def test_trunk_origin_azimuths():
n0 = MockNeuron()
n1 = MockNeuron()
n2 = MockNeuron()
n3 = MockNeuron()
n4 = MockNeuron()
n5 = MockNeuron()
t = PointTree((0, 0, 0, 2))
t.type = NeuriteType.basal_dendrite
n0.neurites = [t]
n1.neurites = [t]
n2.neurites = [t]
n3.neurites = [t]
n4.neurites = [t]
n5.neurites = [t]
pop = [n0, n1, n2, n3, n4, n5]
s0 = make_soma([[0, 0, 1, 4]])
s1 = make_soma([[0, 0, -1, 4]])
s2 = make_soma([[0, 0, 0, 4]])
s3 = make_soma([[-1, 0, -1, 4]])
s4 = make_soma([[-1, 0, 0, 4]])
s5 = make_soma([[1, 0, 0, 4]])
pop[0].soma = s0
pop[1].soma = s1
pop[2].soma = s2
pop[3].soma = s3
pop[4].soma = s4
pop[5].soma = s5
nt.assert_true(np.all(get_feat('trunk_origin_azimuths', pop) ==
[-np.pi/2., np.pi/2., 0.0, np.pi/4., 0.0, np.pi]))
nt.eq_(len(get_feat('trunk_origin_azimuths', pop, neurite_type=NeuriteType.axon)), 0)
def test_remote_bifurcation_angles():
ref_remote_bifangles = list(iter_neurites(NEURON, bifs.remote_angle))
remote_bifangles = get_feat('remote_bifurcation_angles', NEURON)
nt.assert_equal(len(remote_bifangles), 40)
nt.assert_true(np.all(remote_bifangles == ref_remote_bifangles))
remote_bifangles = get_feat('remote_bifurcation_angles', NEURON, neurite_type=NeuriteType.all)
nt.assert_equal(len(remote_bifangles), 40)
nt.assert_true(np.all(remote_bifangles == ref_remote_bifangles))
def test_segment_lengths():
ref_seglen = list(iter_neurites(NEURON, seg.length))
seglen = get_feat('segment_lengths', NEURON)
nt.assert_equal(len(seglen), 840)
nt.assert_true(np.all(seglen == ref_seglen))
seglen = get_feat('segment_lengths', NEURON, neurite_type=NeuriteType.all)
nt.assert_equal(len(seglen), 840)
nt.assert_true(np.all(seglen == ref_seglen))
def test_local_bifurcation_angles():
ref_local_bifangles = list(iter_neurites(NEURON, bifs.local_angle))
local_bifangles = get_feat('local_bifurcation_angles', NEURON)
nt.assert_equal(len(local_bifangles), 40)
nt.assert_true(np.all(local_bifangles == ref_local_bifangles))
local_bifangles = get_feat('local_bifurcation_angles', NEURON, neurite_type=NeuriteType.all)
nt.assert_equal(len(local_bifangles), 40)
nt.assert_true(np.all(local_bifangles == ref_local_bifangles))
def test_get_trunk_section_lengths():
nt.assert_items_equal(get_feat('trunk_section_lengths', NEURON), [9.579117366740002,
7.972322416776259,
8.2245287740603779,
9.212707985134525])
nt.assert_items_equal(get_feat('trunk_section_lengths', NEURON, NeuriteType.apical_dendrite),
[9.212707985134525])
nt.assert_items_equal(get_feat('trunk_section_lengths', NEURON, NeuriteType.basal_dendrite),
[7.972322416776259, 8.2245287740603779])
nt.assert_items_equal(get_feat('trunk_section_lengths', NEURON, NeuriteType.axon), [9.579117366740002])
def extract_density(population, plane='xy', bins=100, neurite_type=NeuriteType.basal_dendrite):
'''Extracts the 2d histogram of the center
coordinates of segments in the selected plane.
