def test_calculate_chpi_positions():
"""Test calculation of cHPI positions
"""
trans, rot, t = head_pos_to_trans_rot_t(read_head_pos(pos_fname))
with warnings.catch_warnings(record=True):
raw = Raw(chpi_fif_fname, allow_maxshield=True, preload=True)
t -= raw.first_samp / raw.info['sfreq']
quats = _calculate_chpi_positions(raw, verbose='debug')
trans_est, rot_est, t_est = head_pos_to_trans_rot_t(quats)
_compare_positions((trans, rot, t), (trans_est, rot_est, t_est), 0.003)
# degenerate conditions
raw_no_chpi = Raw(test_fif_fname)
assert_raises(RuntimeError, _calculate_chpi_positions, raw_no_chpi)
raw_bad = raw.copy()
for d in raw_bad.info['dig']:
if d['kind'] == FIFF.FIFFV_POINT_HPI:
d['coord_frame'] = 999
break
assert_raises(RuntimeError, _calculate_chpi_positions, raw_bad)
raw_bad = raw.copy()
for d in raw_bad.info['dig']:
if d['kind'] == FIFF.FIFFV_POINT_HPI:
d['r'] = np.ones(3)
raw_bad.crop(0, 1., copy=False)
with warnings.catch_warnings(record=True): # bad pos
with catch_logging() as log_file:
_calculate_chpi_positions(raw_bad, verbose=True)
# ignore HPI info header and [done] footer
for line in log_file.getvalue().strip().split('\n')[4:-1]:
assert_true('0/5 good' in line)
def test_calculate_chpi_positions():
"""Test calculation of cHPI positions."""
# Check to make sure our fits match MF decently
mf_quats = read_head_pos(pos_fname)
raw = read_raw_fif(chpi_fif_fname, allow_maxshield='yes', preload=True)
# This is a little hack (aliasing while decimating) to make it much faster
# for testing purposes only. We can relax this later if we find it breaks
# something.
raw_dec = _decimate_chpi(raw, 15)
with catch_logging() as log:
py_quats = _calculate_chpi_positions(raw_dec,
t_step_max=1.,
verbose='debug')
assert log.getvalue().startswith('HPIFIT')
_assert_quats(py_quats, mf_quats, dist_tol=0.004, angle_tol=2.5)
# degenerate conditions
raw_no_chpi = read_raw_fif(test_fif_fname)
pytest.raises(RuntimeError, _calculate_chpi_positions, raw_no_chpi)
raw_bad = raw.copy()
del raw_bad.info['hpi_meas'][0]['hpi_coils'][0]['coil_freq']
pytest.raises(RuntimeError, _calculate_chpi_positions, raw_bad)
raw_bad = raw.copy()
for d in raw_bad.info['dig']:
if d['kind'] == FIFF.FIFFV_POINT_HPI:
d['coord_frame'] = FIFF.FIFFV_COORD_UNKNOWN
break
pytest.raises(RuntimeError, _calculate_chpi_positions, raw_bad)
for d in raw_bad.info['dig']:
if d['kind'] == FIFF.FIFFV_POINT_HPI:
d['coord_frame'] = FIFF.FIFFV_COORD_HEAD
d['r'] = np.ones(3)
raw_bad.crop(0, 1.)
picks = np.concatenate([
np.arange(306, len(raw_bad.ch_names)),
pick_types(raw_bad.info, meg=True)[::16]
])
raw_bad.pick_channels([raw_bad.ch_names[pick] for pick in picks])
with warnings.catch_warnings(record=True): # bad pos
with catch_logging() as log_file:
_calculate_chpi_positions(raw_bad, t_step_min=1., verbose=True)
# ignore HPI info header and [done] footer
assert '0/5 good' in log_file.getvalue().strip().split('\n')[-2]
# half the rate cuts off cHPI coils
raw.info['lowpass'] /= 2.
with pytest.raises(RuntimeError, match='above the'):
_calculate_chpi_positions(raw)
# test on 5k artemis data
raw = read_raw_artemis123(art_fname, preload=True)
mf_quats = read_head_pos(art_mc_fname)
with catch_logging() as log:
py_quats = _calculate_chpi_positions(raw,
t_step_min=2.,
verbose='debug')
_assert_quats(py_quats, mf_quats, dist_tol=0.004, angle_tol=2.5)
def test_calculate_chpi_positions():
"""Test calculation of cHPI positions."""
# Check to make sure our fits match MF decently
mf_quats = read_head_pos(pos_fname)
raw = read_raw_fif(chpi_fif_fname, allow_maxshield='yes', preload=True)
# This is a little hack (aliasing while decimating) to make it much faster
# for testing purposes only. We can relax this later if we find it breaks
# something.
raw_dec = _decimate_chpi(raw, 15)
with catch_logging() as log:
py_quats = _calculate_chpi_positions(raw_dec, t_step_max=1.,
verbose='debug')
assert_true(log.getvalue().startswith('HPIFIT'))
_assert_quats(py_quats, mf_quats, dist_tol=0.004, angle_tol=2.5)
# degenerate conditions
raw_no_chpi = read_raw_fif(test_fif_fname)
assert_raises(RuntimeError, _calculate_chpi_positions, raw_no_chpi)
raw_bad = raw.copy()
del raw_bad.info['hpi_meas'][0]['hpi_coils'][0]['coil_freq']
assert_raises(RuntimeError, _calculate_chpi_positions, raw_bad)
raw_bad = raw.copy()
for d in raw_bad.info['dig']:
if d['kind'] == FIFF.FIFFV_POINT_HPI:
d['coord_frame'] = FIFF.FIFFV_COORD_UNKNOWN
break
assert_raises(RuntimeError, _calculate_chpi_positions, raw_bad)
for d in raw_bad.info['dig']:
if d['kind'] == FIFF.FIFFV_POINT_HPI:
d['coord_frame'] = FIFF.FIFFV_COORD_HEAD
d['r'] = np.ones(3)
raw_bad.crop(0, 1.)
picks = np.concatenate([np.arange(306, len(raw_bad.ch_names)),
pick_types(raw_bad.info, meg=True)[::16]])
raw_bad.pick_channels([raw_bad.ch_names[pick] for pick in picks])
with warnings.catch_warnings(record=True): # bad pos
with catch_logging() as log_file:
_calculate_chpi_positions(raw_bad, t_step_min=1., verbose=True)
# ignore HPI info header and [done] footer
assert_true('0/5 good' in log_file.getvalue().strip().split('\n')[-2])
# half the rate cuts off cHPI coils
raw.info['lowpass'] /= 2.
assert_raises_regex(RuntimeError, 'above the',
_calculate_chpi_positions, raw)
# test on 5k artemis data
raw = read_raw_artemis123(art_fname, preload=True)
mf_quats = read_head_pos(art_mc_fname)
with catch_logging() as log:
py_quats = _calculate_chpi_positions(raw, t_step_min=2.,
verbose='debug')
_assert_quats(py_quats, mf_quats, dist_tol=0.004, angle_tol=2.5)
def test_calculate_chpi_positions():
"""Test calculation of cHPI positions."""
