def test_psg_fixed():
psg = PoissonSpikeGenerator(population='test', seed=100)
psg.add(node_ids=range(10), firing_rate=5.0, times=(0.0, 3.0))
assert (psg.populations == ['test'])
assert (np.all(psg.node_ids() == list(range(10))))
assert (psg.n_spikes() == 143)
assert (psg.n_spikes(population='test') == 143)
assert (np.allclose(psg.time_range(),
(5.380662350673328, 2986.5205688893295)))
df = psg.to_dataframe()
assert (df.shape == (143, 3))
assert (np.allclose(psg.get_times(node_id=0), [
156.7916, 222.0400, 332.5493, 705.1267, 706.0727, 731.9963, 954.1834,
1303.7542, 1333.1543, 1504.3314, 1948.2045, 1995.1471, 2036.1411,
2059.0835, 2108.6982, 2877.7935
],
atol=1.0e-3))
assert (np.allclose(psg.get_times(node_id=9, population='test'), [
23.3176, 241.7332, 390.1951, 428.2215, 1001.0229, 1056.4003, 2424.8442,
2599.6312, 2640.1228, 2737.9504, 2780.0140, 2885.8020
],
atol=1.0e-3))
def test_psg_fixed():
psg = PoissonSpikeGenerator(population='test', seed=0.0)
psg.add(node_ids=range(10), firing_rate=10.0, times=(0.0, 10.0))
assert(psg.populations == ['test'])
assert(psg.nodes() == list(range(10)))
time_range = psg.time_range()
assert(0 <= time_range[0] < 1.0)
assert(9.0 < time_range[1] <= 10.0)
# This may fail on certain versions
assert(psg.get_times(node_id=5).size > 10)
assert(0 < psg.get_times(node_id=8).size < 300)
for i in range(10):
spikes = psg.get_times(i)
assert(np.max(spikes) > 0.1)
def test_psg_variable():
times = np.linspace(0.0, 3.0, 1000)
fr = np.exp(-np.power(times - 1.0, 2) / (2 * np.power(.5, 2))) * 5
psg = PoissonSpikeGenerator(population='test', seed=0.0)
psg.add(node_ids=range(10), firing_rate=fr, times=times)
assert (psg.populations == ['test'])
assert (np.all(psg.node_ids() == list(range(10))))
assert (psg.n_spikes() == 59)
assert (np.allclose(psg.time_range(),
(0.13932107933711294, 2.9013003727909172)))
assert (psg.to_dataframe().shape == (59, 3))
assert (np.allclose(psg.get_times(node_id=0),
[0.442, 0.520, 0.640, 1.099, 1.393, 1.725],
atol=1.0e-3))
assert (np.allclose(psg.get_times(node_id=9),
[0.729, 0.885, 1.047, 1.276, 1.543, 1.669, 1.881],
atol=1.0e-3))
def test_psg_variable():
times = np.linspace(0.0, 3.0, 1000)
fr = np.exp(-np.power(times - 1.0, 2) / (2 * np.power(.5, 2))) * 5
psg = PoissonSpikeGenerator(population='test', seed=0.0)
psg.add(node_ids=range(10), firing_rate=fr, times=times)
assert (psg.populations == ['test'])
assert (np.all(psg.node_ids() == list(range(10))))
assert (psg.n_spikes() == 59)
assert (np.allclose(psg.time_range(),
(139.32107933711294, 2901.3003727909172)))
assert (psg.to_dataframe().shape == (59, 3))
assert (np.allclose(
psg.get_times(node_id=0),
[442.8378, 520.3624, 640.3880, 1099.0661, 1393.0794, 1725.6109],
atol=1.0e-3))
assert (np.allclose(psg.get_times(node_id=9), [
729.6267, 885.2469, 1047.7728, 1276.3554, 1543.6557, 1669.9070,
1881.3605
],
atol=1.0e-3))
def test_psg_fixed():
psg = PoissonSpikeGenerator(population='test', seed=100)
psg.add(node_ids=range(10), firing_rate=5.0, times=(0.0, 3.0))
assert (psg.populations == ['test'])
assert (np.all(psg.node_ids() == list(range(10))))
assert (psg.n_spikes() == 143)
assert (psg.n_spikes(population='test') == 143)
assert (np.allclose(psg.time_range(),
(0.005380662350673328, 2.9865205688893295)))
df = psg.to_dataframe()
assert (df.shape == (143, 3))
assert (np.allclose(psg.get_times(node_id=0), [
0.156, 0.222, 0.332, 0.705, 0.706, 0.731, 0.954, 1.303, 1.333, 1.504,
1.948, 1.995, 2.036, 2.059, 2.108, 2.877
],
atol=1.0e-3))
assert (np.allclose(psg.get_times(node_id=9, population='test'), [
0.0233, 0.241, 0.390, 0.428, 1.001, 1.056, 2.424, 2.599, 2.640, 2.737,
2.780, 2.885
],
atol=1.0e-3))