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])