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Use overlap_e

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jan 2019-09-05 22:42:39 +02:00
parent 2289c6d116
commit 10e275611d
1 changed files with 5 additions and 5 deletions
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examples/fdfd.py
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@ -137,9 +137,9 @@ def test1(solver=generic_solver):
wg_results = waveguide_mode.solve_waveguide_mode(mode_number=0, **wg_args)
J = waveguide_mode.compute_source(**wg_args, E=wg_results['E'], wavenumber=wg_results['wavenumber'])
H_overlap, slices = waveguide_mode.compute_overlap_ce(E=wg_results['E'], wavenumber=wg_results['wavenumber'],
dxes=dxes, axis=src_axis, polarity=wg_args['polarity'],
slices=wg_args['slices'])
e_overlap = waveguide_mode.compute_overlap_e(E=wg_results['E'], wavenumber=wg_results['wavenumber'],
dxes=dxes, axis=src_axis, polarity=wg_args['polarity'],
slices=wg_args['slices'])
pecg = gridlock.Grid(edge_coords, initial=0.0, num_grids=3)
# pecg.draw_cuboid(center=[700, 0, 0], dimensions=[80, 1e8, 1e8], eps=1)
@ -212,8 +212,8 @@ def test1(solver=generic_solver):
q = []
for i in range(-5, 30):
H_rolled = [numpy.roll(h, i, axis=0) for h in H_overlap]
q += [numpy.abs(vec(E) @ vec(H_rolled).conj())]
e_ovl_rolled = numpy.roll(e_overlap, i, axis=1)
q += [numpy.abs(vec(E) @ vec(e_ovl_rolled).conj())]
pyplot.figure()
pyplot.plot(q)
pyplot.title('Overlap with mode')