def createMorphoMlFile(fileName, cell):
'''
Convert to new neuroml structures and write
'''
if not muscle_dict.has_key(cell.name):
neuroMlwriter = NeuroMlWriter(fileName, cell.name)
neuroMlwriter.addCell(cell)
neuroMlwriter.writeDocumentToFile()
return
#
# Incomplete code to use the neuroml interface to write the file,
# used for muscles, doesn't produce good enough result on neurons yet.
#
seg0 = cell.segments[0].position
soma = Segment(proximal=cvt_pt(seg0.proximal_point),
distal=cvt_pt(seg0.distal_point))
soma.name = 'Soma'
soma.id = 0
axon_segments = []
for seg1 in cell.segments[1:]:
parent = SegmentParent(segments=seg1.parent)
if seg1.position.proximal_point is None:
p = None
else:
p = cvt_pt(seg1.position.proximal_point)
axon_segment = Segment(proximal = p,
distal = cvt_pt(seg1.position.distal_point),
parent = parent)
axon_segment.id = seg1.id
axon_segment.name = seg1.name
axon_segments.append(axon_segment)
morphology = Morphology()
morphology.segments.append(soma)
morphology.segments += axon_segments
morphology.id = 'morphology_' + cell.name
nml_cell = neuroml_Cell()
nml_cell.id = cell.name
nml_cell.morphology = morphology
doc = NeuroMLDocument()
doc.cells.append(nml_cell)
#addCell(doc, cell)
doc.id = "TestNeuroMLDocument"
writers.NeuroMLWriter.write(doc, "Output/%s.nml" % fileName)
def createMorphoMlFile(fileName, cell):
'''
Convert to new neuroml structures and write
'''
if not muscle_dict.has_key(cell.name):
neuroMlwriter = NeuroMlWriter(fileName, cell.name)
neuroMlwriter.addCell(cell)
neuroMlwriter.writeDocumentToFile()
return
#
# Incomplete code to use the neuroml interface to write the file,
# used for muscles, doesn't produce good enough result on neurons yet.
#
seg0 = cell.segments[0].position
soma = Segment(proximal=cvt_pt(seg0.proximal_point),
distal=cvt_pt(seg0.distal_point))
soma.name = 'Soma'
soma.id = 0
axon_segments = []
for seg1 in cell.segments[1:]:
parent = SegmentParent(segments=seg1.parent)
if seg1.position.proximal_point is None:
p = None
else:
p = cvt_pt(seg1.position.proximal_point)
axon_segment = Segment(proximal=p,
distal=cvt_pt(seg1.position.distal_point),
parent=parent)
axon_segment.id = seg1.id
axon_segment.name = seg1.name
axon_segments.append(axon_segment)
morphology = Morphology()
morphology.segments.append(soma)
morphology.segments += axon_segments
morphology.id = 'morphology_' + cell.name
nml_cell = neuroml_Cell()
nml_cell.id = cell.name
nml_cell.morphology = morphology
doc = NeuroMLDocument()
doc.cells.append(nml_cell)
#addCell(doc, cell)
doc.id = "TestNeuroMLDocument"
writers.NeuroMLWriter.write(doc, "Output/%s.nml" % fileName)
def createMorphoMlFile(fileName, cell):
'''
Convert to new neuroml structures and write
'''
seg0 = cell.segments[0].position
soma = Segment(proximal=cvt_pt(seg0.proximal_point),
distal=cvt_pt(seg0.distal_point))
soma.name = 'Soma'
soma.id = 0
axon_segments = []
for seg1 in cell.segments[1:]:
parent = SegmentParent(segments=seg1.parent)
if seg1.position.distal_point is None:
p = None
else:
p = cvt_pt(seg1.position.distal_point)
axon_segment = Segment(proximal=p,
distal=cvt_pt(seg1.position.distal_point),
parent=parent)
axon_segment.id = seg1.id
axon_segment.name = seg1.name
axon_segments.append(axon_segment)
morphology = Morphology()
morphology.segments.append(soma)
morphology.segments += axon_segments
morphology.id = 'morphology_' + cell.name
nml_cell = neuroml_Cell()
nml_cell.id = cell.name
nml_cell.morphology = morphology
doc = NeuroMLDocument()
#doc.name = "Test neuroML document"
doc.cells.append(nml_cell)
doc.id = fileName
writers.NeuroMLWriter.write(doc, "Output/%s.nml" % fileName)
def createMorphoMlFile(fileName, cell):
'''
Convert to new neuroml structures and write
'''
seg0 = cell.segments[0].position
soma = Segment(proximal=cvt_pt(seg0.proximal_point),
distal=cvt_pt(seg0.distal_point))
soma.name = 'Soma'
soma.id = 0
axon_segments = []
for seg1 in cell.segments[1:]:
parent = SegmentParent(segments=seg1.parent)
if seg1.position.distal_point is None:
p = None
else:
p = cvt_pt(seg1.position.distal_point)
axon_segment = Segment(proximal = p,
distal = cvt_pt(seg1.position.distal_point),
parent = parent)
axon_segment.id = seg1.id
axon_segment.name = seg1.name
axon_segments.append(axon_segment)
morphology = Morphology()
morphology.segments.append(soma)
morphology.segments += axon_segments
morphology.id = 'morphology_' + cell.name
nml_cell = neuroml_Cell()
nml_cell.id = cell.name
nml_cell.morphology = morphology
doc = NeuroMLDocument()
#doc.name = "Test neuroML document"
doc.cells.append(nml_cell)
doc.id = fileName
writers.NeuroMLWriter.write(doc, "Output/%s.nml" % fileName)
def neuroml_single_cell(skeleton_id, nodes, pre, post):
""" Encapsulate a single skeleton into a NeuroML Cell instance.