trans, rot, t = head_pos_to_trans_rot_t(read_head_pos(pos_fname))
raw = read_raw_fif(chpi_fif_fname, allow_maxshield='yes', preload=True,
add_eeg_ref=False)
t -= raw.first_samp / raw.info['sfreq']
quats = _calculate_chpi_positions(raw, verbose='debug')
trans_est, rot_est, t_est = head_pos_to_trans_rot_t(quats)
_compare_positions((trans, rot, t), (trans_est, rot_est, t_est), 0.003)
# degenerate conditions
raw_no_chpi = read_raw_fif(test_fif_fname, add_eeg_ref=False)
assert_raises(RuntimeError, _calculate_chpi_positions, raw_no_chpi)
raw_bad = raw.copy()
for d in raw_bad.info['dig']:
if d['kind'] == FIFF.FIFFV_POINT_HPI:
d['coord_frame'] = 999
break
assert_raises(RuntimeError, _calculate_chpi_positions, raw_bad)
raw_bad = raw.copy()
for d in raw_bad.info['dig']:
if d['kind'] == FIFF.FIFFV_POINT_HPI:
d['r'] = np.ones(3)
raw_bad.crop(0, 1., copy=False)
with warnings.catch_warnings(record=True): # bad pos
with catch_logging() as log_file:
_calculate_chpi_positions(raw_bad, verbose=True)
# ignore HPI info header and [done] footer
assert_true('0/5 good' in log_file.getvalue().strip().split('\n')[-2])
# half the rate cuts off cHPI coils
with warnings.catch_warnings(record=True): # uint cast suggestion
raw.resample(300., npad='auto')
assert_raises_regex(RuntimeError, 'above the',
_calculate_chpi_positions, raw)
def test_calculate_chpi_positions():
"""Test calculation of cHPI positions
"""
trans, rot, t = head_pos_to_trans_rot_t(read_head_pos(pos_fname))
raw = Raw(chpi_fif_fname, allow_maxshield='yes', preload=True)
t -= raw.first_samp / raw.info['sfreq']
quats = _calculate_chpi_positions(raw, verbose='debug')
trans_est, rot_est, t_est = head_pos_to_trans_rot_t(quats)
_compare_positions((trans, rot, t), (trans_est, rot_est, t_est), 0.003)
# degenerate conditions
raw_no_chpi = Raw(test_fif_fname)
assert_raises(RuntimeError, _calculate_chpi_positions, raw_no_chpi)
raw_bad = raw.copy()
for d in raw_bad.info['dig']:
if d['kind'] == FIFF.FIFFV_POINT_HPI:
d['coord_frame'] = 999
break
assert_raises(RuntimeError, _calculate_chpi_positions, raw_bad)
raw_bad = raw.copy()
for d in raw_bad.info['dig']:
if d['kind'] == FIFF.FIFFV_POINT_HPI:
d['r'] = np.ones(3)
raw_bad.crop(0, 1., copy=False)
with warnings.catch_warnings(record=True): # bad pos
with catch_logging() as log_file:
_calculate_chpi_positions(raw_bad, verbose=True)
# ignore HPI info header and [done] footer
for line in log_file.getvalue().strip().split('\n')[4:-1]:
assert_true('0/5 good' in line)
# half the rate cuts off cHPI coils
raw.resample(300., npad='auto')
assert_raises_regex(RuntimeError, 'above the', _calculate_chpi_positions,
raw)
def test_movement_annotation_head_correction():
"""Test correct detection movement artifact and dev_head_t."""
raw = read_raw_fif(raw_fname, allow_maxshield='yes').load_data()
pos = read_head_pos(pos_fname)
# Check 5 rotation segments are detected
annot_rot, [] = annotate_movement(raw, pos, rotation_velocity_limit=5)
assert (annot_rot.duration.size == 5)
# Check 2 translation vel. segments are detected
annot_tra, [] = annotate_movement(raw, pos, translation_velocity_limit=.05)
assert (annot_tra.duration.size == 2)
# Check 1 movement distance segment is detected
annot_dis, disp = annotate_movement(raw, pos, mean_distance_limit=.02)
assert (annot_dis.duration.size == 1)
# Check correct trans mat
raw.set_annotations(annot_rot + annot_tra + annot_dis)
dev_head_t = compute_average_dev_head_t(raw, pos)
dev_head_t_ori = np.array(
[[0.9957292, -0.08688804, 0.03120615, 0.00698271],
[0.09020767, 0.9875856, -0.12859731, -0.0159098],
[-0.01964518, 0.1308631, 0.99120578, 0.07258289], [0., 0., 0., 1.]])
assert_allclose(dev_head_t_ori, dev_head_t['trans'], rtol=1e-5, atol=0)
# Smoke test skipping time due to previous annotations.
raw.set_annotations(Annotations([raw.times[0]], 0.1, 'bad'))
annot_dis, disp = annotate_movement(raw, pos, mean_distance_limit=.02)
assert (annot_dis.duration.size == 1)
def test_calculate_chpi_positions():
"""Test calculation of cHPI positions
"""
trans, rot, t = head_pos_to_trans_rot_t(read_head_pos(pos_fname))
raw = Raw(chpi_fif_fname, allow_maxshield="yes", preload=True)
t -= raw.first_samp / raw.info["sfreq"]
quats = _calculate_chpi_positions(raw, verbose="debug")
trans_est, rot_est, t_est = head_pos_to_trans_rot_t(quats)
_compare_positions((trans, rot, t), (trans_est, rot_est, t_est), 0.003)
# degenerate conditions
raw_no_chpi = Raw(test_fif_fname)
assert_raises(RuntimeError, _calculate_chpi_positions, raw_no_chpi)
raw_bad = raw.copy()
for d in raw_bad.info["dig"]:
if d["kind"] == FIFF.FIFFV_POINT_HPI:
d["coord_frame"] = 999
break
assert_raises(RuntimeError, _calculate_chpi_positions, raw_bad)
raw_bad = raw.copy()
for d in raw_bad.info["dig"]:
if d["kind"] == FIFF.FIFFV_POINT_HPI:
d["r"] = np.ones(3)
raw_bad.crop(0, 1.0, copy=False)
with warnings.catch_warnings(record=True): # bad pos
with catch_logging() as log_file:
_calculate_chpi_positions(raw_bad, verbose=True)
# ignore HPI info header and [done] footer
for line in log_file.getvalue().strip().split("\n")[4:-1]:
assert_true("0/5 good" in line)
# half the rate cuts off cHPI coils
with warnings.catch_warnings(record=True): # uint cast suggestion
raw.resample(300.0, npad="auto")
assert_raises_regex(RuntimeError, "above the", _calculate_chpi_positions, raw)
def test_read_write_head_pos(tmpdir):
"""Test reading and writing head position quaternion parameters."""
temp_name = op.join(str(tmpdir), 'temp.pos')
# This isn't a 100% valid quat matrix but it should be okay for tests
head_pos_rand = np.random.RandomState(0).randn(20, 10)
# This one is valid
head_pos_read = read_head_pos(pos_fname)
for head_pos_orig in (head_pos_rand, head_pos_read):
write_head_pos(temp_name, head_pos_orig)
head_pos = read_head_pos(temp_name)
assert_allclose(head_pos_orig, head_pos, atol=1e-3)
# Degenerate cases
pytest.raises(TypeError, write_head_pos, 0, head_pos_read) # not filename
pytest.raises(ValueError, write_head_pos, temp_name, 'foo') # not array
pytest.raises(ValueError, write_head_pos, temp_name, head_pos_read[:, :9])
pytest.raises(TypeError, read_head_pos, 0)
pytest.raises(IOError, read_head_pos, temp_name + 'foo')
def test_read_write_head_pos(tmpdir):
"""Test reading and writing head position quaternion parameters."""
temp_name = op.join(str(tmpdir), 'temp.pos')
# This isn't a 100% valid quat matrix but it should be okay for tests
head_pos_rand = np.random.RandomState(0).randn(20, 10)
# This one is valid
head_pos_read = read_head_pos(pos_fname)
for head_pos_orig in (head_pos_rand, head_pos_read):
write_head_pos(temp_name, head_pos_orig)
head_pos = read_head_pos(temp_name)
assert_allclose(head_pos_orig, head_pos, atol=1e-3)
# Degenerate cases
pytest.raises(TypeError, write_head_pos, 0, head_pos_read) # not filename
pytest.raises(ValueError, write_head_pos, temp_name, 'foo') # not array
pytest.raises(ValueError, write_head_pos, temp_name, head_pos_read[:, :9])
pytest.raises(TypeError, read_head_pos, 0)
pytest.raises(IOError, read_head_pos, temp_name + 'foo')
def test_simulate_raw_chpi():
"""Test simulation of raw data with cHPI."""
raw = read_raw_fif(raw_chpi_fname, allow_maxshield='yes')
picks = np.arange(len(raw.ch_names))
picks = np.setdiff1d(picks, pick_types(raw.info, meg=True, eeg=True)[::4])
raw.load_data().pick_channels([raw.ch_names[pick] for pick in picks])
raw.info.normalize_proj()
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,
interp='zero',
use_cps=True)
# 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,
interp='zero',
use_cps=True)
# test cHPI indication
hpi_freqs, hpi_pick, hpi_ons = _get_hpi_info(raw.info)
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[:3], picks_eeg[:3]]:
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, t_step_min=10.)
