def do_all_constraint(self):
synfire_run = SynfireRunner()
synfire_run.do_run(n_neurons, neurons_per_core=neurons_per_core,
delay=delay, run_times=[runtime],
placement_constraint=placement_constraint,
record=True, record_7=True, record_v=True,
record_v_7=True, record_gsyn_exc=True,
record_gsyn_exc_7=True, record_gsyn_inh=False)
gsyn_exc = synfire_run.get_output_pop_gsyn_exc_numpy()
v = synfire_run.get_output_pop_voltage_numpy()
spikes = synfire_run.get_output_pop_spikes_numpy()
self.assertEqual(n_neurons * runtime, len(gsyn_exc))
read_gsyn = numpy.loadtxt(gysn_file, delimiter=',')
self.assertTrue(numpy.allclose(read_gsyn, gsyn_exc, rtol=1e-04),
"gsyn neo method mismatch")
self.assertEqual(n_neurons * runtime, len(v))
read_v = numpy.loadtxt(v_file, delimiter=',')
self.assertTrue(numpy.allclose(read_v, v, rtol=1e-03),
"v neo method mismatch")
self.assertEqual(expected_spikes, len(spikes))
spike_checker.synfire_spike_checker(spikes, n_neurons)
read_spikes = numpy.loadtxt(spike_file, delimiter=',')
self.assertTrue(numpy.allclose(read_spikes, spikes),
"spikes neo method mismatch")
def do_spikes_no_constraint(self):
synfire_run = SynfireRunner()
synfire_run.do_run(n_neurons, neurons_per_core=neurons_per_core,
delay=delay, run_times=[runtime], record=True,
record_v=False, record_gsyn_exc_7=False,
record_gsyn_inh=False)
spikes = synfire_run.get_output_pop_spikes_numpy()
self.assertEqual(expected_spikes, len(spikes))
spike_checker.synfire_spike_checker(spikes, n_neurons)
read_spikes = numpy.loadtxt(spike_file, delimiter=',')
self.assertTrue(numpy.allclose(read_spikes, spikes),
"spikes neo method mismatch")
def test_all_no_constarint(self):
synfire_run = SynfireRunner()
synfire_run.do_run(n_neurons,
neurons_per_core=neurons_per_core,
delay=delay,
run_times=[runtime],
record=True,
record_7=True,
record_v=True,
record_v_7=True,
record_gsyn_exc=True,
record_gsyn_exc_7=True,
record_gsyn_inh=False)
gsyn_exc_7 = synfire_run.get_output_pop_gsyn_exc_7()
v_7 = synfire_run.get_output_pop_voltage_7()
spikes_7 = synfire_run.get_output_pop_spikes_7()
gsyn_exc = synfire_run.get_output_pop_gsyn_exc_numpy()
v = synfire_run.get_output_pop_voltage_numpy()
spikes = synfire_run.get_output_pop_spikes_numpy()
self.assertEquals(n_neurons * runtime, len(gsyn_exc))
read_gsyn = numpy.loadtxt(gysn_file, delimiter=',')
if not numpy.allclose(read_gsyn, gsyn_exc_7):
for g1, g2 in zip(read_gsyn, gsyn_exc_7):
if not numpy.allclose(g1, g2, rtol=1e-04):
print(g1, g2, g1[2] - g2[2], (g1[2] - g2[2]) / g1[2])
self.assertTrue(numpy.allclose(read_gsyn, gsyn_exc_7, rtol=1e-04),
"gsyn synakker method mismatch")
self.assertTrue(numpy.allclose(read_gsyn, gsyn_exc, rtol=1e-04),
"gsyn neo method mismatch")
self.assertEquals(n_neurons * runtime, len(v))
read_v = numpy.loadtxt(v_file, delimiter=',')
self.assertTrue(numpy.allclose(read_v, v_7, rtol=1e-03),
"v synakker method mismatch")
self.assertTrue(numpy.allclose(read_v, v, rtol=1e-03),
"v neo method mismatch")
self.assertEquals(expected_spikes, len(spikes))
spike_checker.synfire_spike_checker(spikes, n_neurons)
read_spikes = numpy.loadtxt(spike_file, delimiter=',')
