This example demonstrates the PoissonGroup object. Here we have used a custom function to generate different rates at different times.
This example also demonstrates a custom SpikeMonitor.
#import brian_no_units # uncomment to run faster
from brian import *
# Rates
r1 = arange(101, 201) * 0.1 * Hz
r2 = arange(1, 101) * 0.1 * Hz
def myrates(t):
if t < 10 * second:
return r1
else:
return r2
# More compact: myrates=lambda t: (t<10*second and r1) or r2
# Neuron group
P = PoissonGroup(100, myrates)
# Calculation of rates
ns = zeros(len(P))
def ratemonitor(spikes):
ns[spikes] += 1
Mf = SpikeMonitor(P, function=ratemonitor)
M = SpikeMonitor(P)
# Simulation and plotting
run(10 * second)
print "Rates after 10s:"
print ns / (10 * second)
ns[:] = 0
run(10 * second)
print "Rates after 20s:"
print ns / (10 * second)
raster_plot()
show()