Vous êtes un professionnel et vous avez besoin d'une formation ? Programmation Python
Les fondamentaux Voir le programme détaillé

Module « scipy.signal »

Fonction iirfilter - module scipy.signal

Signature de la fonction iirfilter

def iirfilter(N, Wn, rp=None, rs=None, btype='band', analog=False, ftype='butter', output='ba', fs=None) 

Description

help(scipy.signal.iirfilter)

IIR digital and analog filter design given order and critical points.

Design an Nth-order digital or analog filter and return the filter
coefficients.

Parameters
----------
N : int
    The order of the filter.
Wn : array_like
    A scalar or length-2 sequence giving the critical frequencies.

    For digital filters, `Wn` are in the same units as `fs`. By default,
    `fs` is 2 half-cycles/sample, so these are normalized from 0 to 1,
    where 1 is the Nyquist frequency. (`Wn` is thus in
    half-cycles / sample.)

    For analog filters, `Wn` is an angular frequency (e.g., rad/s).

    When Wn is a length-2 sequence, ``Wn[0]`` must be less than ``Wn[1]``.
rp : float, optional
    For Chebyshev and elliptic filters, provides the maximum ripple
    in the passband. (dB)
rs : float, optional
    For Chebyshev and elliptic filters, provides the minimum attenuation
    in the stop band. (dB)
btype : {'bandpass', 'lowpass', 'highpass', 'bandstop'}, optional
    The type of filter.  Default is 'bandpass'.
analog : bool, optional
    When True, return an analog filter, otherwise a digital filter is
    returned.
ftype : str, optional
    The type of IIR filter to design:

        - Butterworth   : 'butter'
        - Chebyshev I   : 'cheby1'
        - Chebyshev II  : 'cheby2'
        - Cauer/elliptic: 'ellip'
        - Bessel/Thomson: 'bessel'

output : {'ba', 'zpk', 'sos'}, optional
    Filter form of the output:

        - second-order sections (recommended): 'sos'
        - numerator/denominator (default)    : 'ba'
        - pole-zero                          : 'zpk'

    In general the second-order sections ('sos') form  is
    recommended because inferring the coefficients for the
    numerator/denominator form ('ba') suffers from numerical
    instabilities. For reasons of backward compatibility the default
    form is the numerator/denominator form ('ba'), where the 'b'
    and the 'a' in 'ba' refer to the commonly used names of the
    coefficients used.

    Note: Using the second-order sections form ('sos') is sometimes
    associated with additional computational costs: for
    data-intense use cases it is therefore recommended to also
    investigate the numerator/denominator form ('ba').

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.
    Only returned if ``output='ba'``.
z, p, k : ndarray, ndarray, float
    Zeros, poles, and system gain of the IIR filter transfer
    function.  Only returned if ``output='zpk'``.
sos : ndarray
    Second-order sections representation of the IIR filter.
    Only returned if ``output='sos'``.

See Also
--------
butter : Filter design using order and critical points
cheby1, cheby2, ellip, bessel
buttord : Find order and critical points from passband and stopband spec
cheb1ord, cheb2ord, ellipord
iirdesign : General filter design using passband and stopband spec

Notes
-----
The ``'sos'`` output parameter was added in 0.16.0.

Examples
--------
Generate a 17th-order Chebyshev II analog bandpass filter from 50 Hz to
200 Hz and plot the frequency response:

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

>>> b, a = signal.iirfilter(17, [2*np.pi*50, 2*np.pi*200], rs=60,
...                         btype='band', analog=True, ftype='cheby2')
>>> w, h = signal.freqs(b, a, 1000)
>>> fig = plt.figure()
>>> ax = fig.add_subplot(1, 1, 1)
>>> ax.semilogx(w / (2*np.pi), 20 * np.log10(np.maximum(abs(h), 1e-5)))
>>> ax.set_title('Chebyshev Type II bandpass frequency response')
>>> ax.set_xlabel('Frequency [Hz]')
>>> ax.set_ylabel('Amplitude [dB]')
>>> ax.axis((10, 1000, -100, 10))
>>> ax.grid(which='both', axis='both')
>>> plt.show()

Create a digital filter with the same properties, in a system with
sampling rate of 2000 Hz, and plot the frequency response. (Second-order
sections implementation is required to ensure stability of a filter of
this order):

>>> sos = signal.iirfilter(17, [50, 200], rs=60, btype='band',
...                        analog=False, ftype='cheby2', fs=2000,
...                        output='sos')
>>> w, h = signal.freqz_sos(sos, 2000, fs=2000)
>>> fig = plt.figure()
>>> ax = fig.add_subplot(1, 1, 1)
>>> ax.semilogx(w, 20 * np.log10(np.maximum(abs(h), 1e-5)))
>>> ax.set_title('Chebyshev Type II bandpass frequency response')
>>> ax.set_xlabel('Frequency [Hz]')
>>> ax.set_ylabel('Amplitude [dB]')
>>> ax.axis((10, 1000, -100, 10))
>>> ax.grid(which='both', axis='both')
>>> plt.show()

Vous êtes un professionnel et vous avez besoin d'une formation ? Machine Learning
avec Scikit-Learn Voir le programme détaillé