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

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]).

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

Calculate the frequency response of a discrete-time system.

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()

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy.signal._ltisys:dlti.freqresp

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GitHub : /scipy/signal/_ltisys.py#3700
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