self.assertTrue(numpy.allclose(read_spikes, spikes_7),
"spikes synakker method mismatch")
self.assertTrue(numpy.allclose(read_spikes, spikes),
"spikes neo method mismatch")
def do_run(seed=None):
# Simulate using both simulators
synfire_run = SynfireRunner()
synfire_run.do_run(
n_neurons=1, input_class=SpikeSourcePoisson, rate=noise_rate,
start_time=0, duration=simtime, seed=seed,
use_spike_connections=False,
cell_params=cell_params, run_times=[simtime], record=True,
record_v=True, randomise_v_init=True, record_input_spikes=True,
weight_to_spike=0.4)
s_pop_voltages = synfire_run.get_output_pop_voltage_numpy()
s_pop_spikes = synfire_run.get_output_pop_spikes_numpy()
noise_spike_times = synfire_run.get_spike_source_spikes_numpy()
return noise_spike_times, s_pop_spikes, s_pop_voltages
def do_sampling_rate(self):
synfire_run = SynfireRunner()
synfire_run.do_run(n_neurons, neurons_per_core=neurons_per_core,
delay=delay, run_times=[runtime], record=True,
record_7=True, record_v=True, record_v_7=True,
v_sampling_rate=2, gsyn_exc_sampling_rate=3,
record_gsyn_exc=True, record_gsyn_exc_7=True,
record_gsyn_inh=False)
gsyn_exc_7 = synfire_run.get_output_pop_gsyn_exc_7()
v_7 = synfire_run.get_output_pop_voltage_7()
spikes_7 = synfire_run.get_output_pop_spikes_7()
gsyn_exc = synfire_run.get_output_pop_gsyn_exc_numpy()
v = synfire_run.get_output_pop_voltage_numpy()
spikes = synfire_run.get_output_pop_spikes_numpy()
read_gsyn = numpy.loadtxt(gysn_file, delimiter=',')
small_gsyn = read_gsyn[read_gsyn[:, 1] % 3 == 0]
self.assertEqual(len(small_gsyn), len(gsyn_exc_7))
self.assertTrue(numpy.allclose(small_gsyn, gsyn_exc_7, rtol=1e-04),
"gsyn synakker method mismatch")
self.assertTrue(numpy.allclose(small_gsyn, gsyn_exc, rtol=1e-04),
"gsyn neo method mismatch")
self.assertEqual(n_neurons*(runtime/2), len(v))
read_v = numpy.loadtxt(v_file, delimiter=',')
small_v = read_v[read_v[:, 1] % 2 == 0]
self.assertTrue(numpy.allclose(small_v, v_7, rtol=1e-03),
"v synakker method mismatch")
self.assertTrue(numpy.allclose(small_v, v, rtol=1e-03),
"v neo method mismatch")
self.assertEqual(expected_spikes, len(spikes))
spike_checker.synfire_spike_checker(spikes, n_neurons)
read_spikes = numpy.loadtxt(spike_file, delimiter=',')
self.assertTrue(numpy.allclose(read_spikes, spikes_7),
"spikes synakker method mismatch")
self.assertTrue(numpy.allclose(read_spikes, spikes),
"spikes neo method mismatch")
record_v = False
record_gsyn = False
synfire_run = SynfireRunner()
class Synfire200n10pc2chipsWithNoDelaysSpikeRecording(BaseTestCase):
def test_run(self):
self.assert_not_spin_three()
synfire_run.do_run(nNeurons,
delay=delay,
record_v=record_v,
record_gsyn_exc=record_gsyn,
record_gsyn_inh=record_gsyn)
spikes = synfire_run.get_output_pop_spikes_numpy()
self.assertEqual(333, len(spikes))
spike_checker.synfire_spike_checker(spikes, nNeurons)
if __name__ == '__main__':
synfire_run.do_run(nNeurons,
delay=delay,
record_v=record_v,
record_gsyn_exc=record_gsyn,
record_gsyn_inh=record_gsyn)
spikes = synfire_run.get_output_pop_spikes_numpy()
print(len(spikes))
plot_utils.plot_spikes(spikes)
# v and gysn are None
