def verify_output_and_slice(self, material, frequency):
# Since the slice routines average the diagonals, we need to do that too:
chi1 = material.epsilon(frequency).astype(np.complex128)
chi1inv = np.linalg.inv(chi1)
chi1inv = np.diag(chi1inv)
N = chi1inv.size
n = np.sqrt(N / np.sum(chi1inv))
sim = mp.Simulation(cell_size=mp.Vector3(2, 2, 2),
default_material=material,
resolution=20,
eps_averaging=False)
sim.use_output_directory(self.temp_dir)
sim.init_sim()
# Check to make sure the get_slice routine is working with frequency
n_slice = np.sqrt(np.max(sim.get_epsilon(frequency)))
self.assertAlmostEqual(n, n_slice, places=4)
# Check to make sure h5 output is working with frequency
filename = os.path.join(self.temp_dir,
'dispersive_eigenmode-eps-000000.00.h5')
mp.output_epsilon(sim, frequency=frequency)
n_h5 = 0
mp.all_wait()
with h5py.File(filename, 'r') as f:
n_h5 = np.sqrt(
np.max(mp.complexarray(f['eps.r'][()], f['eps.i'][()])))
self.assertAlmostEqual(n, n_h5, places=4)
def verify_output_and_slice(self, material, omega):
# Since the slice routines average the diagonals, we need to do that too:
chi1 = material.epsilon(omega).astype(np.complex128)
if np.any(np.imag(chi1) != 0):
chi1 = np.square(np.real(np.sqrt(chi1)))
chi1inv = np.linalg.inv(chi1)
chi1inv = np.diag(chi1inv)
N = chi1inv.size
n = np.sqrt(N / np.sum(chi1inv))
sim = mp.Simulation(cell_size=mp.Vector3(2, 2, 2),
default_material=material,
resolution=20,
eps_averaging=False)
sim.init_sim()
# Check to make sure the get_slice routine is working with omega
n_slice = np.sqrt(np.max(sim.get_epsilon(omega)))
self.assertAlmostEqual(n, n_slice, places=4)
# Check to make sure h5 output is working with omega
filename = 'dispersive_eigenmode-eps-000000.00.h5'
mp.output_epsilon(sim, omega=omega)
n_h5 = 0
mp.all_wait()
with h5py.File(filename, 'r') as f:
n_h5 = np.sqrt(np.mean(f['eps'][()]))
self.assertAlmostEqual(n, n_h5, places=4)
def test_get_array_output(self):
sim = self.init_simple_simulation()
sim.use_output_directory(self.temp_dir)
sim.symmetries = []
sim.geometry = [mp.Cylinder(0.2, material=mp.Medium(index=3))]
sim.filename_prefix = 'test_get_array_output'
sim.run(until=20)
mp.output_epsilon(sim)
mp.output_efield_z(sim)
mp.output_tot_pwr(sim)
mp.output_efield(sim)
eps_arr = sim.get_epsilon()
efield_z_arr = sim.get_efield_z()
energy_arr = sim.get_tot_pwr()
efield_arr = sim.get_efield()
fname_fmt = os.path.join(self.temp_dir,
'test_get_array_output-{}-000020.00.h5')
with h5py.File(fname_fmt.format('eps'), 'r') as f:
eps = f['eps'][()]
with h5py.File(fname_fmt.format('ez'), 'r') as f:
efield_z = f['ez'][()]
with h5py.File(fname_fmt.format('energy'), 'r') as f:
energy = f['energy'][()]
with h5py.File(fname_fmt.format('e'), 'r') as f:
ex = f['ex'][()]
ey = f['ey'][()]
ez = f['ez'][()]
efield = np.stack([ex, ey, ez], axis=-1)
np.testing.assert_allclose(eps, eps_arr)
np.testing.assert_allclose(efield_z, efield_z_arr)
np.testing.assert_allclose(energy, energy_arr)
np.testing.assert_allclose(efield, efield_arr)
def test_get_array_output(self):
sim = self.init_simple_simulation()
sim.symmetries = []
sim.geometry = [mp.Cylinder(0.2, material=mp.Medium(index=3))]
sim.filename_prefix = 'test_get_array_output'
sim.run(until=20)
mp.output_epsilon(sim)
mp.output_efield_z(sim)
mp.output_tot_pwr(sim)
mp.output_efield(sim)
eps_arr = sim.get_epsilon()
efield_z_arr = sim.get_efield_z()
energy_arr = sim.get_tot_pwr()
efield_arr = sim.get_efield()
fname_fmt = "test_get_array_output-{}-000020.00.h5"
with h5py.File(fname_fmt.format('eps'), 'r') as f:
eps = f['eps'][()]
with h5py.File(fname_fmt.format('ez'), 'r') as f:
efield_z = f['ez'][()]
with h5py.File(fname_fmt.format('energy'), 'r') as f:
energy = f['energy'][()]
with h5py.File(fname_fmt.format('e'), 'r') as f:
ex = f['ex'][()]
ey = f['ey'][()]
ez = f['ez'][()]
efield = np.stack([ex, ey, ez], axis=-1)
np.testing.assert_allclose(eps, eps_arr)
np.testing.assert_allclose(efield_z, efield_z_arr)
np.testing.assert_allclose(energy, energy_arr)
np.testing.assert_allclose(efield, efield_arr)
sources = [
mp.EigenModeSource(src=mp.GaussianSource(fcen, fwidth=df_source),
size=src_size,
center=src_center,
eig_band=mode_num)
]
sim = mp.Simulation(resolution=resolution,
cell_size=cell_size,
boundary_layers=[mp.PML(dpml)],
sources=sources,
geometry=geometry)
sim.init_sim()
mp.output_epsilon(sim)
p1_region = mp.FluxRegion(center=p1_center, size=p1_size)
flux1 = sim.add_flux(fcen, df_flux, nfreq, p1_region)
p2_region = mp.FluxRegion(center=p2_center, size=p2_size)
flux2 = sim.add_flux(fcen, df_flux, nfreq, p2_region)
p3_region = mp.FluxRegion(center=p3_center, size=p3_size)
flux3 = sim.add_flux(fcen, df_flux, nfreq, p3_region)
p4_region = mp.FluxRegion(center=p4_center, size=p4_size)
flux4 = sim.add_flux(fcen, df_flux, nfreq, p4_region)
sim.run(until_after_sources=mp.stop_when_fields_decayed(
25, mp.Ez, p3_center, 1e-8))
