def get_injection_sites(self, experiments, color=None):
"""
Creates Spherse at the location of injections with a volume proportional to the injected volume
:param experiments: list of dictionaries with tractography data
:param color: (Default value = None)
"""
# check arguments
if not isinstance(experiments, list):
raise ValueError("experiments must be a list")
if not isinstance(experiments[0], dict):
raise ValueError("experiments should be a list of dictionaries")
#c= cgeck color
if color is None:
color = INJECTION_DEFAULT_COLOR
injection_sites = []
for exp in experiments:
injection_sites.append(shapes.Sphere(pos=(exp["injection_x"], exp["injection_y"], exp["injection_z"]),
r = INJECTION_VOLUME_SIZE*exp["injection_volume"]*3,
c=color
))
return injection_sites
def render_neuron(self, neuron, neuron_number, neuron_name):
"""
This function takes care of rendering a single neuron.
:param neuron: dictionary with neurons data
:param neuron_number: number of neuron being rendered
:param neuron_name: name of the neuron, used to load/save the .vtk files with the rendered neuron.
"""
# Prepare variables for rendering
soma_color, axon_color, dendrites_color, soma_region = self._render_neuron_get_params(neuron_number, neuron=neuron)
# create soma actor
neuron_actors = None
if USE_MORPHOLOGY_CACHE:
params = dict(
force_to_hemisphere = self.force_to_hemisphere,
neurite_radius = self.neurite_radius,
)
neuron_actors = self._load_cached_neuron(neuron_name, params)
if neuron_actors is not None:
# Color the loaded neuron
for component, color in zip(['soma', 'dendrites', 'axon'], [soma_color, dendrites_color, axon_color]):
if component in list(neuron_actors.keys()):
neuron_actors[component].color(color)
return neuron_actors, {'soma':soma_region, 'dendrites':None, 'axons':None}
if not USE_MORPHOLOGY_CACHE or neuron_actors is None:
print("Parsing neuron: " + neuron_name)
neuron_actors = {}
self.soma_coords = get_coords(neuron["soma"], mirror=self.mirror_coord, mirror_ax=self.mirror_ax)
neuron_actors['soma'] = shapes.Sphere(pos=self.soma_coords, c=soma_color, r=SOMA_RADIUS)
# Draw dendrites and axons
if self.render_neurites:
if self.is_json:
neuron_actors['dendrites'], dendrites_regions = self.neurites_parser(pd.DataFrame(neuron["dendrite"]), dendrites_color)
neuron_actors['axon'], axon_regions = self.neurites_parser(pd.DataFrame(neuron["axon"]), axon_color)
else:
neuron_actors['dendrites'], dendrites_regions = self.neurites_parser_swc(pd.DataFrame(neuron["dendrite"]), dendrites_color)
neuron_actors['axon'], axon_regions = self.neurites_parser_swc(pd.DataFrame(neuron["axon"]), axon_color)
else:
neuron_actors['dendrites'], dendrites_regions = [], None
neuron_actors['axon'], axon_regions = [], None
self.decimate_neuron_actors(neuron_actors)
self.smooth_neurons(neuron_actors)
# force to hemisphere
if self.force_to_hemisphere is not None:
neuron_actors = self.mirror_neuron(neuron_actors)
if USE_MORPHOLOGY_CACHE:
self._cache_neuron(neuron_actors, neuron_name, params)
return neuron_actors, {'soma':soma_region, 'dendrites':dendrites_regions, 'axon':axon_regions}
def parse_neurons_swc_allen(self, morphology, color='blackboard', alpha=1):
"""
SWC parser for Allen neuron's morphology data, they're a bit different from the Mouse Light SWC
:param morphology: data with morphology
:param neuron_number: int, number of the neuron being rendered.
