def test_get_section_path_distances(self):
_close(_nrt.section_path_lengths(self.sec_nrn.neurites[0]),
get('section_path_distances', self.ref_nrn.neurites[0]))
_close(_nrt.section_path_lengths(self.sec_nrn), get('section_path_distances', self.ref_nrn))
for t in NeuriteType:
_close(_nrt.section_path_lengths(self.sec_nrn, neurite_type=t),
get('section_path_distances', self.ref_nrn, neurite_type=t))
pl = [_sec.section_path_length(s) for s in i_chain2(self.sec_nrn_trees)]
_close(pl, get('section_path_distances', self.ref_nrn))
def test_get_remote_bifurcation_angles(self):
_close(_nrt.remote_bifurcation_angles(self.sec_nrn.neurites[0]),
get('remote_bifurcation_angles', self.ref_nrn.neurites[0]))
_close(_nrt.remote_bifurcation_angles(self.sec_nrn),
get('remote_bifurcation_angles', self.ref_nrn))
for t in NeuriteType:
_close(_nrt.remote_bifurcation_angles(self.sec_nrn, neurite_type=t),
get('remote_bifurcation_angles', self.ref_nrn, neurite_type=t))
ba = [_bf.remote_bifurcation_angle(b)
for b in i_chain2(self.sec_nrn_trees, iterator_type=Tree.ibifurcation_point)]
_close(ba, get('remote_bifurcation_angles', self.ref_nrn))
def iter_neurites(obj, mapfun=None, filt=None):
"""Iterator to a neurite, neuron or neuron population
Applies optional neurite filter and element mapping functions.
Example:
Get the lengths of sections in a neuron and a population
>>> from neurom import sections as sec
>>> neuron_lengths = [l for l in iter_neurites(nrn, sec.length)]
>>> population_lengths = [l for l in iter_neurites(pop, sec.length)]
>>> neurite = nrn.neurites[0]
>>> tree_lengths = [l for l in iter_neurites(neurite, sec.length)]
"""
# TODO: optimize case of single neurite and move code to neurom.core.tree
neurites = [obj] if isinstance(obj, Tree) else (obj.neurites if hasattr(obj, "neurites") else obj)
iter_type = None if mapfun is None else mapfun.iter_type
return i_chain2(neurites, iter_type, mapfun, filt)
