switch fft, ifft
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@ -173,7 +173,7 @@ def maxwell_operator(k0: numpy.ndarray,
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m * hin_n) * k_mag
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# divide by epsilon
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e_xyz = ifftn(fftn(d_xyz, axes=range(3)) / epsilon, axes=range(3))
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e_xyz = fftn(ifftn(d_xyz, axes=range(3)) / epsilon, axes=range(3))
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# cross product and transform into mn basis
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b_m = numpy.sum(e_xyz * n, axis=3)[:, :, :, None] * -k_mag
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@ -187,7 +187,7 @@ def maxwell_operator(k0: numpy.ndarray,
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n * b_n[:, :, :, None])
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# divide by mu
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h_xyz = ifftn(fftn(b_xyz, axes=range(3)) / mu, axes=range(3))
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h_xyz = fftn(ifftn(b_xyz, axes=range(3)) / mu, axes=range(3))
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# transform back to mn
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h_m = numpy.sum(h_xyz * m, axis=3)
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@ -227,7 +227,7 @@ def hmn_2_exyz(k0: numpy.ndarray,
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m * hin_n) * k_mag
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# divide by epsilon
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return [ei for ei in numpy.rollaxis(fftn(d_xyz, axes=range(3)) / epsilon, 3)]
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return [ei for ei in numpy.rollaxis(ifftn(d_xyz, axes=range(3)) / epsilon, 3)]
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return operator
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@ -258,7 +258,7 @@ def hmn_2_hxyz(k0: numpy.ndarray,
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hin_m, hin_n = [hi.reshape(shape) for hi in numpy.split(h, 2)]
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h_xyz = (m * hin_m +
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n * hin_n)
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return [fftn(hi) for hi in numpy.rollaxis(h_xyz, 3)]
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return [ifftn(hi) for hi in numpy.rollaxis(h_xyz, 3)]
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return operator
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@ -312,7 +312,7 @@ def inverse_maxwell_operator_approx(k0: numpy.ndarray,
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n * hin_n[:, :, :, None])
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# multiply by mu
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b_xyz = ifftn(fftn(h_xyz, axes=range(3)) * mu, axes=range(3))
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b_xyz = fftn(ifftn(h_xyz, axes=range(3)) * mu, axes=range(3))
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# transform back to mn
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b_m = numpy.sum(b_xyz * m, axis=3)
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@ -323,7 +323,7 @@ def inverse_maxwell_operator_approx(k0: numpy.ndarray,
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m * b_n) / k_mag
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# multiply by epsilon
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d_xyz = ifftn(fftn(e_xyz, axes=range(3)) * epsilon, axes=range(3))
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d_xyz = fftn(ifftn(e_xyz, axes=range(3)) * epsilon, axes=range(3))
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# cross product and transform into mn basis crossinv_t2c
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h_m = numpy.sum(e_xyz * n, axis=3)[:, :, :, None] / +k_mag
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