"""
# Create soma actor
radius = 1
neuron_actors = [
shapes.Sphere(pos=get_coords(morphology.soma)[::-1],
c=color,
r=radius * 3)
]
# loop over trees
for tree in morphology._tree_list:
tree = pd.DataFrame(tree)
branching_points = [
t.id for i, t in tree.iterrows()
if len(t.children) > 2 and t.id < len(tree)
]
branch_starts = []
for bp in branching_points:
branch_starts.extend(tree.iloc[bp].children)
for bp in branch_starts:
parent = tree.iloc[tree.iloc[bp].parent]
branch = [(parent.x, parent.y, parent.z)]
point = tree.iloc[bp]
while True:
branch.append((point.x, point.y, point.z))
if not point.children:
break
else:
try:
point = tree.iloc[point.children[0]]
except:
break
# Create actor
neuron_actors.append(
shapes.Tube(branch, r=radius, c='red', alpha=1, res=24))
actor = merge(*neuron_actors)
actor.color(color)
actor.alpha(alpha)
return actor
def add_sphere_at_point(self, pos=[0, 0, 0], radius=100, color="black", alpha=1, **kwargs): """ Adds a shere at a location specified by the user :param pos: list of x,y,z coordinates (Default value = [0, 0, 0]) :param radius: int, radius of the sphere (Default value = 100) :param color: color of the sphere (Default value = "black") :param alpha: transparency of the sphere (Default value = 1) :param **kwargs: """ sphere = shapes.Sphere(pos=pos, r=radius, c=color, alpha=alpha, **kwargs) self.actors['others'].append(sphere) return sphere
def parse_neuron_swc(self,
filepath,
color='blackboard',
alpha=1,
radius_multiplier=.1,
overwrite=False):
"""
Given an swc file, render the neuron
:param filepath: str with path to swc file
:param neuron_number: numnber of neuron being rendered
"""
# See if we rendered this neuron already
if not overwrite:
loaded = self.load_save_neuron(filepath)
if loaded is not None:
return loaded.color(color)
print(f"Parsing swc file: {filepath}")
# details on swc files: http://www.neuronland.org/NLMorphologyConverter/MorphologyFormats/SWC/Spec.html
_sample = namedtuple("sample", "sampleN structureID x y z r parent"
) # sampleN structureID x y z r parent
if not os.path.isfile(filepath) or not ".swc" in filepath.lower():
raise ValueError("unrecognized file path: {}".format(filepath))
try:
return self.parse_neurons_swc_allen(filepath)
except:
pass # the .swc file fas not generate with by allen
f = open(filepath)
content = f.readlines()
f.close()
content = [
sample.replace("\n", "") for sample in content if sample[0] != '#'
]
content = [sample for sample in content if len(sample) > 3]
# crate empty dicts for soma axon and dendrites
data = dict(id=[],
parentNumber=[],
radius=[],
sampleNumber=[],
x=[],
y=[],
z=[])
# start looping around samples
for sample in content:
s = _sample(
*[float(samp) for samp in sample.lstrip().rstrip().split(" ")])
# append data to dictionary
data['id'] = s.structureID
data['parentNumber'].append(int(s.parent))
data['radius'].append(s.r)
data['x'].append(s.x)
data['y'].append(s.y)
data['z'].append(s.z)
data['sampleNumber'].append(int(s.sampleN))
# Get branches and soma
print(" reconstructing neurites trees")
data = pd.DataFrame(data)
radius = data['radius'].values[0] * radius_multiplier
soma = data.iloc[0]
soma = shapes.Sphere(pos=[soma.x, soma.y, soma.z],
c=color,
r=radius * 4)
neuron_actors = [soma]
branches_end, branches_start = [], [] # Get branches start and end
for parent in data.parentNumber.values:
sons = data.loc[data.parentNumber == parent]
if len(sons) > 1:
branches_end.append(parent)
for i, son in sons.iterrows():
branches_start.append(son.sampleNumber)
print(" creating actors")
for start in branches_start:
node = data.loc[data.sampleNumber == start]
parent = data.loc[data.sampleNumber == node.parentNumber.values[0]]
branch = [(parent.x.values[0], parent.y.values[0],
parent.z.values[0])]
while True:
branch.append(
(node.x.values[0], node.y.values[0], node.z.values[0]))
node = data.loc[data.parentNumber ==
node.sampleNumber.values[0]]
if not len(node): break
if node.sampleNumber.values[0] in branches_end:
branch.append(
(node.x.values[0], node.y.values[0], node.z.values[0]))
break
neuron_actors.append(
shapes.Tube(branch, r=radius, c='red', alpha=1, res=24))
# Merge actors and save
actor = merge(*neuron_actors)
actor.color(color)
actor.alpha(alpha)
self.load_save_neuron(filepath, neuron=actor)
return actor
def neurites_parser(self, neurites, color):
"""
Given a dataframe with all the samples for some neurites, create "Tube" actors that render each neurite segment.
----------------------------------------------------------------
This function works by first identifyingt the branching points of a neurite structure. Then each segment between either two branchin points
or between a branching point and a terminal is modelled as a Tube. This minimizes the number of actors needed to represent the neurites
while stil accurately modelling the neuron.