quats = read_head_pos(pos_fname)
_assert_quats(quats, quats_sim, dist_tol=5e-3, angle_tol=3.5)
def test_spatiotemporal_only():
"""Test tSSS-only processing"""
# Load raw testing data
raw = Raw(raw_fname, allow_maxshield='yes').crop(0, 2,
copy=False).load_data()
picks = pick_types(raw.info, meg='mag', exclude=())
power = np.sqrt(np.sum(raw[picks][0]**2))
# basics
raw_tsss = maxwell_filter(raw, st_duration=1., st_only=True)
assert_equal(raw_tsss.estimate_rank(), 366)
_assert_shielding(raw_tsss, power, 10)
# temporal proj will actually reduce spatial DOF with small windows!
raw_tsss = maxwell_filter(raw, st_duration=0.1, st_only=True)
assert_true(raw_tsss.estimate_rank() < 350)
_assert_shielding(raw_tsss, power, 40)
# with movement
head_pos = read_head_pos(pos_fname)
raw_tsss = maxwell_filter(raw,
st_duration=1.,
st_only=True,
head_pos=head_pos)
assert_equal(raw_tsss.estimate_rank(), 366)
_assert_shielding(raw_tsss, power, 12)
with warnings.catch_warnings(record=True): # st_fixed False
raw_tsss = maxwell_filter(raw,
st_duration=1.,
st_only=True,
head_pos=head_pos,
st_fixed=False)
assert_equal(raw_tsss.estimate_rank(), 366)
_assert_shielding(raw_tsss, power, 12)
# should do nothing
raw_tsss = maxwell_filter(raw,
st_duration=1.,
st_correlation=1.,
st_only=True)
assert_allclose(raw[:][0], raw_tsss[:][0])
# degenerate
assert_raises(ValueError, maxwell_filter, raw, st_only=True) # no ST
# two-step process equivalent to single-step process
raw_tsss = maxwell_filter(raw, st_duration=1., st_only=True)
raw_tsss = maxwell_filter(raw_tsss)
raw_tsss_2 = maxwell_filter(raw, st_duration=1.)
assert_meg_snr(raw_tsss, raw_tsss_2, 1e5)
# now also with head movement, and a bad MEG channel
assert_equal(len(raw.info['bads']), 0)
raw.info['bads'] = ['EEG001', 'MEG2623']
raw_tsss = maxwell_filter(raw,
st_duration=1.,
st_only=True,
head_pos=head_pos)
assert_equal(raw.info['bads'], ['EEG001', 'MEG2623'])
assert_equal(raw_tsss.info['bads'], ['EEG001', 'MEG2623']) # don't reset
raw_tsss = maxwell_filter(raw_tsss, head_pos=head_pos)
assert_equal(raw_tsss.info['bads'], ['EEG001']) # do reset MEG bads
raw_tsss_2 = maxwell_filter(raw, st_duration=1., head_pos=head_pos)
assert_equal(raw_tsss_2.info['bads'], ['EEG001'])
assert_meg_snr(raw_tsss, raw_tsss_2, 1e5)
def test_spatiotemporal_only():
"""Test tSSS-only processing."""
# Load raw testing data
tmax = 0.5
raw = read_crop(raw_fname, (0, tmax)).load_data()
picks = pick_types(raw.info, meg=True, exclude='bads')[::2]
raw.pick_channels([raw.ch_names[pick] for pick in picks])
mag_picks = pick_types(raw.info, meg='mag', exclude=())
power = np.sqrt(np.sum(raw[mag_picks][0]**2))
# basics
raw_tsss = maxwell_filter(raw, st_duration=tmax / 2., st_only=True)
assert_equal(len(raw.info['projs']), len(raw_tsss.info['projs']))
assert_equal(raw_tsss.estimate_rank(), len(picks))
_assert_shielding(raw_tsss, power, 9)
# with movement
head_pos = read_head_pos(pos_fname)
raw_tsss = maxwell_filter(raw,
st_duration=tmax / 2.,
st_only=True,
head_pos=head_pos)
assert_equal(raw_tsss.estimate_rank(), len(picks))
_assert_shielding(raw_tsss, power, 9)
with warnings.catch_warnings(record=True): # st_fixed False
raw_tsss = maxwell_filter(raw,
st_duration=tmax / 2.,
st_only=True,
head_pos=head_pos,
st_fixed=False)
assert_equal(raw_tsss.estimate_rank(), len(picks))
_assert_shielding(raw_tsss, power, 9)
# should do nothing
raw_tsss = maxwell_filter(raw,
st_duration=tmax,
st_correlation=1.,
st_only=True)
assert_allclose(raw[:][0], raw_tsss[:][0])
# degenerate
assert_raises(ValueError, maxwell_filter, raw, st_only=True) # no ST
# two-step process equivalent to single-step process
raw_tsss = maxwell_filter(raw, st_duration=tmax, st_only=True)
raw_tsss = maxwell_filter(raw_tsss)
raw_tsss_2 = maxwell_filter(raw, st_duration=tmax)
assert_meg_snr(raw_tsss, raw_tsss_2, 1e5)
# now also with head movement, and a bad MEG channel
assert_equal(len(raw.info['bads']), 0)
bads = [raw.ch_names[0]]
raw.info['bads'] = list(bads)
raw_tsss = maxwell_filter(raw,
st_duration=tmax,
st_only=True,
head_pos=head_pos)
assert_equal(raw.info['bads'], bads)
assert_equal(raw_tsss.info['bads'], bads) # don't reset
raw_tsss = maxwell_filter(raw_tsss, head_pos=head_pos)
assert_equal(raw_tsss.info['bads'], []) # do reset MEG bads
raw_tsss_2 = maxwell_filter(raw, st_duration=tmax, head_pos=head_pos)
assert_equal(raw_tsss_2.info['bads'], [])
assert_meg_snr(raw_tsss, raw_tsss_2, 1e5)
def test_calculate_chpi_positions():
"""Test calculation of cHPI positions."""
# Check to make sure our fits match MF decently
mf_quats = read_head_pos(pos_fname)
raw = read_raw_fif(chpi_fif_fname, allow_maxshield='yes', preload=True)
# This is a little hack (aliasing while decimating) to make it much faster
# for testing purposes only. We can relax this later if we find it breaks
# something.
raw_dec = _decimate_chpi(raw, 15)
with catch_logging() as log:
py_quats = _calculate_chpi_positions(raw_dec, verbose='debug')
assert_true(log.getvalue().startswith('HPIFIT'))
_assert_quats(py_quats, mf_quats, dist_tol=0.004, angle_tol=2.5)
# degenerate conditions
raw_no_chpi = read_raw_fif(test_fif_fname)
assert_raises(RuntimeError, _calculate_chpi_positions, raw_no_chpi)
raw_bad = raw.copy()
for d in raw_bad.info['dig']:
if d['kind'] == FIFF.FIFFV_POINT_HPI:
d['coord_frame'] = 999
break
assert_raises(RuntimeError, _calculate_chpi_positions, raw_bad)
raw_bad = raw.copy()
for d in raw_bad.info['dig']:
if d['kind'] == FIFF.FIFFV_POINT_HPI:
d['r'] = np.ones(3)
raw_bad.crop(0, 1.)
with warnings.catch_warnings(record=True): # bad pos
with catch_logging() as log_file:
_calculate_chpi_positions(raw_bad, t_step_min=5., verbose=True)
# ignore HPI info header and [done] footer
assert_true('0/5 good' in log_file.getvalue().strip().split('\n')[-2])
# half the rate cuts off cHPI coils
raw.info['lowpass'] /= 2.
assert_raises_regex(RuntimeError, 'above the',
_calculate_chpi_positions, raw)
# test on 5k artemis data
raw = read_raw_artemis123(art_fname, preload=True)
mf_quats = read_head_pos(art_mc_fname)
with catch_logging() as log:
py_quats = _calculate_chpi_positions(raw, verbose='debug')
_assert_quats(py_quats, mf_quats, dist_tol=0.004, angle_tol=2.5)
def test_calculate_head_pos_ctf():
"""Test extracting of cHPI positions from ctf data."""
raw = read_raw_ctf(ctf_chpi_fname)
quats = _calculate_head_pos_ctf(raw)
mc_quats = read_head_pos(ctf_chpi_pos_fname)
_assert_quats(quats, mc_quats, dist_tol=0.004, angle_tol=2.5)
raw = read_raw_fif(ctf_fname)
pytest.raises(RuntimeError, _calculate_head_pos_ctf, raw)
def test_calculate_chpi_positions_vv():
"""Test calculation of cHPI positions."""
