Module « scipy.signal »

Fonction dfreqresp - module scipy.signal

Signature de la fonction dfreqresp

def dfreqresp(system, w=None, n=10000, whole=False) 

Description

dfreqresp.__doc__

    Calculate the frequency response of a discrete-time system.

    Parameters
    ----------
    system : an instance of the `dlti` class or a tuple describing the system.
        The following gives the number of elements in the tuple and
        the interpretation:

            * 1 (instance of `dlti`)
            * 2 (numerator, denominator, dt)
            * 3 (zeros, poles, gain, dt)
            * 4 (A, B, C, D, dt)

    w : array_like, optional
        Array of frequencies (in radians/sample). Magnitude and phase data is
        calculated for every value in this array. If not given a reasonable
        set will be calculated.
    n : int, optional
        Number of frequency points to compute if `w` is not given. The `n`
        frequencies are logarithmically spaced in an interval chosen to
        include the influence of the poles and zeros of the system.
    whole : bool, optional
        Normally, if 'w' is not given, frequencies are computed from 0 to the
        Nyquist frequency, pi radians/sample (upper-half of unit-circle). If
        `whole` is True, compute frequencies from 0 to 2*pi radians/sample.

    Returns
    -------
    w : 1D ndarray
        Frequency array [radians/sample]
    H : 1D ndarray
        Array of complex magnitude values

    Notes
    -----
    If (num, den) is passed in for ``system``, coefficients for both the
    numerator and denominator should be specified in descending exponent
    order (e.g. ``z^2 + 3z + 5`` would be represented as ``[1, 3, 5]``).

    .. versionadded:: 0.18.0

    Examples
    --------
    Generating the Nyquist plot of a transfer function

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

    Construct the transfer function
    :math:`H(z) = \frac{1}{z^2 + 2z + 3}` with a sampling time of 0.05
    seconds:

    >>> sys = signal.TransferFunction([1], [1, 2, 3], dt=0.05)

    >>> w, H = signal.dfreqresp(sys)

    >>> plt.figure()
    >>> plt.plot(H.real, H.imag, "b")
    >>> plt.plot(H.real, -H.imag, "r")
    >>> plt.show()