navis.VoxelNeuron¶

class navis.VoxelNeuron(x, offset=None, cache=True, units=None, **metadata)[source]¶

Neuron represented as voxels.

Parameters:

x (ndarray) –
Data to construct neuron from:
- a 2D (N, 3) array of voxel positions (x, y, z)
- a 2D (N, 4) array of voxel positions + values (x, y, z, value)
- a 3D (N, M, J) array representing the voxel grid
offset ((3, ) array, optional) – An (optional) offset in voxels. This is useful to keep the voxel grid small while still maintaining correct positioning e.g. for plotting.
cache (bool) – Whether to cache different representations (i.e. grid and voxels) of the data. Set to False to save some memory.
units (str | pint.Units | pint.Quantity) – Units (scales) for voxels. Defaults to 1 (dimensionless). Strings must be parsable by pint: e.g. “nm”, “um”, “micrometer” or “8 nanometers”.
**metadata – Any additional data to attach to neuron.

Initialize Voxel Neuron.

__init__(x, offset=None, cache=True, units=None, **metadata)[source]¶: Initialize Voxel Neuron.

Methods

`__init__`(x[, offset, cache, units])	Initialize Voxel 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.
`max`()	Maximum value (excludes zeros).
`memory_usage`([deep, estimate])	Return estimated memory usage of this neuron.
`min`()	Minimum value (excludes zeros).
`plot2d`(**kwargs)	Plot neuron using `navis.plot2d()`.
`plot3d`(**kwargs)	Plot neuron using `navis.plot3d()`.
`strip`([inplace])	Strip empty voxels (leading/trailing planes of zeros).
`summary`([add_props])	Get a summary of this neuron.
`threshold`(threshold[, inplace])	Drop below-threshold voxels.

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) in units.
`connectors`	Connector table.
`core_md5`	MD5 checksum of core data.
`datatables`	Names of all DataFrames attached to this neuron.
`dtype`	Data type of voxel values.
`extents`	Extents of neuron in x/y/z direction (includes connectors).
`grid`	Voxel grid representation.
`id`	Hashable ID.
`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`is_stale`	Test if temporary attributes might be outdated.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.
`offset`	Offset (in voxels).
`postsynapses`	Table with postsynapses.
`presynapses`	Table with presynapses.
`shape`	Shape of voxel grid.
`type`	Neuron type.
`units`	Units for coordinate space.
`units_xyz`	Units for coordinate space.
`values`	(N, ) array of values for each voxel
`volume`	Volume of neuron.
`voxels`	(N, 3) array of x/y/z voxels locations
`soma`