def run_net(tr):
# prefs.codegen.target = 'numpy'
# prefs.codegen.target = 'cython'
set_device('cpp_standalone',
directory='./builds/%.4d' % (tr.v_idx),
build_on_run=False)
print("Started process with id ", str(tr.v_idx))
T = tr.T1 + tr.T2 + tr.T3
namespace = tr.netw.f_to_dict(short_names=True, fast_access=True)
namespace['idx'] = tr.v_idx
defaultclock.dt = tr.netw.sim.dt
GExc = NeuronGroup(
N=tr.N_e,
model=tr.condlif_sig,
threshold=tr.nrnEE_thrshld,
reset=tr.nrnEE_reset, #method=tr.neuron_method,
namespace=namespace)
GInh = NeuronGroup(
N=tr.N_i,
model=tr.condlif_sig,
threshold='V > Vt',
reset='V=Vr_i', #method=tr.neuron_method,
namespace=namespace)
# set initial thresholds fixed, init. potentials uniformly distrib.
GExc.sigma, GInh.sigma = tr.sigma_e, tr.sigma_i
GExc.Vt, GInh.Vt = tr.Vt_e, tr.Vt_i
GExc.V , GInh.V = np.random.uniform(tr.Vr_e/mV, tr.Vt_e/mV,
size=tr.N_e)*mV, \
np.random.uniform(tr.Vr_i/mV, tr.Vt_i/mV,
size=tr.N_i)*mV
print("need to fix?")
synEE_pre_mod = mod.synEE_pre
synEE_post_mod = mod.synEE_post
if tr.PInp_mode == 'pool':
PInp = PoissonGroup(tr.NPInp, rates=tr.PInp_rate, namespace=namespace)
sPN = Synapses(target=GExc,
source=PInp,
model=tr.poisson_mod,
on_pre='ge_post += a_EPoi',
namespace=namespace)
sPN_src, sPN_tar = generate_connections(N_tar=tr.N_e,
N_src=tr.NPInp,
p=tr.p_EPoi)
elif tr.PInp_mode == 'indep':
PInp = PoissonGroup(tr.N_e, rates=tr.PInp_rate, namespace=namespace)
sPN = Synapses(target=GExc,
source=PInp,
model=tr.poisson_mod,
on_pre='ge_post += a_EPoi',
namespace=namespace)
sPN_src, sPN_tar = range(tr.N_e), range(tr.N_e)
sPN.connect(i=sPN_src, j=sPN_tar)
if tr.PInp_mode == 'pool':
sPNInh = Synapses(target=GInh,
source=PInp,
model=tr.poisson_mod,
on_pre='ge_post += a_EPoi',
namespace=namespace)
sPNInh_src, sPNInh_tar = generate_connections(N_tar=tr.N_i,
N_src=tr.NPInp,
p=tr.p_EPoi)
elif tr.PInp_mode == 'indep':
PInp_inh = PoissonGroup(tr.N_i,
rates=tr.PInp_rate,
namespace=namespace)
sPNInh = Synapses(target=GInh,
source=PInp_inh,
model=tr.poisson_mod,
on_pre='ge_post += a_EPoi',
namespace=namespace)
sPNInh_src, sPNInh_tar = range(tr.N_i), range(tr.N_i)
sPNInh.connect(i=sPNInh_src, j=sPNInh_tar)
if tr.stdp_active:
synEE_pre_mod = '''%s
%s''' % (synEE_pre_mod, mod.synEE_pre_STDP)
synEE_post_mod = '''%s
%s''' % (synEE_post_mod, mod.synEE_post_STDP)
if tr.synEE_rec:
synEE_pre_mod = '''%s
%s''' % (synEE_pre_mod, mod.synEE_pre_rec)
synEE_post_mod = '''%s
%s''' % (synEE_post_mod, mod.synEE_post_rec)
# E<-E advanced synapse model, rest simple
SynEE = Synapses(
target=GExc,
source=GExc,
model=tr.synEE_mod,
on_pre=synEE_pre_mod,
on_post=synEE_post_mod,
#method=tr.synEE_method,
namespace=namespace)
SynIE = Synapses(target=GInh,
source=GExc,
on_pre='ge_post += a_ie',
namespace=namespace)
SynEI = Synapses(target=GExc,
source=GInh,
on_pre='gi_post += a_ei',
namespace=namespace)
SynII = Synapses(target=GInh,
source=GInh,
on_pre='gi_post += a_ii',
namespace=namespace)
if tr.strct_active:
sEE_src, sEE_tar = generate_full_connectivity(tr.N_e, same=True)
SynEE.connect(i=sEE_src, j=sEE_tar)
SynEE.syn_active = 0
else:
srcs_full, tars_full = generate_full_connectivity(tr.N_e, same=True)
SynEE.connect(i=srcs_full, j=tars_full)
SynEE.syn_active = 0