# Check to make sure our fits match MF decently
mf_quats = read_head_pos(pos_fname)
raw = read_raw_fif(chpi_fif_fname, allow_maxshield='yes')
raw.crop(0, 5).load_data()
# check "auto" t_window estimation at full sampling rate
with catch_logging() as log:
compute_chpi_amplitudes(raw, t_step_min=0.1, t_window='auto',
tmin=0, tmax=2, verbose=True)
assert '83.3 ms' in log.getvalue()
# This is a little hack (aliasing while decimating) to make it much faster
# for testing purposes only. We can relax this later if we find it breaks
# something.
raw_dec = _decimate_chpi(raw, 15)
with catch_logging() as log:
with pytest.warns(RuntimeWarning, match='cannot determine'):
py_quats = _calculate_chpi_positions(raw_dec, t_window=0.2,
verbose='debug')
log = log.getvalue()
assert '\nHPIFIT' in log
assert 'Computing 4385 HPI location guesses' in log
_assert_quats(py_quats, mf_quats, dist_tol=0.001, angle_tol=0.7)
# degenerate conditions
raw_no_chpi = read_raw_fif(sample_fname)
with pytest.raises(ValueError, match='No appropriate cHPI information'):
_calculate_chpi_positions(raw_no_chpi)
raw_bad = raw.copy()
del raw_bad.info['hpi_meas'][0]['hpi_coils'][0]['coil_freq']
with pytest.raises(ValueError, match='No appropriate cHPI information'):
_calculate_chpi_positions(raw_bad)
raw_bad = raw.copy()
for d in raw_bad.info['dig']:
if d['kind'] == FIFF.FIFFV_POINT_HPI:
d['coord_frame'] = FIFF.FIFFV_COORD_UNKNOWN
break
with pytest.raises(RuntimeError, match='coordinate frame incorrect'):
_calculate_chpi_positions(raw_bad)
for d in raw_bad.info['dig']:
if d['kind'] == FIFF.FIFFV_POINT_HPI:
d['coord_frame'] = FIFF.FIFFV_COORD_HEAD
d['r'] = np.ones(3)
raw_bad.crop(0, 1.)
picks = np.concatenate([np.arange(306, len(raw_bad.ch_names)),
pick_types(raw_bad.info, meg=True)[::16]])
raw_bad.pick_channels([raw_bad.ch_names[pick] for pick in picks])
with pytest.warns(RuntimeWarning, match='Discrepancy'):
with catch_logging() as log_file:
_calculate_chpi_positions(raw_bad, t_step_min=1., verbose=True)
# ignore HPI info header and [done] footer
assert '0/5 good HPI fits' in log_file.getvalue()
# half the rate cuts off cHPI coils
with raw.info._unlock():
raw.info['lowpass'] /= 2.
with pytest.raises(RuntimeError, match='above the'):
_calculate_chpi_positions(raw)
def test_calculate_chpi_positions_artemis():
"""Test on 5k artemis data."""
raw = read_raw_artemis123(art_fname, preload=True)
mf_quats = read_head_pos(art_mc_fname)
mf_quats[:, 8:] /= 100 # old code errantly had this factor
py_quats = _calculate_chpi_positions(raw, t_step_min=2., verbose='debug')
_assert_quats(
py_quats, mf_quats,
dist_tol=0.001, angle_tol=1., err_rtol=0.7, vel_atol=1e-2)
def test_calculate_chpi_positions_on_chpi5_in_shorter_steps():
"""Comparing estimated cHPI positions with MF results (smaller steps)."""
# Check to make sure our fits match MF decently
mf_quats = read_head_pos(chpi5_pos_fname)
raw = read_raw_fif(chpi5_fif_fname, allow_maxshield='yes')
raw = _decimate_chpi(raw.crop(0., 15.).load_data(), decim=8)
py_quats = _calculate_chpi_positions(raw, t_step_min=0.1, t_step_max=0.1,
t_window=0.1, verbose='debug')
# needs interpolation, tolerance must be increased
_assert_quats(py_quats, mf_quats, dist_tol=0.001, angle_tol=0.6)
def test_calculate_chpi_positions_on_chpi5_in_shorter_steps():
"""Comparing estimated cHPI positions with MF results (smaller steps)."""
# Check to make sure our fits match MF decently
mf_quats = read_head_pos(chpi5_pos_fname)
raw = read_raw_fif(chpi5_fif_fname, allow_maxshield='yes')
raw = _decimate_chpi(raw.crop(0., 15.).load_data(), decim=8)
py_quats = _calculate_chpi_positions(raw, t_step_min=0.1, t_step_max=0.1,
t_window=0.1, verbose='debug')
# needs interpolation, tolerance must be increased
_assert_quats(py_quats, mf_quats, dist_tol=0.001, angle_tol=0.6)
def test_simulate_raw_chpi():
"""Test simulation of raw data with cHPI."""
raw = read_raw_fif(raw_chpi_fname, allow_maxshield='yes')
picks = np.arange(len(raw.ch_names))
picks = np.setdiff1d(picks, pick_types(raw.info, meg=True, eeg=True)[::4])
raw.load_data().pick_channels([raw.ch_names[pick] for pick in picks])
raw.info.normalize_proj()
sphere = make_sphere_model('auto', 'auto', raw.info)
# make sparse spherical source space
sphere_vol = tuple(sphere['r0']) + (sphere.radius, )
src = setup_volume_source_space(sphere=sphere_vol,
pos=70.,
sphere_units='m')
stcs = [_make_stc(raw, src)] * 15
# simulate data with cHPI on
raw_sim = simulate_raw(raw.info,
stcs,
None,
src,
sphere,
head_pos=pos_fname,
interp='zero',
first_samp=raw.first_samp)
# need to trim extra samples off this one
raw_chpi = add_chpi(raw_sim.copy(), head_pos=pos_fname, interp='zero')
# test cHPI indication
hpi_freqs, hpi_pick, hpi_ons = get_chpi_info(raw.info, on_missing='raise')
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[:3], picks_eeg[:3]]:
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 (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
chpi_amplitudes = compute_chpi_amplitudes(raw, t_step_min=10.)
coil_locs = compute_chpi_locs(raw.info, chpi_amplitudes)
quats_sim = compute_head_pos(raw_chpi.info, coil_locs)
quats = read_head_pos(pos_fname)
_assert_quats(quats,
quats_sim,
dist_tol=5e-3,
angle_tol=3.5,
vel_atol=0.03) # velicity huge because of t_step_min above
def test_calculate_head_pos_ctf():
"""Test extracting of cHPI positions from ctf data."""
raw = read_raw_ctf(ctf_chpi_fname)
quats = calculate_head_pos_ctf(raw)
mc_quats = read_head_pos(ctf_chpi_pos_fname)
mc_quats[:, 9] /= 10000 # had old factor in there twice somehow...
_assert_quats(quats, mc_quats, dist_tol=0.004, angle_tol=2.5, err_rtol=1.,
vel_atol=7e-3) # 7 mm/s
raw = read_raw_fif(ctf_fname)
with pytest.raises(RuntimeError, match='Could not find'):
calculate_head_pos_ctf(raw)
def test_calculate_head_pos_chpi_on_chpi5_in_shorter_steps():
"""Comparing estimated cHPI positions with MF results (smaller steps)."""
# Check to make sure our fits match MF decently
mf_quats = read_head_pos(chpi5_pos_fname)
raw = read_raw_fif(chpi5_fif_fname, allow_maxshield='yes')
raw = _decimate_chpi(raw.crop(0., 5.).load_data(), decim=8)
with pytest.warns(RuntimeWarning, match='cannot determine'):
py_quats = _calculate_chpi_positions(
raw, t_step_min=0.1, t_step_max=0.1, t_window=0.1, verbose='debug')
# needs interpolation, tolerance must be increased
_assert_quats(py_quats, mf_quats, dist_tol=0.002, angle_tol=1.2,
vel_atol=0.02) # 2 cm/s is not great but probably fine
def add_head_postions(subj, report):
hp_files = list((dirs.hp / subj.name).glob("*_hp.pos"))
hp_files = sorted(hp_files, key=attrgetter("name"))
figs = list()
captions = list()
for f in hp_files:
captions.append(str(f.relative_to(dirs.bids_root.parent)))
pos = read_head_pos(f)
fig = plot_head_positions(pos, show=False)
figs.append(fig)
report.add_figs_to_section(figs, captions, section="Head position")
return report
def test_calculate_chpi_positions_on_chpi5_in_one_second_steps():
"""Comparing estimated cHPI positions with MF results (one second)."""
# Check to make sure our fits match MF decently
mf_quats = read_head_pos(chpi5_pos_fname)
raw = read_raw_fif(chpi5_fif_fname, allow_maxshield='yes')
# the last two seconds contain a maxfilter problem!
# fiff file timing: 26. to 43. seconds
# maxfilter estimates a wrong head position for interval 16: 41.-42. sec
raw = _decimate_chpi(raw.crop(0., 15.).load_data(), decim=8)
# needs no interpolation, because maxfilter pos files comes with 1 s steps
py_quats = _calculate_chpi_positions(raw, t_step_min=1.0, t_step_max=1.0,
t_window=1.0, verbose='debug')
_assert_quats(py_quats, mf_quats, dist_tol=0.0008, angle_tol=.5)
def test_calculate_chpi_positions_on_chpi5_in_one_second_steps():
"""Comparing estimated cHPI positions with MF results (one second)."""
