def is_monotonic(neurite, tol):
'''Check if neurite tree is monotonic
If each child has smaller or equal diameters from its parent
Args:
neurite(Neurite): neurite to operate on
tol(float): tolerance
Returns:
True if neurite flat
'''
for node in neurite.iter_sections():
# check that points in section satisfy monotonicity
sec = node.points
for point_id in range(len(sec) - 1):
if sec[point_id + 1][COLS.R] > sec[point_id][COLS.R] + tol:
return False
# Check that section boundary points satisfy monotonicity
if (node.parent is not None
and sec[0][COLS.R] > node.parent.points[-1][COLS.R] + tol):
return False
return True
def is_monotonic(neurite, tol):
'''Check if neurite tree is monotonic
If each child has smaller or equal diameters from its parent
Args:
neurite(Neurite): neurite to operate on
tol(float): tolerance
Returns:
True if neurite flat
'''
for node in neurite.iter_sections():
# check that points in section satisfy monotonicity
sec = node.points
for point_id in range(len(sec) - 1):
if sec[point_id + 1][COLS.R] > sec[point_id][COLS.R] + tol:
return False
# Check that section boundary points satisfy monotonicity
if(node.parent is not None and
sec[0][COLS.R] > node.parent.points[-1][COLS.R] + tol):
return False
return True
def _make_monotonic(neuron):
for neurite in neuron.neurites:
for node in neurite.iter_sections():
sec = node.points
if node.parent is not None:
sec[0][COLS.R] = node.parent.points[-1][COLS.R] / 2.
for point_id in range(len(sec) - 1):
sec[point_id + 1][COLS.R] = sec[point_id][COLS.R] / 2.
def _make_monotonic(neuron):
for neurite in neuron.neurites:
for node in neurite.iter_sections():
sec = node.points
if node.parent is not None:
sec[0][COLS.R] = node.parent.points[-1][COLS.R] / 2.
for point_id in range(len(sec) - 1):
sec[point_id + 1][COLS.R] = sec[point_id][COLS.R] / 2.
def test_parent():
t = Tree()
for i in range(10):
t.add_child(Tree())
nt.ok_(len(t.children) == 10)
for c in t.children:
nt.ok_(c.parent is t)
def fake_tree(init_radius, mode):
radius = init_radius
sec = []
for _ in range(5):
sec.append([0, 0, 0, radius, 0, 0])
radius = new_radius(radius, mode)
return Section(np.array(sec))
def test_deep_iteration():
root = t = Tree()
for i in range(1, sys.getrecursionlimit() + 2):
child = Tree()
t.add_child(child)
t = child
list(root.ipreorder())
list(root.ipostorder())
list(t.iupstream())
def fake_tree(init_radius, mode):
radius = init_radius
sec = []
for _ in range(5):
sec.append([0, 0, 0, radius, 0, 0])
radius = new_radius(radius, mode)
return Section(np.array(sec))
def section_meander_angles(section):
'''Inter-segment opening angles in a section'''
p = section.points
return [
mm.angle_3points(p[i - 1], p[i - 2], p[i]) for i in range(2, len(p))
]
def section_meander_angles(section):
'''Inter-segment opening angles in a section'''
p = section.points
return [mm.angle_3points(p[i - 1], p[i - 2], p[i])
for i in range(2, len(p))]
