brainrender
is first used to create an instance of brainrender
's Actor
class. This class handles the 3D mesh data for the object to be rendered and provides a few useful methods for the behind-the-scenes work necessary to render your data.Actor
class can be used to render any type of data that can be used to create a vedo Mesh
object, several specific Actor
classes are provided for more conveniently loading commonly used data types.brainrender.actors.Neuron
is used to render neurons morphology (e.g. downloaded with morphapi
or from a .swc
file).brainrender.actors.Points
is used to render anything that can be represented as a set of points (e.g. labelled cells from cellfinder
. Points
can load data directly from a .npy
file or a numpy array of coordinates can be passed to it.brainrender.actors.Streamlines
is used to render streamlines tractography data. It expects the data as a pandas DataFrame
and can load data from a .json
file.brainrender.actors.Volume
renders volumetric data (e.g. gene expression) from a numpy array or from a .npy
file.Cylinder
, Point
and Ruler
can be used to render other types of data.actor
instance can be created by passing the data to be rendered to the dedicated Actor
class. For instance, to render the position of labelled cells, a Nx3 numpy array with the cells coordinates has to be passed to the Points
class to create an actor representing the cells' locations. Some actors can also load data directly from file.Streamlines
and Neuron)
are generally used to visualize several instances of the same neuron at once. For these actors we also provide helper functions that facilitate the generation of multiple instances of the same actor class. Actor
classes should support the vast majority of users' needs, occasionally you might need to render an unsupported type of data: read here to learn how. Scene.add
method and pass to it the actors you would like to see added to your rendering.