def show_segmentation(voxel_segmentation, size=2.0, width=500, height=500):
ipyvolume.figure(width=width, height=height)
ipyvolume.view(0, 90)
def get_color(label, info):
if label == "stem":
color = (128, 128, 128)
elif label == "unknown":
color = (255, 255, 255)
elif 'pm_leaf_number' in info:
color_map = order_color_map()
color = color_map[info['pm_leaf_number']]
color = tuple([int(255 * x) for x in color])
else:
if label == "growing_leaf":
color = (255, 0, 0)
else:
color = (0, 255, 0)
return "rgb" + str(color)
for vo in voxel_segmentation.voxel_organs:
voxels_position = numpy.array(
list(map(tuple, list(vo.voxels_position()))))
plot_voxel(voxels_position,
size=size * 1,
color=get_color(vo.label, vo.info))
if ((vo.label == "mature_leaf" or vo.label == "growing_leaf")
and len(vo.voxel_segments) > 0
and "pm_position_tip" in vo.info):
plot_voxel(numpy.array([vo.info['pm_position_tip']]),
size=size * 2,
color="red",
marker="sphere")
plot_voxel(numpy.array([vo.info['pm_position_base']]),
size=size * 2,
color="blue",
marker="sphere")
voxels_position = numpy.array(
list(voxel_segmentation.get_voxels_position()))
x_min = voxels_position[:, 0].min()
x_max = voxels_position[:, 0].max()
y_min = voxels_position[:, 1].min()
y_max = voxels_position[:, 1].max()
z_min = voxels_position[:, 2].min()
z_max = voxels_position[:, 2].max()
xyz_max = max(x_max - x_min, y_max - y_min, z_max - z_min)
ipyvolume.xlim(x_min, x_min + xyz_max)
ipyvolume.ylim(y_min, y_min + xyz_max)
ipyvolume.zlim(z_min, z_min + xyz_max)
ipyvolume.show()
def show_mesh(vertices,
faces,
color='green',
width=500,
height=500,
colors=None):
ipyvolume.figure(width=width, height=height)
ipyvolume.view(0, 90)
ipyvolume.plot_trisurf(vertices[:, 0],
vertices[:, 1],
vertices[:, 2],
triangles=faces,
color=color)
x_min = vertices[:, 0].min()
x_max = vertices[:, 0].max()
y_min = vertices[:, 1].min()
y_max = vertices[:, 1].max()
z_min = vertices[:, 2].min()
z_max = vertices[:, 2].max()
xyz_max = max(x_max - x_min, y_max - y_min, z_max - z_min)
ipyvolume.xlim(x_min, x_min + xyz_max)
ipyvolume.ylim(y_min, y_min + xyz_max)
ipyvolume.zlim(z_min, z_min + xyz_max)
ipyvolume.show()
def draw_tensor(tensor_img):
ipv.figure()
# ipv.volshow(tensor_img[...,0], level=[0.36, 0.55,1], opacity=[0.11,0.13, 0.13], level_width=0.05, data_min=0, data_max=1 ,lighting=True)
ipv.volshow(tensor_img[...,0], level=[0.36, 0.17,0.36], opacity=[0.05,0.13, 0.10], level_width=0.05, data_min=0, data_max=1 ,lighting=True)
ipv.view(-30, 45)
ipv.show()
def show_syntehtic_plant(vertices,
faces,
meta_data=None,
size=0.5,
color='green',
width=500,
height=500):
ipyvolume.figure(width=width, height=height)
ipyvolume.view(0, 90)
ipyvolume.plot_trisurf(vertices[:, 0],
vertices[:, 1],
vertices[:, 2],
triangles=faces,
color=color)
voxels_position = vertices
if meta_data is not None:
ranks = meta_data['leaf_order']
polylines = {
n:
list(map(numpy.array, list(zip(*meta_data['leaf_polylines'][i]))))
for i, n in enumerate(ranks)
}
voxels = set()
for leaf_order in polylines:
x, y, z, r = polylines[leaf_order]
polyline = numpy.array(list(zip(x, y, z))) * 10 - \
numpy.array([0, 0, 750])
plot_voxel(polyline, size=size, color="red")
voxels = voxels.union(set(map(tuple, list(polyline))))
voxels = voxels.union(set(map(tuple, list(voxels_position))))
voxels_position = numpy.array(list(voxels), dtype=numpy.int)
x_min = voxels_position[:, 0].min()
x_max = voxels_position[:, 0].max()
y_min = voxels_position[:, 1].min()
y_max = voxels_position[:, 1].max()
z_min = voxels_position[:, 2].min()
z_max = voxels_position[:, 2].max()