sIE_src, sIE_tar = generate_connections(tr.N_i, tr.N_e, tr.p_ie)
sEI_src, sEI_tar = generate_connections(tr.N_e, tr.N_i, tr.p_ei)
sII_src, sII_tar = generate_connections(tr.N_i, tr.N_i, tr.p_ii, same=True)
SynIE.connect(i=sIE_src, j=sIE_tar)
SynEI.connect(i=sEI_src, j=sEI_tar)
SynII.connect(i=sII_src, j=sII_tar)
tr.f_add_result('sIE_src', sIE_src)
tr.f_add_result('sIE_tar', sIE_tar)
tr.f_add_result('sEI_src', sEI_src)
tr.f_add_result('sEI_tar', sEI_tar)
tr.f_add_result('sII_src', sII_src)
tr.f_add_result('sII_tar', sII_tar)
SynEE.a = tr.a_ee
SynEE.insert_P = tr.insert_P
SynEE.p_inactivate = tr.p_inactivate
# make synapse active at beginning
SynEE.run_regularly(tr.synEE_p_activate, dt=T, when='start', order=-100)
# synaptic scaling
if tr.netw.config.scl_active:
SynEE.summed_updaters['Asum_post']._clock = Clock(
dt=tr.dt_synEE_scaling)
SynEE.run_regularly(tr.synEE_scaling,
dt=tr.dt_synEE_scaling,
when='end')
# intrinsic plasticity
if tr.netw.config.it_active:
GExc.h_ip = tr.h_ip
GExc.run_regularly(tr.intrinsic_mod, dt=tr.it_dt, when='end')
# structural plasticity
if tr.netw.config.strct_active:
if tr.strct_mode == 'zero':
if tr.turnover_rec:
strct_mod = '''%s
%s''' % (tr.strct_mod, tr.turnover_rec_mod)
else:
strct_mod = tr.strct_mod
SynEE.run_regularly(strct_mod, dt=tr.strct_dt, when='end')
elif tr.strct_mode == 'thrs':
if tr.turnover_rec:
strct_mod_thrs = '''%s
%s''' % (tr.strct_mod_thrs,
tr.turnover_rec_mod)
else:
strct_mod_thrs = tr.strct_mod_thrs
SynEE.run_regularly(strct_mod_thrs, dt=tr.strct_dt, when='end')
# -------------- recording ------------------
#run(tr.sim.preT)
GExc_recvars = []
if tr.memtraces_rec:
GExc_recvars.append('V')
if tr.vttraces_rec:
GExc_recvars.append('Vt')
if tr.getraces_rec:
GExc_recvars.append('ge')
if tr.gitraces_rec:
GExc_recvars.append('gi')
GInh_recvars = GExc_recvars
GExc_stat = StateMonitor(GExc,
GExc_recvars,
record=[0, 1, 2],
dt=tr.GExc_stat_dt)
GInh_stat = StateMonitor(GInh,
GInh_recvars,
record=[0, 1, 2],
dt=tr.GInh_stat_dt)
SynEE_recvars = []
if tr.synee_atraces_rec:
SynEE_recvars.append('a')
if tr.synee_Apretraces_rec:
SynEE_recvars.append('Apre')
if tr.synee_Aposttraces_rec:
SynEE_recvars.append('Apost')
SynEE_stat = StateMonitor(SynEE,
SynEE_recvars,
record=range(tr.n_synee_traces_rec),
when='end',
dt=tr.synEE_stat_dt)
GExc_spks = SpikeMonitor(GExc)
GInh_spks = SpikeMonitor(GInh)
PInp_spks = SpikeMonitor(PInp)
GExc_rate = PopulationRateMonitor(GExc)
GInh_rate = PopulationRateMonitor(GInh)
PInp_rate = PopulationRateMonitor(PInp)
SynEE_a = StateMonitor(SynEE, ['a', 'syn_active'],
record=range(tr.N_e * (tr.N_e - 1)),
dt=T / tr.synee_a_nrecpoints,
when='end',
order=100)
if tr.PInp_mode == 'indep':
net = Network(GExc, GInh, PInp, sPN, sPNInh, SynEE, SynEI, SynIE,
SynII, GExc_stat, GInh_stat, SynEE_stat, SynEE_a,
GExc_spks, GInh_spks, PInp_spks, GExc_rate, GInh_rate,
PInp_rate, PInp_inh)
else:
net = Network(GExc, GInh, PInp, sPN, sPNInh, SynEE, SynEI, SynIE,
SynII, GExc_stat, GInh_stat, SynEE_stat, SynEE_a,
GExc_spks, GInh_spks, PInp_spks, GExc_rate, GInh_rate,
PInp_rate)
net.run(tr.sim.T1, report='text')
# SynEE_a.record_single_timestep()
recorders = [
GExc_spks, GInh_spks, PInp_spks, SynEE_stat, GExc_stat, GInh_stat
]
rate_recorders = [GExc_rate, GInh_rate, PInp_rate]
for rcc in recorders:
rcc.active = False
net.run(tr.sim.T2, report='text')
recorders = [
SynEE_stat, GExc_stat, GInh_stat, GExc_rate, GInh_rate, PInp_rate
]
for rcc in recorders:
rcc.active = True
if tr.spks_rec:
GExc_spks.active = True
GInh_spks.active = True
# PInp_spks.active=True
net.run(tr.sim.T3, report='text')
device.build(directory='../builds/%.4d' % (tr.v_idx), clean=True)
# save monitors as raws in build directory
raw_dir = '../builds/%.4d/raw/' % (tr.v_idx)
if not os.path.exists(raw_dir):
os.makedirs(raw_dir)
with open(raw_dir + 'namespace.p', 'wb') as pfile:
pickle.dump(namespace, pfile)
with open(raw_dir + 'gexc_stat.p', 'wb') as pfile:
pickle.dump(GExc_stat.get_states(), pfile)
with open(raw_dir + 'ginh_stat.p', 'wb') as pfile:
pickle.dump(GInh_stat.get_states(), pfile)
with open(raw_dir + 'synee_stat.p', 'wb') as pfile:
pickle.dump(SynEE_stat.get_states(), pfile)
with open(raw_dir + 'synee_a.p', 'wb') as pfile:
pickle.dump(SynEE_a.get_states(), pfile)
with open(raw_dir + 'gexc_spks.p', 'wb') as pfile:
pickle.dump(GExc_spks.get_states(), pfile)
with open(raw_dir + 'ginh_spks.p', 'wb') as pfile:
pickle.dump(GInh_spks.get_states(), pfile)
with open(raw_dir + 'pinp_spks.p', 'wb') as pfile:
pickle.dump(PInp_spks.get_states(), pfile)
with open(raw_dir + 'gexc_rate.p', 'wb') as pfile:
pickle.dump(GExc_rate.get_states(), pfile)
pickle.dump(GExc_rate.smooth_rate(width=25 * ms), pfile)
with open(raw_dir + 'ginh_rate.p', 'wb') as pfile:
pickle.dump(GInh_rate.get_states(), pfile)
pickle.dump(GInh_rate.smooth_rate(width=25 * ms), pfile)
with open(raw_dir + 'pinp_rate.p', 'wb') as pfile:
pickle.dump(PInp_rate.get_states(), pfile)
pickle.dump(PInp_rate.smooth_rate(width=25 * ms), pfile)
# ----------------- add raw data ------------------------
fpath = '../builds/%.4d/' % (tr.v_idx)
from pathlib import Path
Path(fpath + 'turnover').touch()
turnover_data = np.genfromtxt(fpath + 'turnover', delimiter=',')
os.remove(fpath + 'turnover')
with open(raw_dir + 'turnover.p', 'wb') as pfile:
pickle.dump(turnover_data, pfile)
Path(fpath + 'spk_register').touch()
spk_register_data = np.genfromtxt(fpath + 'spk_register', delimiter=',')
os.remove(fpath + 'spk_register')
with open(raw_dir + 'spk_register.p', 'wb') as pfile:
pickle.dump(spk_register_data, pfile)
def test_ExportDevice_basic():
"""
Test the components and structure of the dictionary exported
by ExportDevice
"""
start_scope()
set_device('exporter')
grp = NeuronGroup(10,
'dv/dt = (1-v)/tau :1',
method='exact',
threshold='v > 0.5',
reset='v = 0',
refractory=2 * ms)
tau = 10 * ms
rate = '1/tau'
grp.v['i > 2 and i < 5'] = -0.2
pgrp = PoissonGroup(10, rates=rate)
smon = SpikeMonitor(pgrp)
smon.active = False
netobj = Network(grp, pgrp, smon)
netobj.run(100 * ms)
dev_dict = device.runs
# check the structure and components in dev_dict
assert dev_dict[0]['duration'] == 100 * ms
assert dev_dict[0]['inactive'][0] == smon.name
components = dev_dict[0]['components']
assert components['spikemonitor'][0]
assert components['poissongroup'][0]
assert components['neurongroup'][0]
initializers = dev_dict[0]['initializers_connectors']
assert initializers[0]['source'] == grp.name
assert initializers[0]['variable'] == 'v'
assert initializers[0]['index'] == 'i > 2 and i < 5'
