def test_section_tortuosity():
sec_a = load_neuron(StringIO(u"""
((CellBody) (0 0 0 2))
((Dendrite)
(0 0 0 2)
(1 0 0 2)
(2 0 0 2)
(3 0 0 2))"""),
reader='asc').sections[SECTION_ID]
sec_b = load_neuron(StringIO(u"""
((CellBody) (0 0 0 2))
((Dendrite)
(0 0 0 2)
(1 0 0 2)
(1 2 0 2)
(0 2 0 2))"""),
reader='asc').sections[SECTION_ID]
assert _sf.section_tortuosity(sec_a) == 1.0
assert _sf.section_tortuosity(sec_b) == 4.0 / 2.0
for s in _nf.iter_sections(NRN):
assert (_sf.section_tortuosity(s) == mmth.section_length(s.points) /
mmth.point_dist(s.points[0], s.points[-1]))
def test_section_tortuosity():
sec_a = load_neuron(StringIO(u"""
((CellBody) (0 0 0 2))
((Dendrite)
(0 0 0 2)
(1 0 0 2)
(2 0 0 2)
(3 0 0 2))"""),
reader='asc').sections[1]
sec_b = load_neuron(StringIO(u"""
((CellBody) (0 0 0 2))
((Dendrite)
(0 0 0 2)
(1 0 0 2)
(1 2 0 2)
(0 2 0 2))"""),
reader='asc').sections[1]
nt.eq_(_sf.section_tortuosity(sec_a), 1.0)
nt.eq_(_sf.section_tortuosity(sec_b), 4.0 / 2.0)
for s in _nf.iter_sections(NRN):
nt.eq_(
_sf.section_tortuosity(s),
mmth.section_length(s.points) /
mmth.point_dist(s.points[0], s.points[-1]))
def trunk_section_lengths(nrn, neurite_type=NeuriteType.all):
"""List of lengths of trunk sections of neurites in a neuron."""
neurite_filter = is_type(neurite_type)
return [
morphmath.section_length(s.root_node.points) for s in nrn.neurites
if neurite_filter(s)
]
def test_section_tortuosity():
sec_a = Section([(0, 0, 0), (1, 0, 0), (2, 0, 0), (3, 0, 0)])
sec_b = Section([(0, 0, 0), (1, 0, 0), (1, 2, 0), (0, 2, 0)])
nt.eq_(_sf.section_tortuosity(sec_a), 1.0)
nt.eq_(_sf.section_tortuosity(sec_b), 4.0 / 2.0)
for s in _nf.iter_sections(NRN):
nt.eq_(_sf.section_tortuosity(s), mmth.section_length(s.points) / mmth.point_dist(s.points[0], s.points[-1]))
def section_tortuosity(section):
'''Tortuosity of a section
The tortuosity is defined as the ratio of the path length of a section
and the euclidian distnce between its end points.
The path length is the sum of distances between consecutive points.
If the section contains less than 2 points, the value 1 is returned.
'''
pts = section.points
return 1 if len(pts) < 2 else mm.section_length(pts) / mm.point_dist(pts[-1], pts[0])
def test_section_tortuosity():
sec_a = Section([(0, 0, 0), (1, 0, 0), (2, 0, 0), (3, 0, 0)])
sec_b = Section([(0, 0, 0), (1, 0, 0), (1, 2, 0), (0, 2, 0)])
nt.eq_(_sf.section_tortuosity(sec_a), 1.0)
nt.eq_(_sf.section_tortuosity(sec_b), 4.0 / 2.0)
for s in _nf.iter_sections(NRN):
nt.eq_(
_sf.section_tortuosity(s),
mmth.section_length(s.points) /
mmth.point_dist(s.points[0], s.points[-1]))
def has_all_nonzero_section_lengths(neuron, threshold=0.0):
'''Check presence of neuron sections with length not above threshold
Arguments:
neuron: Neuron object whose segments will be tested
threshold: value above which a section length is considered to be non-zero
Return:
status and list of ids bad sections
'''
bad_ids = [s.id for s in _nf.iter_sections(neuron.neurites)
if section_length(s.points) <= threshold]
return CheckResult(len(bad_ids) == 0, bad_ids)
def has_all_nonzero_section_lengths(neuron, threshold=0.0):
'''Check presence of neuron sections with length not above threshold
Arguments:
neuron(Neuron): The neuron object to test
threshold(float): value above which a section length is considered
to be non-zero
Returns:
CheckResult with result including list of ids bad sections
'''
bad_ids = [s.id for s in _nf.iter_sections(neuron.neurites)
if section_length(s.points) <= threshold]
return CheckResult(len(bad_ids) == 0, bad_ids)
def has_all_nonzero_section_lengths(neuron, threshold=0.0):
'''Check presence of neuron sections with length not above threshold
Arguments:
neuron(Neuron): The neuron object to test
threshold(float): value above which a section length is considered
to be non-zero
Returns:
CheckResult with result including list of ids of bad sections
'''
bad_ids = [s.id for s in _nf.iter_sections(neuron.neurites)
if section_length(s.points) <= threshold]
return CheckResult(len(bad_ids) == 0, bad_ids)
def length(self):
"""Return the path length of this section."""
return morphmath.section_length(self.points)
def _seclen(sec, **kwargs):
"""get section length of `sec`"""
return morphmath.section_length(sec.points, **kwargs)
def trunk_section_lengths(nrn, neurite_type=NeuriteType.all):
'''list of lengths of trunk sections of neurites in a neuron'''
neurite_filter = is_type(neurite_type)
return [mm.section_length(s.root_node.points) for s in nrn.neurites if neurite_filter(s)]
def _section_length(section):
"""Get section length of `section`."""
return morphmath.section_length(section.points)
def sec_len(sec):
"""Return the length of a section."""
return mm.section_length(sec.points)
def length(section):
'''Return the length of a section'''
return mm.section_length(section)
def sec_len(sec):
'''Return the length of a section'''
return mm.section_length(sec.points)
def length(self):
'''Return the path length of this section.'''
return morphmath.section_length(self.points)
def length(self):
'''Return the path length of this section.'''
return morphmath.section_length(self.points)
def _seclen(sec, **kwargs):
'''get section length of `sec`'''
return morphmath.section_length(sec.points, **kwargs)
def _section_length(section):
'''get section length of `section`'''
return morphmath.section_length(section.points)
def section_path_length(section):
'''Path length from section to root'''
return sum(mm.section_length(s.points) for s in section.iupstream())
def _section_length(section):
'''get section length of `section`'''
return morphmath.section_length(section.points)
def sec_len(sec):
'''Return the length of a section'''
return mm.section_length(sec.points)