def test_x_y_to_zeta_eta():
x = np.random.rand(16) * 3000
y = np.random.rand(16) * 3000
x[-1] = y[-1] = 56.0
x[-2] = y[-2] = 0.0
factor_ = 4 / np.pi
zeta_ = []
eta_ = []
for x_, y_ in zip(x, y):
z = np.sqrt(x_**2 + y_**2)
if x_ < y_:
eta_.append(factor_ * np.arctan(x_ / y_))
zeta_.append(z)
elif x_ > y_:
eta_.append(factor_ * np.arctan(y_ / x_))
zeta_.append(-z)
else:
zeta_.append(z)
eta_.append(1.0)
z_temp, e_temp = x_y_to_zeta_eta([x_], [y_])
assert np.allclose(zeta_[-1], z_temp)
assert np.allclose(eta_[-1], e_temp)
zeta, eta = x_y_to_zeta_eta(x, y)
assert np.allclose(zeta, np.asarray(zeta_))
assert np.allclose(eta, np.asarray(eta_))
def test_extended_czjzek_polar():
S0 = {"zeta": 1, "eta": 0.1}
x, y = ExtCzjzekDistribution(S0, eps=0.05, polar=True).rvs(size=COUNT)
x1, y1 = x_y_from_zeta_eta(*x_y_to_zeta_eta(x, y))
np.testing.assert_almost_equal(x, x1)
np.testing.assert_almost_equal(y, y1)
def test_czjzek_polar():
x, y = CzjzekDistribution(sigma=0.5, polar=True).rvs(size=COUNT)
x1, y1 = x_y_from_zeta_eta(*x_y_to_zeta_eta(x, y))
np.testing.assert_almost_equal(x, x1)
np.testing.assert_almost_equal(y, y1)
