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Alternate approach to poynting matrices

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jan 2019-09-14 19:59:08 +02:00
parent 9cd2dd131b
commit a1a7aa5511
1 changed files with 8 additions and 7 deletions
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15
meanas/fdfd/operators.py
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@ -456,9 +456,8 @@ def poynting_e_cross(e: vfield_t, dxes: dx_lists_t) -> sparse.spmatrix:
bx, by, bz = [rotation(i, shape, -1) for i in range(3)]
dxag = [dx.ravel(order='C') for dx in numpy.meshgrid(*dxes[0], indexing='ij')]
dbgx, dbgy, dbgz = [sparse.diags(dx.ravel(order='C'))
for dx in numpy.meshgrid(*dxes[1], indexing='ij')]
dxbg = [dx.ravel(order='C') for dx in numpy.meshgrid(*dxes[1], indexing='ij')]
dbgx, dbgy, dbgz = [sparse.diags(dx) for dx in dxbg]
Ex, Ey, Ez = [sparse.diags(ei * da) for ei, da in zip(numpy.split(e, 3), dxag)]
n = numpy.prod(shape)
@ -467,6 +466,9 @@ def poynting_e_cross(e: vfield_t, dxes: dx_lists_t) -> sparse.spmatrix:
[[ None, -bx @ Ez @ dbgy, bx @ Ey @ dbgz],
[ by @ Ez @ dbgx, None, -by @ Ex @ dbgz],
[-bz @ Ey @ dbgx, bz @ Ex @ dbgy, None]])
#TODO
P2 = sparse.block_diag((bx, by, bz)) @ cross([Ex, Ey, Ez]) @ sparse.diags(numpy.concatenate(dxbg))
print(sparse.linalg.norm((P-P2)), sparse.linalg.norm(P), sparse.linalg.norm(P2))
return P
@ -490,12 +492,11 @@ def poynting_h_cross(h: vfield_t, dxes: dx_lists_t) -> sparse.spmatrix:
Hx, Hy, Hz = [sparse.diags(hi * db) for hi, db in zip(numpy.split(h, 3), dxbg)]
n = numpy.prod(shape)
zero = sparse.csr_matrix((n, n))
P = sparse.bmat(
[[ zero, -by @ Hz @ fx @ dagy, bz @ Hy @ fx @ dagz],
[ bx @ Hz @ fy @ dagx, zero, -bz @ Hx @ fy @ dagz],
[-bx @ Hy @ fz @ dagx, by @ Hx @ fz @ dagy, zero]])
[[ None, Hz @ bx @ dagy, Hy @ bx @ dagz],
[ Hz @ by @ dagx, None, -Hx @ by @ dagz],
[-Hy @ bz @ dagx, Hx @ bz @ dagy, None]])
return P