parameters: (system, w=None, n=100)
return_statement: return w, mag, phase
docstring: Calculate Bode magnitude and phase data of a continuous-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 `lti`)
              * 2 (num, den)
              * 3 (zeros, poles, gain)
              * 4 (A, B, C, D)
  
      w : array_like, optional
          Array of frequencies (in rad/s). 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/s]
      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. ``s^2 + 3s + 5`` would be represented as ``[1, 3, 5]``).
  
      .. versionadded:: 0.11.0
  
      Examples
      --------
      >>> from scipy import signal
      >>> import matplotlib.pyplot as plt
  
      >>> sys = signal.TransferFunction([1], [1, 1])
      >>> w, mag, phase = signal.bode(sys)
  
      >>> plt.figure()
      >>> plt.semilogx(w, mag)    # Bode magnitude plot
      >>> plt.figure()
      >>> plt.semilogx(w, phase)  # Bode phase plot
      >>> plt.show()
docstring_summary: Calculate Bode magnitude and phase data of a continuous-time system.
docstring_tokens: Calculate Bode magnitude and phase data of a continuous - time system .
function: def bode(system, w=None, n=100):
      """
      Calculate Bode magnitude and phase data of a continuous-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 `lti`)
              * 2 (num, den)
              * 3 (zeros, poles, gain)
              * 4 (A, B, C, D)
  
      w : array_like, optional
          Array of frequencies (in rad/s). 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/s]
      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. ``s^2 + 3s + 5`` would be represented as ``[1, 3, 5]``).
  
      .. versionadded:: 0.11.0
  
      Examples
      --------
      >>> from scipy import signal
      >>> import matplotlib.pyplot as plt
  
      >>> sys = signal.TransferFunction([1], [1, 1])
      >>> w, mag, phase = signal.bode(sys)
  
      >>> plt.figure()
      >>> plt.semilogx(w, mag)    # Bode magnitude plot
      >>> plt.figure()
      >>> plt.semilogx(w, phase)  # Bode phase plot
      >>> plt.show()
  
      """
      w, y = freqresp(system, w=w, n=n)
  
      mag = 20.0 * numpy.log10(abs(y))
      phase = numpy.unwrap(numpy.arctan2(y.imag, y.real)) * 180.0 / numpy.pi
  
      return w, mag, phase
function_tokens: def bode ( system , w = None , n = 100 ) : w , y = freqresp ( system , w = w , n = n ) mag = 20.0 * numpy . log10 ( abs ( y ) ) phase = numpy . unwrap ( numpy . arctan2 ( y . imag , y . real ) ) * 180.0 / numpy . pi return w , mag , phase