def test_trunk_origin_elevations():
class Mock(object):
pass
n0 = Mock()
n1 = Mock()
s = make_soma([[0, 0, 0, 4]])
t0 = Section(((1, 0, 0, 2), (2, 1, 1, 2)))
t0.type = NeuriteType.basal_dendrite
t1 = Section(((0, 1, 0, 2), (1, 2, 1, 2)))
t1.type = NeuriteType.basal_dendrite
n0.neurites = [Neurite(t0), Neurite(t1)]
n0.soma = s
t2 = Section(((0, -1, 0, 2), (-1, -2, -1, 2)))
t2.type = NeuriteType.basal_dendrite
n1.neurites = [Neurite(t2)]
n1.soma = s
pop = Population([n0, n1])
nt.eq_(list(_nf.trunk_origin_elevations(pop)),
[0.0, np.pi/2., -np.pi/2.])
nt.eq_(
list(_nf.trunk_origin_elevations(pop, neurite_type=NeuriteType.basal_dendrite)),
[0.0, np.pi/2., -np.pi/2.])
nt.eq_(len(_nf.trunk_origin_elevations(pop, neurite_type=NeuriteType.axon)),
0)
nt.eq_(len(_nf.trunk_origin_elevations(pop, neurite_type=NeuriteType.apical_dendrite)),
0)
def test_trunk_origin_elevations():
n0 = load_neuron(StringIO(u"""
1 1 0 0 0 4 -1
2 3 1 0 0 2 1
3 3 2 1 1 2 2
4 3 0 1 0 2 1
5 3 1 2 1 2 4
"""), reader='swc')
n1 = load_neuron(StringIO(u"""
1 1 0 0 0 4 -1
2 3 0 -1 0 2 1
3 3 -1 -2 -1 2 2
"""), reader='swc')
pop = Population([n0, n1])
assert_array_equal(_nf.trunk_origin_elevations(pop),
[0.0, np.pi/2., -np.pi/2.])
assert_array_equal(_nf.trunk_origin_elevations(pop, neurite_type=NeuriteType.basal_dendrite),
[0.0, np.pi/2., -np.pi/2.])
assert_array_equal(_nf.trunk_origin_elevations(pop, neurite_type=NeuriteType.axon),
[])
assert_array_equal(_nf.trunk_origin_elevations(pop, neurite_type=NeuriteType.apical_dendrite),
[])
def test_segment_radial_distances_origin():
origin = (-100, -200, -300)
ref_segs = nf.segment_radial_distances(NEURON)
ref_segs_origin = nf.segment_radial_distances(NEURON, origin=origin)
rad_dists = get_feature('segment_radial_distances', NEURON)
rad_dists_origin = get_feature('segment_radial_distances',
NEURON,
origin=origin)
nt.ok_(np.all(rad_dists == ref_segs))
nt.ok_(np.all(rad_dists_origin == ref_segs_origin))
nt.ok_(np.all(rad_dists_origin != ref_segs))
nrns = [
nm.load_neuron(Path(SWC_PATH, f))
for f in ('point_soma_single_neurite.swc',
'point_soma_single_neurite2.swc')
]
pop = Population(nrns)
rad_dist_nrns = []
for nrn in nrns:
rad_dist_nrns.extend(nm.get('segment_radial_distances', nrn))
rad_dist_nrns = np.array(rad_dist_nrns)
rad_dist_pop = nm.get('segment_radial_distances', pop)
assert_allclose(rad_dist_nrns, rad_dist_pop)
def test_population(): pop = Population(NEURONS, name='foo') nt.assert_equal(len(pop.neurons), 3) nt.ok_(pop.neurons[0].name, 'Neuron') nt.ok_(pop.neurons[1].name, 'Single_basal') nt.ok_(pop.neurons[2].name, 'Neuron_small_radius') nt.assert_equal(len(pop.somata), 3) nt.assert_equal(len(pop.neurites),TOT_NEURITES) nt.assert_equal(pop.name, 'foo')
def test_section_radial_distances_endpoint():
ref_sec_rad_dist = nf.section_radial_distances(NEURON)
rad_dists = fst_get('section_radial_distances', NEURON)
nt.eq_(len(rad_dists), 84)
nt.ok_(np.all(rad_dists == ref_sec_rad_dist))
nrns = [nm.load_neuron(os.path.join(SWC_PATH, f)) for
