def _get_data():
"""Helper to get some starting data"""
# raw with ECG channel
raw = Raw(raw_fname).crop(0.0, 5.0).load_data()
data_picks = pick_types(raw.info, meg=True, eeg=True)
other_picks = pick_types(raw.info, meg=False, stim=True, eog=True)
picks = np.sort(np.concatenate((data_picks[::16], other_picks)))
raw = raw.pick_channels([raw.ch_names[p] for p in picks])
ecg = RawArray(np.zeros((1, len(raw.times))), create_info(["ECG 063"], raw.info["sfreq"], "ecg"))
for key in ("dev_head_t", "buffer_size_sec", "highpass", "lowpass", "filename", "dig"):
ecg.info[key] = raw.info[key]
raw.add_channels([ecg])
src = read_source_spaces(src_fname)
trans = read_trans(trans_fname)
sphere = make_sphere_model("auto", "auto", raw.info)
stc = _make_stc(raw, src)
return raw, src, stc, trans, sphere
def _get_data():
"""Helper to get some starting data"""
# raw with ECG channel
raw = Raw(raw_fname).crop(0., 5.0).load_data()
data_picks = pick_types(raw.info, meg=True, eeg=True)
other_picks = pick_types(raw.info, meg=False, stim=True, eog=True)
picks = np.sort(np.concatenate((data_picks[::16], other_picks)))
raw = raw.pick_channels([raw.ch_names[p] for p in picks])
ecg = RawArray(np.zeros((1, len(raw.times))),
create_info(['ECG 063'], raw.info['sfreq'], 'ecg'))
for key in ('dev_head_t', 'buffer_size_sec', 'highpass', 'lowpass',
'filename', 'dig'):
ecg.info[key] = raw.info[key]
raw.add_channels([ecg])
src = read_source_spaces(src_fname)
trans = read_trans(trans_fname)
sphere = make_sphere_model('auto', 'auto', raw.info)
stc = _make_stc(raw, src)
return raw, src, stc, trans, sphere
def _get_data():
"""Helper to get some starting data"""
# raw with ECG channel
raw = Raw(raw_fname).crop(0., 5.0, copy=False).load_data()
data_picks = pick_types(raw.info, meg=True, eeg=True)
other_picks = pick_types(raw.info, meg=False, stim=True, eog=True)
picks = np.sort(np.concatenate((data_picks[::16], other_picks)))
raw = raw.pick_channels([raw.ch_names[p] for p in picks])
ecg = RawArray(np.zeros((1, len(raw.times))),
create_info(['ECG 063'], raw.info['sfreq'], 'ecg'))
for key in ('dev_head_t', 'buffer_size_sec', 'highpass', 'lowpass',
'filename', 'dig'):
ecg.info[key] = raw.info[key]
raw.add_channels([ecg])
src = read_source_spaces(src_fname)
trans = read_trans(trans_fname)
sphere = make_sphere_model('auto', 'auto', raw.info)
stc = _make_stc(raw, src)
return raw, src, stc, trans, sphere
def save_setup(self):
de = self.data_entries.copy()
raw_fname = de.pop('New File').get()
loc_fname = de.pop('Loc File').get()
suffix = raw_fname.split('.')[-1]
if suffix == 'fif':
try:
raw = Raw(raw_fname, preload=False)
except Exception as e:
print(e)
messagebox.showerror('Error', 'Failed to read fif')
return
if loc_fname:
messagebox.showwarning('Warning',
'Ignoring location file given')
elif suffix == 'vhdr':
if not loc_fname:
messagebox.showerror('Error', 'Location file not specified')
try:
raw = read_raw_brainvision(raw_fname,
preload=os.path.join(
self.sub_dirs['tmp'],
'raw_tmp'))
except Exception as e:
print(e)
messagebox.showerror('Error',
'Failed to read BrainVision raw file')
return
try:
montage = read_dig_montage(bvct=loc_fname)
ref_name = [
ch for ch in montage.dig_ch_pos
if not ch in raw.info['ch_names']
]
if len(ref_name) != 1:
ref_name = simpledialog.askstring(
'Reference Channel',
'What is the reference channel name?',
parent=self.root)
else:
ref_name = ref_name[0]
info = create_info([ref_name], raw.info['sfreq'], ['eeg'])
