navis.prune_at_depth¶

navis.prune_at_depth(x, depth, *, source=None, inplace=False)[source]¶

Prune all neurites past a given distance from a source.

Parameters:

x (TreeNeuron | MeshNeuron | NeuronList) –
depth (int | float | str) – Distance from source at which to start pruning. If neuron has its .units set, you can also pass this as a string such as “50 microns”.
source (int, optional) – Source node for depth calculation. If None, will use root (first root if multiple). If x is a list of neurons then must provide a source for each neuron.
inplace (bool, optional) – If False, pruning is performed on copy of original neuron which is then returned.
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:

Pruned neuron(s).

Return type:

TreeNeuron/List

Examples

>>> import navis
>>> n = navis.example_neurons(2)
>>> # Reroot to soma
>>> n.reroot(n.soma, inplace=True)
>>> # Prune all twigs farther from the root than 100 microns
>>> # (example neuron are in 8x8x8nm units)
>>> n_pr = navis.prune_at_depth(n,
...                             depth=100e3 / 8,
...                             inplace=False)
>>> all(n.n_nodes > n_pr.n_nodes)
True