def get_far_data_from_one(nearfield, nsize):
# simulation data are saved in nearfield
freqs = mp.get_near2far_freqs(nearfield)
r = 1000 * 3.8 # 1000 wavelengths out from the source
thetas = np.concatenate(
[np.arange(0.5, 20, 1),
np.arange(22.5, 89, 3)]) # polar angle
phis = [
45,
] # azimuthal angle
data = np.empty(shape=[0, 16])
for phi in phis:
for theta in thetas:
phi0 = np.radians(phi)
theta0 = np.radians(theta)
pt = r * mp.Vector3(
math.sin(theta0) * math.cos(phi0),
math.sin(theta0) * math.sin(phi0), math.cos(theta0))
fields = sim.get_farfield(nearfield, pt)
mat = np.vstack((np.real(fields), np.imag(fields)))
fields = mat.T.reshape((1, -1)).reshape((-1, 12))
infos = np.vstack(
(freqs, nsize * np.ones(len(freqs)),
theta * np.ones(len(freqs)), phi * np.ones(len(freqs))))
data = np.vstack((data, np.hstack((infos.T, fields))))
return data
boundary_layers=pml_layers,
geometry=geometry,
k_point=k_point,
sources=sources,
symmetries=symmetries)
n2f_obj = sim.add_near2far(fcen, df, nfreq, mp.Near2FarRegion(center=n2f_pt, size=mp.Vector3(y=sy-2*dpml)))
sim.run(until_after_sources=mp.stop_when_fields_decayed(50, mp.Ez, n2f_pt, 1e-9))
ff_supercell = sim.get_farfields(n2f_obj, ff_res, center=mp.Vector3(ff_distance,0.5*ff_length), size=mp.Vector3(y=ff_length))
norm_err = LA.norm(ff_unitcell['Ez']-ff_supercell['Ez'])/nperiods
print("error:, {}, {}".format(nperiods,norm_err))
freqs = mp.get_near2far_freqs(n2f_obj)
wvl = np.divide(1,freqs)
ff_lengths = np.linspace(0,ff_length,ff_npts)
angles = [math.degrees(math.atan(f)) for f in ff_lengths/ff_distance]
wvl_slice = 0.5
idx_slice = np.where(np.asarray(freqs) == 1/wvl_slice)[0][0]
rel_enh = np.absolute(ff_unitcell['Ez'])**2/np.absolute(ff_source['Ez'])**2
plt.figure(dpi=150)
plt.subplot(1,2,1)
plt.pcolormesh(wvl,angles,rel_enh,cmap='Blues',shading='flat')
plt.axis([wvl_min,wvl_max,0,ff_angle])
plt.xlabel("wavelength (μm)")