def test_brain_timeviewer_traces(renderer_interactive, hemi):
"""Test _TimeViewer traces."""
if renderer_interactive._get_3d_backend() != 'pyvista':
pytest.skip()
brain_data = _create_testing_brain(hemi=hemi)
time_viewer = _TimeViewer(brain_data, show_traces=True)
assert hasattr(time_viewer, "picked_points")
assert hasattr(time_viewer, "_spheres")
# test points picked by default
picked_points = brain_data.get_picked_points()
spheres = time_viewer._spheres
hemi_str = [hemi] if hemi in ('lh', 'rh') else ['lh', 'rh']
for current_hemi in hemi_str:
assert len(picked_points[current_hemi]) == 1
assert len(spheres) == len(hemi_str)
# test removing points
time_viewer.clear_points()
assert len(picked_points['lh']) == 0
assert len(picked_points['rh']) == 0
# test picking a cell at random
for idx, current_hemi in enumerate(hemi_str):
current_mesh = brain_data._hemi_meshes[current_hemi]
cell_id = np.random.randint(0, current_mesh.n_cells)
test_picker = TstVTKPicker(current_mesh, cell_id)
assert cell_id == test_picker.cell_id
assert test_picker.point_id is None
time_viewer.on_pick(test_picker, None)
assert test_picker.point_id is not None
assert len(picked_points[current_hemi]) == 1
assert picked_points[current_hemi][0] == test_picker.point_id
sphere = spheres[idx]
vertex_id = sphere._vertex_id
assert vertex_id == test_picker.point_id
line = sphere._line
hemi_prefix = 'L' if current_hemi == 'lh' else 'R'
hemi_int = 0 if current_hemi == 'lh' else 1
mni = vertex_to_mni(vertices=vertex_id,
hemis=hemi_int,
subject=brain_data._subject_id,
subjects_dir=brain_data._subjects_dir)
label = "{}:{} MNI: {}".format(hemi_prefix,
str(vertex_id).ljust(6),
', '.join('%5.1f' % m for m in mni))
assert line.get_label() == label
assert len(spheres) == len(hemi_str)
def test_brain_traces(renderer_interactive, hemi, src, tmpdir, brain_gc):
"""Test brain traces."""
if renderer_interactive._get_3d_backend() != 'pyvista':
pytest.skip('Only PyVista supports traces')
hemi_str = list()
if src in ('surface', 'vector', 'mixed'):
hemi_str.extend([hemi] if hemi in ('lh', 'rh') else ['lh', 'rh'])
if src in ('mixed', 'volume'):
hemi_str.extend(['vol'])
# label traces
brain = _create_testing_brain(
hemi=hemi,
surf='white',
src=src,
show_traces='label',
volume_options=None, # for speed, don't upsample
n_time=5,
initial_time=0,
)
if src == 'surface':
brain._data['src'] = None # test src=None
if src in ('surface', 'vector', 'mixed'):
assert brain.show_traces
assert brain.traces_mode == 'label'
brain.widgets["extract_mode"].set_value('max')
# test picking a cell at random
rng = np.random.RandomState(0)
for idx, current_hemi in enumerate(hemi_str):
if current_hemi == 'vol':
continue
current_mesh = brain._layered_meshes[current_hemi]._polydata
cell_id = rng.randint(0, current_mesh.n_cells)
test_picker = TstVTKPicker(current_mesh, cell_id, current_hemi,
brain)
assert len(brain.picked_patches[current_hemi]) == 0
brain._on_pick(test_picker, None)
assert len(brain.picked_patches[current_hemi]) == 1
for label_id in list(brain.picked_patches[current_hemi]):
label = brain._annotation_labels[current_hemi][label_id]
assert isinstance(label._line, Line2D)
brain.widgets["extract_mode"].set_value('mean')
brain.clear_glyphs()
assert len(brain.picked_patches[current_hemi]) == 0
brain._on_pick(test_picker, None) # picked and added
assert len(brain.picked_patches[current_hemi]) == 1
brain._on_pick(test_picker, None) # picked again so removed
assert len(brain.picked_patches[current_hemi]) == 0
# test switching from 'label' to 'vertex'
brain.widgets["annotation"].set_value('None')
brain.widgets["extract_mode"].set_value('max')
else: # volume
assert "annotation" not in brain.widgets
assert "extract_mode" not in brain.widgets
brain.close()
# test colormap
if src != 'vector':
brain = _create_testing_brain(
hemi=hemi,
surf='white',
src=src,
show_traces=0.5,
initial_time=0,
volume_options=None, # for speed, don't upsample
n_time=1 if src == 'mixed' else 5,
diverging=True,
add_data_kwargs=dict(colorbar_kwargs=dict(n_labels=3)),
)
# mne_analyze should be chosen
ctab = brain._data['ctable']
assert_array_equal(ctab[0], [0, 255, 255, 255]) # opaque cyan
assert_array_equal(ctab[-1], [255, 255, 0, 255]) # opaque yellow