'''
horiz = get_feat('segment_%s_coordinates' % plane[0],
population, neurite_type=neurite_type)
vert = get_feat('segment_%s_coordinates' % plane[1],
population, neurite_type=neurite_type)
return np.histogram2d(np.array(horiz), np.array(vert),
bins=(bins, bins))
def test_segment_radial_distances_origin():
origin = (-100, -200, -300)
ref_segs = []
ref_segs2 = []
for t in NEURON.neurites:
ref_segs.extend(ll for ll in iter_neurites(t, seg.radial_dist(t.value)))
ref_segs2.extend(ll for ll in iter_neurites(t, seg.radial_dist(origin)))
rad_dists = get_feat('segment_radial_distances', NEURON)
rad_dists2 = get_feat('segment_radial_distances', NEURON, origin=origin)
nt.assert_true(np.all(rad_dists == ref_segs))
nt.assert_true(np.all(rad_dists2 == ref_segs2))
nt.assert_true(np.all(rad_dists2 != ref_segs))
def test_trunk_origin_radii():
nt.assert_items_equal(get_feat('trunk_origin_radii', NEURON),
[0.85351288499400002,
0.18391483031299999,
0.66943255462899998,
0.14656092843999999])
nt.assert_items_equal(get_feat('trunk_origin_radii', NEURON, NeuriteType.apical_dendrite),
[0.14656092843999999])
nt.assert_items_equal(get_feat('trunk_origin_radii', NEURON, NeuriteType.basal_dendrite),
[0.18391483031299999,
0.66943255462899998])
nt.assert_items_equal(get_feat('trunk_origin_radii', NEURON, NeuriteType.axon),
[0.85351288499400002])
def test_segment_radial_distances():
ref_segs = []
for t in NEURON.neurites:
ref_segs.extend(ll for ll in iter_neurites(t, seg.radial_dist(t.value)))
rad_dists = get_feat('segment_radial_distances', NEURON)
nt.assert_true(np.all(rad_dists == ref_segs))
def test_section_path_distances_endpoint():
ref_sec_path_len_start = list(iter_neurites(NEURON, sec.start_point_path_length))
ref_sec_path_len = list(iter_neurites(NEURON, sec.end_point_path_length))
path_lengths = get_feat('section_path_distances', NEURON)
nt.assert_true(ref_sec_path_len != ref_sec_path_len_start)
nt.assert_equal(len(path_lengths), 84)
nt.assert_true(np.all(path_lengths == ref_sec_path_len))
def test_section_radial_distances_start_point():
ref_sec_rad_dist_start = []
for t in NEURON.neurites:
ref_sec_rad_dist_start.extend(
ll for ll in iter_neurites(t, sec.radial_dist(t.value, use_start_point=True)))
rad_dists = get_feat('section_radial_distances', NEURON, use_start_point=True)
nt.assert_equal(len(rad_dists), 84)
nt.assert_true(np.all(rad_dists == ref_sec_rad_dist_start))
def test_principal_directions_extents():
points = np.array([[-10., 0., 0.],
[-9., 0., 0.],
[9., 0., 0.],
[10., 0., 0.]])
tree = PointTree(np.array([points[0][0], points[0][1], points[0][2], 1., 0., 0.]))
tree.add_child(PointTree(np.array([points[1][0], points[1][1], points[1][2], 1., 0., 0.])))
tree.children[0].add_child(PointTree(np.array([points[2][0], points[2][1], points[2][2], 1., 0., 0.])))
tree.children[0].add_child(PointTree(np.array([points[3][0], points[3][1], points[3][2], 1., 0., 0.])))
neurites = [tree, tree, tree]
extents0 = get_feat('principal_direction_extents', neurites, direction='first')
nt.assert_true(np.allclose(extents0, [20., 20., 20.]))
extents1 = get_feat('principal_direction_extents', neurites, direction='second')
nt.assert_true(np.allclose(extents1, [0., 0., 0.]))
extents2 = get_feat('principal_direction_extents', neurites, direction='third')
nt.assert_true(np.allclose(extents2, [0., 0., 0.]))
def test_neurite_number():
nt.assert_equal(get_feat('number_of_neurites', NEURON)[0], 4)
nt.assert_equal(get_feat('number_of_neurites', NEURON, neurite_type=NeuriteType.all)[0], 4)
nt.assert_equal(get_feat('number_of_neurites', NEURON, neurite_type=NeuriteType.axon)[0], 1)
nt.assert_equal(get_feat('number_of_neurites', NEURON, neurite_type=NeuriteType.basal_dendrite)[0], 2)
nt.assert_equal(get_feat('number_of_neurites', NEURON, neurite_type=NeuriteType.apical_dendrite)[0], 1)
nt.assert_equal(get_feat('number_of_neurites', NEURON, neurite_type=NeuriteType.soma)[0], 0)
nt.assert_equal(get_feat('number_of_neurites', NEURON, neurite_type=NeuriteType.undefined)[0], 0)
def test_trunk_origin_elevations():
n0 = MockNeuron()
n1 = MockNeuron()
s = make_soma([[0, 0, 0, 4]])
t0 = PointTree((1, 0, 0, 2))
t0.type = NeuriteType.basal_dendrite
t1 = PointTree((0, 1, 0, 2))
t1.type = NeuriteType.basal_dendrite
n0.neurites = [t0, t1]
n0.soma = s
t2 = PointTree((0, -1, 0, 2))
t2.type = NeuriteType.basal_dendrite
n1.neurites = [t2]
n1.soma = s
pop = [n0, n1]
nt.assert_true(np.all(get_feat('trunk_origin_elevations', pop) ==
[0.0, np.pi/2., -np.pi/2.]))
