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[fdfd.farfield] fix kys calculation and some near-0 behavior

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Jan Petykiewicz 2026-04-17 19:37:35 -07:00
commit 74bebea837
1 changed files with 40 additions and 27 deletions
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65
meanas/fdfd/farfield.py
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@ -78,15 +78,12 @@ def near_to_farfield(
kx, ky = numpy.meshgrid(kxx, kyy, indexing='ij')
kxy2 = kx * kx + ky * ky
kxy = numpy.sqrt(kxy2)
kz = numpy.sqrt(k * k - kxy2)
kz = numpy.sqrt(numpy.maximum(0, k * k - kxy2))
sin_th = ky / kxy
cos_th = kx / kxy
sin_th = numpy.divide(ky, kxy, out=numpy.zeros_like(ky), where=kxy != 0)
cos_th = numpy.divide(kx, kxy, out=numpy.ones_like(kx), where=kxy != 0)
cos_phi = kz / k
sin_th[numpy.logical_and(kx == 0, ky == 0)] = 0
cos_th[numpy.logical_and(kx == 0, ky == 0)] = 1
# Normalized vector potentials N, L
N = [-Hn_fft[1] * cos_phi * cos_th + Hn_fft[0] * cos_phi * sin_th,
Hn_fft[1] * sin_th + Hn_fft[0] * cos_th] # noqa: E127
@ -114,8 +111,8 @@ def near_to_farfield(
outputs = {
'E': E_far,
'H': H_far,
'dkx': kx[1] - kx[0],
'dky': ky[1] - ky[0],
'dkx': float(kxx[1] - kxx[0]),
'dky': float(kyy[1] - kyy[0]),
'kx': kx,
'ky': ky,
'theta': theta,
@ -177,22 +174,19 @@ def far_to_nearfield(
padded_shape = cast('Sequence[int]', padded_size)
k = 2 * pi
kxs = fftshift(fftfreq(s[0], 1 / (s[0] * dkx)))
kys = fftshift(fftfreq(s[0], 1 / (s[1] * dky)))
kxs = dkx * fftshift(fftfreq(s[0], d=1 / s[0]))
kys = dky * fftshift(fftfreq(s[1], d=1 / s[1]))
kx, ky = numpy.meshgrid(kxs, kys, indexing='ij')
kxy2 = kx * kx + ky * ky
kxy = numpy.sqrt(kxy2)
kz = numpy.sqrt(k * k - kxy2)
kz = numpy.sqrt(numpy.maximum(0, k * k - kxy2))
sin_th = ky / kxy
cos_th = kx / kxy
sin_th = numpy.divide(ky, kxy, out=numpy.zeros_like(ky), where=kxy != 0)
cos_th = numpy.divide(kx, kxy, out=numpy.ones_like(kx), where=kxy != 0)
cos_phi = kz / k
sin_th[numpy.logical_and(kx == 0, ky == 0)] = 0
cos_th[numpy.logical_and(kx == 0, ky == 0)] = 1
theta = numpy.arctan2(ky, kx)
phi = numpy.arccos(cos_phi)
theta[numpy.logical_and(kx == 0, ky == 0)] = 0
@ -212,21 +206,41 @@ def far_to_nearfield(
N = [L[1],
-L[0]] # noqa: E128
En_fft = [-( L[0] * sin_th + L[1] * cos_phi * cos_th) / cos_phi,
-(-L[0] * cos_th + L[1] * cos_phi * sin_th) / cos_phi]
En_fft = [
numpy.divide(
-(L[0] * sin_th + L[1] * cos_phi * cos_th),
cos_phi,
out=numpy.zeros_like(L[0]),
where=cos_phi != 0,
),
numpy.divide(
-(-L[0] * cos_th + L[1] * cos_phi * sin_th),
cos_phi,
out=numpy.zeros_like(L[0]),
where=cos_phi != 0,
),
]
Hn_fft = [( N[0] * sin_th + N[1] * cos_phi * cos_th) / cos_phi,
(-N[0] * cos_th + N[1] * cos_phi * sin_th) / cos_phi]
for i in range(2):
En_fft[i][cos_phi == 0] = 0
Hn_fft[i][cos_phi == 0] = 0
Hn_fft = [
numpy.divide(
N[0] * sin_th + N[1] * cos_phi * cos_th,
cos_phi,
out=numpy.zeros_like(N[0]),
where=cos_phi != 0,
),
numpy.divide(
-N[0] * cos_th + N[1] * cos_phi * sin_th,
cos_phi,
out=numpy.zeros_like(N[0]),
where=cos_phi != 0,
),
]
E_near = [ifftshift(ifft2(ifftshift(Ei), s=padded_shape)) for Ei in En_fft]
H_near = [ifftshift(ifft2(ifftshift(Hi), s=padded_shape)) for Hi in Hn_fft]
dx = 2 * pi / (s[0] * dkx)
dy = 2 * pi / (s[0] * dky)
dy = 2 * pi / (s[1] * dky)
outputs = {
'E': E_near,
@ -236,4 +250,3 @@ def far_to_nearfield(
}
return outputs