skeleton_id: the ID of the skeleton to which all nodes belong.
nodes: a dictionary of node ID vs tuple of node parent ID, location as a tuple of 3 floats, and radius. In nanometers.
pre: a dictionary of node ID vs list of connector ID
post: a dictionary of node ID vs list of connector ID
Returns a Cell with id=skeleton_id.
"""
# Collect the children of every node
successors = defaultdict(list) # parent node ID vs list of children node IDs
rootID = None
for nodeID, props in nodes.iteritems():
parentID = props[0]
if not parentID:
rootID = nodeID
continue
successors[parentID].append(nodeID)
# Cache of Point3DWithDiam
points = {}
def asPoint(nodeID):
""" Return the node as a Point3DWithDiam, in micrometers. """
p = points.get(nodeID)
if not p:
props = nodes[nodeID]
radius = props[2]
if radius < 0:
radius = 0.1 # FUTURE Will have to change
loc = props[1]
# Point in micrometers
p = Point3DWithDiam(loc[0] / 1000.0, loc[1] / 1000.0, loc[2] / 1000.0, radius)
points[nodeID] = p
return p
# Starting from the root node, iterate towards the end nodes, adding a segment
# for each parent-child pair.
segments = []
segment_id = 1
todo = [rootID]
# VERY CONFUSINGLY, the Segment.parent is a SegmentParent with the same id as the parent Segment. An unseemly overheady way to reference the parent Segment.
while todo:
nodeID = todo.pop()
children = successors[nodeID]
if not children:
continue
p1 = asPoint(nodeID)
parent = segments[-1] if segments else None
segment_parent = SegmentParent(segments=parent.id) if parent else None
for childID in children:
p2 = asPoint(childID)
segment_id += 1
segment = Segment(proximal=p1, distal=p2, parent=segment_parent)
segment.id = segment_id
segment.name = "%s-%s" % (nodeID, childID)
segments.append(segment)
todo.append(childID)
# Pack the segments into a Cell
morphology = Morphology()
morphology.segments.extend(segments)
morphology.id = "Skeleton #%s" % skeleton_id
# Synapses: TODO requires input from Padraig Gleeson
cell = Cell()
cell.name = 'Cell'
cell.id = skeleton_id
cell.morphology = morphology
return cell
def neuroml_single_cell(skeleton_id, nodes, pre, post):
""" Encapsulate a single skeleton into a NeuroML Cell instance.
skeleton_id: the ID of the skeleton to which all nodes belong.
nodes: a dictionary of node ID vs tuple of node parent ID, location as a tuple of 3 floats, and radius. In nanometers.
pre: a dictionary of node ID vs list of connector ID
post: a dictionary of node ID vs list of connector ID
Returns a Cell with id=skeleton_id.
"""
# Collect the children of every node
successors = defaultdict(
list) # parent node ID vs list of children node IDs
rootID = None
for nodeID, props in nodes.iteritems():
parentID = props[0]
if not parentID:
rootID = nodeID
continue
successors[parentID].append(nodeID)
# Cache of Point3DWithDiam
points = {}
def asPoint(nodeID):
""" Return the node as a Point3DWithDiam, in micrometers. """
p = points.get(nodeID)
if not p:
props = nodes[nodeID]
radius = props[2]
if radius < 0:
radius = 0.1 # FUTURE Will have to change
loc = props[1]
# Point in micrometers
p = Point3DWithDiam(loc[0] / 1000.0, loc[1] / 1000.0,
loc[2] / 1000.0, radius)
points[nodeID] = p
return p
# Starting from the root node, iterate towards the end nodes, adding a segment
# for each parent-child pair.
segments = []
segment_id = 1
todo = [rootID]
# VERY CONFUSINGLY, the Segment.parent is a SegmentParent with the same id as the parent Segment. An unseemly overheady way to reference the parent Segment.
while todo:
nodeID = todo.pop()
children = successors[nodeID]
if not children:
continue
p1 = asPoint(nodeID)
parent = segments[-1] if segments else None
segment_parent = SegmentParent(segments=parent.id) if parent else None
for childID in children:
p2 = asPoint(childID)
segment_id += 1
segment = Segment(proximal=p1, distal=p2, parent=segment_parent)
segment.id = segment_id
segment.name = "%s-%s" % (nodeID, childID)
segments.append(segment)
todo.append(childID)
# Pack the segments into a Cell
morphology = Morphology()
morphology.segments.extend(segments)
morphology.id = "Skeleton #%s" % skeleton_id
# Synapses: TODO requires input from Padraig Gleeson
cell = Cell()
cell.name = 'Cell'
cell.id = skeleton_id
cell.morphology = morphology
return cell
