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import timeit
import itertools
import numpy as np
GENERAL_SETUP = ['import numpy as np',
'from brian2.tests.test_spikequeue import create_all_to_all, create_one_to_one',
'from brian2.units.stdunits import ms',
'from brian2.synapses.spikequeue import SpikeQueue']
def get_setup_code(N, create_func):
return GENERAL_SETUP + [
'synapses, delays = {}({})'.format(create_func, N),
'queue = SpikeQueue(synapses, delays, 0.1*ms)']
def test_compress(N, create_func):
setup_code = get_setup_code(N, create_func)
number = 1000/N
results = timeit.repeat('queue.compress()', ';'.join(setup_code), repeat=5,
number=number)
return np.array(results) / number
def test_push(N, create_func):
setup_code = get_setup_code(N, create_func) + ['queue.compress()']
number = 5000/N
results = timeit.repeat('queue.push(np.arange({}));queue.next()'.format(N),
';'.join(setup_code), repeat=5,
number=number)
return np.array(results) / number
def run_benchmark(test_func, N, create_func):
result = test_func(N, create_func)
print('{} -- {}({}) : {}'.format(test_func.__name__, create_func, N,
np.median(result)))
if __name__ == '__main__':
for test, N, create_func in itertools.product((test_compress, test_push),
(10, 100),
('create_all_to_all',
'create_one_to_one')):
run_benchmark(test, N, create_func)
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