scipy.signal.cheb2ord¶

scipy.signal.
cheb2ord
(wp, ws, gpass, gstop, analog=False, fs=None)[source]¶ Chebyshev type II filter order selection.
Return the order of the lowest order digital or analog Chebyshev Type II filter that loses no more than gpass dB in the passband and has at least gstop dB attenuation in the stopband.
Parameters:  wp, ws : float
Passband and stopband edge frequencies.
For digital filters, these are in the same units as fs. By default, fs is 2 halfcycles/sample, so these are normalized from 0 to 1, where 1 is the Nyquist frequency. (wp and ws are thus in halfcycles / sample.) For example:
 Lowpass: wp = 0.2, ws = 0.3
 Highpass: wp = 0.3, ws = 0.2
 Bandpass: wp = [0.2, 0.5], ws = [0.1, 0.6]
 Bandstop: wp = [0.1, 0.6], ws = [0.2, 0.5]
For analog filters, wp and ws are angular frequencies (e.g. rad/s).
 gpass : float
The maximum loss in the passband (dB).
 gstop : float
The minimum attenuation in the stopband (dB).
 analog : bool, optional
When True, return an analog filter, otherwise a digital filter is returned.
 fs : float, optional
The sampling frequency of the digital system.
New in version 1.2.0.
Returns: See also
Examples
Design a digital bandstop filter which rejects 60 dB from 0.2*(fs/2) to 0.5*(fs/2), while staying within 3 dB below 0.1*(fs/2) or above 0.6*(fs/2). Plot its frequency response, showing the passband and stopband constraints in gray.
>>> from scipy import signal >>> import matplotlib.pyplot as plt
>>> N, Wn = signal.cheb2ord([0.1, 0.6], [0.2, 0.5], 3, 60) >>> b, a = signal.cheby2(N, 60, Wn, 'stop') >>> w, h = signal.freqz(b, a) >>> plt.semilogx(w / np.pi, 20 * np.log10(abs(h))) >>> plt.title('Chebyshev II bandstop filter fit to constraints') >>> plt.xlabel('Normalized frequency') >>> plt.ylabel('Amplitude [dB]') >>> plt.grid(which='both', axis='both') >>> plt.fill([.01, .1, .1, .01], [3, 3, 99, 99], '0.9', lw=0) # stop >>> plt.fill([.2, .2, .5, .5], [ 9, 60, 60, 9], '0.9', lw=0) # pass >>> plt.fill([.6, .6, 2, 2], [99, 3, 3, 99], '0.9', lw=0) # stop >>> plt.axis([0.06, 1, 80, 3]) >>> plt.show()