ref = RawArray(np.zeros((1, len(raw.times))), info)
ref.info['lowpass'] = raw.info['lowpass']
raw = raw.add_channels([ref]) #, force_update_info=True)
#
for ch_type in ['eog', 'ecg', 'emg', 'stim']:
chs = [
ch for ch in raw.info['ch_names']
if ch_type in ch.lower()
]
for ch in chs:
ch_ix = raw.ch_names.index(ch)
raw._data[ch_ix, :] *= 1e-6
raw.set_channel_types({ch: ch_type})
raw = raw.set_montage(montage, verbose=False)
except Exception as e:
print(e)
messagebox.showerror(
'Error', 'Failed to read BrainVision location file')
return
else:
messagebox.showerror('Error', 'Unrecognized raw file format')
return
self.save_exp(raw)
def save_setup(self):
de = self.data_entries.copy()
raw_fname = de.pop('Load New File').get()
loc_fname = de.pop('Load Location File').get()
suffix = raw_fname.split('.')[-1]
if suffix == 'fif':
try:
raw = Raw(raw_fname,preload=False)
except Exception as e:
print(e)
messagebox.showerror('Error','Failed to read fif')
return
if loc_fname:
messagebox.showwarning('Warning','Ignoring location file given')
elif suffix == 'vhdr':
if not loc_fname:
messagebox.showerror('Error','Location file not specified')
try:
raw = read_raw_brainvision(raw_fname,
preload=op.join(self.sub_dirs['tmp'],'raw_tmp'))
except Exception as e:
print(e)
messagebox.showerror('Error','Failed to read BrainVision raw file')
return
try:
montage = read_dig_montage(bvct=loc_fname)
ref_name = [ch for ch in montage.dig_ch_pos if not
ch in raw.info['ch_names']]
if len(ref_name) != 1:
ref_name = simpledialog.askstring('Reference Channel',
'What is the reference channel name?',
parent=self.root)
else:
ref_name = ref_name[0]
info = create_info([ref_name], raw.info['sfreq'], ['eeg'])
ref = RawArray(np.zeros((1, len(raw.times))), info)
ref.info['lowpass'] = raw.info['lowpass']
raw = raw.add_channels([ref]) #, force_update_info=True)
#
for ch_type in ['eog','ecg','emg','stim']:
chs = [ch for ch in raw.info['ch_names']
if ch_type in ch.lower()]
for ch in chs:
ch_ix = raw.ch_names.index(ch)
raw._data[ch_ix, :] *= 1e-6
raw.set_channel_types({ch:ch_type})
raw = raw.set_montage(montage,verbose=False)
except Exception as e:
print(e)
messagebox.showerror('Error','Failed to read BrainVision location file')
return
else:
messagebox.showerror('Error','Unrecognized raw file format')
return
self.save_exp(raw)
transf = self.data_entries['Coord Trans fname'].get()
if not op.isfile(transf):
subject = self.data_entries['Subject'].get()
os.environ['SUBJECT'] = subject
fs_dir = self.data_entries['FS Dir'].get()
os.environ['SUBJECTS_DIR'] = fs_dir
messagebox.showinfo(
'Coregistration','In this next interactive GUI, will need to\n' +
'1. Load the pial surface file -> Load Surface -> Select Pial Surface\n' +
'2. Load the subject\'s digitization data: File -> Load digitizer data ->' +
' Select the raw data file for this session\n' +
'3. Open the coordinate alignment window: Adjust -> Coordinate Alignment\n' +
'4. Open the viewer window: View -> Show viewer\n' +
'5. In the coordinate alignment window, click RAP, LAP and Naision, ' +
'and then after clicking each of those click on the corresponing ' +
'fiducial points on the reconstructed head model\n' +
'6. Click align using fiducials\n' +
'7. In the View window: select Options -> Show digitizer data\n'
'8. Adjust the x, y and z coordinates and rotation until ' +
'the alignment is as close to the ground truth as possible\n' +
'If you don\'t know these instructions, feel free to copy and paste')
self.output_to_terminal('mne_analyze')
