def test_bounding_box():
soma = neuron.make_soma([[0, 0, 0, 1, 1, 1, -1]])
nrn = neuron.Neuron(soma, [TREE])
ref1 = ((-1, -1, -1), (4.0, 6.0, 3.0))
for a, b in izip(nrn.bounding_box(), ref1):
nt.assert_true(np.allclose(a, b))
soma = neuron.make_soma(SOMA_A_PTS)
nrn = neuron.Neuron(soma, [TREE])
ref2 = ((-33, -22, -11), (55, 66, 77))
for a, b in izip(nrn.bounding_box(), ref2):
nt.assert_true(np.allclose(a, b))
def test_bounding_box():
soma = neuron.make_soma([[0, 0, 0, 1, 1, 1, -1]])
nrn = neuron.Neuron(soma, [TREE])
ref1 = ((-1, -1, -1), (4.0, 6.0, 3.0))
for a, b in izip(nrn.bounding_box(), ref1):
nt.assert_true(np.allclose(a, b))
soma = neuron.make_soma(SOMA_A_PTS)
nrn = neuron.Neuron(soma, [TREE])
ref2 = ((-33, -22, -11), (55, 66, 77))
for a, b in izip(nrn.bounding_box(), ref2):
nt.assert_true(np.allclose(a, b))
def test_neuron():
soma = neuron.make_soma(SOMA_A_PTS)
nrn = neuron.Neuron(soma, ['foo', 'bar'])
nt.assert_equal(nrn.soma.center, (11, 22, 33))
nt.assert_equal(nrn.neurites, ['foo', 'bar'])
nt.assert_equal(nrn.name, 'Neuron')
nrn = neuron.Neuron(soma, ['foo', 'bar'], 'test')
nt.assert_equal(nrn.name, 'test')
def test_neuron():
soma = neuron.make_soma(SOMA_A_PTS)
nrn = neuron.Neuron(soma, ['foo', 'bar'])
nt.assert_items_equal(nrn.soma.center, (11, 22, 33))
nt.assert_equal(nrn.neurites, ['foo', 'bar'])
nt.assert_equal(nrn.name, 'Neuron')
nrn = neuron.Neuron(soma, ['foo', 'bar'], 'test')
nt.assert_equal(nrn.name, 'test')
def test_i_neurites_filter():
soma = neuron.make_soma(SOMA_A_PTS)
nrn = neuron.Neuron(soma, ['foo', 'bar', 'baz'])
ref = 'barbaz'
for i, j in izip(ref,
nrn.i_neurites(iter,
tree_filter=lambda s: s.startswith('b'))):
nt.assert_equal(i, j)
def test_i_neurites_filter():
soma = neuron.make_soma(SOMA_A_PTS)
nrn = neuron.Neuron(soma, ['foo', 'bar', 'baz'])
ref = 'barbaz'
for i, j in izip(ref,
nrn.i_neurites(iter,
tree_filter=lambda s: s.startswith('b'))):
nt.assert_equal(i, j)
def test_trunk_elevation():
t = Tree((1, 0, 0, 2))
s = make_soma([[0, 0, 0, 4]])
nt.assert_equal(trunk_elevation(t, s), 0.0)
t = Tree((0, 1, 0, 2))
nt.assert_equal(trunk_elevation(t, s), np.pi/2)
t = Tree((0, -1, 0, 2))
nt.assert_equal(trunk_elevation(t, s), -np.pi/2)
t = Tree((0, 0, 0, 2))
try:
trunk_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 RawDataWrapper 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.get_row(s_id) for s_id in get_soma_ids(raw_data)])
_trees = [make_tree(raw_data, iseg, tree_action) for iseg in get_initial_neurite_segment_ids(raw_data)]
return Neuron(_soma, _trees)
def test_copy():
soma = neuron.make_soma([[0, 0, 0, 1, 1, 1, -1]])
nrn1 = neuron.Neuron(soma, [TREE], name="Rabbit of Caerbannog")
nrn2 = nrn1.copy()
# check if two neurons are identical
# somata
nt.assert_true(isinstance(nrn2.soma, type(nrn1.soma)))
nt.assert_true(nrn1.soma.radius == nrn2.soma.radius)
for v1, v2 in izip(nrn1.soma.iter(), nrn2.soma.iter()):
nt.assert_true(np.allclose(v1, v2))
# neurites
for neu1, neu2 in izip(nrn1.neurites, nrn2.neurites):
nt.assert_true(isinstance(neu2, type(neu1)))
for v1, v2 in izip(val_iter(ipreorder(neu1)), val_iter(ipreorder(neu2))):
nt.assert_true(np.allclose(v1, v2))
# check if the ids are different
# somata
nt.assert_true( nrn1.soma is not nrn2.soma)
# neurites
for neu1, neu2 in izip(nrn1.neurites, nrn2.neurites):
nt.assert_true(neu1 is not neu2)
# check if changes are propagated between neurons
nrn2.soma.radius = 10.
