def main():
# For each current value, create a cell
for c in xrange(0,len(amps)):
cells.append(mkgranule(gcid))
g=h.Graph(0)
g.size(0,tstop,-80,50)
g.view(0,-80,tstop,130, (c % 2)*425,(c / 2)*260,400,200) # Position the graphs on screen
addVars(g, c)
graphs.append(g)
stim = h.IClamp(0.5, sec = cells[c].soma)
stim.delay = delay
stim.amp = amps[c]
stim.dur = duration
stims.append(stim)
data.append([])
# For one of the current values, create a closeup of the AP
focusampindex = 1
closedupStartTime = 120 # ms
closedupEndTime = 150 # ms
closeup.size(closedupStartTime,closedupEndTime,-80,50)
closeup.view(closedupStartTime,-80,closedupEndTime-closedupStartTime,130, 850,0,400,200)
addVars(closeup, focusampindex)
initialize()
integrate() # Plot the graphs
def exportNetworkGCs(netFile):
with open(netFile, "r") as file:
nml = file.read()
import re
rx = re.compile(r"Granule_0_(\d*?).cell")
gcids = [int(match) for match in rx.findall(nml)]
cells = {}
for gcid in gcids:
cells.update({ gcid: { 'cell': mkgranule(gcid), 'index': len(cells)} })
exportToNML(cells)
def __main__():
numMitralsToUse = 1
numGranulesPerMitralToExport = 1
numGranulesTotal = numMitralsToUse * numGranulesPerMitralToExport
mitral2granule = {}
import cPickle as pickle
with open('mitral2granule.p', 'rb') as fp1:
mitral2granule.update(pickle.load(fp1))
cells = {}
for mcid in xrange(0, numMitralsToUse):
for gcid in set(mitral2granule[mcid][0:numGranulesPerMitralToExport]):
cells.update({ gcid: { 'cell': mkgranule(gcid), 'index': len(cells)} })
exportToNML(cells)