f in ('point_soma_single_neurite.swc', 'point_soma_single_neurite2.swc')]
pop = Population(nrns)
rad_dist_nrns = [nm.get('section_radial_distances', nrn) for nrn in nrns]
rad_dist_pop = nm.get('section_radial_distances', pop)
assert_items_equal(rad_dist_pop, rad_dist_nrns)
def test_section_radial_distances_endpoint():
ref_sec_rad_dist = nf.section_radial_distances(NEURON)
rad_dists = get_feature('section_radial_distances', NEURON)
assert len(rad_dists) == 84
assert np.all(rad_dists == ref_sec_rad_dist)
nrns = [
nm.load_neuron(Path(SWC_PATH, f))
for f in ('point_soma_single_neurite.swc',
'point_soma_single_neurite2.swc')
]
pop = Population(nrns)
rad_dist_nrns = [nm.get('section_radial_distances', nrn) for nrn in nrns]
rad_dist_pop = nm.get('section_radial_distances', pop)
assert_items_equal(rad_dist_pop, rad_dist_nrns)
def test_segment_meander_angles_single_section():
feat = 'segment_meander_angles'
nrn = nm.load_neuron(StringIO(u"""((CellBody) (0 0 0 0))
((Dendrite)
(0 0 0 2)
(1 0 0 2)
(1 1 0 2)
(2 1 0 2)
(2 2 0 2)))"""),
reader='asc')
nrt = nrn.neurites[0]
pop = Population([nrn])
ref = [math.pi / 2, math.pi / 2, math.pi / 2]
assert ref == get_feature(feat, nrt).tolist()
assert ref == get_feature(feat, nrn).tolist()
assert ref == get_feature(feat, pop).tolist()
load_neuron, fst)
from neurom.fst import get as fst_get
from neurom.fst import NEURITEFEATURES
from neurom.fst import _neuritefunc as nf
from neurom.core.types import tree_type_checker as _is_type
from neurom.exceptions import NeuroMError
_PWD = os.path.dirname(os.path.abspath(__file__))
DATA_PATH = os.path.join(_PWD, '../../../test_data')
NRN_FILES = [os.path.join(DATA_PATH, 'h5/v1', f)
for f in ('Neuron.h5', 'Neuron_2_branch.h5', 'bio_neuron-001.h5')]
NRNS = load_neurons(NRN_FILES)
NRN = NRNS[0]
POP = Population(NRNS)
NEURITES = (NeuriteType.axon,
NeuriteType.apical_dendrite,
NeuriteType.basal_dendrite,
NeuriteType.all)
def assert_items_equal(a, b):
nt.eq_(sorted(a), sorted(b))
def assert_features_for_neurite(feat, neurons, expected, exact=True):
for neurite_type, expected_values in expected.items():
print('neurite_type: %s' % neurite_type)
from os.path import join as joinp
from nose import tools as nt
from neurom.core.population import Population
from neurom import load_neuron
_path = os.path.dirname(os.path.abspath(__file__))
DATA_PATH = joinp(_path, '../../../test_data')
NRN1 = load_neuron(joinp(DATA_PATH, 'swc/Neuron.swc'))
NRN2 = load_neuron(joinp(DATA_PATH, 'swc/Single_basal.swc'))
NRN3 = load_neuron(joinp(DATA_PATH, 'swc/Neuron_small_radius.swc'))
NEURONS = [NRN1, NRN2, NRN3]
TOT_NEURITES = sum(len(N.neurites) for N in NEURONS)
POP = Population(NEURONS, name='foo')
def test_population():
nt.assert_equal(len(POP.neurons), 3)
nt.ok_(POP.neurons[0].name, 'Neuron')
nt.ok_(POP.neurons[1].name, 'Single_basal')
nt.ok_(POP.neurons[2].name, 'Neuron_small_radius')
nt.assert_equal(len(POP.somata), 3)
nt.assert_equal(len(POP.neurites), TOT_NEURITES)
nt.assert_equal(POP.name, 'foo')