assert_allclose(ctab[len(ctab) // 2], [128, 128, 128, 0], atol=3)
brain.close()
# vertex traces
brain = _create_testing_brain(
hemi=hemi,
surf='white',
src=src,
show_traces=0.5,
initial_time=0,
volume_options=None, # for speed, don't upsample
n_time=1 if src == 'mixed' else 5,
add_data_kwargs=dict(colorbar_kwargs=dict(n_labels=3)),
)
assert brain.show_traces
assert brain.traces_mode == 'vertex'
assert hasattr(brain, "picked_points")
assert hasattr(brain, "_spheres")
assert brain.plotter.scalar_bar.GetNumberOfLabels() == 3
# add foci should work for volumes
brain.add_foci([[0, 0, 0]], hemi='lh' if src == 'surface' else 'vol')
# test points picked by default
picked_points = brain.get_picked_points()
spheres = brain._spheres
for current_hemi in hemi_str:
assert len(picked_points[current_hemi]) == 1
n_spheres = len(hemi_str)
if hemi == 'split' and src in ('mixed', 'volume'):
n_spheres += 1
assert len(spheres) == n_spheres
# test switching from 'vertex' to 'label'
if src == 'surface':
brain.widgets["annotation"].set_value('aparc')
brain.widgets["annotation"].set_value('None')
# test removing points
brain.clear_glyphs()
assert len(spheres) == 0
for key in ('lh', 'rh', 'vol'):
assert len(picked_points[key]) == 0
# test picking a cell at random
rng = np.random.RandomState(0)
for idx, current_hemi in enumerate(hemi_str):
assert len(spheres) == 0
if current_hemi == 'vol':
current_mesh = brain._data['vol']['grid']
vertices = brain._data['vol']['vertices']
values = current_mesh.cell_arrays['values'][vertices]
cell_id = vertices[np.argmax(np.abs(values))]
else:
current_mesh = brain._layered_meshes[current_hemi]._polydata
cell_id = rng.randint(0, current_mesh.n_cells)
test_picker = TstVTKPicker(None, None, current_hemi, brain)
assert brain._on_pick(test_picker, None) is None
test_picker = TstVTKPicker(current_mesh, cell_id, current_hemi, brain)
assert cell_id == test_picker.cell_id
assert test_picker.point_id is None
brain._on_pick(test_picker, None)
brain._on_pick(test_picker, None)
assert test_picker.point_id is not None
assert len(picked_points[current_hemi]) == 1
assert picked_points[current_hemi][0] == test_picker.point_id
assert len(spheres) > 0
sphere = spheres[-1]
vertex_id = sphere._vertex_id
assert vertex_id == test_picker.point_id
line = sphere._line
hemi_prefix = current_hemi[0].upper()
if current_hemi == 'vol':
assert hemi_prefix + ':' in line.get_label()
assert 'MNI' in line.get_label()
continue # the MNI conversion is more complex
hemi_int = 0 if current_hemi == 'lh' else 1
mni = vertex_to_mni(vertices=vertex_id,
hemis=hemi_int,
subject=brain._subject_id,
subjects_dir=brain._subjects_dir)
label = "{}:{} MNI: {}".format(hemi_prefix,
str(vertex_id).ljust(6),
', '.join('%5.1f' % m for m in mni))
assert line.get_label() == label
# remove the sphere by clicking in its vicinity
old_len = len(spheres)
test_picker._actors = sum((s._actors for s in spheres), [])
brain._on_pick(test_picker, None)
assert len(spheres) < old_len
screenshot = brain.screenshot()
screenshot_all = brain.screenshot(time_viewer=True)
assert screenshot.shape[0] < screenshot_all.shape[0]
# and the scraper for it (will close the instance)
# only test one condition to save time
if not (hemi == 'rh' and src == 'surface'
and check_version('sphinx_gallery')):
brain.close()
return
fnames = [str(tmpdir.join(f'temp_{ii}.png')) for ii in range(2)]
block_vars = dict(image_path_iterator=iter(fnames),
example_globals=dict(brain=brain))
block = ('code', """
something
# brain.save_movie(time_dilation=1, framerate=1,
# interpolation='linear', time_viewer=True)
#
""", 1)
gallery_conf = dict(src_dir=str(tmpdir), compress_images=[])
scraper = _BrainScraper()
rst = scraper(block, block_vars, gallery_conf)
assert brain.plotter is None # closed
gif_0 = fnames[0][:-3] + 'gif'
for fname in (gif_0, fnames[1]):
assert path.basename(fname) in rst
assert path.isfile(fname)
img = image.imread(fname)
assert img.shape[1] == screenshot.shape[1] # same width
assert img.shape[0] > screenshot.shape[0] # larger height
assert img.shape[:2] == screenshot_all.shape[:2]
def test_brain_timeviewer_traces(renderer_interactive, hemi, src, tmpdir):
"""Test _TimeViewer traces."""
