def test_channel_specificity(monkeypatch, tmp_path, fold_files):
raw = read_raw_nirx(fname_nirx_15_3_short, preload=True)
raw.pick(range(2))
kwargs = dict()
n_want = 6
if fold_files is list:
kwargs = dict(fold_files=[foldfile])
elif fold_files is str:
kwargs = dict(fold_files=tmp_path)
n_want *= 2
else:
assert fold_files is None
monkeypatch.setenv('MNE_NIRS_FOLD_PATH', str(tmp_path))
assert len(kwargs) == 0
with pytest.raises(FileNotFoundError, match=r'fold_files\[0\] does.*'):
fold_channel_specificity(raw)
n_want *= 2
copyfile(foldfile, tmp_path / '10-10.xls')
copyfile(foldfile, tmp_path / '10-5.xls')
res = fold_channel_specificity(raw, **kwargs)
assert len(res) == 2
assert res[0].shape == (n_want, 14)
montage = make_standard_montage(
'standard_1005', head_size=0.09700884729534559)
fids = read_fiducials(
Path(mne.__file__).parent / 'data' / 'fsaverage' /
'fsaverage-fiducials.fif')[0]
for f in fids:
f['coord_frame'] = montage.dig[0]['coord_frame']
montage.dig[:3] = fids
S, D = raw.ch_names[0].split()[0].split('_')
assert S == 'S1' and D == 'D2'
montage.rename_channels({'PO8': S, 'P6': D}) # not in the tables!
# taken from standard_1020.elc
s_mri = np.array([55.6666, -97.6251, 2.7300]) / 1000.
d_mri = np.array([67.8877, -75.9043, 28.0910]) / 1000.
trans = mne.transforms._get_trans('fsaverage', 'mri', 'head')[0]
ch_pos = montage.get_positions()['ch_pos']
assert_allclose(ch_pos[S], s_mri, atol=1e-6)
assert_allclose(ch_pos[D], d_mri, atol=1e-6)
raw.set_montage(montage)
montage = transform_to_head(montage)
s_head = mne.transforms.apply_trans(trans, s_mri)
d_head = mne.transforms.apply_trans(trans, d_mri)
assert_allclose(montage._get_ch_pos()['S1'], s_head, atol=1e-6)
assert_allclose(montage._get_ch_pos()['D2'], d_head, atol=1e-6)
for ch in raw.info['chs']:
assert_allclose(ch['loc'][3:6], s_head, atol=1e-6)
assert_allclose(ch['loc'][6:9], d_head, atol=1e-6)
res_1 = fold_channel_specificity(raw, **kwargs)[0]
assert res_1.shape == (0, 14)
# TODO: This is wrong, should be P08 not P08h, and distance should be 0 mm!
with pytest.warns(RuntimeWarning, match='.*PO8h?/P6.*TP8/T8.*'):
res_1 = fold_channel_specificity(raw, interpolate=True, **kwargs)[0]
montage.rename_channels({S: D, D: S}) # reversed
with pytest.warns(RuntimeWarning, match='.*PO8h?/P6.*TP8/T8.*'):
res_2 = fold_channel_specificity(raw, interpolate=True, **kwargs)[0]
# We should check the whole thing, but this is probably good enough
assert (res_1['Specificity'] == res_2['Specificity']).all()
def test_get_mni_fiducials():
"""Test get_mni_fiducials."""
fids, coord_frame = read_fiducials(fid_fname)
assert coord_frame == FIFF.FIFFV_COORD_MRI
assert [f['ident'] for f in fids] == list(range(1, 4))
fids = np.array([f['r'] for f in fids])
fids_est = get_mni_fiducials('sample', subjects_dir)
fids_est = np.array([f['r'] for f in fids_est])
dists = np.linalg.norm(fids - fids_est, axis=-1) * 1000. # -> mm
assert (dists < 8).all(), dists
def test_fiducials_io(tmpdir):
"""Test fiducials i/o."""