Known issue: the axon initial segment is missing from renderings.
:param neurites: dataframe with each sample for the neurites
:param color: color to be assigned to the Tube actor
"""
neurite_radius = self._get_neurites_radius()
# get branching points
try:
parent_counts = neurites["parentNumber"].value_counts()
except:
if len(neurites) == 0:
print("Couldn't find neurites data")
return [], []
else:
raise ValueError(
"Something went wrong while rendering neurites:\n{}".
format(neurites))
branching_points = parent_counts.loc[parent_counts > 1]
# loop over each branching point
actors = []
for idx, bp in branching_points.iteritems():
# get neurites after the branching point
bp = neurites.loc[neurites.sampleNumber == idx]
post_bp = neurites.loc[neurites.parentNumber == idx]
parent = neurites.loc[neurites.sampleNumber ==
bp.parentNumber.values[0]]
# loop on each branch after the branching point
for bi, branch in post_bp.iterrows():
# Start coordinates in a list, including parent and branch point
if len(parent):
branch_points = [
get_coords(parent,
mirror=self.mirror_coord,
mirror_ax=self.mirror_ax)
]
else:
branch_points = []
branch_points.extend([
get_coords(bp,
mirror=self.mirror_coord,
mirror_ax=self.mirror_ax),
get_coords(branch,
mirror=self.mirror_coord,
mirror_ax=self.mirror_ax)
])
# loop over all following points along the branch, until you meet either a terminal or another branching point. store the points
idx = branch.sampleNumber
while True:
nxt = neurites.loc[neurites.parentNumber == idx]
if len(nxt) != 1:
break
else:
branch_points.append(
get_coords(nxt,
mirror=self.mirror_coord,
mirror_ax=self.mirror_ax))
idx = nxt.sampleNumber.values[0]
# if the branch is too short for a tube, create a sphere instead
if len(
branch_points
) < 2: # plot either a line between two branch_points or a spheere
actors.append(shapes.Sphere(branch_points[0], c="g",
r=100))
continue
# create tube actor
actors.append(
shapes.Tube(branch_points,
r=neurite_radius,
c=color,
alpha=1,
res=NEURON_RESOLUTION))
# merge actors' meshes to make rendering faster
merged = merge(*actors)
if merged is None:
return None, None
merged.color(color)
# get regions the neurites go through
regions = []
if "allenId" in neurites.columns:
for rid in set(neurites.allenId.values):
try:
region = self.alleninfo.loc[self.alleninfo.allenId ==
rid].acronym.values[0]
regions.append(
self.scene.get_structure_parent(region)['acronym'])
except:
pass
return merged, regions
def addAxes(axtype=None, c=None):
"""Draw axes on scene. Available axes types:
:param int axtype:
- 0, no axes,
- 1, draw three gray grid walls
- 2, show cartesian axes from (0,0,0)
- 3, show positive range of cartesian axes from (0,0,0)
- 4, show a triad at bottom left
- 5, show a cube at bottom left
- 6, mark the corners of the bounding box
- 7, draw a simple ruler at the bottom of the window
- 8, show the ``vtkCubeAxesActor`` object
- 9, show the bounding box outLine
- 10, show three circles representing the maximum bounding box
"""
vp = settings.plotter_instance
