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# -*- coding: utf-8 -*-
# Authors: Alex Rockhill <aprockhill@mailbox.org>
#
# License: BSD-3-clause
import os.path as op
import numpy as np
from numpy.testing import assert_allclose
import pytest
import mne
from mne.datasets import testing
from mne.transforms import apply_trans
from mne.utils import requires_nibabel, requires_version, use_log_level
from mne.viz.utils import _fake_click
data_path = testing.data_path(download=False)
subject = 'sample'
subjects_dir = op.join(data_path, 'subjects')
sample_dir = op.join(data_path, 'MEG', subject)
raw_path = op.join(sample_dir, 'sample_audvis_trunc_raw.fif')
fname_trans = op.join(sample_dir, 'sample_audvis_trunc-trans.fif')
@requires_nibabel()
@pytest.fixture
def _fake_CT_coords(skull_size=5, contact_size=2):
"""Make somewhat realistic CT data with contacts."""
import nibabel as nib
brain = nib.load(
op.join(subjects_dir, subject, 'mri', 'brain.mgz'))
verts = mne.read_surface(
op.join(subjects_dir, subject, 'bem', 'outer_skull.surf'))[0]
verts = apply_trans(np.linalg.inv(brain.header.get_vox2ras_tkr()), verts)
x, y, z = np.array(brain.shape).astype(int) // 2
coords = [(x, y - 14, z), (x - 10, y - 15, z),
(x - 20, y - 16, z + 1), (x - 30, y - 16, z + 1)]
center = np.array(brain.shape) / 2
# make image
np.random.seed(99)
ct_data = np.random.random(brain.shape).astype(np.float32) * 100
# make skull
for vert in verts:
x, y, z = np.round(vert).astype(int)
ct_data[slice(x - skull_size, x + skull_size + 1),
slice(y - skull_size, y + skull_size + 1),
slice(z - skull_size, z + skull_size + 1)] = 1000
# add electrode with contacts
for (x, y, z) in coords:
# make sure not in skull
assert np.linalg.norm(center - np.array((x, y, z))) < 50
ct_data[slice(x - contact_size, x + contact_size + 1),
slice(y - contact_size, y + contact_size + 1),
slice(z - contact_size, z + contact_size + 1)] = \
1000 - np.linalg.norm(np.array(np.meshgrid(
*[range(-contact_size, contact_size + 1)] * 3)), axis=0)
ct = nib.MGHImage(ct_data, brain.affine)
coords = apply_trans(ct.header.get_vox2ras_tkr(), np.array(coords))
return ct, coords
@pytest.fixture
def _locate_ieeg(renderer_interactive_pyvistaqt):
# Use a fixture to create these classes so we can ensure that they
# are closed at the end of the test
guis = list()
def fun(*args, **kwargs):
guis.append(mne.gui.locate_ieeg(*args, **kwargs))
return guis[-1]
yield fun
for gui in guis:
try:
gui.close()
except Exception:
pass
def test_ieeg_elec_locate_io(_locate_ieeg):
"""Test the input/output of the intracranial location GUI."""
import nibabel as nib
info = mne.create_info([], 1000)
aligned_ct = nib.MGHImage(np.zeros((256, 256, 256), dtype=np.float32),
np.eye(4))
trans = mne.transforms.Transform('head', 'mri')
with pytest.raises(ValueError,
match='No channels found in `info` to locate'):
_locate_ieeg(info, trans, aligned_ct, subject, subjects_dir)
@requires_version('sphinx_gallery')
@testing.requires_testing_data
def test_locate_scraper(_locate_ieeg, _fake_CT_coords, tmp_path):
"""Test sphinx-gallery scraping of the GUI."""
