def setUp(self):
sim.setup()
self.p1 = sim.Population(7, sim.IF_cond_exp())
self.p2 = sim.Population(4, sim.IF_cond_exp())
self.p3 = sim.Population(5, sim.IF_curr_alpha())
self.syn1 = sim.StaticSynapse(weight=0.123, delay=0.5)
self.syn2 = sim.StaticSynapse(weight=0.456, delay=0.4)
self.random_connect = sim.FixedNumberPostConnector(n=2)
self.all2all = sim.AllToAllConnector()
from pyNN.utility.plotting import Figure, Panel
t_stop = 100000
dt = 0.1
sim.setup(timestep=dt)
cell_parameters = {
'v_reset': 10.0,
'tau_m': 20.0,
'v_rest': 0.0,
'tau_refrac': 2.0,
'v_thresh': 20.0,
'tau_syn_E': 2.0
}
p = sim.Population(1, sim.IF_curr_alpha(**cell_parameters))
p.initialize(v=0.0)
rate = 20
stim = sim.Population(
1,
nineml_cell_type('Poisson',
read("../sources/Poisson.xml")['Poisson'], {})(rate=rate))
stim.initialize(t_next=numpy.random.exponential(1000 / rate))
weight = 0.1
delay = 0.5
prj = sim.Projection(stim,
p,
sim.AllToAllConnector(),
sim.StaticSynapse(weight=weight, delay=delay),
eta = 2.0 # nu_ext / nu_thresh
Je = J # excitatory weights
Ji = -g * Je # inhibitory weights
Jext = Je # external weights
theta = 20.0 # firing thresholds
tau = 20.0 # membrane time constant
tau_syn = 0.5 # synapse time constant
nu_thresh = theta * v2i / (Je * Ce * tau * exp(1.0) * tau_syn) # threshold rate
nu_ext = eta * nu_thresh # external rate per synapse
input_rate = 1000.0 * nu_ext # mean input spiking rate
v_init = RandomDistribution("uniform", (theta/2, theta), rng=NumpyRNG(seed=79845634))
sim.setup()
celltype = sim.IF_curr_alpha(tau_m=tau, v_thresh=theta,
tau_refrac=2.0, v_reset=10.0,
v_rest=0.0, cm=tau/1.5,
tau_syn_E=tau_syn, tau_syn_I=tau_syn)
ext_stim = sim.SpikeSourcePoisson(rate=input_rate)
exc_cells = sim.Population(Ne, celltype, initial_values={'v': v_init}, label="Exc")
inh_cells = sim.Population(Ni, celltype, initial_values={'v': v_init}, label="Inh")
external = sim.Population(int(Cext), ext_stim, label="Ext")
all_cells = exc_cells + inh_cells
all_to_all = sim.AllToAllConnector(callback=ProgressBar())
random_uniform = sim.FixedProbabilityConnector(p_connect=epsilon, callback=ProgressBar())
static_ext = sim.StaticSynapse(delay=delay, weight=Jext)
static_exc = sim.StaticSynapse(delay=delay, weight=Je)