def test_sample_with_one_intervall():
"""
Test the position and handling of the 21 sampling points.
"""
e_test = 0.1
a_test = 2.0
a = -10
b = 10
x_exp = (kronrod21 + 1.0) / 2.0 * (b - a) + a
lorentz_exp, lorentz_normed_exp = lorentz_approx(x_exp, e_test, a_test)
sampler = MVFSampler(
lorentz_approx,
(e_test, a_test),
(np.float64, np.float64),
epsrel=1e-4,
epsabs=1e-8,
n_intervalls_max=1,
do_sort=False,
)
xs, [lorentz, lorentz_normed] = sampler.eval_interval(a, b)
print("n_intrvalls = {0}".format(sampler.n_intervalls))
print("n_eval = {0}".format(sampler.n_samples))
print("integral_value = {0}".format(sampler.integral_value))
np.testing.assert_allclose(lorentz, lorentz_exp, rtol=3e-10, atol=1e-10)
np.testing.assert_allclose(xs, x_exp, rtol=3e-10, atol=1e-10)
np.testing.assert_allclose(lorentz_normed, lorentz_normed_exp, rtol=3e-10, atol=1e-10)
assert_equal(sampler.n_intervalls, 1)
assert_equal(sampler.n_samples, 21)
def test_sorting_sample():
"""
Test the sorting of the sample.
"""
e_test = 0.1
a_test = 2.0
a = -10
b = 10
x_exp = (kronrod21_sorted + 1.0) / 2.0 * (b - a) + a
lorentz_exp, lorentz_normed_exp = lorentz_approx(x_exp, e_test, a_test)
sampler = MVFSampler(
lorentz_approx,
(e_test, a_test),
(np.float64, np.float64),
epsrel=1e-4,
epsabs=1e-8,
n_intervalls_max=1,
do_sort=True,
)
xs, [lorentz, lorentz_normed] = sampler.eval_interval(a, b)
np.testing.assert_allclose(xs, x_exp)
np.testing.assert_allclose(lorentz, lorentz_exp)
def calc(self):
k_vac = 2.*np.pi/self.wl
n_e = self.N_top[0].real
ow_h = self.stack.emitter.orientation_weights[0]
ow_v = self.stack.emitter.orientation_weights[1]
iqe = self.stack.emitter.iqe
pfunc_args = (
k_vac, n_e,
self.stack.top.L, self.stack.bot.L,
self.N_top, self.N_bot,
self.mu_top, self.mu_bot,
self.hs_top, self.hs_bot,
ow_h, ow_v, self.radiationborder_cheatshift)
try:
u_points = (self.angular_range.get_array()).data
except TypeError:
# do adaptive sampling
sampler = MVFSampler(
self._get_p_func(), pfunc_args,
(np.float32, np.complex64, np.float32, np.float32, np.float32),
epsabs=0, epsrel=1e-7, n_intervalls_max=50, do_sort=True
)
sampler_result = sampler.eval_interval(
self.angular_range.begin, self.angular_range.end)
else:
# do fixed sampling
sampler = MVFFixedSampler(
self._get_p_func(), pfunc_args,
(np.float32, np.complex64, np.float32, np.float32, np.float32),
)
sampler_result = sampler.eval_points(u_points)
self.us = sampler_result[0]
self.p_u = sampler_result[1][0]
self.we_u = sampler_result[1][1]
self.p_hTE_u = sampler_result[1][2]
self.p_hTM_u = sampler_result[1][3]
self.p_vTM_u = sampler_result[1][4]
self.P = sampler.integral_value
self.f_u = self.p_u / ((1. - iqe) / iqe + self.P)
self.f_hTE_u = self.p_hTE_u / ((1. - iqe) / iqe + self.P)
self.f_hTM_u = self.p_hTM_u / ((1. - iqe) / iqe + self.P)
self.f_vTM_u = self.p_vTM_u / ((1. - iqe) / iqe + self.P)
def test_integration_of_lorentz_delta():
"""
Test the integration of the lorentz delta approximation.
"""
e_test = 0.001
a_test = 2.0
a = -100
b = 100
i_exp = a_test * (np.arctan(b / e_test) - np.arctan(a / e_test)) / np.pi
sampler = MVFSampler(
lorentz_approx, (e_test, a_test), (np.float64, np.float64), epsrel=1e-6, epsabs=1e-6, do_sort=False
)
xs, [lorentz, lorentz_normed] = sampler.eval_interval(a, b)
np.testing.assert_allclose(sampler.integral_value, i_exp, rtol=1e-6, atol=1e-6)