Module « scipy.signal »

Fonction freqs_zpk - module scipy.signal

Signature de la fonction freqs_zpk

def freqs_zpk(z, p, k, worN=200) 

Description

freqs_zpk.__doc__

    Compute frequency response of analog filter.

    Given the zeros `z`, poles `p`, and gain `k` of a filter, compute its
    frequency response::

                (jw-z[0]) * (jw-z[1]) * ... * (jw-z[-1])
     H(w) = k * ----------------------------------------
                (jw-p[0]) * (jw-p[1]) * ... * (jw-p[-1])

    Parameters
    ----------
    z : array_like
        Zeroes of a linear filter
    p : array_like
        Poles of a linear filter
    k : scalar
        Gain of a linear filter
    worN : {None, int, array_like}, optional
        If None, then compute at 200 frequencies around the interesting parts
        of the response curve (determined by pole-zero locations). If a single
        integer, then compute at that many frequencies. Otherwise, compute the
        response at the angular frequencies (e.g., rad/s) given in `worN`.

    Returns
    -------
    w : ndarray
        The angular frequencies at which `h` was computed.
    h : ndarray
        The frequency response.

    See Also
    --------
    freqs : Compute the frequency response of an analog filter in TF form
    freqz : Compute the frequency response of a digital filter in TF form
    freqz_zpk : Compute the frequency response of a digital filter in ZPK form

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

    Examples
    --------
    >>> from scipy.signal import freqs_zpk, iirfilter

    >>> z, p, k = iirfilter(4, [1, 10], 1, 60, analog=True, ftype='cheby1',
    ...                     output='zpk')

    >>> w, h = freqs_zpk(z, p, k, worN=np.logspace(-1, 2, 1000))

    >>> import matplotlib.pyplot as plt
    >>> plt.semilogx(w, 20 * np.log10(abs(h)))
    >>> plt.xlabel('Frequency')
    >>> plt.ylabel('Amplitude response [dB]')
    >>> plt.grid()
    >>> plt.show()