xyz_max = max(x_max - x_min, y_max - y_min, z_max - z_min)
ipyvolume.xlim(x_min, x_min + xyz_max)
ipyvolume.ylim(y_min, y_min + xyz_max)
ipyvolume.zlim(z_min, z_min + xyz_max)
ipyvolume.show()
def show_voxel_grid(voxel_grid, color='green', size=2, width=500, height=500):
ipyvolume.figure(width=width, height=height, controls=True, lighting=True)
plot_voxel(voxel_grid.voxels_position, size=size, color=color)
x_min = voxel_grid.voxels_position[:, 0].min()
x_max = voxel_grid.voxels_position[:, 0].max()
y_min = voxel_grid.voxels_position[:, 1].min()
y_max = voxel_grid.voxels_position[:, 1].max()
z_min = voxel_grid.voxels_position[:, 2].min()
z_max = voxel_grid.voxels_position[:, 2].max()
xyz_max = max(x_max - x_min, y_max - y_min, z_max - z_min)
ipyvolume.xlim(x_min, x_min + xyz_max)
ipyvolume.ylim(y_min, y_min + xyz_max)
ipyvolume.zlim(z_min, z_min + xyz_max)
ipyvolume.view(0, 90)
ipyvolume.show()
def show_skeleton(voxel_skeleton,
size=2,
with_voxel=True,
voxels_color='green',
polyline_color='red',
width=500,
height=500):
ipyvolume.figure(width=width, height=height)
ipyvolume.view(0, 90)
if with_voxel:
voxels_position = voxel_skeleton.voxels_position()
plot_voxel(voxels_position, size=size / 2, color=voxels_color)
voxels_position = voxel_skeleton.voxels_position_polyline()
plot_voxel(voxels_position, size=size, color=polyline_color)
for vs in voxel_skeleton.segments:
for color, index in [("blue", 0), ("red", -1)]:
plot_voxel(numpy.array([vs.polyline[index]]),
size=size * 2,
marker="sphere",
color=color)
x_min = voxels_position[:, 0].min()
x_max = voxels_position[:, 0].max()
y_min = voxels_position[:, 1].min()
y_max = voxels_position[:, 1].max()
z_min = voxels_position[:, 2].min()
z_max = voxels_position[:, 2].max()
xyz_max = max(x_max - x_min, y_max - y_min, z_max - z_min)
ipyvolume.xlim(x_min, x_min + xyz_max)
ipyvolume.ylim(y_min, y_min + xyz_max)
ipyvolume.zlim(z_min, z_min + xyz_max)
ipyvolume.show()
def test_view():
fig = ipv.figure()
az0, el0, r0 = ipv.view()
ipv.view(azimuth=az0 + 42)
az, el, r = ipv.view()
assert az == az0 + 42
assert el == el0
assert r == r0
ipv.view(elevation=el0 + 42)
az, el, r = ipv.view()
assert az == az0 + 42
assert el == el0 + 42
assert r == r0
ipv.view(distance=r0 + 42)
az, el, r = ipv.view()
assert az == az0 + 42
assert el == el0 + 42
assert r == r0 + 42
ipv.view(42, 42, 42)
az, el, r = ipv.view()
assert az == 42
assert el == 42
assert r == 42
def test_view():
ipv.figure()
az0, el0, r0 = ipv.view()
ipv.view(azimuth=az0 + 42)
az, el, r = ipv.view()
assert az == pytest.approx(az0 + 42)
assert el == el0
assert r == r0
ipv.view(elevation=el0 + 42)
az, el, r = ipv.view()
assert az == pytest.approx(az0 + 42)
assert el == pytest.approx(el0 + 42)
assert r == r0
ipv.view(distance=r0 + 42)
az, el, r = ipv.view()
assert az == pytest.approx(az0 + 42)
assert el == pytest.approx(el0 + 42)
assert r == pytest.approx(r0 + 42)
ipv.view(42, 42, 42)
az, el, r = ipv.view()
assert az == pytest.approx(42)
assert el == pytest.approx(42)
assert r == pytest.approx(42)
def __init__(self,
subject_id,
hemi,
surf,
title=None,
cortex='classic',
alpha=1.0,
size=800,
background='black',
foreground=None,
figure=None,
subjects_dir=None,
views=['lateral'],
offset=True,
show_toolbar=False,
offscreen=False,
interaction=None,
units='mm'):
# surf = surface
if cortex != 'classic':
raise ValueError('Options for parameter "cortex" ' +
'is not yet supported.')
if figure is not None:
raise ValueError('figure parameter is not supported yet.')
if interaction is not None:
raise ValueError('"interaction" parameter is not supported.')
