def _make_simple_tree():
p = [0.0, 0.0, 0.0, 1.0, 1, 1, 1]
T = PointTree(p)
T1 = T.add_child(PointTree([0.0, 2.0, 0.0, 1.0, 1, 1, 1]))
T2 = T1.add_child(PointTree([0.0, 4.0, 0.0, 1.0, 1, 1, 1]))
T3 = T2.add_child(PointTree([0.0, 6.0, 0.0, 1.0, 1, 1, 1]))
T4 = T3.add_child(PointTree([0.0, 8.0, 0.0, 1.0, 1, 1, 1]))
T5 = T.add_child(PointTree([0.0, 0.0, 2.0, 1.0, 1, 1, 1]))
T6 = T5.add_child(PointTree([0.0, 0.0, 4.0, 1.0, 1, 1, 1]))
T7 = T6.add_child(PointTree([0.0, 0.0, 6.0, 1.0, 1, 1, 1]))
T8 = T7.add_child(PointTree([0.0, 0.0, 8.0, 1.0, 1, 1, 1]))
return T
def test_principal_direction_extent():
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.])))
extent = mtr.principal_direction_extent(tree)
nt.assert_true(np.allclose(extent, [20., 0., 0.]))
def _make_odd_tree():
''' The infamous invisible tree. This should fail check
in case of integer division in partition
'''
p = [0.0, 0.0, 0.0, 0.0, 0, 0, 0]
T = PointTree(p)
T.add_child(PointTree([0.0, 0.0, 0.0, 0.0, 0, 0, 0]))
T.add_child(PointTree([0.0, 0.0, 0.0, 0.0, 0, 0, 0]))
T.children[0].add_child(PointTree([0.0, 0.0, 0.0, 0.0, 0, 0, 0]))
T.children[0].add_child(PointTree([0.0, 0.0, 0.0, 0.0, 0, 0, 0]))
T.children[1].add_child(PointTree([0.0, 0.0, 0.0, 0.0, 0, 0, 0]))
T.children[1].add_child(PointTree([0.0, 0.0, 0.0, 0.0, 0, 0, 0]))
T.children[1].children[0].add_child(PointTree([0.0, 0.0, 0.0, 0.0, 0, 0, 0]))
T.children[1].children[0].add_child(PointTree([0.0, 0.0, 0.0, 0.0, 0, 0, 0]))
return T
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 _make_tree():
'''This tree has 3 branching points'''
p = [0.0, 0.0, 0.0, 1.0, 1, 1, 2]
T = PointTree(p)
T1 = T.add_child(PointTree([0.0, 1.0, 0.0, 2.0, 1, 1, 2]))
T2 = T1.add_child(PointTree([0.0, 2.0, 0.0, 3.0, 1, 1, 2]))
T3 = T2.add_child(PointTree([0.0, 4.0, 0.0, 4.0, 1, 1, 2]))
T4 = T3.add_child(PointTree([0.0, 5.0, 0.0, 5.0, 1, 1, 2]))
T5 = T4.add_child(PointTree([2.0, 5.0, 0.0, 6.0, 1, 1, 2]))
T6 = T4.add_child(PointTree([0.0, 5.0, 2.0, 7.0, 1, 1, 2]))
return T
def _make_neuron_tree():
p = [0.0, 0.0, 0.0, 1.0, 1, 1, 2]
T = PointTree(p)
T1 = T.add_child(PointTree([0.0, 1.0, 0.0, 1.0, 1, 1, 2]))
T2 = T1.add_child(PointTree([0.0, 2.0, 0.0, 1.0, 1, 1, 2]))
T3 = T2.add_child(PointTree([0.0, 4.0, 0.0, 2.0, 1, 1, 2]))
T4 = T3.add_child(PointTree([0.0, 5.0, 0.0, 2.0, 1, 1, 2]))
T5 = T4.add_child(PointTree([2.0, 5.0, 0.0, 1.0, 1, 1, 2]))
T6 = T4.add_child(PointTree([0.0, 5.0, 2.0, 1.0, 1, 1, 2]))
T7 = T5.add_child(PointTree([3.0, 5.0, 0.0, 0.75, 1, 1, 2]))
T8 = T7.add_child(PointTree([4.0, 5.0, 0.0, 0.75, 1, 1, 2]))
T9 = T6.add_child(PointTree([0.0, 5.0, 3.0, 0.75, 1, 1, 2]))
T10 = T9.add_child(PointTree([0.0, 6.0, 3.0, 0.75, 1, 1, 2]))
return T
def _form_branching_tree():
p = [0.0, 0.0, 0.0, 1.0, 1, 1, 2]
T = PointTree(p)
T1 = T.add_child(PointTree([0.0, 1.0, 0.0, 1.0, 1, 1, 2]))
