def test_cube(subject_id, subjects_dir, eeg, electrode_names, t_map, affine):
depth_list = seeg.create_depths(electrode_names,
eeg.baseline['eeg'].ch_names,
eeg.electrodes)
brain = seeg.create_depths_plot(depth_list, subject_id, subjects_dir)
seeg.draw_volume(brain.plotter, t_map, affine)
brain.show()
brain.plotter.app.exec_()
def test_create_depth_epi_image_map(subject_id, subjects_dir, eeg,
electrode_names, electrodes, raw, T_x_inv):
values = seeg.create_depth_epi_image_map(eeg, low_freq=120,
high_freq=200)
depth_list = seeg.create_depths(electrode_names, raw.info['ch_names'],
electrodes)
brain = seeg.create_depths_plot(depth_list, subject_id, subjects_dir)
seeg.show_depth_bipolar_values(depth_list, brain.plotter, values[0],
radius=3, affine=T_x_inv)
brain.show()
brain.plotter.app.exec_()
def test_show_depth_bipolar_values(subject_id, subjects_dir, electrode_names,
electrodes, raw, T_x_inv):
depth_list = seeg.create_depths(electrode_names, raw.info['ch_names'],
electrodes)
brain = seeg.create_depths_plot(depth_list, subject_id, subjects_dir)
values = 10*np.random.normal(size=len(raw.info['ch_names']))
radius = 1 + (values - np.min(values))/12
seeg.show_depth_bipolar_values(depth_list, brain.plotter, values, radius,
affine=T_x_inv)
brain.show()
brain.plotter.app.exec_()
def test_create_depths_plot(subject_id, subjects_dir, electrode_names,
electrodes, raw):
depth_list = seeg.create_depths(electrode_names, raw.info['ch_names'],
electrodes)
num_contacts = 0
for depth in depth_list:
num_contacts += depth.num_contacts
values = 10*np.random.normal(size=num_contacts)
colors = seeg.map_colors(values)[:, :3]
brain = seeg.create_depths_plot(depth_list, subject_id, subjects_dir,
contact_colors=colors)
brain.show()
brain.plotter.app.exec_()
def test_show_depth_values(subject_id, subjects_dir, electrode_names,
electrodes, raw, T_x_inv):
depth_list = seeg.create_depths(electrode_names, raw.info['ch_names'],
electrodes)
brain = seeg.create_depths_plot(depth_list, subject_id, subjects_dir)
num_contacts = 0
for depth in depth_list:
num_contacts += depth.num_contacts
values = 10*np.random.normal(size=num_contacts)
radius = 1 + (values - np.min(values))/12
seeg.show_depth_values(depth_list, brain.plotter, values, radius,
affine=T_x_inv)
brain.show()
brain.plotter.app.exec_()
subjects_dir = op.join(data_path, 'subjects')
subject = 'sample'
misc_path = mne.datasets.misc.data_path()
seeg_path = op.join(misc_path, 'seeg')
eeg_file = op.join(seeg_path, 'sample_seeg.edf')
electrode_file = op.join(seeg_path, 'sample_seeg_electrodes.tsv')
eeg = mne.io.read_raw_edf(eeg_file)
electrodes = pd.read_table(electrode_file)
electrodes.rename(columns={'name': 'contact'}, inplace=True)
# electrodes['x'] = (electrodes['x']-10)/1000
# electrodes['y'] = (electrodes['y']-40)/1000
# electrodes['z'] = (electrodes['z']-20)/1000
electrodes['x'] /= 1000
electrodes['y'] /= 1000
electrodes['z'] /= 1000
ELECTRODE_NAMES = [r"L'", r"N'", r"F'", r"O'", r"G'", r"X'"]
ch_names = [
electrodes.contact[i] for i in range(len(electrodes))
if electrodes.contact[i][:2] in ELECTRODE_NAMES
]
depth_list = seeg.create_depths(ELECTRODE_NAMES, ch_names, electrodes)
brain = seeg.create_depths_plot(depth_list, subject, subjects_dir)
mlab.show()
# eeg.plot()
# plt.show()