if axtype is not None:
vp.axes = axtype # overrride
r = vp.renderers.index(vp.renderer)
if not vp.axes:
return
if c is None: # automatic black or white
c = (0.9, 0.9, 0.9)
if numpy.sum(vp.renderer.GetBackground()) > 1.5:
c = (0.1, 0.1, 0.1)
if not vp.renderer:
return
if vp.axes_exist[r]:
return
# calculate max actors bounds
bns = []
for a in vp.actors:
if a and a.GetPickable():
b = a.GetBounds()
if b:
bns.append(b)
if len(bns):
max_bns = numpy.max(bns, axis=0)
min_bns = numpy.min(bns, axis=0)
vbb = (min_bns[0], max_bns[1], min_bns[2], max_bns[3], min_bns[4],
max_bns[5])
else:
vbb = vp.renderer.ComputeVisiblePropBounds()
max_bns = vbb
min_bns = vbb
sizes = (max_bns[1] - min_bns[0], max_bns[3] - min_bns[2],
max_bns[5] - min_bns[4])
############################################################
if vp.axes == 1 or vp.axes == True: # gray grid walls
nd = 4 # number of divisions in the smallest axis
off = -0.04 # label offset
step = numpy.min(sizes) / nd
if not step:
# bad proportions, use vtkCubeAxesActor
vp.addAxes(axtype=8, c=c)
vp.axes = 1
return
rx, ry, rz = numpy.rint(sizes / step).astype(int)
if max([rx / ry, ry / rx, rx / rz, rz / rx, ry / rz, rz / ry]) > 15:
# bad proportions, use vtkCubeAxesActor
vp.addAxes(axtype=8, c=c)
vp.axes = 1
return
gxy = shapes.Grid(pos=(0.5, 0.5, 0),
normal=[0, 0, 1],
bc=None,
resx=rx,
resy=ry)
gxz = shapes.Grid(pos=(0.5, 0, 0.5),
normal=[0, 1, 0],
bc=None,
resx=rz,
resy=rx)
gyz = shapes.Grid(pos=(0, 0.5, 0.5),
normal=[1, 0, 0],
bc=None,
resx=rz,
resy=ry)
gxy.alpha(0.06).wire(False).color(c).lineWidth(1)
gxz.alpha(0.04).wire(False).color(c).lineWidth(1)
gyz.alpha(0.04).wire(False).color(c).lineWidth(1)
xa = shapes.Line([0, 0, 0], [1, 0, 0], c=c, lw=1)
ya = shapes.Line([0, 0, 0], [0, 1, 0], c=c, lw=1)
za = shapes.Line([0, 0, 0], [0, 0, 1], c=c, lw=1)
xt, yt, zt, ox, oy, oz = [None] * 6
if vp.xtitle:
xtitle = vp.xtitle
if min_bns[0] <= 0 and max_bns[1] > 0: # mark x origin
ox = shapes.Cube([-min_bns[0] / sizes[0], 0, 0],
side=0.008,
c=c)
if len(vp.xtitle) == 1: # add axis length info
xtitle = vp.xtitle + " /" + utils.precision(sizes[0], 4)
wpos = [1 - (len(vp.xtitle) + 1) / 40, off, 0]
xt = shapes.Text(xtitle,
pos=wpos,
normal=(0, 0, 1),
s=0.025,
c=c,
justify="bottom-right")
if vp.ytitle:
if min_bns[2] <= 0 and max_bns[3] > 0: # mark y origin
oy = shapes.Cube([0, -min_bns[2] / sizes[1], 0],
side=0.008,
c=c)
yt = shapes.Text(vp.ytitle,
pos=(0, 0, 0),
normal=(0, 0, 1),
s=0.025,
c=c,
justify="bottom-right")
if len(vp.ytitle) == 1:
wpos = [off, 1 - (len(vp.ytitle) + 1) / 40, 0]
yt.pos(wpos)
else:
wpos = [off * 0.7, 1 - (len(vp.ytitle) + 1) / 40, 0]
yt.rotateZ(90).pos(wpos)
if vp.ztitle:
if min_bns[4] <= 0 and max_bns[5] > 0: # mark z origin
oz = shapes.Cube([0, 0, -min_bns[4] / sizes[2]],
side=0.008,
c=c)
zt = shapes.Text(vp.ztitle,
pos=(0, 0, 0),
normal=(1, -1, 0),
s=0.025,
c=c,
justify="bottom-right")
if len(vp.ztitle) == 1:
wpos = [off * 0.6, off * 0.6, 1 - (len(vp.ztitle) + 1) / 40]
zt.rotate(90, (1, -1, 0)).pos(wpos)
else:
