diff --git a/meanas/fdfd/waveguide_mode.py b/meanas/fdfd/waveguide_mode.py index 1cce856..59a3f37 100644 --- a/meanas/fdfd/waveguide_mode.py +++ b/meanas/fdfd/waveguide_mode.py @@ -169,9 +169,9 @@ def compute_source(E: field_t, M = numpy.zeros_like(E, dtype=complex) src_order = numpy.roll(range(3), -axis) - exp_iphi = numpy.exp(1j * polarity * wavenumber * dxes[1][axis][slices[axis]]) - rollby = -1 if polarity > 0 else 0 +# exp_iphi = numpy.exp(1j * polarity * wavenumber * dxes[1][axis][slices[axis]]) +# rollby = -1 if polarity > 0 else 0 # J[src_order[1]] = +exp_iphi * H[src_order[2]] * polarity / dxes[1][axis][slices[axis]] # J[src_order[2]] = -exp_iphi * H[src_order[1]] * polarity / dxes[1][axis][slices[axis]] # M[src_order[1]] = +numpy.roll(E[src_order[2]], rollby, axis=axis) / dxes[0][axis][slices[axis]] @@ -181,14 +181,16 @@ def compute_source(E: field_t, s2[axis] = slice(slices[axis].start, slices[axis].stop) s2 = (src_order, *s2) - J[s2] = numpy.roll(functional.curl_h(dxes=dxes)(H), rollby, axis=axis+1)[s2] * polarity * exp_iphi - M[s2] = numpy.roll(functional.curl_e(dxes=dxes)(E), -rollby, axis=axis+1)[s2] + rollby = 1 if polarity > 0 else 0 + exp_iphi = numpy.exp(-1j * polarity * wavenumber * dxes[1][axis][slices[axis]]) + J[s2] = numpy.roll(functional.curl_h(dxes=dxes)(H.conj()), -rollby, axis=axis+1)[s2] * polarity * exp_iphi + M[s2] = -numpy.roll(functional.curl_e(dxes=dxes)(E.conj()), rollby, axis=axis+1)[s2] m2j = functional.m2j(omega, dxes, mu) Jm = m2j(M) Jtot = J + Jm - return Jtot.conj() + return Jtot def compute_overlap_e(E: field_t, @@ -371,6 +373,17 @@ def compute_source_e(QE: field_t, else: start = slices[aa].start stop = slices[aa].stop +# if start is not None or stop is not None: +# if start is None: +# start = 1 +# stop -= 1 +# elif stop is None: +# stop = E.shape[aa + 1] - 1 +# start += 1 +# else: +# start += 1 +# stop -= 1 +# slices_reduced[aa] = slice(start, stop) slices_reduced = (slice(None), *slices_reduced) # Don't actually need to mask out E here since it needs to be pre-masked (QE)