pts, coord_frame = read_fiducials(fiducials_fname)
assert pts[0]['coord_frame'] == FIFF.FIFFV_COORD_MRI
assert pts[0]['ident'] == FIFF.FIFFV_POINT_CARDINAL
temp_fname = tmpdir.join('test.fif')
write_fiducials(temp_fname, pts, coord_frame)
pts_1, coord_frame_1 = read_fiducials(temp_fname)
assert coord_frame == coord_frame_1
for pt, pt_1 in zip(pts, pts_1):
assert pt['kind'] == pt_1['kind']
assert pt['ident'] == pt_1['ident']
assert pt['coord_frame'] == pt_1['coord_frame']
assert_array_equal(pt['r'], pt_1['r'])
# test safeguards
pts[0]['coord_frame'] += 1
pytest.raises(ValueError, write_fiducials, temp_fname, pts, coord_frame)
def test_fiducials_io():
"""Test fiducials i/o"""
pts, coord_frame = read_fiducials(fiducials_fname)
assert_equal(pts[0]['coord_frame'], FIFF.FIFFV_COORD_MRI)
assert_equal(pts[0]['ident'], FIFF.FIFFV_POINT_CARDINAL)
temp_fname = op.join(tempdir, 'test.fif')
write_fiducials(temp_fname, pts, coord_frame)
pts_1, coord_frame_1 = read_fiducials(temp_fname)
assert_equal(coord_frame, coord_frame_1)
for pt, pt_1 in zip(pts, pts_1):
assert_equal(pt['kind'], pt_1['kind'])
assert_equal(pt['ident'], pt_1['ident'])
assert_equal(pt['coord_frame'], pt_1['coord_frame'])
assert_array_equal(pt['r'], pt_1['r'])
# test safeguards
pts[0]['coord_frame'] += 1
assert_raises(ValueError, write_fiducials, temp_fname, pts, coord_frame)
def test_fiducials_io():
"""Test fiducials i/o."""
tempdir = _TempDir()
pts, coord_frame = read_fiducials(fiducials_fname)
assert pts[0]['coord_frame'] == FIFF.FIFFV_COORD_MRI
assert pts[0]['ident'] == FIFF.FIFFV_POINT_CARDINAL
temp_fname = op.join(tempdir, 'test.fif')
write_fiducials(temp_fname, pts, coord_frame)
pts_1, coord_frame_1 = read_fiducials(temp_fname)
assert coord_frame == coord_frame_1
for pt, pt_1 in zip(pts, pts_1):
assert pt['kind'] == pt_1['kind']
assert pt['ident'] == pt_1['ident']
assert pt['coord_frame'] == pt_1['coord_frame']
assert_array_equal(pt['r'], pt_1['r'])
# test safeguards
pts[0]['coord_frame'] += 1
pytest.raises(ValueError, write_fiducials, temp_fname, pts, coord_frame)
def test_fiducials_io():
"""Test fiducials i/o."""
tempdir = _TempDir()
pts, coord_frame = read_fiducials(fiducials_fname)
assert_equal(pts[0]["coord_frame"], FIFF.FIFFV_COORD_MRI)
assert_equal(pts[0]["ident"], FIFF.FIFFV_POINT_CARDINAL)
temp_fname = op.join(tempdir, "test.fif")
write_fiducials(temp_fname, pts, coord_frame)
pts_1, coord_frame_1 = read_fiducials(temp_fname)
assert_equal(coord_frame, coord_frame_1)
for pt, pt_1 in zip(pts, pts_1):
assert_equal(pt["kind"], pt_1["kind"])
assert_equal(pt["ident"], pt_1["ident"])
assert_equal(pt["coord_frame"], pt_1["coord_frame"])
assert_array_equal(pt["r"], pt_1["r"])
# test safeguards
pts[0]["coord_frame"] += 1
assert_raises(ValueError, write_fiducials, temp_fname, pts, coord_frame)
def test_fiducials_io(tmp_path):
"""Test fiducials i/o."""
pts, coord_frame = read_fiducials(fiducials_fname)
assert pts[0]['coord_frame'] == FIFF.FIFFV_COORD_MRI
assert pts[0]['ident'] == FIFF.FIFFV_POINT_CARDINAL
temp_fname = tmp_path / 'test.fif'
write_fiducials(temp_fname, pts, coord_frame)
pts_1, coord_frame_1 = read_fiducials(temp_fname)
assert coord_frame == coord_frame_1
for pt, pt_1 in zip(pts, pts_1):
assert pt['kind'] == pt_1['kind']
assert pt['ident'] == pt_1['ident']
assert pt['coord_frame'] == pt_1['coord_frame']
assert_array_equal(pt['r'], pt_1['r'])
assert isinstance(pt, DigPoint)
assert isinstance(pt_1, DigPoint)
# test safeguards
pts[0]['coord_frame'] += 1
with pytest.raises(ValueError, match='coord_frame entries that are incom'):
write_fiducials(temp_fname, pts, coord_frame, overwrite=True)
def test_fiducials():
"""Test handling of fiducials."""