wpos = [off * 0.3, off * 0.3, 1 - (len(vp.ztitle) + 1) / 40]
zt.rotate(180, (1, -1, 0)).pos(wpos)
acts = [gxy, gxz, gyz, xa, ya, za, xt, yt, zt, ox, oy, oz]
for a in acts:
if a:
a.PickableOff()
aa = Assembly(acts)
aa.pos(min_bns[0], min_bns[2], min_bns[4])
aa.SetScale(sizes)
aa.PickableOff()
vp.renderer.AddActor(aa)
vp.axes_exist[r] = aa
elif vp.axes == 2 or vp.axes == 3:
vbb = vp.renderer.ComputeVisiblePropBounds() # to be double checked
xcol, ycol, zcol = "db", "dg", "dr"
s = 1
alpha = 1
centered = False
x0, x1, y0, y1, z0, z1 = vbb
dx, dy, dz = x1 - x0, y1 - y0, z1 - z0
aves = numpy.sqrt(dx * dx + dy * dy + dz * dz) / 2
x0, x1 = min(x0, 0), max(x1, 0)
y0, y1 = min(y0, 0), max(y1, 0)
z0, z1 = min(z0, 0), max(z1, 0)
if vp.axes == 3:
if x1 > 0:
x0 = 0
if y1 > 0:
y0 = 0
if z1 > 0:
z0 = 0
dx, dy, dz = x1 - x0, y1 - y0, z1 - z0
acts = []
if x0 * x1 <= 0 or y0 * z1 <= 0 or z0 * z1 <= 0: # some ranges contain origin
zero = shapes.Sphere(r=aves / 120 * s, c="k", alpha=alpha, res=10)
acts += [zero]
if len(vp.xtitle) and dx > aves / 100:
xl = shapes.Cylinder([[x0, 0, 0], [x1, 0, 0]],
r=aves / 250 * s,
c=xcol,
alpha=alpha)
xc = shapes.Cone(pos=[x1, 0, 0],
c=xcol,
alpha=alpha,
r=aves / 100 * s,
height=aves / 25 * s,
axis=[1, 0, 0],
res=10)
wpos = [
x1 - (len(vp.xtitle) + 1) * aves / 40 * s, -aves / 25 * s, 0
] # aligned to arrow tip
if centered:
wpos = [(x0 + x1) / 2 - len(vp.xtitle) / 2 * aves / 40 * s,
-aves / 25 * s, 0]
xt = shapes.Text(vp.xtitle,
pos=wpos,
normal=(0, 0, 1),
s=aves / 40 * s,
c=xcol)
acts += [xl, xc, xt]
if len(vp.ytitle) and dy > aves / 100:
yl = shapes.Cylinder([[0, y0, 0], [0, y1, 0]],
r=aves / 250 * s,
c=ycol,
alpha=alpha)
yc = shapes.Cone(pos=[0, y1, 0],
c=ycol,
alpha=alpha,
r=aves / 100 * s,
height=aves / 25 * s,
axis=[0, 1, 0],
res=10)
wpos = [
-aves / 40 * s, y1 - (len(vp.ytitle) + 1) * aves / 40 * s, 0
]
if centered:
wpos = [
-aves / 40 * s,
(y0 + y1) / 2 - len(vp.ytitle) / 2 * aves / 40 * s, 0
]
yt = shapes.Text(vp.ytitle,
pos=(0, 0, 0),
normal=(0, 0, 1),
s=aves / 40 * s,
c=ycol)
yt.rotate(90, [0, 0, 1]).pos(wpos)
acts += [yl, yc, yt]
if len(vp.ztitle) and dz > aves / 100:
zl = shapes.Cylinder([[0, 0, z0], [0, 0, z1]],
r=aves / 250 * s,
c=zcol,
alpha=alpha)
zc = shapes.Cone(pos=[0, 0, z1],
c=zcol,
alpha=alpha,
r=aves / 100 * s,
height=aves / 25 * s,
axis=[0, 0, 1],
res=10)
wpos = [
-aves / 50 * s, -aves / 50 * s,
z1 - (len(vp.ztitle) + 1) * aves / 40 * s
]
if centered:
wpos = [
-aves / 50 * s, -aves / 50 * s,
(z0 + z1) / 2 - len(vp.ztitle) / 2 * aves / 40 * s
]
zt = shapes.Text(vp.ztitle,
pos=(0, 0, 0),
normal=(1, -1, 0),
s=aves / 40 * s,
c=zcol)
zt.rotate(180, (1, -1, 0)).pos(wpos)
acts += [zl, zc, zt]
for a in acts:
a.PickableOff()
ass = Assembly(acts)
ass.PickableOff()
vp.renderer.AddActor(ass)
vp.axes_exist[r] = ass
elif vp.axes == 4:
axact = vtk.vtkAxesActor()
axact.SetShaftTypeToCylinder()
axact.SetCylinderRadius(0.03)
axact.SetXAxisLabelText(vp.xtitle)
axact.SetYAxisLabelText(vp.ytitle)
axact.SetZAxisLabelText(vp.ztitle)
axact.GetXAxisShaftProperty().SetColor(0, 0, 1)