raw = mne.io.read_raw_fif(raw_path)
raw.pick_types(eeg=True)
ch_dict = {'EEG 001': 'LAMY 1', 'EEG 002': 'LAMY 2',
'EEG 003': 'LSTN 1', 'EEG 004': 'LSTN 2'}
raw.pick_channels(list(ch_dict.keys()))
raw.rename_channels(ch_dict)
raw.set_montage(None)
aligned_ct, _ = _fake_CT_coords
trans = mne.read_trans(fname_trans)
with pytest.warns(RuntimeWarning, match='`pial` surface not found'):
gui = _locate_ieeg(raw.info, trans, aligned_ct,
subject=subject, subjects_dir=subjects_dir)
(tmp_path / '_images').mkdir()
image_path = str(tmp_path / '_images' / 'temp.png')
gallery_conf = dict(builder_name='html', src_dir=str(tmp_path))
block_vars = dict(
example_globals=dict(gui=gui),
image_path_iterator=iter([image_path]))
assert not op.isfile(image_path)
assert not getattr(gui, '_scraped', False)
mne.gui._GUIScraper()(None, block_vars, gallery_conf)
assert op.isfile(image_path)
assert gui._scraped
@testing.requires_testing_data
def test_ieeg_elec_locate_display(_locate_ieeg, _fake_CT_coords):
"""Test that the intracranial location GUI displays properly."""
raw = mne.io.read_raw_fif(raw_path, preload=True)
raw.pick_types(eeg=True)
ch_dict = {'EEG 001': 'LAMY 1', 'EEG 002': 'LAMY 2',
'EEG 003': 'LSTN 1', 'EEG 004': 'LSTN 2'}
raw.pick_channels(list(ch_dict.keys()))
raw.rename_channels(ch_dict)
raw.set_eeg_reference('average')
raw.set_channel_types({name: 'seeg' for name in raw.ch_names})
raw.set_montage(None)
aligned_ct, coords = _fake_CT_coords
trans = mne.read_trans(fname_trans)
with pytest.warns(RuntimeWarning, match='`pial` surface not found'):
gui = _locate_ieeg(raw.info, trans, aligned_ct,
subject=subject, subjects_dir=subjects_dir,
verbose=True)
with pytest.raises(ValueError, match='read-only'):
gui._ras[:] = coords[0] # start in the right position
gui._set_ras(coords[0])
gui._mark_ch()
assert not gui._lines and not gui._lines_2D # no lines for one contact
for ci, coord in enumerate(coords[1:], 1):
coord_vox = apply_trans(gui._ras_vox_t, coord)
with use_log_level('debug'):
_fake_click(gui._figs[2], gui._figs[2].axes[0],
coord_vox[:-1], xform='data', kind='release')
assert_allclose(coord[:2], gui._ras[:2], atol=0.1,
err_msg=f'coords[{ci}][:2]')
assert_allclose(coord[2], gui._ras[2], atol=2,
err_msg=f'coords[{ci}][2]')
gui._mark_ch()
# ensure a 3D line was made for each group
assert len(gui._lines) == 2
# test snap to center
gui._ch_index = 0
gui._set_ras(coords[0]) # move to first position
gui._mark_ch()
assert_allclose(coords[0], gui._chs['LAMY 1'], atol=0.2)
gui._snap_button.click()
assert gui._snap_button.text() == 'Off'
# now make sure no snap happens
gui._ch_index = 0
gui._set_ras(coords[1] + 1)
gui._mark_ch()
assert_allclose(coords[1] + 1, gui._chs['LAMY 1'], atol=0.01)
# check that it turns back on
gui._snap_button.click()
assert gui._snap_button.text() == 'On'
# test remove
gui._ch_index = 1
gui._update_ch_selection()
gui._remove_ch()
assert np.isnan(gui._chs['LAMY 2']).all()
# check that raw object saved
assert not np.isnan(raw.info['chs'][0]['loc'][:3]).any() # LAMY 1
assert np.isnan(raw.info['chs'][1]['loc'][:3]).all() # LAMY 2 (removed)
# move sliders
gui._alpha_slider.setValue(75)
assert gui._ch_alpha == 0.75
gui._radius_slider.setValue(5)
assert gui._radius == 5
ct_sum_before = np.nansum(gui._images['ct'][0].get_array().data)
gui._ct_min_slider.setValue(500)
assert np.nansum(gui._images['ct'][0].get_array().data) < ct_sum_before
# test buttons
gui._toggle_show_brain()
assert 'mri' in gui._images
assert 'local_max' not in gui._images
gui._toggle_show_max()
assert 'local_max' in gui._images
assert 'mip' not in gui._images
gui._toggle_show_mip()
assert 'mip' in gui._images
assert 'mip_chs' in gui._images
assert len(gui._lines_2D) == 1 # LAMY only has one contact
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