def selection(method='python', it=10000000):
import lognormal
import lognormal_cy
mu = np.array([1.0, 2.0, 3.0], dtype=DTYPE)
sigma = np.array([2.0, 2.0, 2.0], dtype=DTYPE)
x = 0.1
y = 3.0
k = np.array([0.1, 0.2, 0.3], dtype=DTYPE)
args = [mu, sigma]
python_res = lognormal.selectionfunc(x, k, *args)
cython_res = lognormal_cy.selectionfunc(x, k, args)
assert python_res == cython_res, 'Values not match'
if method == 'python':
total = 0
for i in range(it):
tic = time.time()
res = lognormal.selectionfunc(x, k, *args)
toc = time.time()
total += toc - tic
aver_time = total / it * 1e6
print('breakage function takes %5.2f \u03BCs.' % aver_time)
elif method == 'cython':
total = 0
for i in range(it):
tic = time.time()
res = lognormal_cy.selectionfunc(x, k, args)
toc = time.time()
total += toc - tic
aver_time = total / it * 1e6
print('breakage function takes %5.2f \u03BCs.' % aver_time)
def den_integrand(x, k, *args):
return x**3 * selectionfunc(x, k, args)
def selection_integrand(x, k, *args):
return (particle_number(x, k, *args) - 1) * selectionfunc(x, k, args)
def num_integrand(x, y, k, *args):
return x**3 * selectionfunc(y, k, args) * breakagefunc(x, y, k, args)