[SciPy-User] FFT Filter

Anders Harrysson anders.harrysson@fem4fun....
Tue Sep 27 04:47:31 CDT 2011


Hi,
Thanks a lot for the reply. I have started to look into this and 
currently I am trying to use firwin2 to generate the filter coefficients 
according to below

b=signal.firwin2(512,freq,gain,nfreqs=N,nyq=nf)

X2=signal.lfilter(b,[1.0],y)


However I get strange results, when trying to filter even a very simple 
signal :(. This is probably not a scipy related question, but how to put 
the numtaps number? How is this related to the other inputs.

Regards,
Anders **

Christophe Grimault skrev 2011-09-26 18:32:
> Hi Anders,
>
> Use : scipy.signals.lfilter(b, a, x)
>
> Where x is your signal (complex or real, it doesn't matter). As a filter
> in the Fourier domain is basically FIR filter, you only need to pass the
> b array (the response of the filter) and set a = [1.0].
>
> Chris
>
> On Sat, 2011-09-24 at 09:33 +0200, Anders Harrysson wrote:
>> Dear all,
>>
>> I am kind of new to scipy and also new to the signal processing field
>> that this question relates to.
>> I am trying to do a bandpass FFT filter using python. The filter shape
>> is symmetric around 11 Hz and is defined by the parameters ff and Hz below.
>>
>> x=loadtxt('file')
>>
>> sr = 250                    # [samples/s]
>> nf = sr/2.0                # Nyquist frequence
>> Ns = len(tr[:,0])       # Total number of samples
>> N=float(8192)          # Fourier settings
>>
>> # Fourier transform
>> X1 = fft(x,n=int(N))
>> X1 = fftshift(X1)
>> F1 = arange(-N/2.0,N/2.0)/N*sr
>>
>> # Filter
>> ff=[0,1,1,0]
>> Hz = [9.5, 10, 12, 12.5]
>> k1=interp(-F1,Hz,ff)+interp(F1,Hz,ff)
>> X1_f=X1*k1
>> X1_f=ifftshift(X1_f)
>> x1_f=ifft(X1_f,n=int(N))
>>
>> My question is now:
>> Are ther built in functionallity for filtering in scioy and, if so, how
>> would a similar filter looks like.
>>
>> Regards,
>> Anders Harrysson
>> _______________________________________________
>> SciPy-User mailing list
>> SciPy-User@scipy.org
>> http://mail.scipy.org/mailman/listinfo/scipy-user
>

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