def test_brain_init(renderer, tmpdir, pixel_ratio, brain_gc):
"""Test initialization of the Brain instance."""
if renderer._get_3d_backend() != 'pyvista':
pytest.skip('TimeViewer tests only supported on PyVista')
from mne.source_estimate import _BaseSourceEstimate
class FakeSTC(_BaseSourceEstimate):
def __init__(self):
pass
hemi = 'lh'
surf = 'inflated'
cortex = 'low_contrast'
title = 'test'
size = (300, 300)
kwargs = dict(subject_id=subject_id, subjects_dir=subjects_dir)
with pytest.raises(ValueError, match='"size" parameter must be'):
Brain(hemi=hemi, surf=surf, size=[1, 2, 3], **kwargs)
with pytest.raises(KeyError):
Brain(hemi='foo', surf=surf, **kwargs)
with pytest.raises(TypeError, match='figure'):
Brain(hemi=hemi, surf=surf, figure='foo', **kwargs)
with pytest.raises(TypeError, match='interaction'):
Brain(hemi=hemi, surf=surf, interaction=0, **kwargs)
with pytest.raises(ValueError, match='interaction'):
Brain(hemi=hemi, surf=surf, interaction='foo', **kwargs)
renderer.backend._close_all()
brain = Brain(hemi=hemi,
surf=surf,
size=size,
title=title,
cortex=cortex,
units='m',
silhouette=dict(decimate=0.95),
**kwargs)
with pytest.raises(TypeError, match='not supported'):
brain._check_stc(hemi='lh', array=FakeSTC(), vertices=None)
with pytest.raises(ValueError, match='add_data'):
brain.setup_time_viewer(time_viewer=True)
brain._hemi = 'foo' # for testing: hemis
with pytest.raises(ValueError, match='not be None'):
brain._check_hemi(hemi=None)
with pytest.raises(ValueError, match='either "lh" or "rh"'):
brain._check_hemi(hemi='foo')
with pytest.raises(ValueError, match='either "lh" or "rh"'):
brain._check_hemis(hemi='foo')
brain._hemi = hemi # end testing: hemis
with pytest.raises(ValueError, match='bool or positive'):
brain._to_borders(None, None, 'foo')
assert brain.interaction == 'trackball'
# add_data
stc = read_source_estimate(fname_stc)
fmin = stc.data.min()
fmax = stc.data.max()
for h in brain._hemis:
if h == 'lh':
hi = 0
else:
hi = 1
hemi_data = stc.data[:len(stc.vertices[hi]), 10]
hemi_vertices = stc.vertices[hi]
with pytest.raises(TypeError, match='scale_factor'):
brain.add_data(hemi_data, hemi=h, scale_factor='foo')
with pytest.raises(TypeError, match='vector_alpha'):
brain.add_data(hemi_data, hemi=h, vector_alpha='foo')
with pytest.raises(ValueError, match='thresh'):
brain.add_data(hemi_data, hemi=h, thresh=-1)
with pytest.raises(ValueError, match='remove_existing'):
brain.add_data(hemi_data, hemi=h, remove_existing=-1)
with pytest.raises(ValueError, match='time_label_size'):
brain.add_data(hemi_data,
hemi=h,
time_label_size=-1,
vertices=hemi_vertices)
with pytest.raises(ValueError, match='is positive'):
brain.add_data(hemi_data,
hemi=h,
smoothing_steps=-1,
vertices=hemi_vertices)
with pytest.raises(TypeError, match='int or NoneType'):
brain.add_data(hemi_data, hemi=h, smoothing_steps='foo')
with pytest.raises(ValueError, match='dimension mismatch'):
brain.add_data(array=np.array([0, 1, 2]),
hemi=h,
vertices=hemi_vertices)
with pytest.raises(ValueError, match='vertices parameter must not be'):
brain.add_data(hemi_data,
fmin=fmin,
hemi=hemi,
fmax=fmax,
vertices=None)
with pytest.raises(ValueError, match='has shape'):
brain.add_data(hemi_data[:, np.newaxis],
fmin=fmin,
hemi=hemi,
fmax=fmax,
vertices=None,
time=[0, 1])
brain.add_data(hemi_data,
fmin=fmin,
hemi=h,
fmax=fmax,
colormap='hot',
vertices=hemi_vertices,
smoothing_steps='nearest',
colorbar=(0, 0),
time=None)
with pytest.raises(ValueError, match='brain has no defined times'):
brain.set_time(0.)
