%matplotlib widget
import matplotlib.pyplot as plt
import numpy
from tvb.simulator.lab import *
White noise is added to one specific state variable to emulate the external stochastic stimulus p(t) as described in [JansenRit_1995]
jrm = models.JansenRit(mu=numpy.array([0.]), v0=numpy.array([6.]))
phi_n_scaling = (jrm.a * jrm.A * (jrm.p_max-jrm.p_min) * 0.5 )**2 / 2.
sigma = numpy.zeros(6)
sigma[3] = phi_n_scaling
# the other aspects of the simulator are standard
sim = simulator.Simulator(
model=jrm,
connectivity=connectivity.Connectivity.from_file(),
coupling=coupling.SigmoidalJansenRit(a=numpy.array([10.0])),
integrator=integrators.HeunStochastic(dt=2 ** -4, noise=noise.Additive(nsig=sigma)),
monitors=(monitors.TemporalAverage(period=2 ** -2),),
simulation_length=1e3,
).configure()
# run it
(time, data), = sim.run()
# visualize time series
plt.figure()
plt.plot(time, data[:, 0, :, 0], 'k', alpha=0.1)
plt.title("Temporal Average")