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# arrange for InputPreSyn to be on queue after finitialize
from neuron import h
pc = h.ParallelContext()
def sortspikes(spiketime, gidvec):
return sorted(zip(spiketime, gidvec))
def test_inputpresyn():
# NetStim with gid = 1 connected to IntFire1 with gid = 2
# sadly IntFire1 does not exist in coreneuron so use IntervalFire
# make cells
nstim = 3
ncell = 15
cells = {gid: None for gid in range(pc.id(), ncell, pc.nhost())}
for gid in cells:
pc.set_gid2node(gid, pc.id())
cells[gid] = h.NetStim() if gid < nstim else h.IntervalFire()
pc.cell(gid, h.NetCon(cells[gid], None))
# connect
netcons = {}
for gid in cells:
if gid >= nstim:
for srcgid in range(nstim):
netcons[(srcgid, gid)] = nc = pc.gid_connect(srcgid, cells[gid])
nc.delay = 1
nc.weight[0] = 2
else: # The NetStim
ns = cells[gid]
ns.start = 0
ns.number = 1
ns.interval = 10
# does it look like what we want?
if False:
for gid in cells:
print(pc.id(), gid, cells[gid])
for con in netcons:
print(pc.id(), con)
spiketime = h.Vector()
gidvec = h.Vector()
pc.spike_record(-1, spiketime, gidvec)
def run(tstop):
spiketime.resize(0)
gidvec.resize(0)
pc.set_maxstep(10)
h.finitialize()
pc.psolve(tstop)
run(2)
spikes_std = sortspikes(spiketime, gidvec)
def same():
spikes = sortspikes(spiketime, gidvec)
assert spikes_std == spikes
h.CVode().cache_efficient(1)
from neuron import coreneuron
coreneuron.enable = 1
coreneuron.verbose = 0
run(2)
same()
pc.barrier()
if __name__ == "__main__":
test_inputpresyn()
if pc.nhost() > 1:
pc.barrier()
h.quit()
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