def test_volume():
s = Scene(inset=False, root=True)
data = np.load("examples/data/volume.npy")
s.add(Volume(data, voxel_size=200, as_surface=False, c="Reds"))
s.add(Volume(data, voxel_size=200, as_surface=True, c="Reds", mode=2))
del s
def test_volume():
scene = Scene(inset=False, root=True)
data = np.load("examples/data/volume.npy")
scene.add(Volume(data, voxel_size=200, as_surface=False, c="Reds"))
scene.add(Volume(data, voxel_size=200, as_surface=True, c="Reds", mode=2))
scene.render(interactive=False)
def griddata_to_volume(
self,
griddata,
min_quantile=None,
min_value=None,
cmap="bwr",
):
"""
Takes a 3d numpy array with volumetric gene expression
and returns a vedo.Volume.isosurface actor.
The isosurface needs a lower bound threshold, this can be
either a user defined hard value (min_value) or the value
corresponding to some percentile of the gene expression data.
:param griddata: np.ndarray, 3d array with gene expression data
:param min_quantile: float, percentile for threshold
:param min_value: float, value for threshold
"""
return Volume(
griddata,
min_quantile=min_quantile,
voxel_size=self.voxel_size,
min_value=min_value,
cmap=cmap,
name=self.gene_name,
br_class="Gene Data",
)
def add(self, *items, names=None, classes=None, **kwargs):
"""
General method to add Actors to the scene.
:param items: vedo.Mesh, Actor, (str, Path).
If str/path it should be a path to a .obj or .stl file.
Whatever the input it's turned into an instance of Actor
before adding it to the scne
:param names: names to be assigned to the Actors
:param classs: br_classes to be assigned to the Actors
:param **kwargs: parameters to be passed to the individual
loading functions (e.g. to load from file and specify the color)
"""
names = names or [None for a in items]
classes = classes or [None for a in items]
# turn items into Actors
actors = []
for item, name, _class in zip(items, listify(names), listify(classes)):
if item is None:
continue
if isinstance(item, (Mesh, Assembly)):
actors.append(Actor(item, name=name, br_class=_class))
elif pi.utils._class_name(item) == "vtkCornerAnnotation":
# Mark text actors differently because they don't behave like
# other 3d actors
actors.append(
Actor(
item,
name=name,
br_class=_class,
is_text=True,
**kwargs,
))
elif pi.utils._class_name(item) == "Volume" and not isinstance(
item, Volume):
actors.append(
Volume(item, name=name, br_class=_class, **kwargs))
elif isinstance(item, Actor):
actors.append(item)
elif isinstance(item, (str, Path)):
mesh = load_mesh_from_file(item, **kwargs)
name = name or Path(item).name
_class = _class or "from file"
actors.append(Actor(mesh, name=name, br_class=_class))
else:
raise ValueError(
f"Unrecognized argument: {item} [{pi.utils._class_name(item)}]"
)
# Add to the lists actors
self.actors.extend(actors)
return return_list_smart(actors)
"""
This example shows how to render volumetric (i.e. organized in voxel)
data in brainrender. The data used are is the localized expression of
'Gpr161' from the Allen Atlas database, downloaded with brainrender
and saved to a numpy file
"""
import numpy as np
from brainrender import Scene
from brainrender import settings
from brainrender.actors import Volume
settings.SHOW_AXES = False
scene = Scene(inset=False)
data = np.load("examples/data/volume.npy")
# make a volume actor and add
actor = Volume(
data,
voxel_size=200, # size of a voxel's edge in microns
as_surface=False, # if true a surface mesh is rendered instead of a volume
c="Reds", # use matplotlib colormaps to color the volume
)
scene.add(actor)
scene.render(zoom=1.6)
# create scene
scene = Scene(
atlas_name="mpin_zfish_1um",
inset=INSET,
screenshots_folder="paper/screenshots",
)
scene.root.alpha(0.2)
# add custom meshes from file, but don't show them (alpha=0)
m = scene.add("paper/data/T_AVG_nk1688CGt_GFP.obj", color=gene1_color, alpha=0)
m2 = scene.add("paper/data/T_AVG_brn3c_GFP.obj", color=gene2_color, alpha=0)
# adjust meshes position
for mesh in (m, m2):
mesh.mesh.addPos(dp_x=SHIFT)
# convert meshes to volumetric data showing gene expression density
vol1 = Volume(m.density(), as_surface=True, min_value=20000, cmap="Reds")
vol1.lw(1)
scene.add(vol1)
vol2 = Volume(m2.density(), as_surface=True, min_value=600, cmap="Blues")
vol2.lw(1)
scene.add(vol2)
# render
scene.render(camera=cam, zoom=2.5)
scene.screenshot(name="zfish_gene_expression")