def test_surface():
"""Test IO for Surface class"""
subj_dir = utils._get_subjects_dir()
for subjects_dir in [None, subj_dir]:
surface = utils.Surface('fsaverage',
'lh',
'inflated',
subjects_dir=subjects_dir)
surface.load_geometry()
surface.load_label('BA1')
surface.load_curvature()
xfm = np.eye(4)
xfm[:3, -1] += 2 # translation
x = surface.x
surface.apply_xfm(xfm)
x_ = surface.x
assert_array_almost_equal(x + 2, x_)
# normals
nn = _slow_compute_normals(surface.coords, surface.faces[:10000])
nn_fast = utils._compute_normals(surface.coords, surface.faces[:10000])
assert_array_almost_equal(nn, nn_fast)
assert 50 < np.linalg.norm(surface.coords, axis=-1).mean() < 100 # mm
surface = utils.Surface('fsaverage',
'lh',
'inflated',
subjects_dir=subj_dir,
units='m')
surface.load_geometry()
assert 0.05 < np.linalg.norm(surface.coords, axis=-1).mean() < 0.1 # m
def add_coords(self,
coords,
map_surface=None,
scale_factor=1.5,
color="red",
alpha=1,
name=None,
labels=None,
hemi=None,
text_size=5,
txt_pos=[1.4, 1.1, 1.1]):
"""
Plot locations onto the brain surface as spheres.
:param coords: list of co-ordinates or (n, 3) numpy array. Co-ordinate
space must match that of the underlying MRI image
:param map_surface: Freesurfer surf or None.
surface to map coordinates through, or None to use raw coords
:param scale_factor: int
controls the size of the foci spheres
:param color: matplotlib color code
HTML name, RGB tuple or hex code
:param alpha: float in [0, 1]
opacity of coordinate spheres
:param name: str
internal name to use (_foci and _labels will be appended)
:param labels:
List of text strings used to label co-ordinates
:param hemi: str | None
If None, assumed to belong to the hemisphere being shown.
If two hemispheresa are being shown, an error will be thrown
:param text_size: int
Text size of labels
"""
hemi = self._check_hemi(hemi)
if map_surface is None:
foci_vtxs = surfer.utils.find_closest_vertices(
self.geo[hemi].coords, coords)
foci_coords = self.geo[hemi].coords[foci_vtxs]
else:
foci_surf = utils.Surface(self.subject_id,
hemi,
map_surface,
subjects_dir=self.subjects_dir)
foci_surf.load_geometry()
foci_vtxs = utils.find_closest_vertices(foci_surf.coords, coords)
foci_coords = self.geo[hemi].coords[foci_vtxs]
# Convert the color code
if not isinstance(color, tuple):
color = colorConverter.to_rgb(color)
if name is None:
name = "coords_%s" % (max(
len(self.foci_dict) + 1,
len(self.labels_dict) + 1))
views = self._toggle_render(False)
# Store the coords in the foci list and the label in the labels list
fl = []
# Create the visualization
for brain in self._brain_list:
if brain['hemi'] == hemi:
fl.append(
mlab.points3d(foci_coords[:, 0],
foci_coords[:, 1],
foci_coords[:, 2],
np.ones(foci_coords.shape[0]),
scale_factor=(10. * scale_factor),
color=color,
opacity=alpha,
name=name + '_foci',
figure=brain['brain']._f))
self.foci_dict[name + '_foci'] = fl
if labels is not None:
tl = []
for i in xrange(coords.shape[0]):
tl.append(
mlab.text3d(foci_coords[i, 0] * txt_pos[0],
foci_coords[i, 1] * txt_pos[1],
foci_coords[i, 2] * txt_pos[2],
labels[i],
color=(1.0, 1.0, 1.0),
scale=text_size,
name=name + '_label',
figure=brain['brain']._f))
self.labels_dict[name + '_label'] = fl
self._toggle_render(True, views)
def add_arrow(self,
coords,
map_surface=None,
tube_radius=3.0,
color="white",
alpha=1,
name=None,
hemi=None):
"""
Add an arrow across the brain between two co-ordinates
:param coords: list of co-ordinates or (n, 3) numpy array. Co-ordinate
space must match that of the underlying MRI image
:param tube_radius: float
controls the size of the arrow
:param color: matplotlib color code
HTML name, RGB tuple or hex code
:param alpha: float in [0, 1]
opacity of coordinate spheres
:param name: str
internal name to use
:param hemi: str | None
If None, assumed to belong to the hemisphere being shown.
If two hemispheresa are being shown, an error will be thrown
"""
hemi = self._check_hemi(hemi)
if map_surface is None:
foci_vtxs = surfer.utils.find_closest_vertices(
self.geo[hemi].coords, coords)
foci_coords = self.geo[hemi].coords[foci_vtxs]
else:
foci_surf = utils.Surface(self.subject_id,
hemi,
map_surface,
subjects_dir=self.subjects_dir)
foci_surf.load_geometry()
foci_vtxs = utils.find_closest_vertices(foci_surf.coords, coords)
foci_coords = self.geo[hemi].coords[foci_vtxs]
# foci_vtxs = surfer.utils.find_closest_vertices(self.geo[hemi].coords, coords)
# foci_coords = self.geo[hemi].coords[foci_vtxs]
# Convert the color code
if not isinstance(color, tuple):
color = colorConverter.to_rgb(color)
if name is None:
name = "arrow_%s" % (len(self.arrows_dict) + 1)
nsegs = 100
x = np.linspace(foci_coords[0, 0], foci_coords[1, 0], nsegs)
y = np.linspace(foci_coords[0, 1], foci_coords[1, 1], nsegs)
z = np.linspace(foci_coords[0, 2], foci_coords[1, 2], nsegs)
line_coords = np.vstack((x, y, z)).transpose()
step = 5
idx_a = range(0, nsegs + 1, step)
idx_b = range(10, nsegs + 1, step)
views = self._toggle_render(False)
al = []
for brain in self._brain_list:
if brain['hemi'] == hemi:
for start, end in zip(idx_a, idx_b):
seg_width = tube_radius - (start *
(tube_radius - .5) / 100.)
al.append(
mlab.plot3d(line_coords[start:end, 0],
line_coords[start:end, 1],
line_coords[start:end, 2],
np.ones_like(line_coords[start:end, 0]),
color=color,
opacity=alpha,
tube_radius=seg_width,
name=name,
figure=brain['brain']._f))
self.arrows_dict[name] = al
self._toggle_render(True, views)