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import numpy as np
import pytest
from numpy.testing import assert_equal
from brian2.memory.dynamicarray import DynamicArray1D
from brian2.synapses.spikequeue import SpikeQueue
from brian2.units.stdunits import ms
def create_all_to_all(N, dt):
"""
Return a tuple containing `synapses` and `delays` in the form that is needed
for the `SpikeQueue` initializer.
Every synapse has a delay depending on the presynaptic neuron.
"""
data = np.repeat(np.arange(N, dtype=np.int32), N)
delays = DynamicArray1D(data.shape, dtype=np.float64)
delays[:] = data * dt
synapses = data
return synapses, delays
def create_one_to_one(N, dt):
"""
Return a tuple containing `synapses` and `delays` in the form that is needed
for the `SpikeQueue` initializer.
Every synapse has a delay depending on the presynaptic neuron.
"""
data = np.arange(N, dtype=np.int32)
delays = DynamicArray1D(data.shape, dtype=np.float64)
delays[:] = data * dt
synapses = data
return synapses, delays
@pytest.mark.codegen_independent
def test_spikequeue():
N = 100
dt = float(0.1 * ms)
synapses, delays = create_one_to_one(N, dt)
queue = SpikeQueue(source_start=0, source_end=N)
queue.prepare(delays[:], dt, synapses)
queue.push(np.arange(N, dtype=np.int32))
for i in range(N):
assert_equal(queue.peek(), np.array([i]))
queue.advance()
for i in range(N):
assert_equal(queue.peek(), np.array([]))
queue.advance()
synapses, delays = create_all_to_all(N, dt)
queue = SpikeQueue(source_start=0, source_end=N)
queue.prepare(delays[:], dt, synapses)
queue.push(np.arange(N * N, dtype=np.int32))
for i in range(N):
assert_equal(queue.peek(), i * N + np.arange(N))
queue.advance()
for i in range(N):
assert_equal(queue.peek(), np.array([]))
queue.advance()
if __name__ == "__main__":
test_spikequeue()
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