dfreqresp(system, w=None, n=10000, whole=False)
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]
).
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)
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.
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.
Normally, if 'w' is not given, frequencies are computed from 0 to the Nyquist frequency, pi radians/sample (upper-half of unit-circle). If :None:None:`whole` is True, compute frequencies from 0 to 2*pi radians/sample.
Calculate the frequency response of a discrete-time system.
Generating the Nyquist plot of a transfer function
>>> from scipy import signal
... import matplotlib.pyplot as plt
Construct the transfer function $H(z) = \frac{1}{z^2 + 2z + 3}$ 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()
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.signal._ltisys.dfreqresp
scipy.signal._ltisys.dlti.freqresp
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