# Eventually the code used here should be unified with montage.py, but for
# now it uses code in odd places
for fname in (fif_fname, ctf_fif_fname):
fids, coord_frame = read_fiducials(fname)
points = _fiducial_coords(fids, coord_frame)
assert points.shape == (3, 3)
# Fids
assert_allclose(points[:, 2], 0., atol=1e-6)
assert_allclose(points[::2, 1], 0., atol=1e-6)
assert points[2, 0] > 0 # RPA
assert points[0, 0] < 0 # LPA
# Nasion
assert_allclose(points[1, 0], 0., atol=1e-6)
assert points[1, 1] > 0
def test_fiducials():
"""Test handling of fiducials."""
# Eventually the code used here should be unified with montage.py, but for
# now it uses code in odd places
for fname in (fif_fname, ctf_fif_fname):
fids, coord_frame = read_fiducials(fname)
points = _fiducial_coords(fids, coord_frame)
assert points.shape == (3, 3)
# Fids
assert_allclose(points[:, 2], 0., atol=1e-6)
assert_allclose(points[::2, 1], 0., atol=1e-6)
assert points[2, 0] > 0 # RPA
assert points[0, 0] < 0 # LPA
# Nasion
assert_allclose(points[1, 0], 0., atol=1e-6)
assert points[1, 1] > 0
def _get_landmarks_from_fiducials_file(*, bids_path, fname, fs_subject,
fs_subjects_dir):
"""Get anatomical landmarks from fiducials file, in MRI voxel space."""
# avoid dicrular imports
from mne_bids.write import (
_get_t1w_mgh, _mri_landmarks_to_mri_voxels, _get_fid_coords
)
digpoints, coord_frame = read_fiducials(fname)
# All of this should be guaranteed, but better be safe than sorry!
assert coord_frame == FIFF.FIFFV_COORD_MRI
assert digpoints[0]['ident'] == FIFF.FIFFV_POINT_LPA
assert digpoints[1]['ident'] == FIFF.FIFFV_POINT_NASION
assert digpoints[2]['ident'] == FIFF.FIFFV_POINT_RPA
montage_loaded = make_dig_montage(
lpa=digpoints[0]['r'],
nasion=digpoints[1]['r'],
rpa=digpoints[2]['r'],
coord_frame='mri'
)
landmark_coords_mri, _ = _get_fid_coords(dig_points=montage_loaded.dig)
landmark_coords_mri = np.asarray(
(landmark_coords_mri['lpa'],
landmark_coords_mri['nasion'],
landmark_coords_mri['rpa'])
)
t1w_mgh = _get_t1w_mgh(fs_subject, fs_subjects_dir)
landmark_coords_voxels = _mri_landmarks_to_mri_voxels(
mri_landmarks=landmark_coords_mri * 1000, # in mm
t1_mgh=t1w_mgh
)
montage_voxels = make_dig_montage(
lpa=landmark_coords_voxels[0],
nasion=landmark_coords_voxels[1],
rpa=landmark_coords_voxels[2],
coord_frame='mri_voxel'
)
return montage_voxels
def test_coreg_class_init(drop_point_kind):
"""Test that Coregistration can be instantiated with various digs."""
fiducials, _ = read_fiducials(fid_fname)
info = read_info(raw_fname)
dig_list = []
eeg_chans = []
for pt in info['dig']:
if pt['kind'] != drop_point_kind:
dig_list.append(pt)
if pt['kind'] == FIFF.FIFFV_POINT_EEG:
eeg_chans.append(f"EEG {pt['ident']:03d}")
this_info = info.copy()
this_info.set_montage(DigMontage(dig=dig_list, ch_names=eeg_chans),
on_missing='ignore')
Coregistration(this_info,
subject='sample',
subjects_dir=subjects_dir,
fiducials=fiducials)
def test_coreg_class_gui_match():
"""Test that using Coregistration matches mne coreg."""
