def __main__():
import customsim
import modeldata
MCs = 1
GCsPerMC = 1
networkTemplate = FileTemplate("../NeuroML2/Networks/NetworkTemplate.xml")
includeTemplate = FileTemplate("../NeuroML2/Networks/IncludeTemplate.xml")
populationTemplate = FileTemplate("../NeuroML2/Networks/PopulationTemplate.xml")
projectionTemplate = FileTemplate("../NeuroML2/Networks/ProjectionTemplate.xml")
customsim.setup(MCs, GCsPerMC)
model = modeldata.getmodel()
netFile = "../NeuroML2/Networks/Bulb_%iMC_%iGC.net.nml" % (len(model.mitral_gids), len(model.granule_gids))
includes = ""
populations = ""
projections = ""
mcNMLs = {}
gcNMLs = {}
#import pydevd
#pydevd.settrace('10.211.55.3', port=4200, stdoutToServer=True, stderrToServer=True)
# Make MC includes and populations
for mcgid in model.mitral_gids:
includes += includeTemplate.text\
.replace("[CellType]", "Mitral")\
.replace("[GID]", `mcgid`)
populations += populationTemplate.text\
.replace("[CellType]", "Mitral")\
.replace("[GID]", `mcgid`)\
.replace("[X]", `model.mitrals[mcgid].x`)\
.replace("[Y]", `model.mitrals[mcgid].y`)\
.replace("[Z]", `model.mitrals[mcgid].z`)
# Retain mitral cell NML
mcNML = pynml\
.read_neuroml2_file("../NeuroML2/MitralCells/Exported/Mitral_0_%i.cell.nml" % mcgid)\
.cells[0]
mcNMLs.update({mcgid:mcNML})
# Make GC includes and populations
import granules
from neuroml.nml.nml import NeuroMLDocument
for gcgid in model.granule_gids:
includes += includeTemplate.text\
.replace("[CellType]", "Granule")\
.replace("[GID]", `gcgid`)
populations += populationTemplate.text\
.replace("[CellType]", "Granule")\
.replace("[GID]", `gcgid`)\
.replace("[X]", `granules.gid2pos[gcgid][0]`)\
.replace("[Y]", `granules.gid2pos[gcgid][1]`)\
.replace("[Z]", `granules.gid2pos[gcgid][2]`)
# Retain granule cell NML
gcNML = pynml\
.read_neuroml2_file("../NeuroML2/GranuleCells/Exported/Granule_0_%i.cell.nml" % gcgid)\
gcNMLs.update({gcgid:gcNML})
# Add a projection for each synapse
synCount = len(model.mgrss.keys())
curSyn = 0
for sgid in model.mgrss.keys():
print('Building synapse %i of %i' % (curSyn+1,synCount))
synapse = model.mgrss[sgid]
nsecden = model.mitrals[synapse.mgid].secden[synapse.isec].nseg
secdenIndex = min(nsecden-1, int(synapse.xm * nsecden))
postSegmentId = [seg.id\
for seg in mcNMLs[synapse.mgid].morphology.segments\
if seg.name == "Seg%i_secden_%i"%(secdenIndex,synapse.isec)\
][0]
gcNML = gcNMLs[synapse.ggid].cells[0]
# Position the spine along the GC priden
import exportHelper
exportHelper.splitSegmentAlongFraction(gcNML,"Seg0_priden2_0","priden2_0",synapse.xg,'Seg0_neck')
pynml.write_neuroml2_file(gcNMLs[synapse.ggid], "../NeuroML2/GranuleCells/Exported/Granule_0_%i.cell.nml" % synapse.ggid)
# Add Dendro-dendritic synapses
# GC -> MC part
projections += projectionTemplate.text\
.replace("[ProjectionID]", `sgid`+'_G2M')\
.replace("[PreCellType]", "Granule")\
.replace("[PreGID]", `synapse.ggid`)\
.replace("[PreSegment]", `4`)\
.replace("[PreAlong]", `0.5`)\
.replace("[PostCellType]", "Mitral")\
.replace("[PostGID]", `synapse.mgid`)\
.replace("[PostSegment]", `postSegmentId`)\
.replace("[PostAlong]", "0.5")\
.replace("[Synapse]", "FIsyn")\
# MC -> GC part
projections += projectionTemplate.text\
.replace("[ProjectionID]", `sgid`+'_M2G')\
.replace("[PreCellType]", "Mitral")\
.replace("[PreGID]", `synapse.mgid`)\