# Check to make sure our fits match MF decently
mf_quats = read_head_pos(chpi5_pos_fname)
raw = read_raw_fif(chpi5_fif_fname, allow_maxshield='yes')
# the last two seconds contain a maxfilter problem!
# fiff file timing: 26. to 43. seconds
# maxfilter estimates a wrong head position for interval 16: 41.-42. sec
raw = _decimate_chpi(raw.crop(0., 15.).load_data(), decim=8)
# needs no interpolation, because maxfilter pos files comes with 1 s steps
py_quats = _calculate_chpi_positions(raw, t_step_min=1.0, t_step_max=1.0,
t_window=1.0, verbose='debug')
_assert_quats(py_quats, mf_quats, dist_tol=0.0008, angle_tol=.5)
def test_spatiotemporal_only():
"""Test tSSS-only processing"""
# Load raw testing data
raw = Raw(raw_fname,
allow_maxshield='yes').crop(0, 2, copy=False).load_data()
picks = pick_types(raw.info, meg='mag', exclude=())
power = np.sqrt(np.sum(raw[picks][0] ** 2))
# basics
raw_tsss = maxwell_filter(raw, st_duration=1., st_only=True)
assert_equal(raw_tsss.estimate_rank(), 366)
_assert_shielding(raw_tsss, power, 10)
# temporal proj will actually reduce spatial DOF with small windows!
raw_tsss = maxwell_filter(raw, st_duration=0.1, st_only=True)
assert_true(raw_tsss.estimate_rank() < 350)
_assert_shielding(raw_tsss, power, 40)
# with movement
head_pos = read_head_pos(pos_fname)
raw_tsss = maxwell_filter(raw, st_duration=1., st_only=True,
head_pos=head_pos)
assert_equal(raw_tsss.estimate_rank(), 366)
_assert_shielding(raw_tsss, power, 12)
with warnings.catch_warnings(record=True): # st_fixed False
raw_tsss = maxwell_filter(raw, st_duration=1., st_only=True,
head_pos=head_pos, st_fixed=False)
assert_equal(raw_tsss.estimate_rank(), 366)
_assert_shielding(raw_tsss, power, 12)
# should do nothing
raw_tsss = maxwell_filter(raw, st_duration=1., st_correlation=1.,
st_only=True)
assert_allclose(raw[:][0], raw_tsss[:][0])
# degenerate
assert_raises(ValueError, maxwell_filter, raw, st_only=True) # no ST
# two-step process equivalent to single-step process
raw_tsss = maxwell_filter(raw, st_duration=1., st_only=True)
raw_tsss = maxwell_filter(raw_tsss)
raw_tsss_2 = maxwell_filter(raw, st_duration=1.)
assert_meg_snr(raw_tsss, raw_tsss_2, 1e5)
# now also with head movement, and a bad MEG channel
assert_equal(len(raw.info['bads']), 0)
raw.info['bads'] = ['EEG001', 'MEG2623']
raw_tsss = maxwell_filter(raw, st_duration=1., st_only=True,
head_pos=head_pos)
assert_equal(raw.info['bads'], ['EEG001', 'MEG2623'])
assert_equal(raw_tsss.info['bads'], ['EEG001', 'MEG2623']) # don't reset
raw_tsss = maxwell_filter(raw_tsss, head_pos=head_pos)
assert_equal(raw_tsss.info['bads'], ['EEG001']) # do reset MEG bads
raw_tsss_2 = maxwell_filter(raw, st_duration=1., head_pos=head_pos)
assert_equal(raw_tsss_2.info['bads'], ['EEG001'])
assert_meg_snr(raw_tsss, raw_tsss_2, 1e5)
def test_spatiotemporal_only():
"""Test tSSS-only processing."""
# Load raw testing data
tmax = 0.5
raw = read_crop(raw_fname, (0, tmax)).load_data()
picks = pick_types(raw.info, meg=True, exclude='bads')[::2]
raw.pick_channels([raw.ch_names[pick] for pick in picks])
mag_picks = pick_types(raw.info, meg='mag', exclude=())
power = np.sqrt(np.sum(raw[mag_picks][0] ** 2))
# basics
raw_tsss = maxwell_filter(raw, st_duration=tmax / 2., st_only=True)
assert_equal(len(raw.info['projs']), len(raw_tsss.info['projs']))
assert_equal(raw_tsss.estimate_rank(), len(picks))
_assert_shielding(raw_tsss, power, 9)
# with movement
head_pos = read_head_pos(pos_fname)
raw_tsss = maxwell_filter(raw, st_duration=tmax / 2., st_only=True,
head_pos=head_pos)
assert_equal(raw_tsss.estimate_rank(), len(picks))
_assert_shielding(raw_tsss, power, 9)
with pytest.warns(RuntimeWarning, match='st_fixed'):
raw_tsss = maxwell_filter(raw, st_duration=tmax / 2., st_only=True,
head_pos=head_pos, st_fixed=False)
assert_equal(raw_tsss.estimate_rank(), len(picks))
_assert_shielding(raw_tsss, power, 9)
# should do nothing
raw_tsss = maxwell_filter(raw, st_duration=tmax, st_correlation=1.,
st_only=True)
assert_allclose(raw[:][0], raw_tsss[:][0])
# degenerate
pytest.raises(ValueError, maxwell_filter, raw, st_only=True) # no ST
# two-step process equivalent to single-step process
raw_tsss = maxwell_filter(raw, st_duration=tmax, st_only=True)
raw_tsss = maxwell_filter(raw_tsss)
raw_tsss_2 = maxwell_filter(raw, st_duration=tmax)
assert_meg_snr(raw_tsss, raw_tsss_2, 1e5)
# now also with head movement, and a bad MEG channel
assert_equal(len(raw.info['bads']), 0)
bads = [raw.ch_names[0]]
raw.info['bads'] = list(bads)
raw_tsss = maxwell_filter(raw, st_duration=tmax, st_only=True,
head_pos=head_pos)
assert_equal(raw.info['bads'], bads)
assert_equal(raw_tsss.info['bads'], bads) # don't reset
raw_tsss = maxwell_filter(raw_tsss, head_pos=head_pos)
assert_equal(raw_tsss.info['bads'], []) # do reset MEG bads
raw_tsss_2 = maxwell_filter(raw, st_duration=tmax, head_pos=head_pos)
assert_equal(raw_tsss_2.info['bads'], [])
assert_meg_snr(raw_tsss, raw_tsss_2, 1e5)
def test_simulate_raw_chpi():
"""Test simulation of raw data with cHPI."""
raw = read_raw_fif(raw_chpi_fname, allow_maxshield='yes')
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)
def test_simulate_raw_chpi():
"""Test simulation of raw data with cHPI."""
raw = read_raw_fif(raw_chpi_fname, allow_maxshield='yes')
picks = np.arange(len(raw.ch_names))
picks = np.setdiff1d(picks, pick_types(raw.info, meg=True, eeg=True)[::4])
raw.load_data().pick_channels([raw.ch_names[pick] for pick in picks])
raw.info.normalize_proj()
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(sphere=sphere_vol, pos=70.)
stc = _make_stc(raw, src)
# simulate data with cHPI on
with pytest.deprecated_call():
raw_sim = simulate_raw(raw, stc, None, src, sphere, cov=None,
head_pos=pos_fname, interp='zero')
# need to trim extra samples off this one
with pytest.deprecated_call():
raw_chpi = simulate_raw(raw, stc, None, src, sphere, cov=None,
chpi=True, head_pos=pos_fname, interp='zero')
# test cHPI indication
hpi_freqs, hpi_pick, hpi_ons = _get_hpi_info(raw.info)
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[:3], picks_eeg[:3]]:
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 (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, t_step_min=10.)
quats = read_head_pos(pos_fname)
_assert_quats(quats, quats_sim, dist_tol=5e-3, angle_tol=3.5)
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_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)
def get_headposition(self):
COMMAND = [
"ssh",
"%s" % self.host, 'maxfilter', '-f', self.filename, '-hp',
self.posfile, '-headpos', '-o', self.fname_out, '-force'
]
p = subprocess.Popen(COMMAND,
shell=False,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
(output, err) = p.communicate()
if output.split()[-6] == 'successfully':
head_pos = read_head_pos(self.posfile)
head_pos[:, 0] += self.raw.first_samp / self.raw.info['sfreq']
silentremove(self.fname_out)
self.head_pos = head_pos
return self.head_pos
else:
print err
return None
def test_calculate_chpi_positions():
"""Test calculation of cHPI positions."""
