def has_valid_soma(data_wrapper):
"""Check if a data block has a valid soma"""
try:
make_soma(data_wrapper.soma_points())
return CheckResult(True)
except SomaError:
return CheckResult(False)
def has_valid_soma(data_wrapper):
"""Check if a data block has a valid soma.
Returns:
CheckResult with result
"""
try:
make_soma(data_wrapper.soma_points())
return CheckResult(True)
except SomaError:
return CheckResult(False)
def has_valid_soma(data_wrapper):
'''Check if a data block has a valid soma
Returns:
CheckResult with result
'''
try:
make_soma(data_wrapper.soma_points())
return CheckResult(True)
except SomaError:
return CheckResult(False)
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():
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 / 2.0, -np.pi / 2.0])
nt.eq_(
list(_nf.trunk_origin_elevations(pop, neurite_type=NeuriteType.basal_dendrite)),
[0.0, np.pi / 2.0, -np.pi / 2.0],
)
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 __init__(self, data_wrapper, name="Neuron"):
self._data = data_wrapper
neurites, sections = make_neurites(self._data)
soma = make_soma(self._data.soma_points(), _SOMA_ACTION[self._data.fmt])
super(FstNeuron, self).__init__(soma, neurites, sections)
self.name = name
self._points = None
def __init__(self, data_wrapper, name='Neuron'):
self._data = data_wrapper
neurites, sections = make_neurites(self._data)
soma = make_soma(self._data.soma_points(),
_SOMA_ACTION[self._data.fmt])
super(FstNeuron, self).__init__(soma, neurites, sections)
self.name = name
self._points = None
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_trunk_origin_elevation():
t = PointTree((1, 0, 0, 2))
s = make_soma([[0, 0, 0, 4]])
nt.assert_equal(mtr.trunk_origin_elevation(t, s), 0.0)
t = PointTree((0, 1, 0, 2))
nt.assert_equal(mtr.trunk_origin_elevation(t, s), np.pi/2)
t = PointTree((0, -1, 0, 2))
nt.assert_equal(mtr.trunk_origin_elevation(t, s), -np.pi/2)
t = PointTree((0, 0, 0, 2))
try:
mtr.trunk_origin_elevation(t, s)
nt.ok_(False)
except ValueError:
nt.ok_(True)
def make_neuron(raw_data, tree_action=None):
'''Build a neuron from a raw data block
The tree contains rows of raw data.
Parameters:
raw_data: a DataWrapper object.
tree_action: optional function to run on the built trees.
Raises:
SomaError if no soma points in raw_data or points incompatible with soma.
IDSequenceError if filename contains invalid ID sequence
'''
_soma = make_soma(raw_data.soma_points())
_trees = [make_point_tree(raw_data, iseg, tree_action)
for iseg in get_initial_neurite_segment_ids(raw_data)]
nrn = PointNeuron(_soma, _trees)
nrn.data_block = raw_data
return nrn
def test_trunk_origin_azimuth():
t = PointTree((0, 0, 0, 2))
s = make_soma([[0, 0, 1, 4]])
nt.assert_equal(mtr.trunk_origin_azimuth(t, s), -np.pi/2)
s = make_soma([[0, 0, -1, 4]])
nt.assert_equal(mtr.trunk_origin_azimuth(t, s), np.pi/2)
s = make_soma([[0, 0, 0, 4]])
nt.assert_equal(mtr.trunk_origin_azimuth(t, s), 0.0)
s = make_soma([[-1, 0, -1, 4]])
nt.assert_equal(mtr.trunk_origin_azimuth(t, s), np.pi/4)
s = make_soma([[-1, 0, 0, 4]])
nt.assert_equal(mtr.trunk_origin_azimuth(t, s), 0.0)
s = make_soma([[1, 0, 0, 4]])
nt.assert_equal(mtr.trunk_origin_azimuth(t, s), np.pi)
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)
from neurom.point_neurite.core import Neuron
from neurom.core import make_soma
from neurom.core import NeuriteType
from neurom.point_neurite.treefunc import set_tree_type
import neurom.point_neurite.dendrogram as dm
TREE = PointTree(np.array([0., 0., 0., 10., 4., 0., 0.]))
TREE.add_child(PointTree(np.array([3., 3., 3., 9., 4., 0., 0.])))
TREE.children[0].add_child(PointTree(np.array([10., 10., 10., 5., 4., 0., 0.])))
TREE.children[0].add_child(PointTree(np.array([-10., -10., -10., 7., 4., 0., 0.])))
set_tree_type(TREE)
SOMA = make_soma(np.array([[0., 0., 0., 1., 1., 1., -1.]]))
NEURON = Neuron(SOMA, [TREE, TREE, TREE])
OLD_OFFS = [1.2, -1.2]
NEW_OFFS = [2.3, -2.3]
SPACING = (40., 0.)
def test_n_rectangles_tree():
nt.assert_equal(dm._n_rectangles(TREE), 5)
def test_n_rectangles_neuron():
nt.assert_equal(dm._n_rectangles(NEURON), 16)
def test_deep_copy():
soma = make_soma([[0, 0, 0, 1, 1, 1, -1]])
nrn1 = Neuron(soma, [TREE])
nrn2 = deepcopy(nrn1)
check_cloned_neuron(nrn1, nrn2)
def test_trunk_origin_direction():
t = PointTree((1, 0, 0, 2))
s = make_soma([[0, 0, 0, 4]])
nt.ok_(np.allclose(mtr.trunk_origin_direction(t, s), np.array([1, 0, 0])))