if renderer_interactive._get_3d_backend() != 'pyvista':
pytest.skip('Only PyVista supports traces')
brain_data = _create_testing_brain(
hemi=hemi,
surf='white',
src=src,
show_traces=0.5,
initial_time=0,
volume_options=None, # for speed, don't upsample
)
with pytest.raises(RuntimeError, match='already'):
_TimeViewer(brain_data)
time_viewer = brain_data.time_viewer
assert time_viewer.show_traces
assert hasattr(time_viewer, "picked_points")
assert hasattr(time_viewer, "_spheres")
# test points picked by default
picked_points = brain_data.get_picked_points()
spheres = time_viewer._spheres
hemi_str = list()
if src in ('surface', 'mixed'):
hemi_str.extend([hemi] if hemi in ('lh', 'rh') else ['lh', 'rh'])
if src in ('mixed', 'volume'):
hemi_str.extend(['vol'])
for current_hemi in hemi_str:
assert len(picked_points[current_hemi]) == 1
n_spheres = len(hemi_str)
if hemi == 'split' and src in ('mixed', 'volume'):
n_spheres += 1
assert len(spheres) == n_spheres
# test removing points
time_viewer.clear_points()
assert len(spheres) == 0
for key in ('lh', 'rh', 'vol'):
assert len(picked_points[key]) == 0
# test picking a cell at random
rng = np.random.RandomState(0)
for idx, current_hemi in enumerate(hemi_str):
assert len(spheres) == 0
if current_hemi == 'vol':
current_mesh = brain_data._data['vol']['grid']
vertices = brain_data._data['vol']['vertices']
values = current_mesh.cell_arrays['values'][vertices]
cell_id = vertices[np.argmax(np.abs(values))]
else:
current_mesh = brain_data._hemi_meshes[current_hemi]
cell_id = rng.randint(0, current_mesh.n_cells)
test_picker = TstVTKPicker(None, None, current_hemi, brain_data)
assert time_viewer.on_pick(test_picker, None) is None
test_picker = TstVTKPicker(current_mesh, cell_id, current_hemi,
brain_data)
assert cell_id == test_picker.cell_id
assert test_picker.point_id is None
time_viewer.on_pick(test_picker, None)
assert test_picker.point_id is not None
assert len(picked_points[current_hemi]) == 1
assert picked_points[current_hemi][0] == test_picker.point_id
assert len(spheres) > 0
sphere = spheres[-1]
vertex_id = sphere._vertex_id
assert vertex_id == test_picker.point_id
line = sphere._line
hemi_prefix = current_hemi[0].upper()
if current_hemi == 'vol':
assert hemi_prefix + ':' in line.get_label()
assert 'MNI' in line.get_label()
continue # the MNI conversion is more complex
hemi_int = 0 if current_hemi == 'lh' else 1
mni = vertex_to_mni(vertices=vertex_id,
hemis=hemi_int,
subject=brain_data._subject_id,
subjects_dir=brain_data._subjects_dir)
label = "{}:{} MNI: {}".format(hemi_prefix,
str(vertex_id).ljust(6),
', '.join('%5.1f' % m for m in mni))
assert line.get_label() == label
# remove the sphere by clicking in its vicinity
old_len = len(spheres)
test_picker._actors = sum((s._actors for s in spheres), [])
time_viewer.on_pick(test_picker, None)
assert len(spheres) < old_len
# and the scraper for it (will close the instance)
if not check_version('sphinx_gallery'):
return
screenshot = brain_data.screenshot()
fnames = [str(tmpdir.join('temp.png'))]
block_vars = dict(image_path_iterator=iter(fnames),
example_globals=dict(brain=brain_data))
gallery_conf = dict(src_dir=str(tmpdir))
scraper = _BrainScraper()
rst = scraper(None, block_vars, gallery_conf)
assert 'temp.png' in rst
assert path.isfile(fnames[0])
img = image.imread(fnames[0])
assert img.shape[1] == screenshot.shape[1] # same width
assert img.shape[0] > screenshot.shape[0] # larger height
def test_brain_timeviewer_traces(renderer_interactive, hemi, tmpdir):
"""Test _TimeViewer traces."""
