except RuntimeError:
hasErred = 1
print "Too large g!"
if iterg == 1:
nextgs = [0.0, 0.0015, 0.00075]
continue
else:
nextgs = [
nextgs[0], nextgs[2],
nextgs[0] + nextgs[2]
]
continue
times = np.array(h.tvec)
Vsoma = np.array(h.vsoma)
spikes = mytools.spike_times(
times, Vsoma, -50, -50)
nSpikes1 = len(spikes)
hasSpiked = hasSpiked or (nSpikes1 > 0)
if nSpikes1 > 0 and nSpikes1 < minNSpikes:
minNSpikes = nSpikes1
print "iterg=" + str(iterg) + " done, g=" + str(
thisg) + ", " + str(nSpikes1) + " spikes"
if iterg == 0 and nSpikes1 > 0:
print "Even zero g causes spiking!! igene=" + str(
igene) + ", imut=" + str(
imut) + ", iallmutval=" + str(
iallmutval) + ", iter=" + str(
iter) + ", spike at " + str(
spikes[0])
nextgs = [0.0, 0.0, 0.0]
v_init = """ + str(v0) + """
cai0_ca_ion = """ + str(ca0) + """
st1.amp = """ + str(squareAmp) + """
st1.del = 200
st1.dur = """ + str(squareDur) + """
""")
h.init()
h.run()
times = np.array(h.tvec)
Vsoma = np.array(h.vsoma)
close("all")
f, axarr = subplots(2, 1)
axarr[0].plot(times, Vsoma)
axarr[1].plot(times, Vsoma)
spikes = mytools.spike_times(times, Vsoma, -20, -45)
spikes2 = mytools.spike_times(times, Vsoma, -35, 100)
isis = [y - x for x, y in zip(spikes[0:-1], spikes[1:])]
if len(isis) > 0 and mean(isis) != 0:
CVISI = std(isis) / mean(isis) #std is defined in pylab
else:
CVISI = nan #NaN defined in pylab
ispikelastburst = -1
nspikesperbursts = []
nspikesperbursts2 = []
for ispike in range(0, len(isis)):
if isis[ispike] > 1.1 * mean(isis):
nspikesperbursts.append(ispike - ispikelastburst)
ispikelastburst = ispike
if len(nspikesperbursts) >= 2:
h("""
tstop = """+str(tstop)+"""
v_init = """+str(v0)+"""
cai0_ca_ion = """+str(ca0)+"""
st1.amp = """+str(squareAmp)+"""
st1.dur = """+str(squareDur)+"""
""")
h.init()
h.run()
times=np.array(h.tvec)
Vsoma=np.array(h.vsoma)
Vdend=np.array(h.vdend)
Casoma=np.array(h.casoma)
Cadend=np.array(h.cadend)
spikes = mytools.spike_times(times,Vsoma,0,100)
spikfreqs[iI] = sum([1 for x in spikes if x >= 500.0])/3.5
f, axarr = subplots(1, 1)
axarr.plot(times, Vsoma)
axarr.plot(spikes, [1 for x in spikes],'r.')
axarr.set_title("Perisomatic firing, nspikes="+str(len(spikes))+", after 300ms nspikes="+str(sum([1 for x in spikes if x >= 3700.0])))
axarr.set_ylim([-100,40])
axarr.set_xlim([3390,7200])
f.savefig("runcontrols_cs"+str(icell)+"_"+str(iI)+".eps")
if abs(Is[iI]-1.0) < 0.0001:
Vsoma_control = Vsoma
Casoma_control = Casoma
Vdend_control = Vdend
Cadend_control = Cadend
""")
timeStart_dt = time.time()
h.init()
h.run()
print "Simulation done in " + str(
time.time() - timeStart_dt) + " seconds"
times = np.array(h.tvec)
Vsoma = np.array(h.vsoma)
Casoma = np.array(h.casoma)
SKsoma = np.array(h.sksoma)
Vdend = np.array(h.vdend)
Vdend2 = np.array(h.vdend2)
Vdend3 = np.array(h.vdend3)
Cadend3 = np.array(h.cadend3)
SKdend3 = np.array(h.skdend3)
spikes = mytools.spike_times(times, Vsoma, -35, -45)
CasomaupThisIter.append(max(Casoma))
SKsomaupThisIter.append(max(SKsoma))
VdendupThisIter.append(max(Vdend))
Vdend2upThisIter.append(max(Vdend2))
Vdend3upThisIter.append(max(Vdend3))
Cadend3upThisIter.append(max(Cadend3))
SKdend3upThisIter.append(max(SKdend3))
spikesupThisIter.append(spikes[:])
times_tcshort = [2900 + x for x in range(0, 301)]
Vdend3tcupThisIter.append(
mytools.interpolate(times, Vdend3, times_tcshort))
Cadend3tcupThisIter.append(
mytools.interpolate(times, Cadend3, times_tcshort))
cai0_ca_ion = """ + str(ca0) + """
v_init = """ + str(v0) + """
syn1.onset = """ + str(1000) + """
""")
h.init()
try:
h.run()
except RuntimeError:
print "Too large I!"
nextIs = [nextIs[0], nextIs[2], 0.5 * (nextIs[0] + nextIs[2])]
continue
times = np.array(h.tvec)
Vsoma = np.array(h.vsoma)
Vdend = np.array(h.vdend)
nSpikes = len(mytools.spike_times(times, Vsoma, -20, -45))
if iter > 2 and nSpikes > 0:
nextIs = [nextIs[0], nextIs[2], 0.5 * (nextIs[0] + nextIs[2])]
if iter > 2 and nSpikes == 0:
nextIs = [nextIs[2], nextIs[1], 0.5 * (nextIs[2] + nextIs[1])]
print str(nSpikes) + ", nextIs=" + str(nextIs)
Is.append(nextIs[2])
picklelist = [Is, dists, idist]
file = open(
'apicalthresholds_epsp_icell' + str(icell) + '_dist' +
str(dists[idist]) + '.sav', 'w')
pickle.dump(picklelist, file)
file.close()
IsAll.append(Is[:])