assert brain.data['lh']['array'] is hemi_data
assert brain.views == ['lateral']
assert brain.hemis == ('lh', )
brain.add_data(hemi_data[:, np.newaxis],
fmin=fmin,
hemi=h,
fmax=fmax,
colormap='hot',
vertices=hemi_vertices,
smoothing_steps=1,
initial_time=0.,
colorbar=False,
time=[0])
with pytest.raises(ValueError, match='the range of available times'):
brain.set_time(7.)
brain.set_time(0.)
brain.set_time_point(0) # should hit _safe_interp1d
with pytest.raises(ValueError, match='consistent with'):
brain.add_data(hemi_data[:, np.newaxis],
fmin=fmin,
hemi=h,
fmax=fmax,
colormap='hot',
vertices=hemi_vertices,
smoothing_steps='nearest',
colorbar=False,
time=[1])
with pytest.raises(ValueError, match='different from'):
brain.add_data(hemi_data[:, np.newaxis][:, [0, 0]],
fmin=fmin,
hemi=h,
fmax=fmax,
colormap='hot',
vertices=hemi_vertices)
with pytest.raises(ValueError, match='need shape'):
brain.add_data(hemi_data[:, np.newaxis],
time=[0, 1],
fmin=fmin,
hemi=h,
fmax=fmax,
colormap='hot',
vertices=hemi_vertices)
with pytest.raises(ValueError, match='If array has 3'):
brain.add_data(hemi_data[:, np.newaxis, np.newaxis],
fmin=fmin,
hemi=h,
fmax=fmax,
colormap='hot',
vertices=hemi_vertices)
# add label
label = read_label(fname_label)
with pytest.raises(ValueError, match="not a filename"):
brain.add_label(0)
with pytest.raises(ValueError, match="does not exist"):
brain.add_label('foo', subdir='bar')
label.name = None # test unnamed label
brain.add_label(label, scalar_thresh=0., color="green")
assert isinstance(brain.labels[label.hemi], list)
overlays = brain._layered_meshes[label.hemi]._overlays
assert 'unnamed0' in overlays
assert np.allclose(overlays['unnamed0']._colormap[0],
[0, 0, 0, 0]) # first component is transparent
assert np.allclose(overlays['unnamed0']._colormap[1],
[0, 128, 0, 255]) # second is green
brain.remove_labels()
assert 'unnamed0' not in overlays
brain.add_label(fname_label)
brain.add_label('V1', borders=True)
brain.remove_labels()
brain.remove_labels()
# add foci
brain.add_foci([0], coords_as_verts=True, hemi=hemi, color='blue')
# add text
brain.add_text(x=0, y=0, text='foo')
brain.close()
# add annotation
annots = [
'aparc',
path.join(subjects_dir, 'fsaverage', 'label',
'lh.PALS_B12_Lobes.annot')
]
borders = [True, 2]
alphas = [1, 0.5]
colors = [None, 'r']
brain = Brain(subject_id='fsaverage',
hemi='both',
size=size,
surf='inflated',
subjects_dir=subjects_dir)
with pytest.raises(RuntimeError, match="both hemispheres"):
brain.add_annotation(annots[-1])
with pytest.raises(ValueError, match="does not exist"):
brain.add_annotation('foo')
brain.close()
brain = Brain(subject_id='fsaverage',
hemi=hemi,
size=size,
surf='inflated',
subjects_dir=subjects_dir)
for a, b, p, color in zip(annots, borders, alphas, colors):
brain.add_annotation(a, b, p, color=color)
brain.show_view(dict(focalpoint=(1e-5, 1e-5, 1e-5)), roll=1, distance=500)
# image and screenshot
fname = path.join(str(tmpdir), 'test.png')
assert not path.isfile(fname)
brain.save_image(fname)
assert path.isfile(fname)
brain.show_view(view=dict(azimuth=180., elevation=90.))
img = brain.screenshot(mode='rgb')
if renderer._get_3d_backend() == 'mayavi':
pixel_ratio = 1. # no HiDPI when using the testing backend
want_size = np.array([size[0] * pixel_ratio, size[1] * pixel_ratio, 3])
assert_allclose(img.shape, want_size)
brain.close()
def test_brain_gc(renderer, brain_gc):
"""Test that a minimal version of Brain gets GC'ed."""