.replace("[PreSegment]", `postSegmentId`)\
.replace("[PreAlong]", `0.5`)\
.replace("[PostCellType]", "Granule")\
.replace("[PostGID]", `synapse.ggid`)\
.replace("[PostSegment]", `4`)\
.replace("[PostAlong]", "0.5")\
.replace("[Synapse]", "AmpaNmdaSyn")\
curSyn += 1
network = networkTemplate.text\
.replace("[IncludesPlaceholder]", includes)\
.replace("[PopulationsPlaceholder]", populations)\
.replace("[ProjectionsPlaceholder]", projections)
with open(netFile, "w") as file:
file.write(network)
print('Net file saved to: ' + netFile)
def exportToNML(cells):
nml_net_file = "../NeuroML2/GranuleCells/Exported/GCnet%iG.net.nml" % len(cells)
export_to_neuroml2(None,
nml_net_file,
includeBiophysicalProperties=False,
separateCellFiles=True)
# Rename files so their cell GIDs are preserved
for gcid in cells.keys():
fileId = cells[gcid]['index']
oldFile = '../NeuroML2/GranuleCells/Exported/Granule_0_%i.cell.nml' % fileId
newFile = '../NeuroML2/GranuleCells/Exported/Granule_0_%i.cell.nml_TEMP' % gcid
# Using TEMP files to avoid naming conflicts
os.rename(oldFile, newFile)
# Remove temp files after all have been renamed
for gcid in cells.keys():
oldFile = '../NeuroML2/GranuleCells/Exported/Granule_0_%i.cell.nml_TEMP' % gcid
newFile = '../NeuroML2/GranuleCells/Exported/Granule_0_%i.cell.nml' % gcid
os.rename(oldFile, newFile)
for gcid in cells.keys():
cell, nml_doc, nml_cell_file = readGCnml(gcid)
print("Loaded GC cell %i with %i segments"%(gcid, len(cell.morphology.segments)))
# Change cell ID to preserve GCID
cell.id = "Granule_0_%i" % gcid
# Change segment ids to start at 0 and increment
exportHelper.resetRoot(cell)
# Replace ModelViewParmSubset_N groups with all, axon, soma, dendrite groups
buildStandardSegmentGroups(cell)
# Add channel placeholders
nml_doc.includes.append(neuroml.IncludeType(href="channelIncludesPLACEHOLDER"))
cell.biophysical_properties = neuroml.BiophysicalProperties(id="biophysPLACEHOLDER")
cell.morphology.segments.append(neuroml.Segment(id="spinePLACEHOLDER"))
# Save the new NML
pynml.write_neuroml2_file(nml_doc, nml_cell_file)
# Replace placeholders with contents from GranuleCell...xml files
replaceChannelPlaceholders(nml_cell_file)
cell, nml_doc, nml_cell_file = readGCnml(gcid)
# Fix the fractionAlong parent segment bug ( https://github.com/NeuroML/org.neuroml.export/issues/46 )
exportHelper.splitSegmentAlongFraction(cell, "Seg0_priden", "priden", 0.8, "Seg0_priden2_0")
# Orient cell along the versor
versor = granules.granule_position_orientation(gcid)[1]
for seg in cell.morphology.segments:
segLength = seg.length
if seg.parent is not None:
parentDistal = [parent for parent in cell.morphology.segments if parent.id == seg.parent.segments][0].distal
seg.proximal.x = parentDistal.x
seg.proximal.y = parentDistal.y
seg.proximal.z = parentDistal.z
seg.distal = setAlongVersor(seg.distal, versor, seg.proximal, segLength)
# Make sure spine is in the all group
[group for group in cell.morphology.segment_groups if group.id == 'all'][0]\
.includes\
.append(neuroml.Include(segment_groups='spine_group'))\
# and Dendrite group
[group for group in cell.morphology.segment_groups if group.id == 'dendrite_group'][0]\
.includes\
.append(neuroml.Include(segment_groups='spine_group'))
# Save orientation
pynml.write_neuroml2_file(nml_doc, nml_cell_file)
print(nml_cell_file)