fiducials, _ = read_fiducials(fid_fname)
info = read_info(raw_fname)
coreg = Coregistration(info,
subject='sample',
subjects_dir=subjects_dir,
fiducials=fiducials)
assert_allclose(coreg.trans['trans'], np.eye(4), atol=1e-6)
# mne coreg -s sample -d subjects -f MEG/sample/sample_audvis_trunc_raw.fif
# then "Fit Fid.", Save... to get trans, read_trans:
want_trans = [
[9.99428809e-01, 2.94733196e-02, 1.65350307e-02, -8.76054692e-04],
[-1.92420650e-02, 8.98512006e-01, -4.38526988e-01, 9.39774036e-04],
[-2.77817696e-02, 4.37958330e-01, 8.98565888e-01, -8.29207990e-03],
[0, 0, 0, 1]
]
coreg.set_fid_match('matched')
coreg.fit_fiducials(verbose=True)
assert_allclose(coreg.trans['trans'], want_trans, atol=1e-6)
# Set ICP iterations to one, click "Fit ICP"
want_trans = [
[9.99512792e-01, 2.80128177e-02, 1.37659665e-02, 6.08855276e-04],
[-1.91694051e-02, 8.98992002e-01, -4.37545270e-01, 9.66848747e-04],
[-2.46323701e-02, 4.37068194e-01, 8.99091005e-01, -1.44129358e-02],
[0, 0, 0, 1]
]
coreg.fit_icp(1, verbose=True)
assert_allclose(coreg.trans['trans'], want_trans, atol=1e-6)
# Set ICP iterations to 20, click "Fit ICP"
with catch_logging() as log:
coreg.fit_icp(20, verbose=True)
log = log.getvalue()
want_trans = [
[9.97582495e-01, 2.12266613e-02, 6.61706254e-02, -5.07694029e-04],
[1.81089472e-02, 8.39900672e-01, -5.42437911e-01, 7.81218382e-03],
[-6.70908988e-02, 5.42324841e-01, 8.37485850e-01, -2.50057746e-02],
[0, 0, 0, 1]
]
assert_allclose(coreg.trans['trans'], want_trans, atol=1e-6)
assert 'ICP 19' in log
assert 'ICP 20' not in log # converged on 19
# Change to uniform scale mode, "Fit Fiducials" in scale UI
coreg.set_scale_mode('uniform')
coreg.fit_fiducials()
want_scale = [0.975] * 3
want_trans = [
[9.99428809e-01, 2.94733196e-02, 1.65350307e-02, -9.25998494e-04],
[-1.92420650e-02, 8.98512006e-01, -4.38526988e-01, -1.03350170e-03],
[-2.77817696e-02, 4.37958330e-01, 8.98565888e-01, -9.03170835e-03],
[0, 0, 0, 1]
]
assert_allclose(coreg.scale, want_scale, atol=5e-4)
assert_allclose(coreg.trans['trans'], want_trans, atol=1e-6)
# Click "Fit ICP" in scale UI
with catch_logging() as log:
coreg.fit_icp(20, verbose=True)
log = log.getvalue()
assert 'ICP 18' in log
assert 'ICP 19' not in log
want_scale = [1.036] * 3
want_trans = [
[9.98992383e-01, 1.72388796e-02, 4.14364934e-02, 6.19427126e-04],
[6.80460501e-03, 8.54430079e-01, -5.19521892e-01, 5.58008114e-03],
[-4.43605632e-02, 5.19280374e-01, 8.53451848e-01, -2.03358755e-02],
[0, 0, 0, 1]
]
assert_allclose(coreg.scale, want_scale, atol=5e-4)
assert_allclose(coreg.trans['trans'], want_trans, atol=1e-6)
# Change scale mode to 3-axis, click "Fit ICP" in scale UI
coreg.set_scale_mode('3-axis')
with catch_logging() as log:
coreg.fit_icp(20, verbose=True)
log = log.getvalue()
assert 'ICP 7' in log
assert 'ICP 8' not in log
want_scale = [1.025, 1.010, 1.121]
want_trans = [
[9.98387098e-01, 2.04762165e-02, 5.29526398e-02, 4.97257097e-05],
[1.13287698e-02, 8.42087150e-01, -5.39222538e-01, 7.09863892e-03],
[-5.56319728e-02, 5.38952649e-01, 8.40496957e-01, -1.46372067e-02],
[0, 0, 0, 1]
]
assert_allclose(coreg.scale, want_scale, atol=5e-4)
assert_allclose(coreg.trans['trans'], want_trans, atol=1e-6)
def test_coregistration(scale_mode, ref_scale, grow_hair, fiducials,
fid_match):
"""Test automated coregistration."""
