navis.longest_neurite

navis.longest_neurite(x, n=1, reroot_soma=False, from_root=True, inverse=False, inplace=False)

Return a neuron consisting of only the longest neurite(s).

Based on geodesic distances.

Parameters:

• x (TreeNeuron | NeuronList) – Neuron(s) to prune.

• n (int | slice) –

  Number of longest neurites to preserve. For example:

  • n=1 keeps the longest neurites

  • n=2 keeps the two longest neurites

  • n=slice(1, None) removes the longest neurite

• reroot_soma (bool) – If True, neuron will be rerooted to soma.

• from_root (bool) – If True, will look for longest neurite from root. If False, will look for the longest neurite between any two tips.

• inverse (bool) – If True, will instead remove the longest neurite.

• inplace (bool) – If False, copy of the neuron will be trimmed down to longest neurite and 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.

Return type:

TreeNeuron/List

See also

split_into_fragments()

Split neuron into fragments based on longest neurites.

Examples

>>> import navis
>>> n = navis.example_neurons(1)
>>> # Keep only the longest neurite
>>> ln1 = navis.longest_neurite(n, n=1, reroot_soma=True)
>>> # Keep the two longest neurites
>>> ln2 = navis.longest_neurite(n, n=2, reroot_soma=True)
>>> # Keep everything but the longest neurite
>>> ln3 = navis.longest_neurite(n, n=slice(1, None), reroot_soma=True)