def test_is_monotonic():
# tree with decreasing radii
neuron = load_neuron(StringIO(u"""
((Dendrite)
(0 0 0 1.0)
(0 0 0 0.99)
(
(0 0 0 0.99)
(0 0 0 0.1)
|
(0 0 0 0.5)
(0 0 0 0.2)
))"""),
reader='asc')
assert mt.is_monotonic(neuron.neurites[0], 1e-6)
# tree with equal radii
neuron = load_neuron(StringIO(u"""
((Dendrite)
(0 0 0 1.0)
(0 0 0 1.0)
(
(0 0 0 1.0)
(0 0 0 1.0)
|
(0 0 0 1.0)
(0 0 0 1.0)
))"""),
reader='asc')
assert mt.is_monotonic(neuron.neurites[0], 1e-6)
# tree with increasing radii
neuron = load_neuron(StringIO(u"""
((Dendrite)
(0 0 0 1.0)
(0 0 0 1.0)
(
(0 0 0 1.1)
(0 0 0 1.1)
|
(0 0 0 0.3)
(0 0 0 0.1)
))"""),
reader='asc')
assert not mt.is_monotonic(neuron.neurites[0], 1e-6)
# Tree with larger child initial point
neuron = load_neuron(StringIO(u"""
((Dendrite)
(0 0 0 1.0)
(0 0 0 0.75)
(0 0 0 0.5)
(0 0 0 0.25)
(
(0 0 0 0.375)
(0 0 0 0.125)
(0 0 0 0.625)
))"""),
reader='asc')
assert not mt.is_monotonic(neuron.neurites[0], 1e-6)
def test_is_monotonic(): # tree with decreasing radii decr_diams = _generate_tree(0) # tree with equal radii equl_diams = _generate_tree(1) # tree with increasing radii incr_diams = _generate_tree(2) nt.assert_true(is_monotonic(decr_diams, 1e-6)) nt.assert_true(is_monotonic(equl_diams, 1e-6)) nt.assert_false(is_monotonic(incr_diams, 1e-6))
def test_is_monotonic():
# tree with decreasing radii
decr_diams = _generate_neurite(0)
nt.assert_true(mt.is_monotonic(decr_diams, 1e-6))
# tree with equal radii
equl_diams = _generate_neurite(1)
nt.assert_true(mt.is_monotonic(equl_diams, 1e-6))
# tree with increasing radii
incr_diams = _generate_neurite(2)
nt.assert_false(mt.is_monotonic(incr_diams, 1e-6))
# Tree with larger child initial point
bad_child = _genetate_tree_non_monotonic_section_boundary()
nt.assert_false(mt.is_monotonic(bad_child, 1e-6))
def test_is_monotonic():
# tree with decreasing radii
decr_diams = _generate_neurite(0)
nt.assert_true(mt.is_monotonic(decr_diams, 1e-6))
# tree with equal radii
equl_diams = _generate_neurite(1)
nt.assert_true(mt.is_monotonic(equl_diams, 1e-6))
# tree with increasing radii
incr_diams = _generate_neurite(2)
nt.assert_false(mt.is_monotonic(incr_diams, 1e-6))
# Tree with larger child initial point
bad_child = _genetate_tree_non_monotonic_section_boundary()
nt.assert_false(mt.is_monotonic(bad_child, 1e-6))
def get_nonmonotonic_neurites(neuron, tol=1e-6):
'''Get neurites that are not monotonic
Argument:
neuron : The neuron object to test
tol : the tolerance for testing monotonicity
Returns:
list of neurites that do not satisfy monotonicity test
'''
return [n for n in neuron.neurites if not is_monotonic(n, tol)]
