def ignored_warning(warning):
'''Context manager during which a warning is ignored'''
try:
set_ignored_warning(warning, True)
yield
finally:
set_ignored_warning(warning, False)
def repair(
inputfile: Path, # pylint: disable=too-many-arguments
outputfile: Path,
axons: Optional[List[Path]] = None,
seed: int = 0,
cut_leaves_coordinates: Optional[NDArray[(3, Any)]] = None,
legacy_detection: bool = False,
plot_file: Optional[Path] = None,
repair_flags: Optional[Dict[RepairType, bool]] = None,
apical_point: List = None,
params: Dict = None):
'''The repair function
Args:
inputfile: the input morph
outputfile: the output morph
axons: the axons
seed: the numpy seed
cut_leaves_coordinates: List of 3D coordinates from which to start the repair
plot_file: the filename of the plot
repair_flags: a dict of flags where key is a RepairType and value is whether
it should be repaired or not. If not provided, all types will be repaired.
apical_point: 3d vector for apical point, else, the automatic apical detection is used
params: repair internal parameters, None will use defaults
'''
ignored_warnings = (
# We append the section at the wrong place and then we reposition them
# afterwards so we can ignore the warning
morphio.Warning.wrong_duplicate,
# the repair process creates new sections that may not have siblings
morphio.Warning.only_child,
# We are appending empty section and filling them later on
morphio.Warning.appending_empty_section,
)
for warning in ignored_warnings:
morphio.set_ignored_warning(warning, True)
if axons is None:
axons = list()
if params is None:
params = _PARAMS
obj = Repair(inputfile,
axons=axons,
seed=seed,
cut_leaves_coordinates=cut_leaves_coordinates,
legacy_detection=legacy_detection,
repair_flags=repair_flags,
apical_point=apical_point,
params=params)
obj.run(outputfile, plot_file=plot_file)
for warning in ignored_warnings:
morphio.set_ignored_warning(warning, False)
def repair(inputfile: Path,
outputfile: Path,
axons: Optional[Path] = None,
seed: int = 0,
cut_leaves_coordinates: Optional[NDArray[(3, Any)]] = None,
legacy_detection: bool = False,
plot_file: Optional[Path] = None,
repair_flags: Optional[Dict[RepairType, bool]] = None):
'''The repair function
Args:
inputfile: the input morph
outputfile: the output morph
axons: the axons
seed: the numpy seed
cut_leaves_coordinates: List of 3D coordinates from which to start the repair
plot_file: the filename of the plot
repair_flags: a dict of flags where key is a RepairType and value is whether
it should be repaired or not. If not provided, all types will be repaired.
'''
ignored_warnings = (
# We append the section at the wrong place and then we reposition them
# afterwards so we can ignore the warning
morphio.Warning.wrong_duplicate,
# the repair process creates new sections that may not have siblings
morphio.Warning.only_child,
# We are appending empty section and filling them later on
morphio.Warning.appending_empty_section)
for warning in ignored_warnings:
morphio.set_ignored_warning(warning, True)
if axons is None:
axons = list()
obj = Repair(inputfile,
axons=axons,
seed=seed,
cut_leaves_coordinates=cut_leaves_coordinates,
legacy_detection=legacy_detection,
repair_flags=repair_flags)
obj.run(outputfile, plot_file=plot_file)
for warning in ignored_warnings:
morphio.set_ignored_warning(warning, False)
def __init__(self, filename, name=None):
"""Neuron constructor.