self._foreground = foreground
self._hemi = hemi
self._units = units
self._title = title
self._subject_id = subject_id
self._views = views
# for now only one color bar can be added
# since it is the same for all figures
self._colorbar_added = False
# array of data used by TimeViewer
self._data = {}
# load geometry for one or both hemispheres as necessary
offset = None if (not offset or hemi != 'both') else 0.0
if hemi in ('both', 'split'):
self._hemis = ('lh', 'rh')
elif hemi in ('lh', 'rh'):
self._hemis = (hemi, )
else:
raise ValueError('hemi has to be either "lh", "rh", "split", ' +
'or "both"')
if isinstance(size, int):
fig_w = size
fig_h = size
else:
fig_w, fig_h = size
self.geo = {}
self._figures = [[] for v in views]
self._hemi_meshes = {}
self._overlays = {}
for h in self._hemis:
# Initialize a Surface object as the geometry
geo = Surface(subject_id,
h,
surf,
subjects_dir,
offset,
units=self._units)
# Load in the geometry and curvature
geo.load_geometry()
geo.load_curvature()
self.geo[h] = geo
for ri, v in enumerate(views):
fig = ipv.figure(width=fig_w, height=fig_h, lighting=True)
fig.animation = 0
self._figures[ri].append(fig)
ipv.style.box_off()
ipv.style.axes_off()
ipv.style.background_color(background)
ipv.view(views_dict[v].azim, views_dict[v].elev)
for ci, h in enumerate(self._hemis):
if ci == 1 and hemi == 'split':
# create a separate figure for right hemisphere
fig = ipv.figure(width=fig_w, height=fig_h, lighting=True)
fig.animation = 0
self._figures[ri].append(fig)
ipv.style.box_off()
ipv.style.axes_off()
ipv.style.background_color(background)
ipv.view(views_dict[v].azim, views_dict[v].elev)
hemi_mesh = self._plot_hemi_mesh(self.geo[h].coords,
self.geo[h].faces,
self.geo[h].grey_curv)
self._hemi_meshes[h + '_' + v] = hemi_mesh
ipv.squarelim()
self._add_title()
def plot_brain_mesh(rh_vertices=None,
lh_vertices=None,
rh_faces=None,
lh_faces=None,
rh_color='grey',
lh_color='grey',
fig_size=(500, 500),
azimuth=90,
elevation=90):
"""Function for plotting triangular format Freesurfer surface of the brain.
Parameters
----------
rh_vertices : numpy.array, optional
Array of right hemisphere vertex (x, y, z) coordinates, of size
number_of_vertices x 3. Default is None.
lh_vertices : numpy.array, optional
Array of left hemisphere vertex (x, y, z) coordinates, of size
number_of_vertices x 3. Default is None.
rh_faces : numpy.array, optional
Array defining right hemisphere mesh triangles, of size
number_of_faces x 3. Default is None.
lh_faces : numpy.array, optional
Array defining mesh triangles, of size number_of_faces x 3.
Default is None.
rh_color : str | numpy.array, optional
Color for each point/vertex/symbol of the right hemisphere,
can be string format, examples for red:’red’, ‘#f00’, ‘#ff0000’ or
‘rgb(1,0,0), or rgb array of shape (N, 3). Default value is 'grey'.
lh_color : str | numpy.array, optional
Color for each point/vertex/symbol of the left hemisphere,
can be string format, examples for red:’red’, ‘#f00’, ‘#ff0000’ or
‘rgb(1,0,0), or rgb array of shape (N, 3). Default value is 'grey'.
fig_size : (int, int), optional
Width and height of the figure. Default is (500, 500).
azimuth : int, optional
Angle of rotation about the z-axis (pointing up) in degrees.
Default is 90.
elevation : int, optional
Vertical rotation where 90 means ‘up’, -90 means ‘down’, in degrees.
Default is 90.
Returns
-------
fig : ipyvolume.Figure
Ipyvolume object presenting the figure.
rh_mesh : ipyvolume.Mesh
Ipyvolume object presenting the built mesh for right hemisphere.
lh_mesh : ipyvolume.Mesh
Ipyvolume object presenting the built mesh for right hemisphere.
"""
rh_mesh = None
lh_mesh = None
fig = ipv.figure(width=fig_size[0], height=fig_size[1], lighting=True)
if (rh_vertices is not None) and (rh_faces is not None):
rh_mesh = plot_hemisphere_mesh(rh_vertices, rh_faces, rh_color)
if (lh_vertices is not None) and (lh_faces is not None):
lh_mesh = plot_hemisphere_mesh(lh_vertices, lh_faces, lh_color)
style.use('minimal')
ipv.view(azimuth, elevation)
ipv.squarelim()
ipv.show()
return fig, rh_mesh, lh_mesh