nt.assert_false(nrn1.soma.radius == nrn2.soma.radius)
# neurites
for neu1, neu2 in izip(nrn1.neurites, nrn2.neurites):
for v1, v2 in izip(val_iter(ipreorder(neu1)), val_iter(ipreorder(neu2))):
v2 = np.array([-1000., -1000., -1000., 1000., -100., -100., -100.])
nt.assert_false(any(v1 == v2))
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 RawDataWrapper 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.
'''
_soma = make_soma(
[raw_data.get_row(s_id) for s_id in get_soma_ids(raw_data)])
_trees = [
make_tree(raw_data, iseg, tree_action)
for iseg in get_initial_segment_ids(raw_data)
]
return Neuron(_soma, _trees)
def test_trunk_azimuth():
t = Tree((0, 0, 0, 2))
s = make_soma([[0, 0, 1, 4]])
nt.assert_equal(trunk_azimuth(t, s), -np.pi/2)
s = make_soma([[0, 0, -1, 4]])
nt.assert_equal(trunk_azimuth(t, s), np.pi/2)
s = make_soma([[0, 0, 0, 4]])
nt.assert_equal(trunk_azimuth(t, s), 0.0)
s = make_soma([[-1, 0, -1, 4]])
nt.assert_equal(trunk_azimuth(t, s), np.pi/4)
s = make_soma([[-1, 0, 0, 4]])
nt.assert_equal(trunk_azimuth(t, s), 0.0)
s = make_soma([[1, 0, 0, 4]])
nt.assert_equal(trunk_azimuth(t, s), np.pi)
iterator: tree iterator for a tree holding raw data rows.
'''
return imap(as_point, tree.val_iter(iterator))
if __name__ == '__main__':
filename = 'test_data/swc/Neuron.swc'
rd = load_data(filename)
init_seg_ids = get_initial_segment_ids(rd)
trees = [make_tree(rd, sg) for sg in init_seg_ids]
soma = neuron.make_soma([rd.get_row(si) for si in get_soma_ids(rd)])
for tr in trees:
for p in point_iter(tree.ipreorder(tr)):
LOG.debug(p)
LOG.info('Initial segment IDs: %s', init_seg_ids)
nrn = neuron.Neuron(soma, trees)
LOG.info('Neuron soma raw data % s', [r for r in nrn.soma.iter()])
LOG.info('Neuron soma points %s', [as_point(p)
for p in nrn.soma.iter()])
LOG.info('Neuron tree init points, types')
for tt in nrn.neurites:
def test_i_neurites_chains():
soma = neuron.make_soma(SOMA_A_PTS)
nrn = neuron.Neuron(soma, ['foo', 'bar', 'baz'])
s = 'foobarbaz'
for i, j in izip(s, nrn.i_neurites(iter)):
nt.assert_equal(i, j)
iterator: tree iterator for a tree holding raw data rows.
