navis.MeshNeuron

class navis.MeshNeuron(x, units=None, process=True, validate=False, **metadata)

Neuron represented as mesh with vertices and faces.

Parameters:

• x (Union[DataFrame, BufferedIOBase, str, TreeNeuron, DiGraph]) –

  Data to construct neuron from:

  • any object that has .vertices and .faces properties (e.g. a trimesh.Trimesh)

  • a tuple (vertices, faces)

  • a dictionary {"vertices": (N, 3), "faces": (M, 3)}

  • filepath to a file that can be read by trimesh.load

  • None will initialize an empty MeshNeuron

  • skeletor.Skeleton will use the mesh and the skeleton (including the vertex to node map)

• units (str | pint.Units | pint.Quantity) – Units for coordinates. Defaults to None (dimensionless). Strings must be parsable by pint: e.g. “nm”, “um”, “micrometer” or “8 nanometers”.

• process (bool) – If True (default and highly recommended), will remove NaN and infinite values, and merge duplicate vertices.

• validate (bool) – If True, will try to fix some common problems with meshes. See navis.fix_mesh for details.

• **metadata – Any additional data to attach to neuron.

Initialize Mesh Neuron.

__init__(x, units=None, process=True, validate=False, **metadata)

Initialize Mesh Neuron.

Methods

__init__(x[, units, process, validate])	Initialize Mesh Neuron.
convert_units(to[, inplace])	Convert coordinates to different unit.
copy()	Return a copy of the neuron.
map_units(units[, on_error])	Convert units to match neuron space.
memory_usage([deep, estimate])	Return estimated memory usage of this neuron.
plot2d(**kwargs)	Plot neuron using navis.plot2d().
plot3d(**kwargs)	Plot neuron using navis.plot3d().
skeletonize([method, heal, inv_dist])	Skeletonize mesh.
snap(locs[, to])	Snap xyz location(s) to closest vertex or synapse.
summary([add_props])	Get a summary of this neuron.
validate([inplace])	Use trimesh to try and fix some common mesh issues.

Attributes

CORE_DATA	Core data table(s) used to calculate hash
EQ_ATTRIBUTES	Attributes to be used when comparing two neurons.
SUMMARY_PROPS	Attributes used for neuron summary
TEMP_ATTR	Temporary attributes that need clearing when neuron data changes
bbox	Bounding box (includes connectors).
connectors	Connector table.
core_md5	MD5 checksum of core data.
datatables	Names of all DataFrames attached to this neuron.
extents	Extents of neuron in x/y/z direction (includes connectors).
faces	Faces making up the neuron.
graph	Networkx Graph representation of the vertex connectivity.
id	Hashable ID.
igraph	iGraph representation of the vertex connectivity.
is_isometric	Test if neuron is isometric.
is_locked	Test if neuron is locked.
is_stale	Test if temporary attributes might be outdated.
label	Label (e.g.
name	Neuron name.
postsynapses	Table with postsynapses.
presynapses	Table with presynapses.
sampling_resolution	Average distance between vertices.
skeleton	Skeleton representation of this neuron.
trimesh	Trimesh representation of the neuron.
type	Neuron type.
units	Units for coordinate space.
units_xyz	Units for coordinate space.
vertices	Vertices making up the neuron.
volume	Volume of the neuron.
soma