Args:
filename (str|Path): a filename
name (str): a option neuron name
"""
try:
morphio.set_ignored_warning([
morphio.Warning.wrong_root_point,
morphio.Warning.no_soma_found, morphio.Warning.zero_diameter
], True)
morphio.set_raise_warnings(True)
super().__init__(filename)
finally:
morphio.set_raise_warnings(False)
self.name = name if name else 'Neuron'
self.morphio_soma = super().soma
self.neurom_soma = make_soma(self.morphio_soma)
def test_equality():
set_ignored_warning([Warning.wrong_duplicate, Warning.only_child], True)
filename = joinp(DATA, 'simple2.asc')
neuron_ref = Morphology(filename)
ok_(not diff(neuron_ref, neuron_ref))
ok_(not diff(neuron_ref, filename))
ok_(not diff(neuron_ref, neuron_ref.as_immutable()))
def mundane_section(neuron):
'''Not a root section, not a leaf section'''
return neuron.root_sections[0].children[0]
a = Morphology(joinp(DATA, 'simple2.asc'))
mundane_section(a).type = SectionType.apical_dendrite
result = diff(neuron_ref, a)
ok_(result)
assert_equal(result.info, 'Section(id=1, points=[(0 5 0),..., (-6 5 0)]) and Section(id=1, points=[(0 5 0),..., (-6 5 0)]) have different section types')
a = Morphology(joinp(DATA, 'simple2.asc'))
mundane_section(a).points = [[0,0,0], [0,0,0], [0,0,1]]
result = diff(neuron_ref, a)
ok_(result)
assert_equal(result.info,
'\n'.join(['Attributes Section.points of:',
'Section(id=1, points=[(0 5 0),..., (-6 5 0)])',
'Section(id=1, points=[(0 0 0),..., (0 0 1)])',
'have the same shape but different values']))
a = Morphology(joinp(DATA, 'simple2.asc'))
mundane_section(a).diameters = [0,0,0]
result = diff(neuron_ref, a)
ok_(result)
assert_equal(result.info,
'\n'.join(['Attributes Section.diameters of:',
'Section(id=1, points=[(0 5 0),..., (-6 5 0)])',
'Section(id=1, points=[(0 5 0),..., (-6 5 0)])',
'have the same shape but different values']))
a = Morphology(joinp(DATA, 'simple2.asc'))
for section in a.iter():
section.perimeters = [1] * len(section.points)
result = diff(neuron_ref, a)
ok_(result)
assert_equal(result.info,
'\n'.join(['Attributes Section.perimeters of:',
'Section(id=0, points=[(0 0 0),..., (0 5 0)])',
'Section(id=0, points=[(0 0 0),..., (0 5 0)])',
'have different shapes: (0,) vs (2,)']))
a = Morphology(joinp(DATA, 'simple2.asc'))
mundane_section(a).append_section(PointLevel([[-6, 5, 0], [4, 5, 6]], [2, 3]))
result = diff(neuron_ref, a)
ok_(result)
assert_equal(result.info, 'Section(id=1, points=[(0 5 0),..., (-6 5 0)]) and Section(id=1, points=[(0 5 0),..., (-6 5 0)]) have different a different number of children')
a = Morphology(joinp(DATA, 'simple2.asc'))
a.delete_section(a.root_sections[0])
result = diff(neuron_ref, a)
ok_(result)
assert_equal(result.info, 'Both morphologies have different a different number of root sections')
result = diff(joinp(DATA, 'single_child.asc'), joinp(DATA, 'not_single_child.asc'))
ok_(not result)
set_ignored_warning([Warning.wrong_duplicate, Warning.only_child], False)
def repair(morphology, section, intact_sections, axon_branches,
used_axon_branches, y_extent):
'''Axonal repair
Reimplementation of:
https://bbpcode.epfl.ch/browse/code/platform/BlueRepairSDK/tree/BlueRepairSDK/src/repair.cpp#n727
1) Find the most similar section in INTACT_SECTIONS list to SECTION
2) Sort AXON_BRANCHES according to a similarity score to the section found at step 1
3) Loop through the sorted AXON_BRANCHES to find a section with same strahler orders
and that, when appended, does not extend further than Y_EXTENT
4) Append the first section that meets the conditions of step 3)
5) Mark this section as used and do not re-use it
Args:
morphology (neurom.Neuron): the morphology to repair
section (neurom.core._neuron.Section): the section to repair
intact_sections (List[Section]): a list of all sections from this morphology
that are part of an intact subtree. Note: these section won't be grafted
axon_branches (List[Section]): a list a intact sections coming from donor morphologies
These are the sections that will be appended
..note::
The original code used to have more parameters. In the context of the bbp-morphology-workflow
it seems that some of the parameters were always used with the same value. This
reimplementation assumes the following BlueRepairSDK options:
- --overlap=true
- --incremental=false
- --restrict=true
- --distmethod=mirror'
'''
if not intact_sections:
L.debug("No intact axon found. Not repairing!")
