navis.resample_skeleton¶

navis.resample_skeleton(x, resample_to, inplace=False, method='linear', skip_errors=True)[source]¶

Resample skeleton(s) to given resolution.

Preserves root, leafs and branchpoints. Soma, connectors and node tags (if present) are mapped onto the closest node in the resampled neuron.

Important

A few things to keep in mind:

This generates an entirely new set of node IDs! They will be unique within a neuron, but you may encounter duplicates across neurons.
Any non-standard node table columns (e.g. “labels”) will be lost.
Soma(s) will be pinned to the closest node in the resampled neuron.

Also: be aware that high-resolution neurons will use A LOT of memory.

Parameters:

x (TreeNeuron | NeuronList) – Neuron(s) to resample.
resample_to (int | float | str) – Target sampling resolution, i.e. one node every N units of cable. Note that hitting the exact sampling resolution might not be possible e.g. if a branch is shorter than the target resolution. If neuron(s) have their .units parameter, you can also pass a string such as “1 micron”.
method (str, optional) – See scipy.interpolate.interp1d for possible options. By default, we’re using linear interpolation.
inplace (bool, optional) – If True, will modify original neuron. If False, a resampled copy is returned.
skip_errors (bool, optional) – If True, will skip errors during interpolation and only print summary.
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:

Downsampled neuron(s).

Return type:

TreeNeuron/List

Examples

>>> import navis
>>> n = navis.example_neurons(1)
>>> # Check sampling resolution (nodes/cable)
>>> round(n.sampling_resolution)
60
>>> # Resample to 1 micron (example neurons are in 8x8x8nm)
>>> n_rs = navis.resample_skeleton(n,
...                                resample_to=1000 / 8,
...                                inplace=False)
>>> round(n_rs.sampling_resolution)
134