Since I noticed this is better suited to the SciPy Users List, I moved it there:
https://mail.scipy.org/pipermail/scipy-user/2016-August/037023.html > On 29 Aug 2016, at 14:34, Matti Viljamaa <mvilja...@kapsi.fi> wrote: > > I’m trying to design an arbitrary frequency response filter as described here: > http://www.dspguide.com/ch17/1.htm <http://www.dspguide.com/ch17/1.htm> > > The technique is said to result in an impulse response in time domain and > later in to a filter kernel. > > I’ve been using scipy.signal.freqz to make magnitude response plots: > > e.g. > > fs = 44100 > > # Design a low-pass filter using remez. > cutoff = 2000.0 > transition_width = 200 > bands = np.array([0, cutoff - 0.5*transition_width, > cutoff + 0.5*transition_width, fs/2.0]) / fs > desired = [1, 0] > lpf = remez(513, bands, desired) > > # Plot the frequency response of the filter. > w, h = freqz(lpf) > plt.figure(1) > plt.plot(fs*w/(2*np.pi), 20*np.log10(abs(h))) > plt.xlim(0, fs/2) > plt.xlabel('Frequency (Hz)') > plt.ylabel('Gain (dB)') > plt.grid(True) > > But my question is, if using the above arbitrary frequency response design > technique, would I be able to use freqz? > > freqz takes as a parameter “numerator of a linear filter” and remez is > returning an array of coefficients, which I read to be the same thing. > > But in the case of the arbitrary frequency response filter, what can I put > into freqz? Is filter kernel perhaps the same as coefficients? > -- > https://mail.python.org/mailman/listinfo/python-list -- https://mail.python.org/mailman/listinfo/python-list