if renderer._get_3d_backend() != 'pyvista':
pytest.skip('TimeViewer tests only supported on PyVista')
brain = Brain('fsaverage', 'both', 'inflated', subjects_dir=subjects_dir)
brain.close()
def test_brain_gc(renderer_pyvistaqt, brain_gc):
"""Test that a minimal version of Brain gets GC'ed."""
brain = Brain('fsaverage', 'both', 'inflated', subjects_dir=subjects_dir)
brain.close()
def test_brain_init(renderer_pyvistaqt, tmpdir, pixel_ratio, brain_gc):
"""Test initialization of the Brain instance."""
from mne.source_estimate import _BaseSourceEstimate
class FakeSTC(_BaseSourceEstimate):
def __init__(self):
pass
hemi = 'lh'
surf = 'inflated'
cortex = 'low_contrast'
title = 'test'
size = (300, 300)
kwargs = dict(subject_id=subject_id, subjects_dir=subjects_dir)
with pytest.raises(ValueError, match='"size" parameter must be'):
Brain(hemi=hemi, surf=surf, size=[1, 2, 3], **kwargs)
with pytest.raises(ValueError, match='.*hemi.*Allowed values.*'):
Brain(hemi='foo', surf=surf, **kwargs)
with pytest.raises(ValueError, match='.*view.*Allowed values.*'):
Brain(hemi='lh', surf=surf, views='foo', **kwargs)
with pytest.raises(TypeError, match='figure'):
Brain(hemi=hemi, surf=surf, figure='foo', **kwargs)
with pytest.raises(TypeError, match='interaction'):
Brain(hemi=hemi, surf=surf, interaction=0, **kwargs)
with pytest.raises(ValueError, match='interaction'):
Brain(hemi=hemi, surf=surf, interaction='foo', **kwargs)
with pytest.raises(FileNotFoundError, match=r'lh\.whatever'):
Brain(subject_id, 'lh', 'whatever')
with pytest.raises(ValueError, match='`surf` cannot be seghead'):
Brain(hemi='lh', surf='seghead', **kwargs)
Brain(subject_id, hemi=None, surf=None) # test no surfaces
renderer_pyvistaqt.backend._close_all()
brain = Brain(hemi=hemi,
surf=surf,
size=size,
title=title,
cortex=cortex,
units='m',
silhouette=dict(decimate=0.95),
**kwargs)
with pytest.raises(TypeError, match='not supported'):
brain._check_stc(hemi='lh', array=FakeSTC(), vertices=None)
with pytest.raises(ValueError, match='add_data'):
brain.setup_time_viewer(time_viewer=True)
brain._hemi = 'foo' # for testing: hemis
with pytest.raises(ValueError, match='not be None'):
brain._check_hemi(hemi=None)
with pytest.raises(ValueError, match='Invalid.*hemi.*Allowed'):
brain._check_hemi(hemi='foo')
brain._hemi = hemi # end testing: hemis
with pytest.raises(ValueError, match='bool or positive'):
brain._to_borders(None, None, 'foo')
assert brain.interaction == 'trackball'
# add_data
stc = read_source_estimate(fname_stc)
fmin = stc.data.min()
fmax = stc.data.max()
for h in brain._hemis:
if h == 'lh':
hi = 0
else:
hi = 1
hemi_data = stc.data[:len(stc.vertices[hi]), 10]
hemi_vertices = stc.vertices[hi]
with pytest.raises(TypeError, match='scale_factor'):
brain.add_data(hemi_data, hemi=h, scale_factor='foo')
with pytest.raises(TypeError, match='vector_alpha'):
brain.add_data(hemi_data, hemi=h, vector_alpha='foo')
with pytest.raises(ValueError, match='thresh'):
brain.add_data(hemi_data, hemi=h, thresh=-1)
with pytest.raises(ValueError, match='remove_existing'):
brain.add_data(hemi_data, hemi=h, remove_existing=-1)
with pytest.raises(ValueError, match='time_label_size'):
brain.add_data(hemi_data,
hemi=h,
time_label_size=-1,
vertices=hemi_vertices)
with pytest.raises(ValueError, match='is positive'):
brain.add_data(hemi_data,
hemi=h,
smoothing_steps=-1,
vertices=hemi_vertices)
with pytest.raises(TypeError, match='int or NoneType'):
brain.add_data(hemi_data, hemi=h, smoothing_steps='foo')
with pytest.raises(ValueError, match='dimension mismatch'):
brain.add_data(array=np.array([0, 1, 2]),
hemi=h,
vertices=hemi_vertices)
with pytest.raises(ValueError, match='vertices parameter must not be'):
brain.add_data(hemi_data,
fmin=fmin,
hemi=hemi,
fmax=fmax,
vertices=None)
with pytest.raises(ValueError, match='has shape'):
brain.add_data(hemi_data[:, np.newaxis],
fmin=fmin,
hemi=hemi,
fmax=fmax,
vertices=None,
time=[0, 1])
brain.add_data(hemi_data,
fmin=fmin,
hemi=h,
fmax=fmax,
colormap='hot',
vertices=hemi_vertices,
smoothing_steps='nearest',
colorbar=(0, 0),
time=None)
with pytest.raises(ValueError, match='brain has no defined times'):
brain.set_time(0.)