axact.GetZAxisShaftProperty().SetColor(1, 0, 0)
axact.GetXAxisTipProperty().SetColor(0, 0, 1)
axact.GetZAxisTipProperty().SetColor(1, 0, 0)
bc = numpy.array(vp.renderer.GetBackground())
if numpy.sum(bc) < 1.5:
lc = (1, 1, 1)
else:
lc = (0, 0, 0)
axact.GetXAxisCaptionActor2D().GetCaptionTextProperty().BoldOff()
axact.GetYAxisCaptionActor2D().GetCaptionTextProperty().BoldOff()
axact.GetZAxisCaptionActor2D().GetCaptionTextProperty().BoldOff()
axact.GetXAxisCaptionActor2D().GetCaptionTextProperty().ItalicOff()
axact.GetYAxisCaptionActor2D().GetCaptionTextProperty().ItalicOff()
axact.GetZAxisCaptionActor2D().GetCaptionTextProperty().ItalicOff()
axact.GetXAxisCaptionActor2D().GetCaptionTextProperty().ShadowOff()
axact.GetYAxisCaptionActor2D().GetCaptionTextProperty().ShadowOff()
axact.GetZAxisCaptionActor2D().GetCaptionTextProperty().ShadowOff()
axact.GetXAxisCaptionActor2D().GetCaptionTextProperty().SetColor(lc)
axact.GetYAxisCaptionActor2D().GetCaptionTextProperty().SetColor(lc)
axact.GetZAxisCaptionActor2D().GetCaptionTextProperty().SetColor(lc)
axact.PickableOff()
icn = addIcon(axact, size=0.1)
vp.axes_exist[r] = icn
elif vp.axes == 5:
axact = vtk.vtkAnnotatedCubeActor()
axact.GetCubeProperty().SetColor(0.75, 0.75, 0.75)
axact.SetTextEdgesVisibility(0)
axact.SetFaceTextScale(0.4)
axact.GetXPlusFaceProperty().SetColor(colors.getColor("b"))
axact.GetXMinusFaceProperty().SetColor(colors.getColor("db"))
axact.GetYPlusFaceProperty().SetColor(colors.getColor("g"))
axact.GetYMinusFaceProperty().SetColor(colors.getColor("dg"))
axact.GetZPlusFaceProperty().SetColor(colors.getColor("r"))
axact.GetZMinusFaceProperty().SetColor(colors.getColor("dr"))
axact.PickableOff()
icn = addIcon(axact, size=0.06)
vp.axes_exist[r] = icn
elif vp.axes == 6:
ocf = vtk.vtkOutlineCornerFilter()
ocf.SetCornerFactor(0.1)
largestact, sz = None, -1
for a in vp.actors:
if a.GetPickable():
b = a.GetBounds()
d = max(b[1] - b[0], b[3] - b[2], b[5] - b[4])
if sz < d:
largestact = a
sz = d
if isinstance(largestact, Assembly):
ocf.SetInputData(largestact.getActor(0).GetMapper().GetInput())
else:
ocf.SetInputData(largestact.polydata())
ocf.Update()
ocMapper = vtk.vtkHierarchicalPolyDataMapper()
ocMapper.SetInputConnection(0, ocf.GetOutputPort(0))
ocActor = vtk.vtkActor()
ocActor.SetMapper(ocMapper)
bc = numpy.array(vp.renderer.GetBackground())
if numpy.sum(bc) < 1.5:
lc = (1, 1, 1)
else:
lc = (0, 0, 0)
ocActor.GetProperty().SetColor(lc)
ocActor.PickableOff()
vp.renderer.AddActor(ocActor)
vp.axes_exist[r] = ocActor
elif vp.axes == 7:
# draws a simple ruler at the bottom of the window
ls = vtk.vtkLegendScaleActor()
ls.RightAxisVisibilityOff()
ls.TopAxisVisibilityOff()
ls.LegendVisibilityOff()
ls.LeftAxisVisibilityOff()
ls.GetBottomAxis().SetNumberOfMinorTicks(1)
ls.GetBottomAxis().GetProperty().SetColor(c)
ls.GetBottomAxis().GetLabelTextProperty().SetColor(c)
ls.GetBottomAxis().GetLabelTextProperty().BoldOff()
ls.GetBottomAxis().GetLabelTextProperty().ItalicOff()
ls.GetBottomAxis().GetLabelTextProperty().ShadowOff()
