On 12/03/15 at 05:39am, Eric Firing wrote:
> On 2015/12/02 10:45 PM, Manolo Martínez wrote:
> >1) this func sorts the absolute value of the amplitudes to find the two
> >most important components, and this seems overkill for large vectors.
>
> Try
>
> inds = np.argpartition(-np.abs(ft), 2)[:2]
>
On 12/03/15 at 12:50pm, Oscar Benjamin wrote:
> In terms of out of the box software I can recommend auto and xpp. Each
> is esoteric and comes with a clunky interface. XPP has a strange GUI
> and auto is controlled through Python bindings using IPython as
> frontend.
Thanks again, Oscar. I'll tr
On 2015/12/02 10:45 PM, Manolo Martínez wrote:
1) this func sorts the absolute value of the amplitudes to find the two
most important components, and this seems overkill for large vectors.
Try
inds = np.argpartition(-np.abs(ft), 2)[:2]
Now inds holds the indices of the two largest components
On 3 December 2015 at 11:58, Manolo Martínez wrote:
>> > This is doing the job for me at the moment, but there are, that I can
>> > see, a couple of things that could be improved (and surely more that I
>> > cannot see):
>
>> If what you have works out fine for you then feel free to ignore this bu
Dear Oscar,
>
> > This is doing the job for me at the moment, but there are, that I can
> > see, a couple of things that could be improved (and surely more that I
> > cannot see):
> If what you have works out fine for you then feel free to ignore this but...
> [snip]
Talk about things I cannot
On 3 December 2015 at 08:45, Manolo Martínez wrote:
>> > >> Is there any way to check for cycles in this situation?
>> >
>> > > Fast fourier transform (fft)?
>> >
>> > +1 For using a discrete Fourier transform, as implemented by numpy.fft.fft.
>> > You mentioned that you sample at points which do
> > >> Is there any way to check for cycles in this situation?
> >
> > > Fast fourier transform (fft)?
> >
> > +1 For using a discrete Fourier transform, as implemented by numpy.fft.fft.
> > You mentioned that you sample at points which do not correspond with the
> > period of the signal; this in
> >> Is there any way to check for cycles in this situation?
>
> > Fast fourier transform (fft)?
>
> +1 For using a discrete Fourier transform, as implemented by numpy.fft.fft.
> You mentioned that you sample at points which do not correspond with the
> period of the signal; this introduces a s
Oops, that leakage document is incomplete. Guess I should finish it up.
On Thu, Nov 26, 2015 at 7:18 AM, Manolo Martínez
wrote:
> Dear all,
>
> Suppose that I have a vector with the numerical solution of a
> differential equation -- more concretely, I am working with evolutionary
> game theory m
Fast fourier transform (fft)?
On Nov 26, 2015 9:21 AM, "Manolo Martínez" wrote:
> Dear all,
>
> Suppose that I have a vector with the numerical solution of a
> differential equation -- more concretely, I am working with evolutionary
> game theory models, and the solutions are frequencies of types
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