# Check to make sure our fits match MF decently
mf_quats = read_head_pos(pos_fname)
raw = read_raw_fif(chpi_fif_fname, allow_maxshield='yes', preload=True)
# This is a little hack (aliasing while decimating) to make it much faster
# for testing purposes only. We can relax this later if we find it breaks
# something.
raw_dec = _decimate_chpi(raw, 15)
with catch_logging() as log:
py_quats = _calculate_chpi_positions(raw_dec, verbose='debug')
assert_true(log.getvalue().startswith('HPIFIT'))
_assert_quats(py_quats, mf_quats, dist_tol=0.004, angle_tol=2.5)
# degenerate conditions
raw_no_chpi = read_raw_fif(test_fif_fname)
assert_raises(RuntimeError, _calculate_chpi_positions, raw_no_chpi)
raw_bad = raw.copy()
for d in raw_bad.info['dig']:
if d['kind'] == FIFF.FIFFV_POINT_HPI:
d['coord_frame'] = 999
break
assert_raises(RuntimeError, _calculate_chpi_positions, raw_bad)
raw_bad = raw.copy()
for d in raw_bad.info['dig']:
if d['kind'] == FIFF.FIFFV_POINT_HPI:
d['r'] = np.ones(3)
raw_bad.crop(0, 1.)
with warnings.catch_warnings(record=True): # bad pos
with catch_logging() as log_file:
_calculate_chpi_positions(raw_bad, t_step_min=5., verbose=True)
# ignore HPI info header and [done] footer
assert_true('0/5 good' in log_file.getvalue().strip().split('\n')[-2])
# half the rate cuts off cHPI coils
raw.info['lowpass'] /= 2.
assert_raises_regex(RuntimeError, 'above the',
_calculate_chpi_positions, raw)
def test_simulate_raw_chpi():
"""Test simulation of raw data with cHPI."""
raw = read_raw_fif(raw_chpi_fname, allow_maxshield='yes')
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)
quats = read_head_pos(pos_fname)
_assert_quats(quats, quats_sim, dist_tol=0.006, angle_tol=4)
def test_movement_compensation():
"""Test movement compensation"""
lims = (0, 8)
with warnings.catch_warnings(record=True): # maxshield
raw = Raw(raw_fname, allow_maxshield=True, preload=True).crop(*lims)
head_pos = read_head_pos(pos_fname)
#
# Movement compensation, no regularization, no tSSS
#
raw_sss = maxwell_filter(raw,
head_pos=head_pos,
origin=mf_head_origin,
regularize=None,
bad_condition='ignore')
assert_meg_snr(raw_sss,
Raw(sss_movecomp_fname).crop(*lims),
4.6,
12.4,
chpi_med_tol=58)
#
# Movement compensation, regularization, no tSSS
#
raw_sss = maxwell_filter(raw, head_pos=head_pos, origin=mf_head_origin)
assert_meg_snr(raw_sss,
Raw(sss_movecomp_reg_in_fname).crop(*lims),
0.7,
1.9,
chpi_med_tol=121)
#
# Movement compensation, regularization, tSSS at the end
#
raw_nohpi = filter_chpi(raw.copy())
with warnings.catch_warnings(record=True) as w: # untested feature
raw_sss_mv = maxwell_filter(raw_nohpi,
head_pos=head_pos,
st_duration=4.,
origin=mf_head_origin,
st_fixed=False)
assert_equal(len(w), 1)
assert_true('is untested' in str(w[0].message))
# Neither match is particularly good because our algorithm actually differs
assert_meg_snr(raw_sss_mv,
Raw(sss_movecomp_reg_in_st4s_fname).crop(*lims), 0.6, 1.3)
tSSS_fname = op.join(sss_path, 'test_move_anon_st4s_raw_sss.fif')
assert_meg_snr(raw_sss_mv,
Raw(tSSS_fname).crop(*lims),
0.6,
1.0,
chpi_med_tol=None)
assert_meg_snr(Raw(sss_movecomp_reg_in_st4s_fname),
Raw(tSSS_fname),
0.8,
1.0,
chpi_med_tol=None)
#
# Movement compensation, regularization, tSSS at the beginning
#
raw_sss_mc = maxwell_filter(raw_nohpi,
head_pos=head_pos,
st_duration=4.,
origin=mf_head_origin)
assert_meg_snr(raw_sss_mc,
Raw(tSSS_fname).crop(*lims),
0.6,
1.0,
chpi_med_tol=None)
assert_meg_snr(raw_sss_mc, raw_sss_mv, 0.6, 1.4)
# some degenerate cases
with warnings.catch_warnings(record=True): # maxshield
raw_erm = Raw(erm_fname, allow_maxshield=True)
assert_raises(ValueError,
maxwell_filter,
raw_erm,
coord_frame='meg',
head_pos=head_pos) # can't do ERM file
head_pos_bad = head_pos[:, :9]
assert_raises(ValueError, maxwell_filter, raw,
head_pos=head_pos_bad) # bad shape
head_pos_bad = 'foo'
assert_raises(TypeError, maxwell_filter, raw,
head_pos=head_pos_bad) # bad type
head_pos_bad = head_pos[::-1]
assert_raises(ValueError, maxwell_filter, raw, head_pos=head_pos_bad)
head_pos_bad = head_pos.copy()
head_pos_bad[0, 0] = 1. # bad time given the first_samp...
assert_raises(ValueError, maxwell_filter, raw, head_pos=head_pos_bad)
def test_movement_compensation(tmpdir):
"""Test movement compensation."""
temp_dir = str(tmpdir)
lims = (0, 4)
raw = read_crop(raw_fname, lims).load_data()
head_pos = read_head_pos(pos_fname)
#
# Movement compensation, no regularization, no tSSS
#
raw_sss = maxwell_filter(raw, head_pos=head_pos, origin=mf_head_origin,
regularize=None, bad_condition='ignore')
assert_meg_snr(raw_sss, read_crop(sss_movecomp_fname, lims),
4.6, 12.4, chpi_med_tol=58)
# IO
temp_fname = op.join(temp_dir, 'test_raw_sss.fif')
raw_sss.save(temp_fname)
raw_sss = read_crop(temp_fname)
assert_meg_snr(raw_sss, read_crop(sss_movecomp_fname, lims),
4.6, 12.4, chpi_med_tol=58)
#
# Movement compensation, regularization, no tSSS
#
raw_sss = maxwell_filter(raw, head_pos=head_pos, origin=mf_head_origin)
assert_meg_snr(raw_sss, read_crop(sss_movecomp_reg_in_fname, lims),
0.5, 1.9, chpi_med_tol=121)
#
# Movement compensation, regularization, tSSS at the end
#
raw_nohpi = filter_chpi(raw.copy(), t_window=0.2)
with pytest.warns(RuntimeWarning, match='untested'):
raw_sss_mv = maxwell_filter(raw_nohpi, head_pos=head_pos,
st_duration=4., origin=mf_head_origin,
st_fixed=False)
# Neither match is particularly good because our algorithm actually differs
assert_meg_snr(raw_sss_mv, read_crop(sss_movecomp_reg_in_st4s_fname, lims),
0.6, 1.3)
tSSS_fname = op.join(sss_path, 'test_move_anon_st4s_raw_sss.fif')
assert_meg_snr(raw_sss_mv, read_crop(tSSS_fname, lims),
0.6, 1.0, chpi_med_tol=None)
assert_meg_snr(read_crop(sss_movecomp_reg_in_st4s_fname),
read_crop(tSSS_fname), 0.8, 1.0, chpi_med_tol=None)
#
# Movement compensation, regularization, tSSS at the beginning
#
raw_sss_mc = maxwell_filter(raw_nohpi, head_pos=head_pos, st_duration=4.,
origin=mf_head_origin)
assert_meg_snr(raw_sss_mc, read_crop(tSSS_fname, lims),
0.6, 1.0, chpi_med_tol=None)
assert_meg_snr(raw_sss_mc, raw_sss_mv, 0.6, 1.4)
# some degenerate cases
raw_erm = read_crop(erm_fname)
pytest.raises(ValueError, maxwell_filter, raw_erm, coord_frame='meg',
head_pos=head_pos) # can't do ERM file
pytest.raises(ValueError, maxwell_filter, raw,
head_pos=head_pos[:, :9]) # bad shape
pytest.raises(TypeError, maxwell_filter, raw, head_pos='foo') # bad type
pytest.raises(ValueError, maxwell_filter, raw, head_pos=head_pos[::-1])
head_pos_bad = head_pos.copy()
head_pos_bad[0, 0] = raw._first_time - 1e-2
pytest.raises(ValueError, maxwell_filter, raw, head_pos=head_pos_bad)
