navis.smooth_voxels¶

navis.smooth_voxels(x, sigma=1, inplace=False)[source]¶

Smooth voxel(s) using a Gaussian filter.

Parameters:

x (TreeNeuron | NeuronList) – Neuron(s) to be processed.
sigma (int | (3, ) ints, optional) – Standard deviation for Gaussian kernel. The standard deviations of the Gaussian filter are given for each axis as a sequence, or as a single number, in which case it is equal for all axes.
inplace (bool, optional) – If False, will use and return copy of original neuron(s).
parallel (bool) – If True and input is NeuronList, use parallel processing. Requires pathos.
n_cores (int, optional) – Numbers of cores to use if parallel=True. Defaults to half the available cores.
progress (bool) – Whether to show a progress bar. Overruled by navis.set_pbars.
omit_failures (bool) – If True will omit failures instead of raising an exception. Ignored if input is single neuron.

Returns:

Smoothed neuron(s).

Return type:

VoxelNeuron/List

Examples

>>> import navis
>>> n = navis.example_neurons(1, kind='mesh')
>>> vx = navis.voxelize(n, pitch='1 micron')
>>> smoothed = navis.smooth_voxels(vx, sigma=2)