# scipy.signal.dbode

scipy.signal.dbode(system, w=None, n=100)

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

  Parameters
    system an 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)

    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.

  Returns
    w 1D ndarray

      Frequency array [rad/time_unit]

    mag 1D ndarray

      Magnitude array [dB]

    phase 1D 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]`).

  New in version 0.18.0.

  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()

scipy.signal.dfreqresp scipy.signal.tf2zpk