iirdesign(wp, ws, gpass, gstop, analog=False, ftype='ellip', output='ba', fs=None)
Given passband and stopband frequencies and gains, construct an analog or digital IIR filter of minimum order for a given basic type. Return the output in numerator, denominator ('ba'), pole-zero ('zpk') or second order sections ('sos') form.
The 'sos'
output parameter was added in 0.16.0.
Passband and stopband edge frequencies. Possible values are scalars (for lowpass and highpass filters) or ranges (for bandpass and bandstop filters). For digital filters, these are in the same units as :None:None:`fs`. By default, :None:None:`fs` is 2 half-cycles/sample, so these are normalized from 0 to 1, where 1 is the Nyquist frequency. 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, :None:None:`wp` and :None:None:`ws` are angular frequencies (e.g., rad/s). Note, that for bandpass and bandstop filters passband must lie strictly inside stopband or vice versa.
The maximum loss in the passband (dB).
The minimum attenuation in the stopband (dB).
When True, return an analog filter, otherwise a digital filter is returned.
The type of IIR filter to design:
Filter form of the output:
The sampling frequency of the digital system.
Numerator (b) and denominator (a) polynomials of the IIR filter. Only returned if output='ba'
.
Zeros, poles, and system gain of the IIR filter transfer function. Only returned if output='zpk'
.
Second-order sections representation of the IIR filter. Only returned if output=='sos'
.
Complete IIR digital and analog filter design.
butter
Filter design using order and critical points
buttord
Find order and critical points from passband and stopband spec
iirfilter
General filter design using order and critical frequencies
>>> from scipy import signal
... import matplotlib.pyplot as plt
... import matplotlib.ticker
>>> wp = 0.2
... ws = 0.3
... gpass = 1
... gstop = 40
>>> system = signal.iirdesign(wp, ws, gpass, gstop)
... w, h = signal.freqz(*system)
>>> fig, ax1 = plt.subplots()See :
... ax1.set_title('Digital filter frequency response')
... ax1.plot(w, 20 * np.log10(abs(h)), 'b')
... ax1.set_ylabel('Amplitude [dB]', color='b')
... ax1.set_xlabel('Frequency [rad/sample]')
... ax1.grid()
... ax1.set_ylim([-120, 20])
... ax2 = ax1.twinx()
... angles = np.unwrap(np.angle(h))
... ax2.plot(w, angles, 'g')
... ax2.set_ylabel('Angle (radians)', color='g')
... ax2.grid()
... ax2.axis('tight')
... ax2.set_ylim([-6, 1])
... nticks = 8
... ax1.yaxis.set_major_locator(matplotlib.ticker.LinearLocator(nticks))
... ax2.yaxis.set_major_locator(matplotlib.ticker.LinearLocator(nticks))
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.signal._filter_design.group_delay
scipy.signal._filter_design.ellipord
scipy.signal._filter_design.iirfilter
scipy.signal._filter_design.cheb1ord
scipy.signal._filter_design.buttord
scipy.signal._filter_design.cheb2ord
scipy.signal._filter_design.iirdesign
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