assert brain.data['lh']['array'] is hemi_data
assert brain.views == ['lateral']
assert brain.hemis == ('lh', )
brain.add_data(hemi_data[:, np.newaxis],
fmin=fmin,
hemi=h,
fmax=fmax,
colormap='hot',
vertices=hemi_vertices,
smoothing_steps=1,
initial_time=0.,
colorbar=False,
time=[0])
with pytest.raises(ValueError, match='the range of available times'):
brain.set_time(7.)
brain.set_time(0.)
brain.set_time_point(0) # should hit _safe_interp1d
with pytest.raises(ValueError, match='consistent with'):
brain.add_data(hemi_data[:, np.newaxis],
fmin=fmin,
hemi=h,
fmax=fmax,
colormap='hot',
vertices=hemi_vertices,
smoothing_steps='nearest',
colorbar=False,
time=[1])
with pytest.raises(ValueError, match='different from'):
brain.add_data(hemi_data[:, np.newaxis][:, [0, 0]],
fmin=fmin,
hemi=h,
fmax=fmax,
colormap='hot',
vertices=hemi_vertices)
with pytest.raises(ValueError, match='need shape'):
brain.add_data(hemi_data[:, np.newaxis],
time=[0, 1],
fmin=fmin,
hemi=h,
fmax=fmax,
colormap='hot',
vertices=hemi_vertices)
with pytest.raises(ValueError, match='If array has 3'):
brain.add_data(hemi_data[:, np.newaxis, np.newaxis],
fmin=fmin,
hemi=h,
fmax=fmax,
colormap='hot',
vertices=hemi_vertices)
# add label
label = read_label(fname_label)
with pytest.raises(ValueError, match="not a filename"):
brain.add_label(0)
with pytest.raises(ValueError, match="does not exist"):
brain.add_label('foo', subdir='bar')
label.name = None # test unnamed label
brain.add_label(label, scalar_thresh=0., color="green")
assert isinstance(brain.labels[label.hemi], list)
overlays = brain._layered_meshes[label.hemi]._overlays
assert 'unnamed0' in overlays
assert np.allclose(overlays['unnamed0']._colormap[0],
[0, 0, 0, 0]) # first component is transparent
assert np.allclose(overlays['unnamed0']._colormap[1],
[0, 128, 0, 255]) # second is green
brain.remove_labels()
assert 'unnamed0' not in overlays
brain.add_label(fname_label)
brain.add_label('V1', borders=True)
brain.remove_labels()
brain.remove_labels()
# add foci
brain.add_foci([0], coords_as_verts=True, hemi=hemi, color='blue')
# add head and skull
brain.add_head(color='red', alpha=0.1)
brain.add_skull(outer=True, color='green', alpha=0.1)
# add volume labels
brain.add_volume_labels(aseg='aseg',
labels=('Brain-Stem', 'Left-Hippocampus',
'Left-Amygdala'))
# add sensors
info = read_info(fname_raw_testing)
brain.add_sensors(info, trans=fname_trans)
info['chs'][0]['coord_frame'] = 99
with pytest.raises(RuntimeError, match='must be "meg", "head" or "mri"'):
brain.add_sensors(info, trans=fname_trans)
# add text
brain.add_text(x=0, y=0, text='foo')
brain.close()
# add annotation
annots = [
'aparc',
op.join(subjects_dir, 'fsaverage', 'label', 'lh.PALS_B12_Lobes.annot')
]
borders = [True, 2]
alphas = [1, 0.5]
colors = [None, 'r']
brain = Brain(subject_id='fsaverage',
hemi='both',
size=size,
surf='inflated',
subjects_dir=subjects_dir)
with pytest.raises(RuntimeError, match="both hemispheres"):
brain.add_annotation(annots[-1])
with pytest.raises(ValueError, match="does not exist"):
brain.add_annotation('foo')
brain.close()
brain = Brain(subject_id='fsaverage',
hemi=hemi,
size=size,
