"""
Simple network, using only the low-level interface, with a Poisson spike source
projecting to a pair of IF_curr_alpha neurons.
Andrew Davison, UNIC, CNRS
August 2006
"""
import numpy
from pyNN.utility import get_script_args
simulator_name = get_script_args(1)[0]
exec("from pyNN.%s import *" % simulator_name)
tstop = 1000.0 # all times in milliseconds
rate = 100.0 # spikes/s
setup(timestep=0.1,min_delay=0.2)
cell_params = {'tau_refrac':2.0, 'v_thresh':-50.0, 'tau_syn_E':2.0, 'tau_syn_I' : 4.0}
ifcell1 = create(IF_curr_alpha, cell_params)
ifcell2 = create(IF_curr_alpha, cell_params)
number = int(2*tstop*rate/1000.0)
numpy.random.seed(637645386)
spike_times = numpy.add.accumulate(numpy.random.exponential(1000.0/rate, size=number))
assert spike_times.max() > tstop
spike_source = create(SpikeSourceArray, {'spike_times': spike_times })
conn1 = connect(spike_source, ifcell1, weight=1.0)
conn2 = connect(spike_source, ifcell2, weight=1.0)
record_v(ifcell1+ifcell2, "Results/simpleNetworkL_%s.v" % simulator_name)
run(tstop)
end()
