Module « scipy.signal »

Fonction iircomb - module scipy.signal

Signature de la fonction iircomb

def iircomb(w0, Q, ftype='notch', fs=2.0) 

Description

iircomb.__doc__

    Design IIR notching or peaking digital comb filter.

    A notching comb 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.

    A peaking comb filter is a band-pass filter with a narrow bandwidth
    (high quality factor). It rejects components outside a narrow
    frequency band.

    Parameters
    ----------
    w0 : float
        Frequency to attenuate (notching) or boost (peaking). 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``.
    ftype : {'notch', 'peak'}
        The type of comb filter generated by the function. If 'notch', then
        it returns a filter with notches at frequencies ``0``, ``w0``,
        ``2 * w0``, etc. If 'peak', then it returns a filter with peaks at
        frequencies ``0.5 * w0``, ``1.5 * w0``, ``2.5 * w0```, etc.
        Default is 'notch'.
    fs : float, optional
        The sampling frequency of the signal. Default is 2.0.

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

    Raises
    ------
    ValueError
        If `w0` is less than or equal to 0 or greater than or equal to
        ``fs/2``, if `fs` is not divisible by `w0`, if `ftype`
        is not 'notch' or 'peak'

    See Also
    --------
    iirnotch
    iirpeak

    Notes
    -----
    For implementation details, see [1]_. The TF implementation of the
    comb filter is numerically stable even at higher orders due to the
    use of a single repeated pole, which won't suffer from precision loss.

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

    Examples
    --------
    Design and plot notching comb filter at 20 Hz for a
    signal sampled at 200 Hz, using quality factor Q = 30

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

    >>> fs = 200.0  # Sample frequency (Hz)
    >>> f0 = 20.0  # Frequency to be removed from signal (Hz)
    >>> Q = 30.0  # Quality factor
    >>> # Design notching comb filter
    >>> b, a = signal.iircomb(f0, Q, ftype='notch', fs=fs)

    >>> # Frequency response
    >>> freq, h = signal.freqz(b, a, fs=fs)
    >>> response = abs(h)
    >>> # To avoid divide by zero when graphing
    >>> response[response == 0] = 1e-20
    >>> # Plot
    >>> fig, ax = plt.subplots(2, 1, figsize=(8, 6))
    >>> ax[0].plot(freq, 20*np.log10(abs(response)), 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([-30, 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, 100])
    >>> ax[1].set_yticks([-90, -60, -30, 0, 30, 60, 90])
    >>> ax[1].set_ylim([-90, 90])
    >>> ax[1].grid()
    >>> plt.show()

    Design and plot peaking comb filter at 250 Hz for a
    signal sampled at 1000 Hz, using quality factor Q = 30

    >>> fs = 1000.0  # Sample frequency (Hz)
    >>> f0 = 250.0  # Frequency to be retained (Hz)
    >>> Q = 30.0  # Quality factor
    >>> # Design peaking filter
    >>> b, a = signal.iircomb(f0, Q, ftype='peak', fs=fs)

    >>> # Frequency response
    >>> freq, h = signal.freqz(b, a, fs=fs)
    >>> response = abs(h)
    >>> # To avoid divide by zero when graphing
    >>> response[response == 0] = 1e-20
    >>> # Plot
    >>> fig, ax = plt.subplots(2, 1, figsize=(8, 6))
    >>> ax[0].plot(freq, 20*np.log10(np.maximum(abs(h), 1e-5)), 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([-80, 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()