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'''
Some simple benchmarks to check how much the performance is impaired when using units (units are not used in the main
simulation loop but also analysing/plotting should not be noticeably slow for the user)
'''
import time
import numpy as np
from brian2 import *
sizes = [10, 100, 1000, 10000, 100000]
access = lambda idx, ar1, ar2: ar1[idx]
multiply = lambda idx, ar1, ar2: 42 * ar1
addition = lambda idx, ar1, ar2: ar1 + ar2
slicing = lambda idx, ar1, ar2: ar1[idx:]
for func_name, func in [('access', access),
('multiply', multiply),
('add', addition),
('slicing', slicing)]:
times_no_unit = []
times_unit = []
for size in sizes:
no_unit1 = np.random.randn(size)
no_unit2 = np.random.randn(size)
with_unit1 = no_unit1 * mV
with_unit2 = no_unit2 * mV
start = time.time()
for x in range(size):
func(x, no_unit1, no_unit2)
times_no_unit.append(time.time() - start)
start = time.time()
for x in range(size):
func(x, with_unit1, with_unit2)
times_unit.append(time.time() - start)
print('')
print(func_name, ':')
print('No unit ', times_no_unit)
print(' unit ', times_unit)
print('relative', np.array(times_unit) / np.array(times_no_unit))
# Dimensionless Quantities
print('*' * 60)
print('Dimensionless quantities')
for func_name, func in [('access', access),
('multiply', multiply),
('add', addition),
('slicing', slicing)]:
times_no_unit = []
times_unit = []
for size in sizes:
no_unit1 = np.random.randn(size)
no_unit2 = np.random.randn(size)
with_unit1 = no_unit1 * mV/mV
with_unit2 = no_unit2 * mV/mV
start = time.time()
for x in range(size):
func(x, no_unit1, no_unit2)
times_no_unit.append(time.time() - start)
start = time.time()
for x in range(size):
func(x, with_unit1, with_unit2)
times_unit.append(time.time() - start)
print('')
print(func_name, ':')
print('No unit ', times_no_unit)
print(' unit ', times_unit)
print('relative', np.array(times_unit) / np.array(times_no_unit))
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