f '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()

z6dfreqresp can only be used with discrete-time systems.Nrö