Here's why there's a discrepancy:
sage: import scipy.fftpack as Fourier
sage: Fourier.ifft([95,20-25*i,-23,20+25*i])
array([ 28.0+0.j, 29.5-0.j, 8.0+0.j, 29.5+0.j])
sage: Fourier.ifft([95,20,-23,20])
array([ 28.0+0.j, 29.5-0.j, 8.0+0.j, 29.5+0.j])
sage: sage: Fourier.ifft([95,20-25j,-23,20+25j])
array([ 28.+0.j, 42.+0.j, 8.+0.j, 17.+0.j])
I encountered a similar bug in numpy last week when using
numpy.loadtxt - any terms involving 'I' were ignored. I think it's an
upstream problem. In my case I could get around it since loadtxt
accepts a list of converters, and you send it this one:
lambda s: complex(s.replace('i','j'))
Does anyone know if this is fixed in newer versions of numpy/scipy?
Cheers,
Felix
On Nov 3, 2:43 am, kcrisman <[email protected]> wrote:
> Dear support,
>
> We get some inconsistencies with using I and j in scipy. Is there
> some reason these should be different?
>
> sage: import scipy.fftpack as Fourier
> sage: Fourier.ifft([95,20-25*i,-23,20+25*i])
> array([ 28.0+0.j, 29.5-0.j, 8.0+0.j, 29.5+0.j])
> sage: Fourier.ifft([95,20-25j,-23,20+25j])
> array([ 28.+0.j, 42.+0.j, 8.+0.j, 17.+0.j])
>
> Thanks for the help,
> - kcrisman
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