neurom.fst¶

NeuroM, lightweight and fast

Examples

Load a neuron

>>> from neurom import fst
>>> nrn = fst.load_neuron('some/data/path/morph_file.swc')

Obtain some morphometrics

>>> ap_seg_len = fst.get('segment_lengths', nrn, neurite_type=fst.NeuriteType.apical_dendrite)
>>> ax_sec_len = fst.get('section_lengths', nrn, neurite_type=fst.NeuriteType.axon)

Load neurons from a directory. This loads all SWC or HDF5 files it finds and returns a list of neurons

>>> import numpy as np  # For mean value calculation
>>> nrns = fst.load_neurons('some/data/directory')
>>> for nrn in nrns:
...     print 'mean section length', np.mean(fst.get('section_lengths', nrn))

Iterate over all the sections in a neuron

>>> for s in fst.iter_sections(nrn): print s.points[0][:3]

Functions

`get`	Obtain a feature from a set of morphology objects
`iter_sections`	Returns an iterator to the nodes in a iterable of neurite objects
`iter_segments`	Return an iterator to the segments in a collection of neurites
`load_neuron`	Build section trees from an h5 or swc file

Classes

`Neurite`	Class representing a neurite tree
`Neuron`	Class representing a neuron
`Section`	Class representing a neurite section