_the samples vs the smoother
xs = kalman_info_sample(*info_args)
def test_info_sample(T=100, D=3, N=10, U=3):
args = make_lds_parameters(T, D, N, U)
# Test the standard Kalman filter
from pylds.lds_messages_interface import E_step as kalman_smoother_ref
ll1, smoothed_mus1, smoothed_Sigmas1, ExnxT1 = kalman_smoother_ref(*args)
# Plot_the samples vs the smoother
info_args = convert_mean_to_info_args(*args)
xs = [kalman_info_sample(*info_args) for _ in range(4)]
import matplotlib.pyplot as plt
for i in range(D):
plt.subplot(D, 1, i+1)
plt.fill_between(np.arange(T),
smoothed_mus1[:, i] - 2 * np.sqrt(smoothed_Sigmas1[:, i, i]),
smoothed_mus1[:, i] + 2 * np.sqrt(smoothed_Sigmas1[:, i, i]),
color='k', alpha=0.25)
plt.plot(smoothed_mus1[:, i], '-k', lw=2)
for x in xs:
plt.plot(x[:, i])
plt.show()