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compare: jan:107c0fcd7e65c61230b628a21cd62c3c77c81fd9
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jan:master
jan:wgsens
jan:spar
jan:v0.9
jan:release
jan:v0.8
jan:v0.7
jan:v0.6

2 Commits
5c3b3532a9 ... 107c0fcd7e

Author SHA1 Message Date
Jan Petykiewicz
107c0fcd7e set fdfd sources in a way that catches incorrect j.e calculation 2024-01-17 23:30:08 -08:00
Jan Petykiewicz
c3b6fd94a6 should be e dot j.conj() 2024-01-17 22:20:59 -08:00
1 changed files with 11 additions and 5 deletions
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meanas/test/test_fdfd.py
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@ -26,6 +26,8 @@ def test_poynting_planes(sim: 'FDResult') -> None:
# for dxa in dxg: # for dxa in dxg:
# if not (dxa == sim.dxes[0][0][0]).all(): # if not (dxa == sim.dxes[0][0][0]).all():
# pytest.skip('test_poynting_planes skips nonuniform dxes') # pytest.skip('test_poynting_planes skips nonuniform dxes')
# pick only the second point
points = numpy.where(mask) points = numpy.where(mask)
mask[points[0][0], points[1][0], points[2][0]] = 0 mask[points[0][0], points[1][0], points[2][0]] = 0
@ -43,10 +45,14 @@ def test_poynting_planes(sim: 'FDResult') -> None:
s[1, mask].sum(), -s[1, my].sum(), s[1, mask].sum(), -s[1, my].sum(),
s[2, mask].sum(), -s[2, mz].sum()] s[2, mask].sum(), -s[2, mz].sum()]
e_dot_j = sim.e * sim.j * sim.dxes[0][0][:, None, None] * sim.dxes[0][1][None, :, None] * sim.dxes[0][2][None, None, :] e_dot_j = sim.e * sim.j.conj()
src_energy = -e_dot_j[:, mask].real / 2 dv = (sim.dxes[0][0][:, None, None]
* sim.dxes[0][1][None, :, None]
* sim.dxes[0][2][None, None, :]
)
src_energy = -(e_dot_j.real * dv)[:, mask] / 2
assert_close(sum(planes), src_energy.sum()) assert_close(sum(planes), src_energy.sum(), rtol=1e-6) # TODO improve energy calculation accuracy?
##################################### #####################################
@ -88,8 +94,8 @@ def j_distribution(
if request.param == 'center': if request.param == 'center':
j[center_mask] = j_mag j[center_mask] = j_mag
elif request.param == 'diag': elif request.param == 'diag':
j[numpy.roll(center_mask, [1, 1, 1], axis=(1, 2, 3))] = j_mag j[numpy.roll(center_mask, [1, 1, 1], axis=(1, 2, 3))] = (1 + 1j) * j_mag
j[numpy.roll(center_mask, [-1, -1, -1], axis=(1, 2, 3))] = -1j * j_mag j[numpy.roll(center_mask, [-1, -1, -1], axis=(1, 2, 3))] = (1 - 1j) * j_mag
yield j yield j