'''
return imap(as_point, tree.val_iter(iterator))
if __name__ == '__main__':
filename = 'test_data/swc/Neuron.swc'
rd = load_data(filename)
init_seg_ids = get_initial_segment_ids(rd)
trees = [make_tree(rd, sg) for sg in init_seg_ids]
soma = neuron.make_soma([rd.get_row(si) for si in get_soma_ids(rd)])
for tr in trees:
for p in point_iter(tree.ipreorder(tr)):
print p
print 'Initial segment IDs:', init_seg_ids
nrn = neuron.Neuron(soma, trees)
print 'Neuron soma raw data', [r for r in nrn.soma.iter()]
print 'Neuron soma points', [as_point(p) for p in nrn.soma.iter()]
print 'Neuron tree init points, types'
for tt in nrn.neurites:
print tt.value[COLS.ID], tt.value[COLS.TYPE]
def test_invalid_soma_points_2_raises_SomaError():
neuron.make_soma(INVALID_PTS_2)
def check_SomaC(points):
soma = neuron.make_soma(points)
nt.ok_('SomaC' in str(soma))
nt.ok_(isinstance(soma, neuron.SomaC))
nt.assert_items_equal(soma.center, (11, 22, 33))
nt.ok_(soma.radius == 0.0)
def test_invalid_soma_points_2_raises_SomaError():
neuron.make_soma(INVALID_PTS_2)
def test_trunk_direction():
t = Tree((1, 0, 0, 2))
s = make_soma([[0, 0, 0, 4]])
nt.ok_(np.allclose(trunk_direction(t, s), np.array([1, 0, 0])))
import numpy as np
from copy import copy
TREE = Tree([0.0, 0.0, 0.0, 1.0, 1, 1, 2])
T1 = TREE.add_child(Tree([0.0, 1.0, 0.0, 1.0, 1, 1, 2]))
T2 = T1.add_child(Tree([0.0, 2.0, 0.0, 1.0, 1, 1, 2]))
T3 = T2.add_child(Tree([0.0, 4.0, 0.0, 2.0, 1, 1, 2]))
T4 = T3.add_child(Tree([0.0, 5.0, 0.0, 2.0, 1, 1, 2]))
T5 = T4.add_child(Tree([2.0, 5.0, 0.0, 1.0, 1, 1, 2]))
T6 = T4.add_child(Tree(np.array([0.0, 5.0, 2.0, 1.0, 1, 1, 2])))
T7 = T5.add_child(Tree(np.array([3.0, 5.0, 0.0, 0.75, 1, 1, 2])))
T8 = T7.add_child(Tree(np.array([4.0, 5.0, 0.0, 0.75, 1, 1, 2])))
T9 = T6.add_child(Tree(np.array([0.0, 5.0, 3.0, 0.75, 1, 1, 2])))
T10 = T9.add_child(Tree(np.array([0.0, 6.0, 3.0, 0.75, 1, 1, 2])))
SOMA = make_soma(np.array([[0., 0., 0., 1., 1., 1., -1.]]))
NEURON = Neuron(SOMA, [TREE])
TREE = NEURON.neurites[0]
TEST_UVEC = np.array([ 0.01856633, 0.37132666, 0.92831665])
TEST_ANGLE = np.pi / 3.
def _Rx(angle):
sn = np.sin(angle)
cs = np.cos(angle)
return np.array([[1., 0., 0.],
[0., cs, -sn],
[0., sn, cs]])
def test_make_Soma_SinglePoint():
soma = neuron.make_soma(SOMA_SINGLE_PTS)
nt.ok_('SomaSinglePoint' in str(soma))
nt.ok_(isinstance(soma, neuron.SomaSinglePoint))
nt.assert_items_equal(soma.center, (11, 22, 33))
nt.ok_(soma.radius == 44)
pass
stylize(ax, cell.name, feature)
return fig
if __name__ == "__main__":
import numpy as np
import os
args = parse_args()
nrns = []
for j, neuronFile in enumerate(get_morph_files(args.datapath)):
_name = os.path.splitext(os.path.split(neuronFile)[-1])[0]
nrn = None
try:
soma = make_soma([np.array([11, 22, 33, 44, 1, 1, -1])])
trees = load_trees(neuronFile)
