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Module « scipy.signal »

Fonction freqs_zpk - module scipy.signal

Signature de la fonction freqs_zpk

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

Description

help(scipy.signal.freqs_zpk)

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
--------
>>> import numpy as np
>>> 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 [rad/s]')
>>> plt.ylabel('Amplitude response [dB]')
>>> plt.grid(True)
>>> plt.show()

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