surf='inflated',
subjects_dir=subjects_dir)
for a, b, p, color in zip(annots, borders, alphas, colors):
brain.add_annotation(a, b, p, color=color)
view_args = dict(roll=1, distance=500, focalpoint=(1e-5, 1e-5, 1e-5))
cam = brain._renderer.figure.plotter.camera
previous_roll = cam.GetRoll()
brain.show_view(**view_args)
assert_allclose(cam.GetFocalPoint(), view_args["focalpoint"])
assert_allclose(cam.GetDistance(), view_args["distance"])
assert_allclose(cam.GetRoll(), previous_roll + view_args["roll"])
del view_args
with pytest.warns(DeprecationWarning, match='`view` is a dict'):
brain.show_view(view=dict(azimuth=180., elevation=90.))
# image and screenshot
fname = op.join(str(tmpdir), 'test.png')
assert not op.isfile(fname)
brain.save_image(fname)
assert op.isfile(fname)
fp = np.array(
brain._renderer.figure.plotter.renderer.ComputeVisiblePropBounds())
fp = (fp[1::2] + fp[::2]) * 0.5
azimuth, elevation = 180., 90.
for view_args in (dict(azimuth=azimuth,
elevation=elevation,
focalpoint='auto'), dict(view='lateral',
hemi='lh')):
brain.show_view(**view_args)
assert_allclose(brain._renderer.figure._azimuth, azimuth)
assert_allclose(brain._renderer.figure._elevation, elevation)
assert_allclose(cam.GetFocalPoint(), fp)
del view_args
img = brain.screenshot(mode='rgba')
want_size = np.array([size[0] * pixel_ratio, size[1] * pixel_ratio, 4])
assert_allclose(img.shape, want_size)
brain.close()
def test_brain_init(renderer, tmpdir, pixel_ratio):
"""Test initialization of the Brain instance."""
from mne.label import read_label
hemi = 'lh'
surf = 'inflated'
cortex = 'low_contrast'
title = 'test'
size = (300, 300)
kwargs = dict(subject_id=subject_id, subjects_dir=subjects_dir)
with pytest.raises(ValueError, match='"size" parameter must be'):
Brain(hemi=hemi, surf=surf, size=[1, 2, 3], **kwargs)
with pytest.raises(TypeError, match='figure'):
Brain(hemi=hemi, surf=surf, figure='foo', **kwargs)
with pytest.raises(TypeError, match='interaction'):
Brain(hemi=hemi, surf=surf, interaction=0, **kwargs)
with pytest.raises(ValueError, match='interaction'):
Brain(hemi=hemi, surf=surf, interaction='foo', **kwargs)
with pytest.raises(KeyError):
Brain(hemi='foo', surf=surf, **kwargs)
brain = Brain(hemi=hemi,
surf=surf,
size=size,
title=title,
cortex=cortex,
units='m',
**kwargs)
assert brain.interaction == 'trackball'
# add_data
stc = read_source_estimate(fname_stc)
fmin = stc.data.min()
fmax = stc.data.max()
for h in brain._hemis:
if h == 'lh':
hi = 0
else:
hi = 1
hemi_data = stc.data[:len(stc.vertices[hi]), 10]
hemi_vertices = stc.vertices[hi]
with pytest.raises(TypeError, match='scale_factor'):
brain.add_data(hemi_data, hemi=h, scale_factor='foo')
with pytest.raises(TypeError, match='vector_alpha'):
brain.add_data(hemi_data, hemi=h, vector_alpha='foo')
with pytest.raises(ValueError, match='thresh'):
brain.add_data(hemi_data, hemi=h, thresh=-1)
with pytest.raises(ValueError, match='remove_existing'):
brain.add_data(hemi_data, hemi=h, remove_existing=-1)
with pytest.raises(ValueError, match='time_label_size'):
brain.add_data(hemi_data,
hemi=h,
time_label_size=-1,
vertices=hemi_vertices)
with pytest.raises(ValueError, match='is positive'):