nt.eq_(len(get_feat('trunk_origin_elevations', pop, neurite_type=NeuriteType.axon)), 0)
def test_total_length_axon():
tl = get_feat('total_length', NEURON, neurite_type=NeuriteType.axon)
nt.assert_equal(len(tl), 1)
nt.assert_true(np.allclose(tl, (207.87975221)))
def test_total_length_per_neurite_basal():
tl = get_feat('total_length_per_neurite', NEURON, neurite_type=NeuriteType.basal_dendrite)
nt.assert_equal(len(tl), 2)
nt.assert_true(np.allclose(tl, (211.11737442, 207.31504202)))
def test_section_lengths_apical():
s = get_feat('section_lengths', NEURON, neurite_type=NeuriteType.apical_dendrite)
nt.assert_equal(len(s), 21)
def test_total_lengths_basal():
s = get_feat('section_lengths', NEURON, neurite_type=NeuriteType.basal_dendrite)
nt.assert_equal(len(s), 42)
def test_section_lengths_axon():
s = get_feat('section_lengths', NEURON, neurite_type=NeuriteType.axon)
nt.assert_equal(len(s), 21)
def test_n_sections_per_neurite_apical():
nsecs = get_feat('number_of_sections_per_neurite', NEURON, neurite_type=NeuriteType.apical_dendrite)
nt.assert_equal(len(nsecs), 1)
nt.assert_true(np.all(nsecs == [21]))
def test_section_lengths_invalid():
s = get_feat('section_lengths', NEURON, neurite_type=NeuriteType.soma)
nt.assert_equal(len(s), 0)
s = get_feat('section_lengths', NEURON, neurite_type=NeuriteType.undefined)
nt.assert_equal(len(s), 0)
def test_number_of_sections_basal():
nt.assert_equal(get_feat('number_of_sections', NEURON, neurite_type=NeuriteType.basal_dendrite)[0], 42)
def test_soma_radii():
nt.assert_true(np.all(get_feat('soma_radii', NEURONS) ==
[0.17071067811865476, 0.17071067811865476]))
def test_seciton_number_invalid():
nt.assert_equal(get_feat('number_of_sections', NEURON, neurite_type=NeuriteType.soma)[0], 0)
nt.assert_equal(get_feat('number_of_sections', NEURON, neurite_type=NeuriteType.undefined)[0], 0)
def test_per_neurite_number_of_sections():
nsecs = get_feat('number_of_sections_per_neurite', NEURON)
nt.assert_equal(len(nsecs), 4)
nt.assert_true(np.all(nsecs == [21, 21, 21, 21]))
def test_total_length_basal():
tl = get_feat('total_length', NEURON, neurite_type=NeuriteType.basal_dendrite)
nt.assert_equal(len(tl), 1)
nt.assert_true(np.allclose(tl, (418.43241644)))
def test_total_length_apical():
tl = get_feat('total_length', NEURON, neurite_type=NeuriteType.apical_dendrite)
nt.assert_equal(len(tl), 1)
nt.assert_true(np.allclose(tl, (214.37304578)))
def test_n_sections_apical():
nt.assert_equal(get_feat('number_of_sections', NEURON, neurite_type=NeuriteType.apical_dendrite)[0], 21)
def test_soma_surface_areas():
area = 4. * math.pi * get_feat('soma_radii', NEURON)[0] ** 2
nt.assert_true(np.all(get_feat('soma_surface_areas', NEURONS) == [area, area]))
def test_per_neurite_number_of_sections_axon():
nsecs = get_feat('number_of_sections_per_neurite', NEURON, neurite_type=NeuriteType.axon)
nt.assert_equal(len(nsecs), 1)
nt.assert_equal(nsecs, [21])
