def __init__(self, morph, PtSrc=None):
PtSrc = SectionVistorFactory.array3_all_points() if PtSrc == None else PtSrc
X = PtSrc(morph)
# Refactored out 'map' in August 2012
offset = np.array([sum(col) for col in X.T]) / len(X)
# _get_mean(PtSrc(morph)) * -1.0
super(MorphologyMeanCenterer, self).__init__(offset)
def cell_location_distance_from_soma(cell_location):
morph = cell_location.cell.morphology
sect_dist_dict = SectionVistorFactory.dict_section_proximal_dist_from_soma(morph, soma_centre=False)()
section_dist = sect_dist_dict[cell_location.morphlocation.section]
celllocdist = (
section_dist + cell_location.morphlocation.section.get_length() * cell_location.morphlocation.sectionpos
)
return celllocdist
def cell_location_distance_from_soma(cell_location):
morph = cell_location.cell.morphology
sect_dist_dict = SectionVistorFactory.dict_section_proximal_dist_from_soma(
morph, soma_centre=False)()
section_dist = sect_dist_dict[cell_location.morphlocation.section]
celllocdist = section_dist + cell_location.morphlocation.section.get_length(
) * cell_location.morphlocation.sectionpos
return celllocdist
def __init__(self, morph):
axes = _pca(SectionVistorFactory.array3_all_points(morph)())
eigenvec1 = axes[0][1] / norm(axes[0][1])
eigenvec2 = axes[1][1] / norm(axes[1][1])
eigenvec3 = axes[2][1] / norm(axes[2][1])
self.eigen_matrix = numpy.array((eigenvec1, eigenvec2, eigenvec3)).T
self.inv_mat = linalg.inv(self.eigen_matrix)
def __init__(self, morph):
axes = _pca(SectionVistorFactory.array3_all_points(morph)())
eigenvec1 = axes[0][1] / norm(axes[0][1])
eigenvec2 = axes[1][1] / norm(axes[1][1])
eigenvec3 = axes[2][1] / norm(axes[2][1])
self.eigen_matrix = numpy.array((eigenvec1, eigenvec2, eigenvec3)).T
self.inv_mat = linalg.inv(self.eigen_matrix)
def __init__(self, morph, PtSrc=None):
PtSrc = SectionVistorFactory.array3_all_points(
) if PtSrc == None else PtSrc
X = PtSrc(morph)
# Refactored out 'map' in August 2012
# offset = array(map(numpy.sum, X.T)) / len(X)
offset = array([sum(col) for col in X.T]) / len(X)
# _get_mean(PtSrc(morph)) * -1.0
super(MorphologyMeanCenterer, self).__init__(offset)
def _showSimple():
morph_pts = [SectionVistorFactory.array4_all_points(morph)() for morph in self.morphs]
pts = numpy.concatenate(morph_pts)
return mlab.points3d(
pts[:, 0],
pts[:, 1],
pts[:, 2],
pts[:, 3],
colormap=self.colormap,
scale_factor=self.scale_factor,
)
def _showSimple():
morph_pts = [
SectionVistorFactory.array4_all_points(morph)()
for morph in self.morphs
]
pts = numpy.concatenate(morph_pts)
return mlab.points3d(
pts[:, 0],
pts[:, 1],
pts[:, 2],
pts[:, 3],
colormap=self.colormap,
scale_factor=self.scale_factor,
)
def trim_axon_from_morphology(cls, morphology, max_dist_to_parent):
dist_to_parent = SectionVistorFactory.dict_section_proximal_dist_from_soma(
morph=morphology, soma_centre=False)()
print sorted(dist_to_parent.values())
section_mapping_table = {}
region_mapping_table = {}
# Create New Regions:
region_mapping_table[None] = None
for rOld in morphology.get_regions():
r_new = Region(name=rOld.name)
region_mapping_table[rOld] = r_new
# Create New Sections:
dummy_root_old = morphology.get_dummy_section()
dummy_root_new = Section(
region=region_mapping_table[dummy_root_old.region],