T2 = T1.add_child(PointTree([0.0, 2.0, 0.0, 1.0, 1, 1, 2]))
T3 = T2.add_child(PointTree([0.0, 4.0, 0.0, 2.0, 1, 1, 2]))
T4 = T3.add_child(PointTree([0.0, 5.0, 0.0, 2.0, 1, 1, 2]))
T5 = T4.add_child(PointTree([2.0, 5.0, 0.0, 1.0, 1, 1, 2]))
T6 = T4.add_child(PointTree([0.0, 5.0, 2.0, 1.0, 1, 1, 2]))
T7 = T5.add_child(PointTree([3.0, 5.0, 0.0, 0.75, 1, 1, 2]))
T8 = T7.add_child(PointTree([4.0, 5.0, 0.0, 0.75, 1, 1, 2]))
T9 = T6.add_child(PointTree([0.0, 5.0, 3.0, 0.75, 1, 1, 2]))
T10 = T9.add_child(PointTree([0.0, 6.0, 3.0, 0.75, 1, 1, 2]))
T11 = T9.add_child(PointTree([0.0, 6.0, 4.0, 0.75, 1, 1, 2]))
T33 = T3.add_child(PointTree([1.0, 5.0, 0.0, 2.0, 1, 1, 2]))
T331 = T33.add_child(PointTree([15.0, 15.0, 0.0, 2.0, 1, 1, 2]))
return T
def _make_branching_tree_zero_length_bif_segments():
'''This tree has 3 branching points'''
p = [0.0, 0.0, 0.0, 1.0, 1, 1, 2]
T = PointTree(p)
T1 = T.add_child(PointTree([0.0, 1.0, 0.0, 1.0, 1, 1, 2]))
T2 = T1.add_child(PointTree([0.0, 2.0, 0.0, 1.0, 1, 1, 2]))
T3 = T2.add_child(PointTree([0.0, 4.0, 0.0, 2.0, 1, 1, 2]))
T4 = T3.add_child(PointTree([0.0, 5.0, 0.0, 2.0, 1, 1, 2]))
T5_0 = T4.add_child(PointTree([0.0, 5.0, 0.0, 2.0, 1, 1, 2]))
T5 = T5_0.add_child(PointTree([2.0, 5.0, 0.0, 1.0, 1, 1, 2]))
T6_0 = T4.add_child(PointTree([0.0, 5.0, 0.0, 2.0, 1, 1, 2]))
T6 = T6_0.add_child(PointTree([0.0, 5.0, 2.0, 1.0, 1, 1, 2]))
T7 = T5.add_child(PointTree([3.0, 5.0, 0.0, 0.75, 1, 1, 2]))
T8 = T7.add_child(PointTree([4.0, 5.0, 0.0, 0.75, 1, 1, 2]))
T9 = T6.add_child(PointTree([0.0, 5.0, 3.0, 0.75, 1, 1, 2]))
T10_0 = T9.add_child(PointTree([0.0, 5.0, 3.0, 0.75, 1, 1, 2]))
T10 = T10_0.add_child(PointTree([0.0, 6.0, 3.0, 0.75, 1, 1, 2]))
T11 = T9.add_child(PointTree([0.0, 6.0, 4.0, 0.75, 1, 1, 2]))
T33 = T3.add_child(PointTree([1.0, 5.0, 0.0, 2.0, 1, 1, 2]))
T331 = T33.add_child(PointTree([15.0, 15.0, 0.0, 2.0, 1, 1, 2]))
return T
import numpy as np
from nose import tools as nt
from neurom.point_neurite.point_tree import PointTree
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)
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from nose import tools as nt
import os
from neurom.point_neurite.core import iter_neurites
from neurom.point_neurite import io
from neurom.point_neurite.io.utils import make_neuron
from neurom.point_neurite.point_tree import PointTree, isection
from neurom.point_neurite import segments as seg
from neurom.point_neurite import sections as sec
# Mock tree holding integers, not points
MOCK_TREE = PointTree(0)
MOCK_TREE.add_child(PointTree(11))
MOCK_TREE.add_child(PointTree(12))
MOCK_TREE.children[0].add_child(PointTree(111))
MOCK_TREE.children[0].add_child(PointTree(112))
MOCK_TREE.children[1].add_child(PointTree(121))
MOCK_TREE.children[1].add_child(PointTree(122))
MOCK_TREE.children[1].children[0].add_child(PointTree(1211))