# TODO: why not a Quantity type?
assert initializers[0]['value'] == '-0.2'
with pytest.raises(KeyError):
initializers[0]['identifiers']
device.reinit()
start_scope()
set_device('exporter', build_on_run=False)
tau = 10 * ms
v0 = -70 * mV
vth = 800 * mV
grp = NeuronGroup(10,
'dv/dt = (v0-v)/tau :volt',
method='exact',
threshold='v > vth',
reset='v = v0',
refractory=2 * ms)
v0 = -80 * mV
grp.v[:] = 'v0 + 2 * mV'
smon = StateMonitor(grp, 'v', record=True)
smon.active = False
net = Network(grp, smon)
net.run(10 * ms) # first run
v0 = -75 * mV
grp.v[3:8] = list(range(3, 8)) * mV
smon.active = True
net.run(20 * ms) # second run
v_new = -5 * mV
grp.v['i >= 5'] = 'v0 + v_new'
v_new = -10 * mV
grp.v['i < 5'] = 'v0 - v_new'
spikemon = SpikeMonitor(grp)
net.add(spikemon)
net.run(5 * ms) # third run
dev_dict = device.runs
# check run1
assert dev_dict[0]['duration'] == 10 * ms
assert dev_dict[0]['inactive'][0] == smon.name
components = dev_dict[0]['components']
assert components['statemonitor'][0]
assert components['neurongroup'][0]
initializers = dev_dict[0]['initializers_connectors']
assert initializers[0]['source'] == grp.name
assert initializers[0]['variable'] == 'v'
assert initializers[0]['index']
assert initializers[0]['value'] == 'v0 + 2 * mV'
assert initializers[0]['identifiers']['v0'] == -80 * mV
with pytest.raises(KeyError):
initializers[0]['identifiers']['mV']
# check run2
assert dev_dict[1]['duration'] == 20 * ms
initializers = dev_dict[1]['initializers_connectors']
assert initializers[0]['source'] == grp.name
assert initializers[0]['variable'] == 'v'
assert (initializers[0]['index'] == grp.indices[slice(3, 8, None)]).all()
assert (initializers[0]['value'] == list(range(3, 8)) * mV).all()
with pytest.raises(KeyError):
dev_dict[1]['inactive']
initializers[1]['identifiers']
# check run3
assert dev_dict[2]['duration'] == 5 * ms
with pytest.raises(KeyError):
dev_dict[2]['inactive']
assert dev_dict[2]['components']['spikemonitor']
initializers = dev_dict[2]['initializers_connectors']
assert initializers[0]['source'] == grp.name
assert initializers[0]['variable'] == 'v'
assert initializers[0]['index'] == 'i >= 5'
assert initializers[0]['value'] == 'v0 + v_new'
assert initializers[0]['identifiers']['v0'] == -75 * mV
assert initializers[0]['identifiers']['v_new'] == -5 * mV
assert initializers[1]['index'] == 'i < 5'
assert initializers[1]['value'] == 'v0 - v_new'
assert initializers[1]['identifiers']['v_new'] == -10 * mV
with pytest.raises(IndexError):
initializers[2]
dev_dict[3]
device.reinit()