head_pos_bad = head_pos.copy()
head_pos_bad[0, 4] = 1. # off by more than 1 m
with pytest.warns(RuntimeWarning, match='greater than 1 m'):
maxwell_filter(raw.copy().crop(0, 0.1), head_pos=head_pos_bad,
bad_condition='ignore')
# make sure numerical error doesn't screw it up, though
head_pos_bad = head_pos.copy()
head_pos_bad[0, 0] = raw._first_time - 5e-4
raw_sss_tweak = maxwell_filter(
raw.copy().crop(0, 0.05), head_pos=head_pos_bad, origin=mf_head_origin)
assert_meg_snr(raw_sss_tweak, raw_sss.copy().crop(0, 0.05), 1.4, 8.,
chpi_med_tol=5)
def test_movement_compensation():
"""Test movement compensation"""
temp_dir = _TempDir()
lims = (0, 4)
raw = Raw(raw_fname, allow_maxshield='yes', preload=True).crop(*lims)
head_pos = read_head_pos(pos_fname)
#
# Movement compensation, no regularization, no tSSS
#
raw_sss = maxwell_filter(raw, head_pos=head_pos, origin=mf_head_origin,
regularize=None, bad_condition='ignore')
assert_meg_snr(raw_sss, Raw(sss_movecomp_fname).crop(*lims),
4.6, 12.4, chpi_med_tol=58)
# IO
temp_fname = op.join(temp_dir, 'test_raw_sss.fif')
raw_sss.save(temp_fname)
raw_sss = Raw(temp_fname)
assert_meg_snr(raw_sss, Raw(sss_movecomp_fname).crop(*lims),
4.6, 12.4, chpi_med_tol=58)
#
# Movement compensation, regularization, no tSSS
#
raw_sss = maxwell_filter(raw, head_pos=head_pos, origin=mf_head_origin)
assert_meg_snr(raw_sss, Raw(sss_movecomp_reg_in_fname).crop(*lims),
0.5, 1.9, chpi_med_tol=121)
#
# Movement compensation, regularization, tSSS at the end
#
raw_nohpi = filter_chpi(raw.copy())
with warnings.catch_warnings(record=True) as w: # untested feature
raw_sss_mv = maxwell_filter(raw_nohpi, head_pos=head_pos,
st_duration=4., origin=mf_head_origin,
st_fixed=False)
assert_equal(len(w), 1)
assert_true('is untested' in str(w[0].message))
# Neither match is particularly good because our algorithm actually differs
assert_meg_snr(raw_sss_mv, Raw(sss_movecomp_reg_in_st4s_fname).crop(*lims),
0.6, 1.3)
tSSS_fname = op.join(sss_path, 'test_move_anon_st4s_raw_sss.fif')
assert_meg_snr(raw_sss_mv, Raw(tSSS_fname).crop(*lims),
0.6, 1.0, chpi_med_tol=None)
assert_meg_snr(Raw(sss_movecomp_reg_in_st4s_fname), Raw(tSSS_fname),
0.8, 1.0, chpi_med_tol=None)
#
# Movement compensation, regularization, tSSS at the beginning
#
raw_sss_mc = maxwell_filter(raw_nohpi, head_pos=head_pos, st_duration=4.,
origin=mf_head_origin)
assert_meg_snr(raw_sss_mc, Raw(tSSS_fname).crop(*lims),
0.6, 1.0, chpi_med_tol=None)
assert_meg_snr(raw_sss_mc, raw_sss_mv, 0.6, 1.4)
# some degenerate cases
raw_erm = Raw(erm_fname, allow_maxshield='yes')
assert_raises(ValueError, maxwell_filter, raw_erm, coord_frame='meg',
head_pos=head_pos) # can't do ERM file
assert_raises(ValueError, maxwell_filter, raw,
head_pos=head_pos[:, :9]) # bad shape
assert_raises(TypeError, maxwell_filter, raw, head_pos='foo') # bad type
assert_raises(ValueError, maxwell_filter, raw, head_pos=head_pos[::-1])
head_pos_bad = head_pos.copy()
head_pos_bad[0, 0] = raw.first_samp / raw.info['sfreq'] - 1e-2
assert_raises(ValueError, maxwell_filter, raw, head_pos=head_pos_bad)
# make sure numerical error doesn't screw it up, though
head_pos_bad[0, 0] = raw.first_samp / raw.info['sfreq'] - 1e-4
raw_sss_tweak = maxwell_filter(raw, head_pos=head_pos_bad,
origin=mf_head_origin)
assert_meg_snr(raw_sss_tweak, raw_sss, 2., 10.)
def test_calculate_chpi_positions_artemis():
"""Test on 5k artemis data."""
raw = read_raw_artemis123(art_fname, preload=True)
mf_quats = read_head_pos(art_mc_fname)
py_quats = _calculate_chpi_positions(raw, t_step_min=2., verbose='debug')
_assert_quats(py_quats, mf_quats, dist_tol=0.001, angle_tol=1.)
def test_movement_compensation():
"""Test movement compensation."""
temp_dir = _TempDir()
lims = (0, 4)
raw = read_crop(raw_fname, lims).load_data()
head_pos = read_head_pos(pos_fname)
#
# Movement compensation, no regularization, no tSSS
#
raw_sss = maxwell_filter(raw, head_pos=head_pos, origin=mf_head_origin,
regularize=None, bad_condition='ignore')
assert_meg_snr(raw_sss, read_crop(sss_movecomp_fname, lims),
4.6, 12.4, chpi_med_tol=58)
# IO
temp_fname = op.join(temp_dir, 'test_raw_sss.fif')
raw_sss.save(temp_fname)
raw_sss = read_crop(temp_fname)
assert_meg_snr(raw_sss, read_crop(sss_movecomp_fname, lims),
4.6, 12.4, chpi_med_tol=58)
#
# Movement compensation, regularization, no tSSS
#
raw_sss = maxwell_filter(raw, head_pos=head_pos, origin=mf_head_origin)
assert_meg_snr(raw_sss, read_crop(sss_movecomp_reg_in_fname, lims),
0.5, 1.9, chpi_med_tol=121)
#
# Movement compensation, regularization, tSSS at the end
#
raw_nohpi = filter_chpi(raw.copy())
with pytest.warns(RuntimeWarning, match='untested'):
raw_sss_mv = maxwell_filter(raw_nohpi, head_pos=head_pos,
st_duration=4., origin=mf_head_origin,
st_fixed=False)
# Neither match is particularly good because our algorithm actually differs
assert_meg_snr(raw_sss_mv, read_crop(sss_movecomp_reg_in_st4s_fname, lims),
0.6, 1.3)
tSSS_fname = op.join(sss_path, 'test_move_anon_st4s_raw_sss.fif')
assert_meg_snr(raw_sss_mv, read_crop(tSSS_fname, lims),
0.6, 1.0, chpi_med_tol=None)
assert_meg_snr(read_crop(sss_movecomp_reg_in_st4s_fname),
read_crop(tSSS_fname), 0.8, 1.0, chpi_med_tol=None)
#
# Movement compensation, regularization, tSSS at the beginning
#
raw_sss_mc = maxwell_filter(raw_nohpi, head_pos=head_pos, st_duration=4.,
origin=mf_head_origin)
assert_meg_snr(raw_sss_mc, read_crop(tSSS_fname, lims),
0.6, 1.0, chpi_med_tol=None)
assert_meg_snr(raw_sss_mc, raw_sss_mv, 0.6, 1.4)
# some degenerate cases
raw_erm = read_crop(erm_fname)
pytest.raises(ValueError, maxwell_filter, raw_erm, coord_frame='meg',
head_pos=head_pos) # can't do ERM file
pytest.raises(ValueError, maxwell_filter, raw,
head_pos=head_pos[:, :9]) # bad shape
pytest.raises(TypeError, maxwell_filter, raw, head_pos='foo') # bad type
pytest.raises(ValueError, maxwell_filter, raw, head_pos=head_pos[::-1])
head_pos_bad = head_pos.copy()
head_pos_bad[0, 0] = raw._first_time - 1e-2
pytest.raises(ValueError, maxwell_filter, raw, head_pos=head_pos_bad)
head_pos_bad = head_pos.copy()
head_pos_bad[0, 4] = 1. # off by more than 1 m
with pytest.warns(RuntimeWarning, match='greater than 1 m'):
maxwell_filter(raw.copy().crop(0, 0.1), head_pos=head_pos_bad,
bad_condition='ignore')
# make sure numerical error doesn't screw it up, though
head_pos_bad = head_pos.copy()
head_pos_bad[0, 0] = raw._first_time - 5e-4
raw_sss_tweak = maxwell_filter(
raw.copy().crop(0, 0.05), head_pos=head_pos_bad, origin=mf_head_origin)
assert_meg_snr(raw_sss_tweak, raw_sss.copy().crop(0, 0.05), 1.4, 8.,
chpi_med_tol=5)
def test_movement_compensation():
"""Test movement compensation."""
