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Return real part of the gradient

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jan 2017-12-17 22:55:55 -08:00
commit f312d73503
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fdfd_tools/bloch.py
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@ -400,7 +400,7 @@ def eigsolve(num_modes: int,
df_dy = scipy_iop @ (AzU - zU @ zTAzU) df_dy = scipy_iop @ (AzU - zU @ zTAzU)
else: else:
df_dy = (AzU - zU @ zTAzU) df_dy = (AzU - zU @ zTAzU)
return numpy.abs(f), numpy.sign(f) * df_dy.ravel() return numpy.abs(f), numpy.sign(f) * numpy.real(df_dy).ravel()
''' '''
Use the conjugate gradient method and the approximate gradient calculation to Use the conjugate gradient method and the approximate gradient calculation to