if renderer_interactive._get_3d_backend() != 'pyvista':
pytest.skip('Only PyVista supports traces')
brain_data = _create_testing_brain(hemi=hemi)
time_viewer = _TimeViewer(brain_data, show_traces=True)
assert hasattr(time_viewer, "picked_points")
assert hasattr(time_viewer, "_spheres")
# test points picked by default
picked_points = brain_data.get_picked_points()
spheres = time_viewer._spheres
hemi_str = [hemi] if hemi in ('lh', 'rh') else ['lh', 'rh']
for current_hemi in hemi_str:
assert len(picked_points[current_hemi]) == 1
assert len(spheres) == len(hemi_str)
# test removing points
time_viewer.clear_points()
assert len(picked_points['lh']) == 0
assert len(picked_points['rh']) == 0
# test picking a cell at random
for idx, current_hemi in enumerate(hemi_str):
current_mesh = brain_data._hemi_meshes[current_hemi]
cell_id = np.random.randint(0, current_mesh.n_cells)
test_picker = TstVTKPicker(current_mesh, cell_id)
assert cell_id == test_picker.cell_id
assert test_picker.point_id is None
time_viewer.on_pick(test_picker, None)
assert test_picker.point_id is not None
assert len(picked_points[current_hemi]) == 1
assert picked_points[current_hemi][0] == test_picker.point_id
sphere = spheres[idx]
vertex_id = sphere._vertex_id
assert vertex_id == test_picker.point_id
line = sphere._line
hemi_prefix = 'L' if current_hemi == 'lh' else 'R'
hemi_int = 0 if current_hemi == 'lh' else 1
mni = vertex_to_mni(vertices=vertex_id,
hemis=hemi_int,
subject=brain_data._subject_id,
subjects_dir=brain_data._subjects_dir)
label = "{}:{} MNI: {}".format(hemi_prefix,
str(vertex_id).ljust(6),
', '.join('%5.1f' % m for m in mni))
assert line.get_label() == label
assert len(spheres) == len(hemi_str)
# and the scraper for it (will close the instance)
if not check_version('sphinx_gallery'):
return
screenshot = brain_data.screenshot()
fnames = [str(tmpdir.join('temp.png'))]
block_vars = dict(image_path_iterator=iter(fnames),
example_globals=dict(brain=brain_data))
gallery_conf = dict(src_dir=str(tmpdir))
scraper = _BrainScraper()
rst = scraper(None, block_vars, gallery_conf)
assert 'temp.png' in rst
assert path.isfile(fnames[0])
img = image.imread(fnames[0])
assert img.shape[1] == screenshot.shape[1] # same width
assert img.shape[0] > screenshot.shape[0] # larger height
if op.isdir(op.join(subjects_dir, subject)):
d = nib.load(op.join(subjects_dir, subject, 'mri', 'orig.mgz'))
subject_orig_header = d.get_header()
else:
raise Exception(
'subject_orig_header is None and subjects_dir/subject is not a dir'
)
return subject_orig_header
if __name__ == '__main__':
from src.utils import preproc_utils as pu
SUBJECTS_DIR, MMVT_DIR, FREESURFER_HOME = pu.get_links()
subject = 'mg78'
points = [[-17.85, -52.18, 42.08]]
true_ras = [[-16.92, -44.43, 29.06]]
true_vox = [[146, 86, 76]]
# point = [-13.1962, -66.5584, 33.3018]
h = get_subject_orig_header(subject, SUBJECTS_DIR)
vox = tkras_to_vox(points, h)
print('vox: {}'.format(vox))
ras = vox_to_ras(vox, h)
print('ras: {}'.format(ras))
import mne
from mne.source_space import vertex_to_mni, combine_transforms, Transform, apply_trans
mni2 = vertex_to_mni(23633, 0, 'mg78', SUBJECTS_DIR)
print('mni2: {}'.format(mni2))
def test_brain_traces(renderer_interactive, hemi, src, tmpdir,
brain_gc):
"""Test brain traces."""