subject = 'sample'
if fiducials is None:
fiducials, coord_frame = read_fiducials(fid_fname)
assert coord_frame == FIFF.FIFFV_COORD_MRI
info = read_info(raw_fname)
for d in info['dig']:
d['r'] = d['r'] * ref_scale
trans = read_trans(trans_fname)
coreg = Coregistration(info,
subject=subject,
subjects_dir=subjects_dir,
fiducials=fiducials)
assert np.allclose(coreg._last_parameters, coreg._parameters)
coreg.set_fid_match(fid_match)
default_params = list(coreg._default_parameters)
coreg.set_rotation(default_params[:3])
coreg.set_translation(default_params[3:6])
coreg.set_scale(default_params[6:9])
coreg.set_grow_hair(grow_hair)
coreg.set_scale_mode(scale_mode)
# Identity transform
errs_id = coreg.compute_dig_mri_distances()
is_scaled = ref_scale != [1., 1., 1.]
id_max = 0.03 if is_scaled and scale_mode == '3-axis' else 0.02
assert 0.005 < np.median(errs_id) < id_max
# Fiducial transform + scale
coreg.fit_fiducials(verbose=True)
assert coreg._extra_points_filter is None
coreg.omit_head_shape_points(distance=0.02)
assert coreg._extra_points_filter is not None
errs_fid = coreg.compute_dig_mri_distances()
assert_array_less(0, errs_fid)
if is_scaled or scale_mode is not None:
fid_max = 0.05
fid_med = 0.02
else:
fid_max = 0.03
fid_med = 0.01
assert_array_less(errs_fid, fid_max)
assert 0.001 < np.median(errs_fid) < fid_med
assert not np.allclose(coreg._parameters, default_params)
coreg.omit_head_shape_points(distance=-1)
coreg.omit_head_shape_points(distance=5. / 1000)
assert coreg._extra_points_filter is not None
# ICP transform + scale
coreg.fit_icp(verbose=True)
assert isinstance(coreg.trans, Transform)
errs_icp = coreg.compute_dig_mri_distances()
assert_array_less(0, errs_icp)
if is_scaled or scale_mode == '3-axis':
icp_max = 0.015
else:
icp_max = 0.01
assert_array_less(errs_icp, icp_max)
assert 0.001 < np.median(errs_icp) < 0.004
assert np.rad2deg(
_angle_between_quats(rot_to_quat(coreg.trans['trans'][:3, :3]),
rot_to_quat(trans['trans'][:3, :3]))) < 13
if scale_mode is None:
atol = 1e-7
else:
atol = 0.35
assert_allclose(coreg._scale, ref_scale, atol=atol)
coreg.reset()
assert_allclose(coreg._parameters, default_params)
from mne.io import read_raw_ctf, read_info, read_fiducials
from mne.coreg import _fiducial_coords, fit_matched_points
from mne.transforms import read_trans, write_trans, Transform
if len(sys.argv) != 2:
print("usage: {} subject".format(sys.argv[0]))
sys.exit(1)
subject = sys.argv[1]
try:
FShome = os.environ['FREESURFER_HOME']
except KeyError:
print("You must set the FREESURFER_HOME environment variable!")
sys.exit(1)
try:
Subjdir = os.environ['SUBJECTS_DIR']
except KeyError:
Subjdir = op.join(FShome, "subjects")
print("Note: Using the default SUBJECTS_DIR:", Subjdir)
name = op.join(Subjdir, subject, "bem", "{}-fiducials.fif".format(subject))
pts, cframe = read_fiducials(name)
fids = _fiducial_coords(pts)
print(fids)
name = op.join(Subjdir, subject, "bem", "{}-trans.fif".format(subject))
t = read_trans(name)
print(t)
if len(sys.argv) != 3:
print("usage: {} subject $ds".format(sys.argv[0]))
sys.exit(1)
subject = sys.argv[1]
dsname = sys.argv[2]
try:
FShome = os.environ['FREESURFER_HOME']
except KeyError:
print("You must set the FREESURFER_HOME environment variable!")
sys.exit(1)
try:
Subjdir = os.environ['SUBJECTS_DIR']
except KeyError:
Subjdir = op.join(FShome, "subjects")
print("Note: Using the default SUBJECTS_DIR:", Subjdir)
name = op.join(Subjdir, subject, "bem", "{}-fiducials.fif".format(subject))
fids = read_fiducials(name)
fidc = _fiducial_coords(fids[0])
raw = read_raw_ctf(dsname, clean_names = True, preload = False)
fidd = _fiducial_coords(raw.info['dig'])
xform = fit_matched_points(fidd, fidc, weights = [1, 10, 1])
t = Transform(FIFF.FIFFV_COORD_HEAD, FIFF.FIFFV_COORD_MRI, xform)
name = op.join(Subjdir, subject, "bem", "{}-trans.fif".format(subject))
write_trans(name, t)