def run(parameters, sim_list):
sim_time = parameters.sim_time
spike_interval = parameters.spike_interval
stgen = StGen()
seed = parameters.seed
stgen.seed(seed)
model_parameters = ParameterSet({
'system':
parameters.system,
'input_spike_times':
stgen.poisson_generator(1000.0 / spike_interval,
t_stop=sim_time,
array=True),
'cell_type':
parameters.cell.type,
'cell_parameters':
parameters.cell.params,
'plasticity': {
'short_term': None,
'long_term': None
},
'weights':
parameters.weights,
'delays':
parameters.delays,
})
networks = MultiSim(sim_list, SimpleNetwork, model_parameters)
networks.run(sim_time)
spike_data = networks.get_spikes()
vm_data = networks.get_v()
networks.end()
return spike_data, vm_data, model_parameters
def run(parameters, sim_list):
sim_time = parameters.sim_time
spike_interval = parameters.spike_interval
stgen = StGen()
seed = parameters.seed
stgen.seed(seed)
model_parameters = ParameterSet({
'system': parameters.system,
'input_spike_times': stgen.poisson_generator(1000.0/spike_interval, t_stop=sim_time, array=True),
'cell_type': parameters.cell.type,
'cell_parameters': parameters.cell.params,
'plasticity': { 'short_term': None, 'long_term': None },
'weights': parameters.weights,
'delays': parameters.delays,
})
networks = MultiSim(sim_list, SimpleNetwork, model_parameters)
networks.run(sim_time)
spike_data = networks.get_spikes()
vm_data = networks.get_v()
networks.end()
return spike_data, vm_data, model_parameters
from time import time
from pyNN import nest, neuron, pcsim
from pyNN.utility import MultiSim
from NeuroTools.parameters import ParameterSet
from NeuroTools.stgen import StGen
from simple_network import SimpleNetwork
from calc import STDPSynapse
PLOT_FIGURES = True
sim_list = [nest, neuron, pcsim]
sim_time = 200.0
spike_interval = 20.0 # ms
recording_interval = 1.0
stgen = StGen()
seed = int(1e9 * (time() % 1))
stgen.seed(seed)
parameters = ParameterSet({
'system': {
'timestep': 0.01,
'min_delay': 0.1,
'max_delay': 10.0
},
'input_spike_times':
stgen.poisson_generator(rate=1000.0 / spike_interval,
t_stop=sim_time,
array=True),
'trigger_spike_times':
stgen.poisson_generator(rate=1000.0 / spike_interval,
t_stop=sim_time,
array=True),
if my_simulator == 'neuron' or my_simulator == 'nest' :
voltDistr = RandomDistribution('uniform',[-65,-50],rng)
cellsA.randomInit(voltDistr)
cellsB.randomInit(voltDistr)
freq = 150 # Hz
number = int(tstop*freq/1000.0)
print "Number of spikes expected in %d ms at %dHz: %d"%(tstop, freq, number)
from NeuroTools.stgen import StGen
stgen = StGen()
stgen.seed(seed)
spike_times = stgen.poisson_generator(rate=freq, t_stop=tstop, array=True)
input_population = Population(cellNumA, SpikeSourceArray, {'spike_times': spike_times}, label="inputsToA")
for i in input_population:
i.spike_times = stgen.poisson_generator(rate=freq, t_stop=tstop, array=True)
print "spike_times: " +str(i.spike_times)
inputConns = []
for i in range(0,cellNumA):
inputConns.append([i, i, 0.1, 3.0])
