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Module « scipy.signal »

Fonction normalize - module scipy.signal

Signature de la fonction normalize

def normalize(b, a) 

Description

help(scipy.signal.normalize)

Normalize numerator/denominator of a continuous-time transfer function.

If values of `b` are too close to 0, they are removed. In that case, a
BadCoefficients warning is emitted.

Parameters
----------
b: array_like
    Numerator of the transfer function. Can be a 2-D array to normalize
    multiple transfer functions.
a: array_like
    Denominator of the transfer function. At most 1-D.

Returns
-------
num: array
    The numerator of the normalized transfer function. At least a 1-D
    array. A 2-D array if the input `num` is a 2-D array.
den: 1-D array
    The denominator of the normalized transfer function.

Notes
-----
Coefficients for both the numerator and denominator should be specified in
descending exponent order (e.g., ``s^2 + 3s + 5`` would be represented as
``[1, 3, 5]``).

Examples
--------
>>> from scipy.signal import normalize

Normalize the coefficients of the transfer function
``(3*s^2 - 2*s + 5) / (2*s^2 + 3*s + 1)``:

>>> b = [3, -2, 5]
>>> a = [2, 3, 1]
>>> normalize(b, a)
(array([ 1.5, -1. ,  2.5]), array([1. , 1.5, 0.5]))

A warning is generated if, for example, the first coefficient of
`b` is 0.  In the following example, the result is as expected:

>>> import warnings
>>> with warnings.catch_warnings(record=True) as w:
...     num, den = normalize([0, 3, 6], [2, -5, 4])

>>> num
array([1.5, 3. ])
>>> den
array([ 1. , -2.5,  2. ])

>>> print(w[0].message)
Badly conditioned filter coefficients (numerator): the results may be meaningless

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