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Module « scipy.signal »

Fonction iirnotch - module scipy.signal

Signature de la fonction iirnotch

def iirnotch(w0, Q, fs=2.0) 

Description

help(scipy.signal.iirnotch)

Design second-order IIR notch digital filter.

A notch filter is a band-stop filter with a narrow bandwidth
(high quality factor). It rejects a narrow frequency band and
leaves the rest of the spectrum little changed.

Parameters
----------
w0 : float
    Frequency to remove from a signal. If `fs` is specified, this is in
    the same units as `fs`. By default, it is a normalized scalar that must
    satisfy  ``0 < w0 < 1``, with ``w0 = 1`` corresponding to half of the
    sampling frequency.
Q : float
    Quality factor. Dimensionless parameter that characterizes
    notch filter -3 dB bandwidth ``bw`` relative to its center
    frequency, ``Q = w0/bw``.
fs : float, optional
    The sampling frequency of the digital system.

    .. versionadded:: 1.2.0

Returns
-------
b, a : ndarray, ndarray
    Numerator (``b``) and denominator (``a``) polynomials
    of the IIR filter.

See Also
--------
iirpeak

Notes
-----
.. versionadded:: 0.19.0

References
----------
.. [1] Sophocles J. Orfanidis, "Introduction To Signal Processing",
       Prentice-Hall, 1996

Examples
--------
Design and plot filter to remove the 60 Hz component from a
signal sampled at 200 Hz, using a quality factor Q = 30

>>> from scipy import signal
>>> import matplotlib.pyplot as plt
>>> import numpy as np

>>> fs = 200.0  # Sample frequency (Hz)
>>> f0 = 60.0  # Frequency to be removed from signal (Hz)
>>> Q = 30.0  # Quality factor
>>> # Design notch filter
>>> b, a = signal.iirnotch(f0, Q, fs)

>>> # Frequency response
>>> freq, h = signal.freqz(b, a, fs=fs)
>>> # 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, 100])
>>> ax[0].set_ylim([-25, 10])
>>> ax[0].grid(True)
>>> ax[1].plot(freq, np.unwrap(np.angle(h))*180/np.pi, color='green')
>>> ax[1].set_ylabel("Phase [deg]", color='green')
>>> ax[1].set_xlabel("Frequency [Hz]")
>>> ax[1].set_xlim([0, 100])
>>> ax[1].set_yticks([-90, -60, -30, 0, 30, 60, 90])
>>> ax[1].set_ylim([-90, 90])
>>> ax[1].grid(True)
>>> plt.show()

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