def test_simulate_raw_chpi():
"""Test simulation of raw data with cHPI"""
with warnings.catch_warnings(record=True): # MaxShield
raw = Raw(raw_chpi_fname, allow_maxshield=True)
sphere = make_sphere_model('auto', 'auto', raw.info)
# make sparse spherical source space
sphere_vol = tuple(sphere['r0'] * 1000.) + (sphere.radius * 1000.,)
src = setup_volume_source_space('sample', sphere=sphere_vol, pos=70.)
stc = _make_stc(raw, src)
# simulate data with cHPI on
raw_sim = simulate_raw(raw, stc, None, src, sphere, cov=None, chpi=False)
# need to trim extra samples off this one
raw_chpi = simulate_raw(raw, stc, None, src, sphere, cov=None, chpi=True,
head_pos=pos_fname)
# test that the cHPI signals make some reasonable values
psd_sim, freqs_sim = compute_raw_psd(raw_sim)
psd_chpi, freqs_chpi = compute_raw_psd(raw_chpi)
assert_array_equal(freqs_sim, freqs_chpi)
hpi_freqs = _get_hpi_info(raw.info)[0]
freq_idx = np.sort([np.argmin(np.abs(freqs_sim - f)) for f in hpi_freqs])
picks_meg = pick_types(raw.info, meg=True, eeg=False)
picks_eeg = pick_types(raw.info, meg=False, eeg=True)
assert_allclose(psd_sim[picks_eeg], psd_chpi[picks_eeg], atol=1e-20)
assert_true((psd_chpi[picks_meg][:, freq_idx] >
100 * psd_sim[picks_meg][:, freq_idx]).all())
# test localization based on cHPI information
trans_sim, rot_sim, t_sim = _calculate_chpi_positions(raw_chpi)
trans, rot, t = get_chpi_positions(pos_fname)
t -= raw.first_samp / raw.info['sfreq']
_compare_positions((trans, rot, t), (trans_sim, rot_sim, t_sim),
max_dist=0.005)
def test_simulate_raw_chpi():
"""Test simulation of raw data with cHPI"""
with warnings.catch_warnings(record=True): # MaxShield
raw = Raw(raw_chpi_fname, allow_maxshield=True)
sphere = make_sphere_model('auto', 'auto', raw.info)
# make sparse spherical source space
sphere_vol = tuple(sphere['r0'] * 1000.) + (sphere.radius * 1000., )
src = setup_volume_source_space('sample', sphere=sphere_vol, pos=70.)
stc = _make_stc(raw, src)
# simulate data with cHPI on
raw_sim = simulate_raw(raw, stc, None, src, sphere, cov=None, chpi=False)
# need to trim extra samples off this one
raw_chpi = simulate_raw(raw,
stc,
None,
src,
sphere,
cov=None,
chpi=True,
head_pos=pos_fname)
# test cHPI indication
hpi_freqs, _, hpi_pick, hpi_on, _ = _get_hpi_info(raw.info)
assert_allclose(raw_sim[hpi_pick][0], 0.)
assert_allclose(raw_chpi[hpi_pick][0], hpi_on)
# test that the cHPI signals make some reasonable values
picks_meg = pick_types(raw.info, meg=True, eeg=False)
picks_eeg = pick_types(raw.info, meg=False, eeg=True)
for picks in [picks_meg, picks_eeg]:
psd_sim, freqs_sim = psd_welch(raw_sim, picks=picks)
psd_chpi, freqs_chpi = psd_welch(raw_chpi, picks=picks)
assert_array_equal(freqs_sim, freqs_chpi)
freq_idx = np.sort(
[np.argmin(np.abs(freqs_sim - f)) for f in hpi_freqs])
if picks is picks_meg:
assert_true(
(psd_chpi[:, freq_idx] > 100 * psd_sim[:, freq_idx]).all())
else:
assert_allclose(psd_sim, psd_chpi, atol=1e-20)
# test localization based on cHPI information
trans_sim, rot_sim, t_sim = _calculate_chpi_positions(raw_chpi)
trans, rot, t = get_chpi_positions(pos_fname)
t -= raw.first_samp / raw.info['sfreq']
_compare_positions((trans, rot, t), (trans_sim, rot_sim, t_sim),
max_dist=0.005)
def test_simulate_raw_chpi():
"""Test simulation of raw data with cHPI."""
raw = read_raw_fif(raw_chpi_fname, allow_maxshield='yes',
add_eeg_ref=False)
sphere = make_sphere_model('auto', 'auto', raw.info)
# make sparse spherical source space
sphere_vol = tuple(sphere['r0'] * 1000.) + (sphere.radius * 1000.,)
src = setup_volume_source_space('sample', sphere=sphere_vol, pos=70.)
stc = _make_stc(raw, src)
# simulate data with cHPI on
raw_sim = simulate_raw(raw, stc, None, src, sphere, cov=None, chpi=False)
# need to trim extra samples off this one
raw_chpi = simulate_raw(raw, stc, None, src, sphere, cov=None, chpi=True,
head_pos=pos_fname)
# test cHPI indication
hpi_freqs, _, hpi_pick, hpi_ons = _get_hpi_info(raw.info)[:4]
assert_allclose(raw_sim[hpi_pick][0], 0.)
assert_allclose(raw_chpi[hpi_pick][0], hpi_ons.sum())
# test that the cHPI signals make some reasonable values
picks_meg = pick_types(raw.info, meg=True, eeg=False)
picks_eeg = pick_types(raw.info, meg=False, eeg=True)
for picks in [picks_meg, picks_eeg]:
psd_sim, freqs_sim = psd_welch(raw_sim, picks=picks)
psd_chpi, freqs_chpi = psd_welch(raw_chpi, picks=picks)
assert_array_equal(freqs_sim, freqs_chpi)
freq_idx = np.sort([np.argmin(np.abs(freqs_sim - f))
for f in hpi_freqs])
if picks is picks_meg:
assert_true((psd_chpi[:, freq_idx] >
100 * psd_sim[:, freq_idx]).all())
else:
assert_allclose(psd_sim, psd_chpi, atol=1e-20)
# test localization based on cHPI information
quats_sim = _calculate_chpi_positions(raw_chpi)
trans_sim, rot_sim, t_sim = head_pos_to_trans_rot_t(quats_sim)
trans, rot, t = head_pos_to_trans_rot_t(read_head_pos(pos_fname))
t -= raw.first_samp / raw.info['sfreq']
_compare_positions((trans, rot, t), (trans_sim, rot_sim, t_sim),
max_dist=0.005)
