def test_SetDefaults(self):
"""SetDefaults"""
m = "sample_neuron"
cynest.ResetKernel()
cynest.SetDefaults(m, {'V_m': -1.})
self.assertEqual(cynest.GetDefaults(m)['V_m'], -1.)
try:
cynest.SetDefaults(m, {'DUMMY': 0})
except:
info = sys.exc_info()[1]
if not "DictError" in info.__str__():
self.fail('wrong error message')
def build(self):
nest.ResetKernel()
nest.SetKernelStatus({'local_num_threads': self.n_threads})
if self.params:
nest.SetDefaults(self.model,self.params)
self.neuron=nest.Create(self.model,self.n_neurons)
self.noise=nest.Create('noise_generator')
self.spike=nest.Create('spike_detector')
nest.SetStatus(self.spike,[{'to_memory':True, 'to_file':False}])
def test_ModelCreateSimulate(self):
"""Model Creation and Simulation"""
cynest.ResetKernel()
cynest.SetDefaults("sample_neuron", {"param": 20})
node = cynest.Create("sample_neuron")
cynest.Simulate(1)
self.assertEqual(cynest.GetStatus(node)[0]["param"], 30)
del tmp
P = a * weight * pylab.convolve(gauss, psp)
l = len(P)
t_P = convolution_resolution * numpy.linspace(
-l / 2., l / 2., l) + pulsetime + 1. # one ms delay
#########################################################################
# simulation section
nest.ResetKernel()
nest.SetStatus([0], [{'resolution': simulation_resolution}])
J = Cm * weight / tau_s * fudge
nest.SetDefaults('static_synapse', {'weight': J})
n = nest.Create(
'iaf_psc_alpha', n_neurons, {
'V_th': Vth,
'tau_m': tau_m,
'tau_syn_ex': tau_s,
'C_m': Cm,
'E_L': V0,
'V_reset': V0,
'V_m': V0
})
pp = nest.Create('pulsepacket_generator', n_neurons, {
'pulse_times': [pulsetime],
'activity': a,
'sdev': sdev
# set neuron parameters:
neuron_param = {
"tau_m": Tau,
"t_ref": TauR,
"tau_syn_ex": Tau_psc,
"tau_syn_in": Tau_psc,
"C_m": C,
"V_reset": U0,
"E_L": U0,
"V_m": U0,
"V_th": Theta
}
# set defaults of desired neuron type with chosen parameters:
nest.SetDefaults("iaf_psc_exp", neuron_param)
# create two neurons of desired type:
neurons = nest.Create("iaf_psc_exp", 2)
# set properties of dc:
nest.SetDefaults("dc_generator", {
"amplitude": I0,
"start": TIstart,
"stop": TIend
})
# create dc_generator:
dc_gen = nest.Create("dc_generator")
# set properties of voltmeter:
import cynest as nest
import cynest.voltage_trace
nest.ResetKernel()
#Parameter set for depression
dep_params = {"U": 0.67, "weight": 250.}
# parameter set for facilitation
fac_params = {"U": 0.1, "tau_fac": 1000., "tau_rec": 100., "weight": 250.}
# Here we assign the parameter set to the synapse models
t1_params = fac_params # for tsodyks_synapse
t2_params = t1_params.copy() # for tsodyks2_synapse
nest.SetDefaults("tsodyks_synapse", t1_params)
nest.SetDefaults("tsodyks2_synapse", t2_params)
nest.SetDefaults("iaf_psc_exp", {"tau_syn_ex": 3.})
neuron = nest.Create("iaf_psc_exp", 3)
nest.Connect([neuron[0]], [neuron[1]], model="tsodyks_synapse")
nest.Connect([neuron[0]], [neuron[2]], model="tsodyks2_synapse")
voltmeter = nest.Create("voltmeter", 2)
nest.SetStatus(voltmeter, {"withgid": True, "withtime": True})
nest.Connect([voltmeter[0]], [neuron[1]])
nest.Connect([voltmeter[1]], [neuron[2]])
nest.SetStatus([neuron[0]], "I_e", 376.0)
nest.Simulate(500.0)
nest.SetStatus([neuron[0]], "I_e", 0.0)
nest.SetKernelStatus({"resolution": dt, "print_time": True})
print("Building network")
neuron_params = {
"C_m": 1.0,
"tau_m": tauMem,
"t_ref": 2.0,
"E_L": 0.0,
"V_reset": 0.0,
"V_m": 0.0,
"V_th": theta
}
nest.SetDefaults("iaf_psc_delta", neuron_params)
nodes_ex = nest.Create("iaf_psc_delta", NE)
nodes_in = nest.Create("iaf_psc_delta", NI)
nest.SetDefaults("poisson_generator", {"rate": p_rate})
noise = nest.Create("poisson_generator")
espikes = nest.Create("spike_detector")
ispikes = nest.Create("spike_detector")
nest.SetStatus([espikes], [{
"label": "brunel-py-ex",
"withtime": True,
"withgid": True
}])