def convert_morphology(root, positions='auto'):
"""Convert moose neuron morphology contained under `root` into a
NeuroML object. The id of the return object is
{root.name}_morphology. Each segment object gets the numeric value
of the moose id of the object. The name of the segments are same
as the corresponding moose compartment.
Parameters
----------
root : a moose element containing a single cell model.
positions : string
flag to indicate if the positions of the end points of the
compartments are explicitly available in the compartments or
should be automatically generated. Possible values:
`auto` - automatically generate z coordinates using length of the
compartments.
`explicit` - model has explicit coordinates for all compartments.
Return
------
a neuroml.Morphology instance.
"""
if positions == 'auto':
queue = deque([autoposition(root)])
elif positions == 'explicit':
compartments = moose.wildcardFind('%s/##[TYPE=Compartment]' % (root.path))
queue = deque([compartment for compartment in map(moose.element, compartments)
if len(compartment.neighbours['axial']) == 0])
if len(queue) != 1:
raise Exception('There must be one and only one top level compartment. Found %d' % (len(topcomp_list)))
else:
raise Exception('allowed values for keyword argument positions=`auto` or `explicit`')
comp_seg = {}
parent = None
while len(queue) > 0:
compartment = queue.popleft()
proximal = neuroml.Point3DWithDiam(x=compartment.x0,
y=compartment.y0,
z=compartment.z0,
diameter=compartment.diameter)
distal = neuroml.Point3DWithDiam(x=compartment.x,
y=compartment.y,
z=compartment.z,
diameter=compartment.diameter)
plist = list(map(moose.element, compartment.neighbours['axial']))
try:
parent = neuroml.SegmentParent(segments=comp_seg[moose.element(plist[0])].id)
except (KeyError, IndexError) as e:
parent = None
segment = neuroml.Segment(id=compartment.id_.value,
proximal=proximal,
distal=distal,
parent=parent)
# TODO: For the time being using numerical value of the moose
# id for neuroml id.This needs to be updated for handling
# array elements
segment.name = compartment.name
comp_seg[compartment] = segment
queue.extend([comp for comp in map(moose.element, compartment.neighbours['raxial'])])
morph = neuroml.Morphology(id='%s_morphology' % (root.name))
morph.segments.extend(comp_seg.values())
return morph
def convert_morphology(root, positions='auto'):
"""Convert moose neuron morphology contained under `root` into a
NeuroML object. The id of the return object is
{root.name}_morphology. Each segment object gets the numeric value
of the moose id of the object. The name of the segments are same
as the corresponding moose compartment.
Parameters
----------
root : a moose element containing a single cell model.
positions : string
flag to indicate if the positions of the end points of the
compartments are explicitly available in the compartments or
should be automatically generated. Possible values:
`auto` - automatically generate z coordinates using length of the
compartments.
`explicit` - model has explicit coordinates for all compartments.
Return
------
a neuroml.Morphology instance.
"""
if positions == 'auto':
queue = deque([autoposition(root)])
elif positions == 'explicit':
compartments = moose.wildcardFind('%s/##[TYPE=Compartment]' % (root.path))
queue = deque([compartment for compartment in map(moose.element, compartments)
if len(compartment.neighbours['axial']) == 0])
if len(queue) != 1:
raise Exception('There must be one and only one top level compartment. Found %d' % (len(topcomp_list)))
else:
raise Exception('allowed values for keyword argument positions=`auto` or `explicit`')
comp_seg = {}
parent = None
while len(queue) > 0:
compartment = queue.popleft()
proximal = neuroml.Point3DWithDiam(x=compartment.x0,
y=compartment.y0,
z=compartment.z0,
diameter=compartment.diameter)
distal = neuroml.Point3DWithDiam(x=compartment.x,
y=compartment.y,
z=compartment.z,
diameter=compartment.diameter)
plist = list(map(moose.element, compartment.neighbours['axial']))
try:
parent = neuroml.SegmentParent(segments=comp_seg[moose.element(plist[0])].id)
except (KeyError, IndexError) as e:
parent = None
segment = neuroml.Segment(id=compartment.id_.value,
proximal=proximal,
distal=distal,
parent=parent)
# TODO: For the time being using numerical value of the moose
# id for neuroml id.This needs to be updated for handling
# array elements
segment.name = compartment.name
comp_seg[compartment] = segment
queue.extend([comp for comp in map(moose.element, compartment.neighbours['raxial'])])
morph = neuroml.Morphology(id='%s_morphology' % (root.name))
morph.segments.extend(comp_seg.values())
return morph