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from __future__ import division
import math
import unittest
import numpy as np
import meep as mp
class TestReflAngular(unittest.TestCase):
def test_refl_angular(self):
resolution = 100
dpml = 1.0
sz = 10
sz = sz + 2 * dpml
cell_size = mp.Vector3(z=sz)
pml_layers = [mp.PML(dpml)]
wvl_min = 0.4
wvl_max = 0.8
fmin = 1 / wvl_max
fmax = 1 / wvl_min
fcen = 0.5 * (fmin + fmax)
df = fmax - fmin
nfreq = 50
theta_r = math.radians(0)
k = mp.Vector3(math.sin(theta_r), 0, math.cos(theta_r)).scale(fcen)
dimensions = 1
sources = [mp.Source(mp.GaussianSource(fcen, fwidth=df), component=mp.Ex,
center=mp.Vector3(z=-0.5 * sz + dpml))]
sim = mp.Simulation(cell_size=cell_size,
boundary_layers=pml_layers,
sources=sources,
k_point=k,
dimensions=dimensions,
resolution=resolution)
refl_fr = mp.FluxRegion(center=mp.Vector3(z=-0.25 * sz))
refl = sim.add_flux(fcen, df, nfreq, refl_fr)
sim.run(until_after_sources=mp.stop_when_fields_decayed(50, mp.Ex, mp.Vector3(z=-0.5 * sz + dpml), 1e-9))
empty_data = sim.get_flux_data(refl)
sim.reset_meep()
geometry = [mp.Block(mp.Vector3(mp.inf, mp.inf, 0.5 * sz), center=mp.Vector3(z=0.25 * sz),
material=mp.Medium(index=3.5))]
sim = mp.Simulation(cell_size=cell_size,
geometry=geometry,
boundary_layers=pml_layers,
sources=sources,
k_point=k,
dimensions=dimensions,
resolution=resolution)
refl = sim.add_flux(fcen, df, nfreq, refl_fr)
sim.load_minus_flux_data(refl, empty_data)
sim.run(until_after_sources=mp.stop_when_fields_decayed(50, mp.Ex, mp.Vector3(z=-0.5 * sz + dpml), 1e-9))
refl_flux = mp.get_fluxes(refl)
freqs = mp.get_flux_freqs(refl)
expected = [
(1.25, -1.123696883299492e-6),
(1.2755102040816326, -2.5749667658387866e-6),
(1.3010204081632653, -5.70480204599006e-6),
(1.3265306122448979, -1.2220464827582253e-5),
(1.3520408163265305, -2.531247480206961e-5),
(1.3775510204081631, -5.069850309492639e-5),
(1.4030612244897958, -9.819256552437341e-5),
(1.4285714285714284, -1.8390448659017395e-4),
(1.454081632653061, -3.330762066794769e-4),
(1.4795918367346936, -5.833650417163753e-4),
(1.5051020408163263, -9.8807834237052e-4),
(1.5306122448979589, -0.001618472171445976),
(1.5561224489795915, -0.0025638388059825985),
(1.5816326530612241, -0.003927863989816029),
(1.6071428571428568, -0.005819831283556752),
(1.6326530612244894, -0.008339881000982728),
(1.658163265306122, -0.011558769654206626),
(1.6836734693877546, -0.015494308354153143),
(1.7091836734693873, -0.02008850084337135),
(1.73469387755102, -0.025190871516857616),
(1.7602040816326525, -0.030553756123198477),
(1.7857142857142851, -0.03584404966066722),
(1.8112244897959178, -0.040672967700428275),
(1.8367346938775504, -0.04464118393086191),
(1.862244897959183, -0.047392712128477496),
(1.8877551020408156, -0.048667403362887635),
(1.9132653061224483, -0.048341494285878264),
(1.938775510204081, -0.04644739000778679),
(1.9642857142857135, -0.043168390293742316),
(1.9897959183673462, -0.0388094755730579),
(2.0153061224489788, -0.03375052221907117),
(2.0408163265306114, -0.02839209067703472),
(2.066326530612244, -0.023104245646230648),
(2.0918367346938767, -0.01818725699718267),
(2.1173469387755093, -0.013849270759480073),
(2.142857142857142, -0.010201733597436358),
(2.1683673469387745, -0.007269616609175294),
(2.193877551020407, -0.005011210495189995),
(2.21938775510204, -0.0033417192031464896),
(2.2448979591836724, -0.0021557351734376256),
(2.270408163265305, -0.0013453062176115673),
(2.2959183673469377, -8.121742663131631e-4),
(2.3214285714285703, -4.7433135191915683e-4),
(2.346938775510203, -2.6799188013374266e-4),
(2.3724489795918355, -1.464781343401766e-4),
(2.397959183673468, -7.745339273024636e-5),
(2.423469387755101, -3.9621374769542025e-5),
(2.4489795918367334, -1.9608458558430508e-5),
(2.474489795918366, -9.38818477949983e-6),
(2.4999999999999987, -4.3484671364929225e-6),
]
np.testing.assert_allclose(expected, list(zip(freqs, refl_flux)), rtol=1e-6)
if __name__ == '__main__':
unittest.main()
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