MOCK_TREE.children[1].children[0].children[0].add_child(PointTree(12111))
MOCK_TREE.children[1].children[0].children[0].add_child(PointTree(12112))
class MockNeuron(object):
pass
DATA_PATH = './test_data'
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from nose import tools as nt
from copy import deepcopy
from neurom.core._neuron import Neuron
from neurom.core import make_soma
from neurom.point_neurite.point_tree import PointTree
from neurom.point_neurite.point_tree import val_iter
from itertools import izip
import numpy as np
SOMA_SINGLE_PTS = [[11, 22, 33, 44, 1, 1, -1]]
TREE = PointTree([0.0, 0.0, 0.0, 1.0, 1, 1, 2])
T1 = TREE.add_child(PointTree([0.0, 1.0, 0.0, 1.0, 1, 1, 2]))
T2 = T1.add_child(PointTree([0.0, 2.0, 0.0, 1.0, 1, 1, 2]))
T3 = T2.add_child(PointTree([0.0, 4.0, 0.0, 2.0, 1, 1, 2]))
T4 = T3.add_child(PointTree([0.0, 5.0, 0.0, 2.0, 1, 1, 2]))
T5 = T4.add_child(PointTree([2.0, 5.0, 0.0, 1.0, 1, 1, 2]))
T6 = T4.add_child(PointTree([0.0, 5.0, 2.0, 1.0, 1, 1, 2]))
T7 = T5.add_child(PointTree([3.0, 5.0, 0.0, 0.75, 1, 1, 2]))
T8 = T7.add_child(PointTree([4.0, 5.0, 0.0, 0.75, 1, 1, 2]))
T9 = T6.add_child(PointTree([0.0, 5.0, 3.0, 0.75, 1, 1, 2]))
T10 = T9.add_child(PointTree([0.0, 6.0, 3.0, 0.75, 1, 1, 2]))
def test_deep_copy():
soma = make_soma([[0, 0, 0, 1, 1, 1, -1]])
nrn1 = Neuron(soma, [TREE])
def test_trunk_section_length():
t = PointTree((0, 0, 0, 42))
tt = t.add_child(PointTree((10, 0, 0, 4)))
tt.add_child(PointTree((10, 15, 0, 4)))
nt.assert_almost_equal(mtr.trunk_section_length(t), 25.0)
def test_trunk_origin_radius():
t = PointTree((0, 0, 0, 42))
t.add_child(PointTree((1, 0, 0, 4)))
nt.assert_equal(mtr.trunk_origin_radius(t), 42.0)
DATA_PATH = './test_data'
SWC_PATH = os.path.join(DATA_PATH, 'swc/')
data = io.load_data(SWC_PATH + 'Neuron.swc')
neuron0 = make_neuron(data)
tree0 = neuron0.neurites[0]
tree_types = [NeuriteType.axon,
NeuriteType.basal_dendrite,
NeuriteType.basal_dendrite,
NeuriteType.apical_dendrite]
# Mock tree holding integers, not points
MOCK_TREE = PointTree(0)
MOCK_TREE.add_child(PointTree(11))
MOCK_TREE.add_child(PointTree(12))
MOCK_TREE.children[0].add_child(PointTree(111))
MOCK_TREE.children[0].add_child(PointTree(112))
MOCK_TREE.children[1].add_child(PointTree(121))
MOCK_TREE.children[1].add_child(PointTree(122))
MOCK_TREE.children[1].children[0].add_child(PointTree(1211))
MOCK_TREE.children[1].children[0].children[0].add_child(PointTree(12111))
MOCK_TREE.children[1].children[0].children[0].add_child(PointTree(12112))
T1111 = MOCK_TREE.children[0].children[0].add_child(PointTree(1111))
T11111 = T1111.add_child(PointTree(11111))
T11112 = T1111.add_child(PointTree(11112))
T11113 = T1111.add_child(PointTree(11113))
REF_TREE3 = PointTree(np.array([0.,0.,0.,1.,0.,0.,0.]))
REF_TREE3.add_child(PointTree(np.array([1.,1.,1.,1.,0.,0.,0.])))