brain.add_data(hemi_data,
hemi=h,
smoothing_steps=-1,
vertices=hemi_vertices)
with pytest.raises(TypeError, match='int or NoneType'):
brain.add_data(hemi_data, hemi=h, smoothing_steps='foo')
with pytest.raises(ValueError, match='dimension mismatch'):
brain.add_data(array=np.array([0, 1, 2]),
hemi=h,
vertices=hemi_vertices)
with pytest.raises(ValueError, match='vertices parameter must not be'):
brain.add_data(hemi_data,
fmin=fmin,
hemi=hemi,
fmax=fmax,
vertices=None)
with pytest.raises(ValueError, match='has shape'):
brain.add_data(hemi_data[:, np.newaxis],
fmin=fmin,
hemi=hemi,
fmax=fmax,
vertices=None,
time=[0, 1])
brain.add_data(hemi_data,
fmin=fmin,
hemi=h,
fmax=fmax,
colormap='hot',
vertices=hemi_vertices,
smoothing_steps='nearest',
colorbar=(0, 0),
time=None)
assert brain.data['lh']['array'] is hemi_data
assert brain.views == ['lateral']
assert brain.hemis == ('lh', )
brain.add_data(hemi_data[:, np.newaxis],
fmin=fmin,
hemi=h,
fmax=fmax,
colormap='hot',
vertices=hemi_vertices,
smoothing_steps=1,
initial_time=0.,
colorbar=False,
time=[0])
brain.set_time_point(0) # should hit _safe_interp1d
with pytest.raises(ValueError, match='consistent with'):
brain.add_data(hemi_data[:, np.newaxis],
fmin=fmin,
hemi=h,
fmax=fmax,
colormap='hot',
vertices=hemi_vertices,
smoothing_steps='nearest',
colorbar=False,
time=[1])
with pytest.raises(ValueError, match='different from'):
brain.add_data(hemi_data[:, np.newaxis][:, [0, 0]],
fmin=fmin,
hemi=h,
fmax=fmax,
colormap='hot',
vertices=hemi_vertices)
with pytest.raises(ValueError, match='need shape'):
brain.add_data(hemi_data[:, np.newaxis],
time=[0, 1],
fmin=fmin,
hemi=h,
fmax=fmax,
colormap='hot',
vertices=hemi_vertices)
with pytest.raises(ValueError, match='If array has 3'):
brain.add_data(hemi_data[:, np.newaxis, np.newaxis],
fmin=fmin,
hemi=h,
fmax=fmax,
colormap='hot',
vertices=hemi_vertices)
# add label
label = read_label(fname_label)
brain.add_label(label, scalar_thresh=0.)
brain.remove_labels()
brain.add_label(fname_label)
brain.add_label('V1', borders=True)
brain.remove_labels()
brain.remove_labels()
# add foci
brain.add_foci([0], coords_as_verts=True, hemi=hemi, color='blue')
# add text
brain.add_text(x=0, y=0, text='foo')
# add annotation
annots = [
'aparc',
path.join(subjects_dir, 'fsaverage', 'label',
'lh.PALS_B12_Lobes.annot')
]
borders = [True, 2]
alphas = [1, 0.5]
colors = [None, 'r']
brain = Brain(subject_id='fsaverage',
hemi=hemi,
size=size,
surf='inflated',
subjects_dir=subjects_dir)
for a, b, p, color in zip(annots, borders, alphas, colors):
brain.add_annotation(a, b, p, color=color)
brain.show_view(dict(focalpoint=(1e-5, 1e-5, 1e-5)), roll=1, distance=500)
# image and screenshot
fname = path.join(str(tmpdir), 'test.png')
assert not path.isfile(fname)
brain.save_image(fname)
assert path.isfile(fname)
brain.show_view(view=dict(azimuth=180., elevation=90.))
img = brain.screenshot(mode='rgb')
if renderer._get_3d_backend() == 'mayavi':
pixel_ratio = 1. # no HiDPI when using the testing backend
want_size = np.array([size[0] * pixel_ratio, size[1] * pixel_ratio, 3])
assert_allclose(img.shape, want_size)
brain.close()