def segment_centre_of_mass(seg):
'''Calculate and return centre of mass of a segment.
C, seg_volalculated as centre of mass of conical frustum'''
h = mm.segment_length(seg)
r0 = seg[0][COLS.R]
r1 = seg[1][COLS.R]
num = r0 * r0 + 2 * r0 * r1 + 3 * r1 * r1
denom = 4 * (r0 * r0 + r0 * r1 + r1 * r1)
centre_of_mass_z_loc = num / denom
return seg[0][0:3] + (centre_of_mass_z_loc / h) * (seg[1][0:3] - seg[0][0:3])
def segment_centre_of_mass(seg):
"""Calculate and return centre of mass of a segment.
C, seg_volalculated as centre of mass of conical frustum"""
h = mm.segment_length(seg)
r0 = seg[0][COLS.R]
r1 = seg[1][COLS.R]
num = r0 * r0 + 2 * r0 * r1 + 3 * r1 * r1
denom = 4 * (r0 * r0 + r0 * r1 + r1 * r1)
centre_of_mass_z_loc = num / denom
return seg[0][COLS.XYZ] + (centre_of_mass_z_loc / h) * (seg[1][COLS.XYZ] - seg[0][COLS.XYZ])
def _generate_dendro(self, current_node, spacing, offsets):
'''Recursive function for dendrogram line computations
'''
max_dims = self._max_dims
start_x = _spacingx(current_node, max_dims, offsets[0], spacing[0])
radii = [0., 0.]
# store the parent radius in order to construct polygonal segments
# isntead of simple line segments
radii[0] = current_node.value[COLS.R] if self._show_diameters else 0.
for child in current_node.children:
# segment length
ln = segment_length((current_node.value, child.value))
# extract the radius of the child node. Need both radius for
# realistic segment representation
radii[1] = child.value[COLS.R] if self._show_diameters else 0.
# number of leaves in child
terminations = n_terminations(child)
# horizontal spacing with respect to the number of
# terminations
new_offsets = _update_offsets(start_x, spacing, terminations, offsets, ln)
# create and store vertical segment
self._rectangles[self._n] = _vertical_segment(offsets, new_offsets, spacing, radii)
# assign segment id to color array
# colors[n[0]] = child.value[4]
self._n += 1
if offsets[1] + spacing[1] * 2 + ln > max_dims[1]:
max_dims[1] = offsets[1] + spacing[1] * 2. + ln
self._max_dims = max_dims
# recursive call to self.
self._generate_dendro(child, spacing, new_offsets)
# update the starting position for the next child
start_x += terminations * spacing[0]
# write the horizontal lines only for bifurcations, where the are actual horizontal
# lines and not zero ones
if offsets[0] != new_offsets[0]:
# horizontal segment. Thickness is either 0 if show_diameters is false
# or 1. if show_diameters is true
self._rectangles[self._n] = _horizontal_segment(offsets, new_offsets, spacing, 0.)
self._n += 1
def has_all_nonzero_segment_lengths(neuron, threshold=0.0):
'''Check presence of neuron segments with length not above threshold
Arguments:
neuron: Neuron object whose segments will be tested
threshold: value above which a segment length is considered to be non-zero
Return:
status and list of (section_id, segment_id) of zero length segments
'''
bad_ids = []
for sec in _nf.iter_sections(neuron):
p = sec.points
for i, s in enumerate(izip(p[:-1], p[1:])):
if segment_length(s) <= threshold:
bad_ids.append((sec.id, i))
return CheckResult(len(bad_ids) == 0, bad_ids)
def has_all_nonzero_segment_lengths(neuron, threshold=0.0):
'''Check presence of neuron segments with length not above threshold
Arguments:
neuron(Neuron): The neuron object to test
threshold(float): value above which a segment length is considered to
be non-zero
Returns:
CheckResult with result including list of (section_id, segment_id)
of zero length segments
'''
bad_ids = []
for sec in _nf.iter_sections(neuron):
p = sec.points
for i, s in enumerate(zip(p[:-1], p[1:])):
if segment_length(s) <= threshold:
bad_ids.append((sec.id, i))
return CheckResult(len(bad_ids) == 0, bad_ids)
def test_segment_length():
assert mm.segment_length(((0, 0, 0), (0, 0, 42))) == 42
assert mm.segment_length(((0, 0, 0), (0, 42, 0))) == 42
assert mm.segment_length(((0, 0, 0), (42, 0, 0))) == 42
def test_segment_length():
nt.ok_(mm.segment_length(((0,0,0), (0,0,42))) == 42)
nt.ok_(mm.segment_length(((0,0,0), (0,42,0))) == 42)
nt.ok_(mm.segment_length(((0,0,0), (42,0,0))) == 42)
# any function that takes a segment or section.
# Get of all neurites in cell by iterating over sections,
# and summing the section lengths
def sec_len(sec):
"""Return the length of a section."""
return mm.section_length(sec.points)
print('Total neurite length (sections):',
sum(sec_len(s) for s in nm.iter_sections(nrn)))
# Get length of all neurites in cell by iterating over segments,
# and summing the segment lengths.
# This should yield the same result as iterating over sections.
print('Total neurite length (segments):',
sum(mm.segment_length(s) for s in nm.iter_segments(nrn)))
# get volume of all neurites in cell by summing over segment
# volumes
print('Total neurite volume:',
sum(mm.segment_volume(s) for s in nm.iter_segments(nrn)))
# get area of all neurites in cell by summing over segment
# areas
print('Total neurite surface area:',
sum(mm.segment_area(s) for s in nm.iter_segments(nrn)))
# get total number of neurite points in cell.
def n_points(sec):
"""number of points in a section."""
n = len(sec.points)
# any function that takes a segment or section.
# Get of all neurites in cell by iterating over sections,
# and summing the section lengths
def sec_len(sec):
'''Return the length of a section'''
return mm.section_length(sec.points)
print('Total neurite length (sections):',
sum(sec_len(s) for s in nm.iter_sections(nrn)))
# Get length of all neurites in cell by iterating over segments,
# and summing the segment lengths.
# This should yield the same result as iterating over sections.
print('Total neurite length (segments):',
sum(mm.segment_length(s) for s in nm.iter_segments(nrn)))
# get volume of all neurites in cell by summing over segment
# volumes
print('Total neurite volume:',
sum(mm.segment_volume(s) for s in nm.iter_segments(nrn)))
# get area of all neurites in cell by summing over segment
# areas
print('Total neurite surface area:',
sum(mm.segment_area(s) for s in nm.iter_segments(nrn)))
# get total number of neurite points in cell.
def n_points(sec):
'''number of points in a section'''
n = len(sec.points)
