scipy.signal.

# dbode#

scipy.signal.dbode(system, w=None, n=100)[source]#

Calculate Bode magnitude and phase data of a discrete-time system.

Parameters:
systeman instance of the LTI 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 (num, den, dt)

• 3 (zeros, poles, gain, dt)

• 4 (A, B, C, D, dt)

warray_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.

nint, 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.

Returns:
w1D ndarray

mag1D ndarray

Magnitude array [dB]

phase1D ndarray

Phase array [deg]

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]).

Examples

>>> 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)


Equivalent: sys.bode()

>>> w, mag, phase = signal.dbode(sys)

>>> plt.figure()
>>> plt.semilogx(w, mag)    # Bode magnitude plot
>>> plt.figure()
>>> plt.semilogx(w, phase)  # Bode phase plot
>>> plt.show()