ls.PickableOff()
vp.renderer.AddActor(ls)
vp.axes_exist[r] = ls
elif vp.axes == 8:
ca = vtk.vtkCubeAxesActor()
ca.SetBounds(vbb)
if vp.camera:
ca.SetCamera(vp.camera)
else:
ca.SetCamera(vp.renderer.GetActiveCamera())
ca.GetXAxesLinesProperty().SetColor(c)
ca.GetYAxesLinesProperty().SetColor(c)
ca.GetZAxesLinesProperty().SetColor(c)
for i in range(3):
ca.GetLabelTextProperty(i).SetColor(c)
ca.GetTitleTextProperty(i).SetColor(c)
ca.SetTitleOffset(5)
ca.SetFlyMode(3)
ca.SetXTitle(vp.xtitle)
ca.SetYTitle(vp.ytitle)
ca.SetZTitle(vp.ztitle)
if vp.xtitle == "":
ca.SetXAxisVisibility(0)
ca.XAxisLabelVisibilityOff()
if vp.ytitle == "":
ca.SetYAxisVisibility(0)
ca.YAxisLabelVisibilityOff()
if vp.ztitle == "":
ca.SetZAxisVisibility(0)
ca.ZAxisLabelVisibilityOff()
ca.PickableOff()
vp.renderer.AddActor(ca)
vp.axes_exist[r] = ca
return
elif vp.axes == 9:
src = vtk.vtkCubeSource()
src.SetXLength(vbb[1] - vbb[0])
src.SetYLength(vbb[3] - vbb[2])
src.SetZLength(vbb[5] - vbb[4])
src.Update()
ca = Actor(src.GetOutput(), c=c, alpha=0.5, wire=1)
ca.pos((vbb[0] + vbb[1]) / 2, (vbb[3] + vbb[2]) / 2,
(vbb[5] + vbb[4]) / 2)
ca.PickableOff()
vp.renderer.AddActor(ca)
vp.axes_exist[r] = ca
elif vp.axes == 10:
x0 = (vbb[0] + vbb[1]) / 2, (vbb[3] + vbb[2]) / 2, (vbb[5] +
vbb[4]) / 2
rx, ry, rz = (vbb[1] - vbb[0]) / 2, (vbb[3] - vbb[2]) / 2, (vbb[5] -
vbb[4]) / 2
rm = max(rx, ry, rz)
xc = shapes.Disc(x0, (0, 0, 1),
r1=rm,
r2=rm,
c='lr',
bc=None,
res=1,
resphi=72)
yc = shapes.Disc(x0, (0, 1, 0),
r1=rm,
r2=rm,
c='lg',
bc=None,
res=1,
resphi=72)
zc = shapes.Disc(x0, (1, 0, 0),
r1=rm,
r2=rm,
c='lb',
bc=None,
res=1,
resphi=72)
xc.clean().alpha(0.2).wire().lineWidth(2.5).PickableOff()
yc.clean().alpha(0.2).wire().lineWidth(2.5).PickableOff()
zc.clean().alpha(0.2).wire().lineWidth(2.5).PickableOff()
ca = xc + yc + zc
ca.PickableOff()
vp.renderer.AddActor(ca)
vp.axes_exist[r] = ca
else:
colors.printc('~bomb Keyword axes must be in range [0-10].', c=1)
colors.printc('''
~target Available axes types:
0 = no axes,
1 = draw three gray grid walls
2 = show cartesian axes from (0,0,0)
3 = show positive range of cartesian axes from (0,0,0)
4 = show a triad at bottom left
5 = show a cube at bottom left
6 = mark the corners of the bounding box
7 = draw a simple ruler at the bottom of the window
8 = show the vtkCubeAxesActor object
9 = show the bounding box outline
10 = show three circles representing the maximum bounding box
''',
c=1,
bold=0)
if not vp.axes_exist[r]:
vp.axes_exist[r] = True
return
def get_tractography(self, tractography, color=None, color_by="manual", others_alpha=1, verbose=True,
VIP_regions=[], VIP_color=None, others_color="white", include_all_inj_regions=False,
extract_region_from_inj_coords=False, display_injection_volume=True):
"""
Renders tractography data and adds it to the scene. A subset of tractography data can receive special treatment using the with VIP regions argument:
if the injection site for the tractography data is in a VIP regions, this is colored differently.
