On 20 May 2013 00:36, wrote:
> One more question. Function np.argmax returns max of non-complex numbers ?
> Because FFT array of my signal is complex.
Use abs() like in my example. This will give the absolute value of the
complex numbers:
>>> z = 1+1j
>>> z
(1+1j)
>>> abs(z)
1.4142135623730951
On 20 mai, 19:56, Christian Gollwitzer wrote:
> Oops, I thought we were posting to comp.dsp. Nevertheless, I think
> numpy.fft does mixed-radix (can't check it now)
>
> Am 20.05.13 19:50, schrieb Christian Gollwitzer:
>
>
>
>
>
>
>
> > Am 20.05.13 19:23, schrieb jmfauth:
> >> Non sense.
>
> > Dito
On 20 May 2013 18:23, jmfauth wrote:
> Non sense.
>
> The discrete fft algorithm is valid only if the number of data
> points you transform does correspond to a power of 2 (2**n).
As with many of your comments about Python's unicode implementation
you are confusing performance with validity. The
Oops, I thought we were posting to comp.dsp. Nevertheless, I think
numpy.fft does mixed-radix (can't check it now)
Am 20.05.13 19:50, schrieb Christian Gollwitzer:
Am 20.05.13 19:23, schrieb jmfauth:
Non sense.
Dito.
The discrete fft algorithm is valid only if the number of data
points you
Am 20.05.13 19:23, schrieb jmfauth:
Non sense.
Dito.
The discrete fft algorithm is valid only if the number of data
points you transform does correspond to a power of 2 (2**n).
Where did you get this? The DFT is defined for any integer point number
the same way.
Just if you want to get i
Non sense.
The discrete fft algorithm is valid only if the number of data
points you transform does correspond to a power of 2 (2**n).
Keywords to the problem: apodization, zero filling, convolution
product, ...
eg. http://en.wikipedia.org/wiki/Convolution
jmf
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On 05/19/2013 07:36 PM, killybear...@gmail.com wrote:
One more question. Function np.argmax returns max of non-complex numbers ?
Because FFT array of my signal is complex.
It'd be easier to track the thread if you actually replied to the
message you're responding to, and also if you included
killybear...@gmail.com wrote:
One more question. Function np.argmax returns max of non-complex numbers ?
Because FFT array of my signal is complex.
You'll want the magnitudes of the complex numbers.
Actually the squares of the magnitudes (assuming the
data from the oscilloscope represents volta
One more question. Function np.argmax returns max of non-complex numbers ?
Because FFT array of my signal is complex.
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On 5/19/2013 6:49 PM, Oscar Benjamin wrote:
import numpy as np
Create a square wave signal:
x = np.zeros(50)
x[:25] = -1
x[25:] = +1
x
array([-1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., 1.,
1.
Got it working, thanks alot :)
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Yes, sorry logged from another account.
Would that work on a numpy array ? Because this signal was imported from
oscilloscope as a numpy array.
Best regards,
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On 19 May 2013 23:25, wrote:
> How can i at least find a peek in FFT spectrum of a square wave ?
> From there i could easily build formula. Sorry for bothering but i am new to
> Python.
Are you the same person who posted the original question?
You probably want to use numpy for this. I'm not s
How can i at least find a peek in FFT spectrum of a square wave ?
>From there i could easily build formula. Sorry for bothering but i am new to
>Python.
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On Sun, May 19, 2013 at 8:52 PM, Anti Log wrote:
> total distortion of a harmonics
I selected this part of your post, right-clicked, and Chrome offered
to do a Google search for those words. And, surprise surprise, the
first hit is a page that appears to have the mathematics behind it.
Now, I don
Hi,
I have a task to calculate total distortion of a harmonics, of a signal that i
imported from oscilloscope as numpy array. I had no problem drawing its
spectrum, and time domain graph, but cant seem to find any functions that
calculate TDH.
Any help?
Best regards
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