x=dummy_root_old.d_x,
y=dummy_root_old.d_y,
z=dummy_root_old.d_z,
r=dummy_root_old.d_r)
section_mapping_table[dummy_root_old] = dummy_root_new
for sectionOld in morphology:
print 'DistToParent', dist_to_parent[sectionOld]
if dist_to_parent[sectionOld] > max_dist_to_parent:
continue
print 'Extruding Section'
old_parent = sectionOld.parent
new_parent = section_mapping_table[old_parent]
section_new = new_parent.create_distal_section(
region=region_mapping_table[sectionOld.region],
x=sectionOld.d_x,
y=sectionOld.d_y,
z=sectionOld.d_z,
r=sectionOld.d_r,
idtag=sectionOld.idtag,
)
section_mapping_table[sectionOld] = section_new
m = MorphologyTree('TrimmedNeuron',
dummysection=dummy_root_new,
metadata={})
return m
def trim_axon_from_morphology(cls, morphology, max_dist_to_parent):
dist_to_parent = SectionVistorFactory.dict_section_proximal_dist_from_soma(morph=morphology, soma_centre=False)()
print sorted(dist_to_parent.values())
section_mapping_table = {}
region_mapping_table = {}
# Create New Regions:
region_mapping_table[None] = None
for rOld in morphology.get_regions():
r_new = Region(name=rOld.name)
region_mapping_table[rOld] = r_new
# Create New Sections:
dummy_root_old = morphology.get_dummy_section()
dummy_root_new = Section(
region=region_mapping_table[dummy_root_old.region],
x=dummy_root_old.d_x,
y=dummy_root_old.d_y,
z=dummy_root_old.d_z,
r=dummy_root_old.d_r)
section_mapping_table[dummy_root_old] = dummy_root_new
for sectionOld in morphology:
print 'DistToParent', dist_to_parent[sectionOld]
if dist_to_parent[sectionOld] > max_dist_to_parent:
continue
print 'Extruding Section'
old_parent = sectionOld.parent
new_parent = section_mapping_table[old_parent]
section_new = new_parent.create_distal_section(
region=region_mapping_table[sectionOld.region],
x=sectionOld.d_x,
y=sectionOld.d_y,
z=sectionOld.d_z,
r=sectionOld.d_r,
idtag=sectionOld.idtag,
)
section_mapping_table[sectionOld] = section_new
m = MorphologyTree('TrimmedNeuron',
dummysection=dummy_root_new, metadata={})
return m
def get_locations_at_distance_away_from_dummy(cls, morphology,
distance, section_predicate=None):
dist_to_section_distal = SectionVistorFactory.dict_section_distal_dist_from_soma(morph=morphology)()
# Section predicates: allows us to generate only on a path, region, etc
section_predicate = section_predicate if section_predicate else lambda s:True
locations = []
for section in morphology:
if not section_predicate(section):
continue
if section.is_a_root_section():
if distance < dist_to_section_distal[section]:
#assert False, 'Not implemented'
locations.append(MorphLocation(section=section, sectionpos=distance/dist_to_section_distal[section]) )
else:
pass
else:
proximal_dist = dist_to_section_distal[section.parent]
distal_dist = dist_to_section_distal[section]
# Does a distance fall on this section:
if proximal_dist < distance < distal_dist:
prop = (distance - proximal_dist) / (distal_dist - proximal_dist)
assert 0.0 <= prop <= 1.0
locations.append(MorphLocation(section=section, sectionpos=prop))
else:
pass
dummy = MorphLocation(morphology.get_dummy_section().children[0], 0.0)
# Some sanity checking:
for loc in locations:
p = MorphPath(loc, dummy)
assert np.fabs(p.get_length() - distance) < 0.01
return locations