if renderer_interactive._get_3d_backend() != 'pyvista':
pytest.skip('Only PyVista supports traces')
brain = _create_testing_brain(
hemi=hemi, surf='white', src=src, show_traces=0.5, initial_time=0,
volume_options=None, # for speed, don't upsample
n_time=1 if src == 'mixed' else 5,
)
assert brain.show_traces
assert hasattr(brain, "picked_points")
assert hasattr(brain, "_spheres")
# test points picked by default
picked_points = brain.get_picked_points()
spheres = brain._spheres
hemi_str = list()
if src in ('surface', 'mixed'):
hemi_str.extend([hemi] if hemi in ('lh', 'rh') else ['lh', 'rh'])
if src in ('mixed', 'volume'):
hemi_str.extend(['vol'])
for current_hemi in hemi_str:
assert len(picked_points[current_hemi]) == 1
n_spheres = len(hemi_str)
if hemi == 'split' and src in ('mixed', 'volume'):
n_spheres += 1
assert len(spheres) == n_spheres
# test removing points
brain.clear_points()
assert len(spheres) == 0
for key in ('lh', 'rh', 'vol'):
assert len(picked_points[key]) == 0
# test picking a cell at random
rng = np.random.RandomState(0)
for idx, current_hemi in enumerate(hemi_str):
assert len(spheres) == 0
if current_hemi == 'vol':
current_mesh = brain._data['vol']['grid']
vertices = brain._data['vol']['vertices']
values = current_mesh.cell_arrays['values'][vertices]
cell_id = vertices[np.argmax(np.abs(values))]
else:
current_mesh = brain._hemi_meshes[current_hemi]
cell_id = rng.randint(0, current_mesh.n_cells)
test_picker = TstVTKPicker(None, None, current_hemi, brain)
assert brain._on_pick(test_picker, None) is None
test_picker = TstVTKPicker(
current_mesh, cell_id, current_hemi, brain)
assert cell_id == test_picker.cell_id
assert test_picker.point_id is None
brain._on_pick(test_picker, None)
assert test_picker.point_id is not None
assert len(picked_points[current_hemi]) == 1
assert picked_points[current_hemi][0] == test_picker.point_id
assert len(spheres) > 0
sphere = spheres[-1]
vertex_id = sphere._vertex_id
assert vertex_id == test_picker.point_id
line = sphere._line
hemi_prefix = current_hemi[0].upper()
if current_hemi == 'vol':
assert hemi_prefix + ':' in line.get_label()
assert 'MNI' in line.get_label()
continue # the MNI conversion is more complex
hemi_int = 0 if current_hemi == 'lh' else 1
mni = vertex_to_mni(
vertices=vertex_id,
hemis=hemi_int,
subject=brain._subject_id,
subjects_dir=brain._subjects_dir
)
label = "{}:{} MNI: {}".format(
hemi_prefix, str(vertex_id).ljust(6),
', '.join('%5.1f' % m for m in mni))
assert line.get_label() == label
# remove the sphere by clicking in its vicinity
old_len = len(spheres)
test_picker._actors = sum((s._actors for s in spheres), [])
brain._on_pick(test_picker, None)
assert len(spheres) < old_len
screenshot = brain.screenshot()
screenshot_all = brain.screenshot(time_viewer=True)
assert screenshot.shape[0] < screenshot_all.shape[0]
# and the scraper for it (will close the instance)
# only test one condition to save time
if not (hemi == 'rh' and src == 'surface' and
check_version('sphinx_gallery')):
brain.close()
return
fnames = [str(tmpdir.join(f'temp_{ii}.png')) for ii in range(2)]
block_vars = dict(image_path_iterator=iter(fnames),
example_globals=dict(brain=brain))
block = ('code', """
something
# brain.save_movie(time_dilation=1, framerate=1,
# interpolation='linear', time_viewer=True)
#
""", 1)
gallery_conf = dict(src_dir=str(tmpdir), compress_images=[])
scraper = _BrainScraper()
rst = scraper(block, block_vars, gallery_conf)
assert brain.plotter is None # closed
gif_0 = fnames[0][:-3] + 'gif'
for fname in (gif_0, fnames[1]):
assert path.basename(fname) in rst
assert path.isfile(fname)
img = image.imread(fname)
assert img.shape[1] == screenshot.shape[1] # same width
assert img.shape[0] > screenshot.shape[0] # larger height
assert img.shape[:2] == screenshot_all.shape[:2]
