Previous topic

scipy.signal.upfirdn

Next topic

scipy.signal.bilinear_zpk

scipy.signal.bilinear

scipy.signal.bilinear(b, a, fs=1.0)[source]

Return a digital IIR filter from an analog one using a bilinear transform.

Transform a set of poles and zeros from the analog s-plane to the digital z-plane using Tustin’s method, which substitutes (z-1) / (z+1) for s, maintaining the shape of the frequency response.

Parameters:
b : array_like

Numerator of the analog filter transfer function.

a : array_like

Denominator of the analog filter transfer function.

fs : float

Sample rate, as ordinary frequency (e.g. hertz). No prewarping is done in this function.

Returns:
z : ndarray

Numerator of the transformed digital filter transfer function.

p : ndarray

Denominator of the transformed digital filter transfer function.

Examples

>>> from scipy import signal
>>> import matplotlib.pyplot as plt
>>> fs = 100
>>> bf = 2 * np.pi * np.array([7, 13])
>>> filts = signal.lti(*signal.butter(4, bf, btype='bandpass', analog=True))
>>> filtz = signal.lti(*signal.bilinear(filts.num, filts.den, fs))
>>> wz, hz = signal.freqz(filtz.num, filtz.den)
>>> ws, hs = signal.freqs(filts.num, filts.den, worN=fs*wz)
>>> plt.semilogx(wz*fs/(2*np.pi), 20*np.log10(np.abs(hz).clip(1e-15)), label=r'$|H(j \omega)|$')
>>> plt.semilogx(wz*fs/(2*np.pi), 20*np.log10(np.abs(hs).clip(1e-15)), label=r'$|H_z(e^{j \omega})|$')
>>> plt.legend()
>>> plt.xlabel('Frequency [Hz]')
>>> plt.ylabel('Magnitude [dB]')
>>> plt.grid()
../_images/scipy-signal-bilinear-1.png