cn = coreNeuron(soma, trees, name=_name)
nrn = ezyNeuron(cn)
except IDSequenceError:
pass
for i, _feature in enumerate(args.features):
f = plot_feature(_feature, nrn)
figname = "{0}_{1}_{2}.eps".format(i, j, _name)
f.savefig(os.path.join(args.odir, figname))
pl.close(f)
def test_make_SomaB():
soma = neuron.make_soma(SOMA_B_PTS)
nt.ok_('SomaB' in str(soma))
nt.ok_(isinstance(soma, neuron.SomaB))
nt.assert_items_equal(soma.center, (11, 22, 33))
nt.ok_(soma.radius == 0.0)
def test_make_SomaB():
soma = neuron.make_soma(SOMA_B_PTS)
nt.ok_('SomaB' in str(soma))
nt.ok_(isinstance(soma, neuron.SomaB))
nt.assert_equal(soma.center, (11, 22, 33))
nt.ok_(soma.radius == 0.0)
def test_make_SomaA():
soma = neuron.make_soma(SOMA_A_PTS)
nt.ok_('SomaA' in str(soma))
nt.ok_(isinstance(soma, neuron.SomaA))
nt.assert_equal(soma.center, (11, 22, 33))
nt.ok_(soma.radius == 44)
def check_SomaC(points):
soma = neuron.make_soma(points)
nt.ok_('SomaC' in str(soma))
nt.ok_(isinstance(soma, neuron.SomaC))
nt.assert_equal(soma.center, (11, 22, 33))
nt.ok_(soma.radius == 0.0)
def test_make_Soma_ThreePoint():
soma = neuron.make_soma(SOMA_THREEPOINTS_PTS)
nt.ok_('SomaThreePoint' in str(soma))
nt.ok_(isinstance(soma, neuron.SomaThreePoint))
nt.assert_items_equal(soma.center, (11, 22, 33))
nt.eq_(soma.radius, 0.0)
def test_i_neurites_chains():
soma = neuron.make_soma(SOMA_A_PTS)
nrn = neuron.Neuron(soma, ['foo', 'bar', 'baz'])
s = 'foobarbaz'
for i, j in izip(s, nrn.i_neurites(iter)):
nt.assert_equal(i, j)
def check_SomaC(points):
soma = neuron.make_soma(points)
nt.ok_('SomaSimpleContour' in str(soma))
nt.ok_(isinstance(soma, neuron.SomaSimpleContour))
np.testing.assert_allclose(soma.center, (0., 0., 0.), atol=1e-16)
nt.eq_(soma.radius, 1.0)
return i_neurites(self.neurites,
lambda n: n.sections(),
neu_filter=tree_type_checker(neurite_type))
if __name__ == '__main__':
from neurom.core.tree import Tree
from neurom.core.neuron import make_soma
TREE = Tree([0.0, 0.0, 0.0, 1.0, 1, 1, 2])
T1 = TREE.add_child(Tree([0.0, 1.0, 0.0, 1.0, 1, 1, 2]))
T2 = T1.add_child(Tree([0.0, 2.0, 0.0, 1.0, 1, 1, 2]))
T3 = T2.add_child(Tree([0.0, 4.0, 0.0, 2.0, 1, 1, 2]))
T4 = T3.add_child(Tree([0.0, 5.0, 0.0, 2.0, 1, 1, 2]))
T5 = T4.add_child(Tree([2.0, 5.0, 0.0, 1.0, 1, 1, 2]))
T6 = T4.add_child(Tree([0.0, 5.0, 2.0, 1.0, 1, 1, 2]))
T7 = T5.add_child(Tree([3.0, 5.0, 0.0, 0.75, 1, 1, 2]))
T8 = T7.add_child(Tree([4.0, 5.0, 0.0, 0.75, 1, 1, 2]))
T9 = T6.add_child(Tree([0.0, 5.0, 3.0, 0.75, 1, 1, 2]))
T10 = T9.add_child(Tree([0.0, 6.0, 3.0, 0.75, 1, 1, 2]))
sm = make_soma([[0, 0, 0, 1, 1, 1, -1]])
nrts = [Neurite(tr) for tr in [TREE, TREE, TREE]]
nrn = Neuron(sm, nrts)
pop = Population([nrn, nrn, nrn, nrn])
print list(pop.segments())
print
print list(pop.neurons[0].segments())
print
print list(pop.neurons[0].neurites[0].segments())
