def test_brain_timeviewer(renderer_interactive, pixel_ratio):
"""Test _TimeViewer primitives."""
if renderer_interactive._get_3d_backend() != 'pyvista':
pytest.skip('TimeViewer tests only supported on PyVista')
brain_data = _create_testing_brain(hemi='both', show_traces=False)
with pytest.raises(RuntimeError, match='already'):
_TimeViewer(brain_data)
time_viewer = brain_data.time_viewer
time_viewer.time_call(value=0)
time_viewer.orientation_call(value='lat', update_widget=True)
time_viewer.orientation_call(value='medial', update_widget=True)
time_viewer.smoothing_call(value=1)
time_viewer.fmin_call(value=12.0)
time_viewer.fmax_call(value=4.0)
time_viewer.fmid_call(value=6.0)
time_viewer.fmid_call(value=4.0)
time_viewer.fscale_call(value=1.1)
time_viewer.toggle_interface()
time_viewer.playback_speed_call(value=0.1)
time_viewer.toggle_playback()
time_viewer.apply_auto_scaling()
time_viewer.restore_user_scaling()
time_viewer.reset()
plt.close('all')
time_viewer.help()
assert len(plt.get_fignums()) == 1
plt.close('all')
# screenshot
brain_data.show_view(view=dict(azimuth=180., elevation=90.))
img = brain_data.screenshot(mode='rgb')
want_shape = np.array([300 * pixel_ratio, 300 * pixel_ratio, 3])
assert_allclose(img.shape, want_shape)
def test_brain_linkviewer(renderer_interactive):
"""Test _LinkViewer primitives."""
brain_data = _create_testing_brain(hemi='split')
_TimeViewer(brain_data)
link_viewer = _LinkViewer([brain_data])
link_viewer.set_time_point(value=0)
link_viewer.set_playback_speed(value=0.1)
link_viewer.toggle_playback()
def test_brain_linkviewer(renderer_interactive):
"""Test _LinkViewer primitives."""
if renderer_interactive._get_3d_backend() != 'pyvista':
pytest.skip()
brain_data = _create_testing_brain(hemi='split')
_TimeViewer(brain_data)
link_viewer = _LinkViewer([brain_data])
link_viewer.set_time_point(value=0)
link_viewer.set_playback_speed(value=0.1)
link_viewer.toggle_playback()
def test_brain_linkviewer(renderer_interactive, travis_macos):
"""Test _LinkViewer primitives."""
if renderer_interactive._get_3d_backend() != 'pyvista':
pytest.skip('Linkviewer only supported on PyVista')
if travis_macos:
pytest.skip('Linkviewer tests unstable on Travis macOS')
brain_data = _create_testing_brain(hemi='split')
_TimeViewer(brain_data)
link_viewer = _LinkViewer([brain_data])
link_viewer.set_time_point(value=0)
link_viewer.set_playback_speed(value=0.1)
link_viewer.toggle_playback()
def test_brain_timeviewer(renderer_interactive):
"""Test _TimeViewer primitives."""
if renderer_interactive._get_3d_backend() != 'pyvista':
pytest.skip()
brain_data = _create_testing_brain(hemi='both')
time_viewer = _TimeViewer(brain_data)
time_viewer.time_call(value=0)
time_viewer.orientation_call(value='lat', update_widget=True)
time_viewer.orientation_call(value='medial', update_widget=True)
time_viewer.smoothing_call(value=1)
time_viewer.fmin_call(value=12.0)
time_viewer.fmax_call(value=4.0)
time_viewer.fmid_call(value=6.0)
time_viewer.fmid_call(value=4.0)
time_viewer.fscale_call(value=1.1)
time_viewer.toggle_interface()
time_viewer.playback_speed_call(value=0.1)
time_viewer.toggle_playback()
time_viewer.apply_auto_scaling()
time_viewer.restore_user_scaling()
# screenshot
brain_data.show_view(view=dict(azimuth=180., elevation=90.))
img = brain_data.screenshot(mode='rgb')
assert (img.shape == (300, 300, 3))
def test_brain_timeviewer(renderer):
"""Test _TimeViewer primitives."""
if renderer.get_3d_backend() == "mayavi":
pytest.skip() # Skip PySurfer.TimeViewer
else:
# Disable testing to allow interactive window
renderer.MNE_3D_BACKEND_TESTING = False
sample_src = read_source_spaces(src_fname)
# dense version
vertices = [s['vertno'] for s in sample_src]
n_time = 5
n_verts = sum(len(v) for v in vertices)
stc_data = np.zeros((n_verts * n_time))
stc_size = stc_data.size
stc_data[(np.random.rand(stc_size // 20) * stc_size).astype(int)] = \
np.random.RandomState(0).rand(stc_data.size // 20)
stc_data.shape = (n_verts, n_time)
stc = SourceEstimate(stc_data, vertices, 1, 1)
fmin = stc.data.min()
fmax = stc.data.max()
brain_data = _Brain(subject_id,
'split',
surf,
size=300,
subjects_dir=subjects_dir)
for hemi in ['lh', 'rh']:
hemi_idx = 0 if hemi == 'lh' else 1
data = getattr(stc, hemi + '_data')
vertices = stc.vertices[hemi_idx]
brain_data.add_data(data,
fmin=fmin,
hemi=hemi,
fmax=fmax,
colormap='hot',
vertices=vertices,
colorbar=True)
time_viewer = _TimeViewer(brain_data)
time_viewer.time_call(value=0)
time_viewer.orientation_call(value='lat', update_widget=True)
time_viewer.orientation_call(value='medial', update_widget=True)
time_viewer.smoothing_call(value=1)
time_viewer.fmin_call(value=12.0)
time_viewer.fmax_call(value=4.0)
time_viewer.fmid_call(value=6.0)
time_viewer.fmid_call(value=4.0)
time_viewer.fscale_call(value=1.1)
time_viewer.toggle_interface()
time_viewer.playback_speed_call(value=0.1)
time_viewer.toggle_playback()
time_viewer.apply_auto_scaling()
time_viewer.restore_user_scaling()
link_viewer = _LinkViewer([brain_data])
link_viewer.set_time_point(value=0)
link_viewer.set_playback_speed(value=0.1)
link_viewer.toggle_playback()
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_timeviewer(renderer_interactive):
"""Test _TimeViewer primitives."""
brain_data = _create_testing_brain(hemi='both')
time_viewer = _TimeViewer(brain_data)
time_viewer.time_call(value=0)
time_viewer.orientation_call(value='lat', update_widget=True)
time_viewer.orientation_call(value='medial', update_widget=True)
time_viewer.smoothing_call(value=1)
time_viewer.fmin_call(value=12.0)
time_viewer.fmax_call(value=4.0)
time_viewer.fmid_call(value=6.0)
time_viewer.fmid_call(value=4.0)
time_viewer.fscale_call(value=1.1)
time_viewer.toggle_interface()
time_viewer.playback_speed_call(value=0.1)
time_viewer.toggle_playback()
time_viewer.apply_auto_scaling()
time_viewer.restore_user_scaling()
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
