ot 0.13),
>
> Oh, that's nice! I'm using 0.11.2. OK, time to upgrade.
Oh wow, does that mean that http://trac.cython.org/cython_trac/ticket/177
is fixed? I couldn't find anything in the release notes about that,
but it would be gr
Bruce Southey gmail.com> writes:
> On 11/15/2010 11:48 AM, Felix wrote:
> > On Nov 15, 2:00 am, Dag Sverre Seljebotn wrote:
> >> On 11/15/2010 06:23 AM, Felix wrote:
> >>
> >>> is there any workaround or fix for the problem described in Ticket
> &g
On Nov 15, 2:00 am, Dag Sverre Seljebotn wrote:
> On 11/15/2010 06:23 AM, Felix wrote:
>
> > is there any workaround or fix for the problem described in Ticket
> > 1504?
> >http://projects.scipy.org/numpy/ticket/1504
>
> You can try to see if sys.setdlopenflags
is there any workaround or fix for the problem described in Ticket
1504?
http://projects.scipy.org/numpy/ticket/1504
Using static linking sounds like it could be the easiest solution. Can
numpy.distutils be used to do that?
Thank you for any tips
Felix
this Python in Marc/Mentat. But how? Do you know
what I can do about it?
Thank you in advance.
Kind regards,
Felix Stoedter
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to what T.J.
Alumbaugh asked some days ago.
Thanks for any hints,
Felix
In [1]:import numpy as np
In [2]:import mpmath
In [3]:m2 = np.array([mpmath.mpc(1+2j),mpmath.mpc(2+3j)])
In [4]:m2
Out[4]:array([(1.0 + 2.0j), (2.0 + 3.0j)], dtype=object)
In [5]:m2.imag
Out[5]:array([0, 0
.
Now I'll try to just resample in the time domain, transform without looking at
the result, then blindly multiply and transform back. This seems to work, but
I'll have to find a different testcase so I can make sure the results are
trus
oscillation frequency is given by the point around which the
function is centered, it would be good to have it centered around zero.
The FFT assumes the x axis to be [0..n], so how should I do this?
The functions I have to transform later won't be symmetrical, so the trick
abs(fftdata) is not
> Do your answers differ from the theory by a constant factor, or are
> they completely unrelated?
No, it's more complicated. Below you'll find my most recent, more stripped
down code.
- I don't know how to scale in a way that works for any n.
- I don't know how to get the oscillations to match.
I learned a few things in the meantime:
In my installation, NumPy uses fftpack_lite while SciPy uses FFTW3. There are
more test cases in SciPy which all pass. So I am confirmed my problem is a
pure usage problem.
One thing I was confused about is the fact that even if I calculate the
function o
exact (I)FT.
Felix
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, but the
Fourier-transform doesn't have anything to do with what it should be
mathematically.
Could you or someone else please have a look at it?
Thanks again,
Felix
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, but they do not check consistency of
results.
I'm using NumPy versions 1.0.4 and 1.1.0 on Linux with fftpack_lite.so (even
though fftw3 is installed and configured, but I'll probably ask for that
later...)
Thanks a lot,
Felix
test_fft.py
Description: applicat
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