scipy.signal.iirpeak¶
-
scipy.signal.
iirpeak
(w0, Q)[source]¶ Design second-order IIR peak (resonant) digital filter.
A peak filter is a band-pass filter with a narrow bandwidth (high quality factor). It rejects components outside a narrow frequency band.
Parameters: - w0 : float
Normalized frequency to be retained in a signal. It is a scalar that must satisfy
0 < w0 < 1
, withw0 = 1
corresponding to half of the sampling frequency.- Q : float
Quality factor. Dimensionless parameter that characterizes peak filter -3 dB bandwidth
bw
relative to its center frequency,Q = w0/bw
.
Returns: - b, a : ndarray, ndarray
Numerator (
b
) and denominator (a
) polynomials of the IIR filter.
See also
Notes
New in version 0.19.0.
References
[1] Sophocles J. Orfanidis, “Introduction To Signal Processing”, Prentice-Hall, 1996 Examples
Design and plot filter to remove the frequencies other than the 300Hz component from a signal sampled at 1000Hz, using a quality factor Q = 30
>>> from scipy import signal >>> import numpy as np >>> import matplotlib.pyplot as plt
>>> fs = 1000.0 # Sample frequency (Hz) >>> f0 = 300.0 # Frequency to be retained (Hz) >>> Q = 30.0 # Quality factor >>> w0 = f0/(fs/2) # Normalized Frequency >>> # Design peak filter >>> b, a = signal.iirpeak(w0, Q)
>>> # Frequency response >>> w, h = signal.freqz(b, a) >>> # Generate frequency axis >>> freq = w*fs/(2*np.pi) >>> # Plot >>> fig, ax = plt.subplots(2, 1, figsize=(8, 6)) >>> ax[0].plot(freq, 20*np.log10(abs(h)), color='blue') >>> ax[0].set_title("Frequency Response") >>> ax[0].set_ylabel("Amplitude (dB)", color='blue') >>> ax[0].set_xlim([0, 500]) >>> ax[0].set_ylim([-50, 10]) >>> ax[0].grid() >>> ax[1].plot(freq, np.unwrap(np.angle(h))*180/np.pi, color='green') >>> ax[1].set_ylabel("Angle (degrees)", color='green') >>> ax[1].set_xlabel("Frequency (Hz)") >>> ax[1].set_xlim([0, 500]) >>> ax[1].set_yticks([-90, -60, -30, 0, 30, 60, 90]) >>> ax[1].set_ylim([-90, 90]) >>> ax[1].grid() >>> plt.show()