temp_dir = _TempDir()
lims = (0, 4)
raw = read_crop(raw_fname, lims).load_data()
head_pos = read_head_pos(pos_fname)
#
# Movement compensation, no regularization, no tSSS
#
raw_sss = maxwell_filter(raw,
head_pos=head_pos,
origin=mf_head_origin,
regularize=None,
bad_condition='ignore')
assert_meg_snr(raw_sss,
read_crop(sss_movecomp_fname, lims),
4.6,
12.4,
chpi_med_tol=58)
# IO
temp_fname = op.join(temp_dir, 'test_raw_sss.fif')
raw_sss.save(temp_fname)
raw_sss = read_crop(temp_fname)
assert_meg_snr(raw_sss,
read_crop(sss_movecomp_fname, lims),
4.6,
12.4,
chpi_med_tol=58)
#
# Movement compensation, regularization, no tSSS
#
raw_sss = maxwell_filter(raw, head_pos=head_pos, origin=mf_head_origin)
assert_meg_snr(raw_sss,
read_crop(sss_movecomp_reg_in_fname, lims),
0.5,
1.9,
chpi_med_tol=121)
#
# Movement compensation, regularization, tSSS at the end
#
raw_nohpi = filter_chpi(raw.copy())
with warnings.catch_warnings(record=True) as w: # untested feature
raw_sss_mv = maxwell_filter(raw_nohpi,
head_pos=head_pos,
st_duration=4.,
origin=mf_head_origin,
st_fixed=False)
assert_equal(len(w), 1)
assert_true('is untested' in str(w[0].message))
# Neither match is particularly good because our algorithm actually differs
assert_meg_snr(raw_sss_mv, read_crop(sss_movecomp_reg_in_st4s_fname, lims),
0.6, 1.3)
tSSS_fname = op.join(sss_path, 'test_move_anon_st4s_raw_sss.fif')
assert_meg_snr(raw_sss_mv,
read_crop(tSSS_fname, lims),
0.6,
1.0,
chpi_med_tol=None)
assert_meg_snr(read_crop(sss_movecomp_reg_in_st4s_fname),
read_crop(tSSS_fname),
0.8,
1.0,
chpi_med_tol=None)
#
# Movement compensation, regularization, tSSS at the beginning
#
raw_sss_mc = maxwell_filter(raw_nohpi,
head_pos=head_pos,
st_duration=4.,
origin=mf_head_origin)
assert_meg_snr(raw_sss_mc,
read_crop(tSSS_fname, lims),
0.6,
1.0,
chpi_med_tol=None)
assert_meg_snr(raw_sss_mc, raw_sss_mv, 0.6, 1.4)
# some degenerate cases
raw_erm = read_crop(erm_fname)
assert_raises(ValueError,
maxwell_filter,
raw_erm,
coord_frame='meg',
head_pos=head_pos) # can't do ERM file
assert_raises(ValueError, maxwell_filter, raw,
head_pos=head_pos[:, :9]) # bad shape
assert_raises(TypeError, maxwell_filter, raw, head_pos='foo') # bad type
assert_raises(ValueError, maxwell_filter, raw, head_pos=head_pos[::-1])
head_pos_bad = head_pos.copy()
head_pos_bad[0, 0] = raw.first_samp / raw.info['sfreq'] - 1e-2
assert_raises(ValueError, maxwell_filter, raw, head_pos=head_pos_bad)
head_pos_bad = head_pos.copy()
head_pos_bad[0, 4] = 1. # off by more than 1 m
with warnings.catch_warnings(record=True) as w:
maxwell_filter(raw.copy().crop(0, 0.1),
head_pos=head_pos_bad,
bad_condition='ignore')
assert_true(any('greater than 1 m' in str(ww.message) for ww in w))
# make sure numerical error doesn't screw it up, though
head_pos_bad = head_pos.copy()
head_pos_bad[0, 0] = raw.first_samp / raw.info['sfreq'] - 5e-4
raw_sss_tweak = maxwell_filter(raw.copy().crop(0, 0.05),
head_pos=head_pos_bad,
origin=mf_head_origin)
assert_meg_snr(raw_sss_tweak,
raw_sss.copy().crop(0, 0.05),
1.4,
8.,
chpi_med_tol=5)
def test_movement_compensation():
"""Test movement compensation"""
lims = (0, 8)
with warnings.catch_warnings(record=True): # maxshield
raw = Raw(raw_fname, allow_maxshield=True, preload=True).crop(*lims)
head_pos = read_head_pos(pos_fname)
#
# Movement compensation, no regularization, no tSSS
#
raw_sss = maxwell_filter(raw, head_pos=head_pos, origin=mf_head_origin,
regularize=None, bad_condition='ignore')
assert_meg_snr(raw_sss, Raw(sss_movecomp_fname).crop(*lims),
4.6, 12.4, chpi_med_tol=58)
#
# Movement compensation, regularization, no tSSS
#
raw_sss = maxwell_filter(raw, head_pos=head_pos, origin=mf_head_origin)
assert_meg_snr(raw_sss, Raw(sss_movecomp_reg_in_fname).crop(*lims),
0.7, 1.9, chpi_med_tol=121)
#
# Movement compensation, regularization, tSSS at the end
#
raw_nohpi = filter_chpi(raw.copy())
with warnings.catch_warnings(record=True) as w: # untested feature
raw_sss_mv = maxwell_filter(raw_nohpi, head_pos=head_pos,
st_duration=4., origin=mf_head_origin,
st_fixed=False)
assert_equal(len(w), 1)
assert_true('is untested' in str(w[0].message))
# Neither match is particularly good because our algorithm actually differs
assert_meg_snr(raw_sss_mv, Raw(sss_movecomp_reg_in_st4s_fname).crop(*lims),
0.6, 1.3)
tSSS_fname = op.join(sss_path, 'test_move_anon_st4s_raw_sss.fif')
assert_meg_snr(raw_sss_mv, Raw(tSSS_fname).crop(*lims),
0.6, 1.0, chpi_med_tol=None)
assert_meg_snr(Raw(sss_movecomp_reg_in_st4s_fname), Raw(tSSS_fname),
0.8, 1.0, chpi_med_tol=None)
#
# Movement compensation, regularization, tSSS at the beginning
#
raw_sss_mc = maxwell_filter(raw_nohpi, head_pos=head_pos, st_duration=4.,
origin=mf_head_origin)
assert_meg_snr(raw_sss_mc, Raw(tSSS_fname).crop(*lims),
0.6, 1.0, chpi_med_tol=None)
assert_meg_snr(raw_sss_mc, raw_sss_mv, 0.6, 1.4)
# some degenerate cases
with warnings.catch_warnings(record=True): # maxshield
raw_erm = Raw(erm_fname, allow_maxshield=True)
assert_raises(ValueError, maxwell_filter, raw_erm, coord_frame='meg',
head_pos=head_pos) # can't do ERM file
head_pos_bad = head_pos[:, :9]
assert_raises(ValueError, maxwell_filter, raw,
head_pos=head_pos_bad) # bad shape
head_pos_bad = 'foo'
assert_raises(TypeError, maxwell_filter, raw,
head_pos=head_pos_bad) # bad type
head_pos_bad = head_pos[::-1]
assert_raises(ValueError, maxwell_filter, raw,
head_pos=head_pos_bad)
head_pos_bad = head_pos.copy()
head_pos_bad[0, 0] = 1. # bad time given the first_samp...
assert_raises(ValueError, maxwell_filter, raw, head_pos=head_pos_bad)