:param tractography: list of dictionaries with tractography data
:param color: color of rendered tractography data
:param color_by: str, specifies which criteria to use to color the tractography (Default value = "manual")
:param others_alpha: float (Default value = 1)
:param verbose: bool (Default value = True)
:param VIP_regions: list of brain regions with VIP treatement (Default value = [])
:param VIP_color: str, color to use for VIP data (Default value = None)
:param others_color: str, color for not VIP data (Default value = "white")
:param include_all_inj_regions: bool (Default value = False)
:param extract_region_from_inj_coords: bool (Default value = False)
:param display_injection_volume: float, if True a spehere is added to display the injection coordinates and volume (Default value = True)
"""
# check argument
if not isinstance(tractography, list):
if isinstance(tractography, dict):
tractography = [tractography]
else:
raise ValueError("the 'tractography' variable passed must be a list of dictionaries")
else:
if not isinstance(tractography[0], dict):
raise ValueError("the 'tractography' variable passed must be a list of dictionaries")
if not isinstance(VIP_regions, list):
raise ValueError("VIP_regions should be a list of acronyms")
# check coloring mode used and prepare a list COLORS to use for coloring stuff
if color_by == "manual":
# check color argument
if color is None:
color = TRACT_DEFAULT_COLOR
COLORS = [color for i in range(len(tractography))]
elif isinstance(color, list):
if not len(color) == len(tractography):
raise ValueError("If a list of colors is passed, it must have the same number of items as the number of tractography traces")
else:
for col in color:
if not check_colors(col): raise ValueError("Color variable passed to tractography is invalid: {}".format(col))
COLORS = color
else:
if not check_colors(color):
raise ValueError("Color variable passed to tractography is invalid: {}".format(color))
else:
COLORS = [color for i in range(len(tractography))]
elif color_by == "region":
COLORS = [self.get_region_color(t['structure-abbrev']) for t in tractography]
elif color_by == "target_region":
if VIP_color is not None:
if not check_colors(VIP_color) or not check_colors(others_color):
raise ValueError("Invalid VIP or other color passed")
try:
if include_all_inj_regions:
COLORS = [VIP_color if is_any_item_in_list( [x['abbreviation'] for x in t['injection-structures']], VIP_regions)\
else others_color for t in tractography]
else:
COLORS = [VIP_color if t['structure-abbrev'] in VIP_regions else others_color for t in tractography]
except:
raise ValueError("Something went wrong while getting colors for tractography")
else:
COLORS = [self.get_region_color(t['structure-abbrev']) if t['structure-abbrev'] in VIP_regions else others_color for t in tractography]
else:
raise ValueError("Unrecognised 'color_by' argument {}".format(color_by))
# add actors to represent tractography data
actors, structures_acronyms = [], []
if VERBOSE and verbose:
print("Structures found to be projecting to target: ")
# Loop over injection experiments
for i, (t, color) in enumerate(zip(tractography, COLORS)):
# Use allen metadata
if include_all_inj_regions:
inj_structures = [x['abbreviation'] for x in t['injection-structures']]
else:
inj_structures = [self.get_structure_parent(t['structure-abbrev'])['acronym']]
if VERBOSE and verbose and not is_any_item_in_list(inj_structures, structures_acronyms):
print(" -- ({})".format(t['structure-abbrev']))
structures_acronyms.append(t['structure-abbrev'])
# get tractography points and represent as list
if color_by == "target_region" and not is_any_item_in_list(inj_structures, VIP_regions):
alpha = others_alpha
else:
alpha = TRACTO_ALPHA
if alpha == 0:
continue # skip transparent ones
# check if we need to manually check injection coords
if extract_region_from_inj_coords:
try:
region = self.get_structure_from_coordinates(t['injection-coordinates'],
just_acronym=False)
if region is None: continue
inj_structures = [self.get_structure_parent(region['acronym'])['acronym']]
except:
raise ValueError(self.get_structure_from_coordinates(t['injection-coordinates'],
just_acronym=False))
if inj_structures is None: continue
elif isinstance(extract_region_from_inj_coords, list):
# check if injection coord are in one of the brain regions in list, otherwise skip
if not is_any_item_in_list(inj_structures, extract_region_from_inj_coords):
continue
# represent injection site as sphere
if display_injection_volume:
actors.append(shapes.Sphere(pos=t['injection-coordinates'],
c=color, r=INJECTION_VOLUME_SIZE*t['injection-volume'], alpha=TRACTO_ALPHA))
points = [p['coord'] for p in t['path']]
actors.append(shapes.Tube(points, r=TRACTO_RADIUS, c=color, alpha=alpha, res=TRACTO_RES))
return actors