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Module « scipy.signal »

Fonction freqs - module scipy.signal

Signature de la fonction freqs

def freqs(b, a, worN=200, plot=None) 

Description

help(scipy.signal.freqs)

Compute frequency response of analog filter.

Given the M-order numerator `b` and N-order denominator `a` of an analog
filter, compute its frequency response::

         b[0]*(jw)**M + b[1]*(jw)**(M-1) + ... + b[M]
 H(w) = ----------------------------------------------
         a[0]*(jw)**N + a[1]*(jw)**(N-1) + ... + a[N]

Parameters
----------
b : array_like
    Numerator of a linear filter.
a : array_like
    Denominator 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`.
plot : callable, optional
    A callable that takes two arguments. If given, the return parameters
    `w` and `h` are passed to plot. Useful for plotting the frequency
    response inside `freqs`.

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

See Also
--------
freqz : Compute the frequency response of a digital filter.

Notes
-----
Using Matplotlib's "plot" function as the callable for `plot` produces
unexpected results, this plots the real part of the complex transfer
function, not the magnitude. Try ``lambda w, h: plot(w, abs(h))``.

Examples
--------
>>> from scipy.signal import freqs, iirfilter
>>> import numpy as np

>>> b, a = iirfilter(4, [1, 10], 1, 60, analog=True, ftype='cheby1')

>>> w, h = freqs(b, a, 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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