def test_ellipsoid_equal_spheroid_z_oriented():
"""An (rx, ry, rz) ellipsoid should equal a z-oriented (rxy, rz) spheroid"""
e = miepy.spheroid([0, 0, 0], rx, rz, material)
T1 = e.compute_tmatrix(lmax, wavelength, 1.0)
e = miepy.ellipsoid([0, 0, 0], rx, ry, rz, material)
T2 = e.compute_tmatrix(lmax, wavelength, 1.0)
assert np.allclose(T1, T2, atol=2e-5)
def test_ellipsoid_equal_spheroid_y_oriented():
"""An (rx, rz, ry) ellipsoid should equal a y-oriented (rxy, rz) spheroid"""
q = miepy.quaternion.from_spherical_coords(np.pi / 2, np.pi / 2)
e = miepy.spheroid([0, 0, 0], rx, rz, material, orientation=q)
T1 = e.compute_tmatrix(lmax, wavelength, 1.0)
e = miepy.ellipsoid([0, 0, 0], rx, rz, ry, material)
T2 = e.compute_tmatrix(lmax, wavelength, 1.0)
assert np.allclose(T1, T2, atol=5e-5)
def gmt_sim():
wavelengths = np.linspace(400 * nm, 1000 * nm, 100)
eps = meep_ext.get_eps(material)(wavelengths)
Au = miepy.data_material(wavelengths, eps)
Au = miepy.constant_material(3.5**2)
C, A, E = [np.zeros_like(wavelengths) for i in range(3)]
particles = []
# orientation = miepy.quaternion.from_spherical_coords(theta[i], phi[i])
particles.append(
miepy.ellipsoid([0, 0, 0], rx, ry, rz, material=Au, orientation=q))
for i, wavelength in enumerate(tqdm(wavelengths)):
sol = miepy.cluster(particles=particles,
source=miepy.sources.plane_wave([1, 0]),
wavelength=wavelength,
lmax=3)
C[i], A[i], E[i] = sol.cross_sections()
return dict(wavelengths=wavelengths, C=C, A=A, E=E)
1 / a**2)
rhat, that, phat = miepy.coordinates.sph_basis_vectors(theta, phi)
sigma = (rhat - 1 / rad * dr_theta * that -
1 / rad * dr_phi * phat) * rad**2 * np.sin(theta)
return rad, sigma
rad, dS = ellipsoid_dS(1 * radius, 1.3 * radius, 1.6 * radius, THETA, PHI)
T = get_tmatrix(rad, dS, eps, 1, wavelength, lmax)
print(T[1, :, 0, 0])
T1 = np.copy(T)
spheroid = miepy.spheroid([0, 0, 0], radius, 1.3 * radius, material)
spheroid = miepy.ellipsoid([0, 0, 0], radius, 1.3 * radius, 1.6 * radius,
material)
T = spheroid.compute_tmatrix(lmax, wavelength, 1)
print(T[1, :, 0, 0])
T2 = np.copy(T)
import matplotlib.pyplot as plt
rmax = lmax * (lmax + 2)
T1 = np.reshape(T1, [2 * rmax, 2 * rmax])
T2 = np.reshape(T2, [2 * rmax, 2 * rmax])
y = np.abs(T1 - T2)
y /= np.max(y)
plt.pcolormesh(y, vmax=.1)
plt.gca().set_aspect('equal')
plt.colorbar()