return
similar = _similar_section(intact_sections, section)
branch_pool = _sort_intact_sections_by_score(section, similar,
axon_branches)
strahler_orders = {
intact_section: strahler_order(intact_section)
for intact_section in intact_sections + branch_pool
}
L.debug('Branch pool count: %s', len(branch_pool))
for branch in branch_pool:
if (branch in used_axon_branches
or strahler_orders[similar] != strahler_orders[branch]):
continue
L.debug("Pasting axon branch with ID %s", branch.id)
end_point = section.points[-1, COLS.XYZ]
appended = section.append_section(branch)
translation = section.points[-1, COLS.XYZ] - appended.points[0,
COLS.XYZ]
align(appended, translation)
translate(appended, translation)
# Make sure the child section first point is exactly the end point of the parent section
appended_points = np.copy(appended.points)
appended_points[0] = end_point
appended.points = appended_points
if any(
np.any(section.points[:, COLS.Y] > y_extent)
for section in appended.iter()):
L.debug("Discarded, exceeds y-limit")
morphology.delete_section(appended)
else:
L.debug('Section appended')
used_axon_branches.add(branch)
return
morphio.set_ignored_warning(morphio.Warning.wrong_duplicate, False)
def test_equality():
set_ignored_warning([Warning.wrong_duplicate, Warning.only_child], True)
filename = DATA / 'simple2.asc'
neuron_ref = Morphology(filename)
assert not diff(neuron_ref, neuron_ref)
assert not diff(neuron_ref, filename)
assert not diff(neuron_ref, neuron_ref.as_immutable())
def mundane_section(neuron):
'''Not a root section, not a leaf section'''
return neuron.root_sections[0].children[0]
a = Morphology(DATA / 'simple2.asc')
mundane_section(a).type = SectionType.apical_dendrite
result = diff(neuron_ref, a)
assert result
assert result.info == 'Section(id=1, points=[(0 5 0),..., (-6 5 0)]) and Section(id=1, points=[(0 5 0),..., (-6 5 0)]) have different section types'
a = Morphology(DATA / 'simple2.asc')
mundane_section(a).points = [[0,0,0], [0,0,0], [0,0,1]]
result = diff(neuron_ref, a)
assert result
assert (result.info ==
'\n'.join(['Attributes Section.points of:',
'Section(id=1, points=[(0 5 0),..., (-6 5 0)])',
'Section(id=1, points=[(0 0 0),..., (0 0 1)])',
'have the same shape but different values',
'Vector points differs at index 0: [0. 5. 0.] != [0. 0. 0.]']))
a = Morphology(DATA / 'simple2.asc')
mundane_section(a).diameters = [0,0,0]
result = diff(neuron_ref, a)
assert result
assert (result.info ==
'\n'.join(['Attributes Section.diameters of:',
'Section(id=1, points=[(0 5 0),..., (-6 5 0)])',
'Section(id=1, points=[(0 5 0),..., (-6 5 0)])',
'have the same shape but different values',
'Vector diameters differs at index 0: 3.0 != 0.0']))
a = Morphology(DATA / 'simple2.asc')
for section in a.iter():
section.perimeters = [1] * len(section.points)
result = diff(neuron_ref, a)
assert result
assert (result.info ==
'\n'.join(['Attributes Section.perimeters of:',
'Section(id=0, points=[(0 0 0),..., (0 5 0)])',
'Section(id=0, points=[(0 0 0),..., (0 5 0)])',
'have different shapes: (0,) vs (2,)']))
a = Morphology(DATA / 'simple2.asc')
mundane_section(a).append_section(PointLevel([[-6, 5, 0], [4, 5, 6]], [2, 3]))
result = diff(neuron_ref, a)
assert result
assert result.info == 'Section(id=1, points=[(0 5 0),..., (-6 5 0)]) and Section(id=1, points=[(0 5 0),..., (-6 5 0)]) have a different number of children'
a = Morphology(DATA / 'simple2.asc')
a.delete_section(a.root_sections[0])
result = diff(neuron_ref, a)
assert result
assert result.info == 'Both morphologies have a different number of root sections'
result = diff(DATA / 'single_child.asc', DATA / 'not_single_child.asc')
if parse_version(get_distribution("morphio").version) < parse_version("3"):
assert not result
else:
assert result
set_ignored_warning([Warning.wrong_duplicate, Warning.only_child], False)
